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COMPUTER SPECIALIZED CROSS DISCIPLINARY
VIEWS ON COMMUNICATION AND LIFE SKILLS
Book Title : COMPUTER SPECIALIZED CROSS DISCIPLINARY
VIEWS ON COMMUNICATION AND LIFE SKILLS
Chief Editor : Dr. M. THENMOZHI
Assistant Professor Senior
Department of English
SSL, VIT, Tamil Nadu, India
Assistant Editors : AKSHWIN T
SAAI PRANAV REDDY DUVVURU
Book Subject : English Communication Studies
Book Category : Research Book
Copy Right : Editor
First Edition : May 2023
Book Size : B5
Paper : 21 kg, Maplitho NS
Price : Rs.800/-
Published by : L ORDINE NUOVO PUBLICATION
E-mail:academicbookpublication@gmail.com
www.nuovopublication.com
Mobile:99442 12131.
ISBN Supported by
Raja Ram Mohan Roy National Agency for ISBN, New Delhi – 110066 (India)
ISBN: 978-93-92995-50-7
9 7 8 9 3 9 2 9 9 5 5 0 7
ISBN 939299550-4
Disclaimer: The Publisher and editors cannot be held responsible for errors or any consequences
arising from the use of information in this Book; the views and opinions expressed herein are of the
authors and do not necessarily reflect those of the publisher and editors.
PREFACE
In today's rapidly evolving world, computer technology has transformed learning,
communication, and life skills. Our journal, "Computer Specialized Cross Disciplinary
Views on Learning, Communication, and Life Skills," provides a platform for diverse
scholars, researchers, educators, and practitioners to contribute their insights on the
intersection of computer technology and its impact. By adopting a cross-disciplinary
approach, we bridge gaps between fields and foster a deeper understanding of the complex
relationship between computers and human development.
The featured papers offer diverse perspectives, methodologies, and empirical studies
that illuminate the multifaceted aspects of computer technology in enhancing learning
outcomes, facilitating effective communication, and nurturing life skills.
Our goal is to foster dialogue, spark innovation, and contribute to the advancement of
knowledge in this evolving field. This research collection is a valuable resource for
academics, policymakers, educators, and professionals interested in leveraging computer
technology for learning, communication, and the development of vital life skills.
We extend our deepest gratitude to the authors, reviewers, and editors whose
contributions shaped this journal and enriched its content. We invite readers to explore the
diverse perspectives, engage in thought-provoking discussions, and discover the untapped
potential of computer technology in fostering learning, communication, and the acquisition
of life skills.
Contents
S.No
Title
Page No.
1
Improving Communication Using Neural Networks
Shourya Mittal & Dr. M. Thenmozhi
1
2
Artificial Intelligence and Machine Learing in E-Learning
Siri R Kulakarni, Ishita Singh, Ojasvi Bhushan, Girish Ashok
Wagh & Dr. M. Thenmozhi
18
3
Computer Assisted Language Learning
Nimisha Kumari, Akshwin T& Dr. M. Thenmozhi
35
4
IOT in Educatoin Especially ESL Classrooms
Manya Chalana & Dr. M. Thenmozhi
54
5
Use of Technology and Analysis to Find Problems and Spread
Awareness Faced by Speech Impediment Patients
Moulik Tejpal, Ambaliya Kaushal & Dr. M. Thenmozhi
70
6
English Learing and Teaching Methodolgy Using Deep Learing
Ishita Jindal, Vansh Dalal, Aditi Singh, Prajwal Sinha, Prateek
& Dr. M. Thenmozhi
81
7
Role of Human Psychology and Technology in Learing English
Chirantan Jain, Aditya Vispute, Prakhar Varshney
& Dr. M. Thenmozhi
99
8
Human Computer Interaction for Better Communication
Priyansh Garg, Aditya Tiwari, Rishabh Yadav &
Dr. M. Thenmozhi
118
9
Web 3.0 Learning and Teaching English
Konkimalla Chaitanya Devi Ganesh, Jeevan B. A &
Dr. M. Thenmozhi
132
10
Awareness of Communication Issues in Children with Down
Syndrome
Viraaj Kumar Kulshreshtha, Saai Pranav Reddy Duvvuru
& Dr. M. Thenmozhi
148
11
Impact of Stereotypical Judgment upon Communication
Harinika .K, Nishanthi .R & Dr. M. Thenmozhi
159
12
Neurologic Music Therapy Techniques for Cognitive Rehabilitation
Bhavna Suresh Rao, K.M. Hareshetha & Dr. M. Thenmozhi
174
13
Attitude and Content Analysis of Online Interactions to Examine the
Social Support Exchanged by Active Substance Users
Monica Sri V, Sugantha S & Dr. M. Thenmozhi
182
14
Analysis of Student's Errors in Solving Higher Order Thinking Skills
(HOTS) Problem
Lallipreethi. U, Sornalakshmi .M & Dr. M. Thenmozhi
194
15
Cloud IoT Application in Agricultural Engineering
Sheethll. P, Annapurna Shobitha .S, Melbin Sam Binoy &
Dr. M. Thenmozhi
204
16
Analysis of Effective Communication in Criminal Justice
Dimple, Shrija & Dr. M. Thenmozhi
211
1
CHAPTER 1
IMPROVING COMMUNICATION USING NEURAL NETWORKS
Shourya Mittal
(21BCE3751)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
Communication is very important in today's world, and an individual must be able to communicate fluently
in order to keep up with the rest of the world. There are a lot of people who struggle to do so and need an
effective mode to aid them, which can be efficiently done using neural networks. This paper investigates the
possibility of using neural networks to improve communication. The study was conducted on
undergraduate and postgraduate students at VIT. It can be further expanded to include students from
other colleges. A questionnaire was presented to the students of VIT through the mode of Google Forms,
consisting of various types of questions. The results of this study are presented in this paper and are
thoroughly analysed. The results show that students are interested in using neural networks to improve
their communication skills, even though they don't know much about neural networks. Some, however, are
sceptical that this would be helpful but are willing to give it a try. This paper shows us the thought process
of the students regarding this topic by analysing their responses to the questionnaire.
Introduction
Nodes in neural networks are connected to one another to create various graphs. The outputs
of the units attached to it, the hyperbolic tangent and the logistic sigmoid weighted sum of
101, serve as typical instances of nonlinear activation functions that a unit uses to generate its
output. Neural networks can be shown to be universal approximators, and the neural
computation model has some intriguing theoretical elements. Although artificial neural
networks are frequently used to predict and categorise various factors, they are still not
commonly used in educational psychology. The practice of employing neural networks for
wire-free communication engineering has gained popularity recently. The fundamental goal of
utilising neural networks is to replace the extended analysis and design cycles necessary to
produce high-performance systems with extremely rapid product development timeframes,
even if they have been applied for a number of purposes and in a variety of methods. Neural
networks (NNs) are able to provide answers to challenging issues in digital communications
due to their nonlinear processing, parallel distributed architecture, self-organisation, ability
for learning and generalization, and effective hardware implementation. The paper provides a
summary of NNs' uses in digital communications, including channel equivalence and
identification; coding and decoding; vector quantization; image processing; nonlinear filtering;
spread spectrum applications; etc. The main challenge is to find the right architecture for
neural network approaches that produce the greatest outcomes. When learning meaningful
2
representations from raw data, the condensing of pertinent details into a compact form, the
omission of extraneous information, and sound are necessary. Constructing a clear model that
best describes the data Analysis of the resulting representation can highlight talent elements,
show previously hidden trends in the data, and assist in understanding the situation being
watched. In many research domains where data comes from many sources and is
characterised by great complexity, finding an appropriate representation is crucial. Neural
networks are a common and useful learning method for representation. Neural networks are
modelled after the cortex in the human brain, as suggested by their name. The paper
demonstrates the selection of neural network architectures and the integration of neural
network algorithms with other methods, including adaptive signal processing, fuzzy systems,
and evolutionary algorithms. The study examines mathematical methods used to comprehend
neural network algorithms' learning and convergence behaviour in its final section.
Literature Review
Farsad N (2018) reviews the basic principles of adaptive signal processing. It provides a
survey of the most popular adaptive signal processing techniques used in wireless
communications. The chapter discusses channel identification and equalization, including
satellite communication channels and Multiple-input multiple output channels. An artificial
neural network is an adaptive, most often nonlinear system that learns to perform a function
from data. The input–output training data are fundamental in neural network technology
because they convey the necessary information to “discover” the optimal operating point. One
fundamental issue is how to adapt the weights win of the multilayer perceptron’s (MLP) to
achieve a given input–output map. The chapter addresses the following aspects: size of
training set versus weights, search procedures, how to stop training, how to set the topology
for maximum generalization. When the tape delay implements the short-term memory,
straight backpropagation can be utilized since the only adaptive parameters are the MLP
weights.
Ibnkahla (2000) stated that more than 200 applications of neural networks in image
processing and discuss the present and possible future role of neural networks, especially
feed-forward neural networks, Kohonen feature maps and Hopfield neural networks.
The various applications are categorised into a novel two-dimensional taxonomy for image
processing algorithms. One dimension specifies the type of task performed by the algorithm:
pre-processing, data reduction/feature extraction, segmentation, object recognition, image
understanding and optimisation. The other dimension captures the abstraction level of the
input data processed by the algorithm: pixel level, local feature-level, structure-level, object-
level, object-set-level and scene characterisation. Each of the six types of tasks poses specific
constraints to a neural-based approach. These specific conditions are discussed in detail.
A synthesis is made of unresolved problems related to the application of pattern recognition
techniques in image processing and specifically to the application of neural networks. Finally,
we present an outlook into the future application of neural networks and relate them to novel
developments.
3
Eriksson (2017) stated that In a wireless communication system, wireless location is the
technique used to estimate the location of a mobile station (MS). To enhance the accuracy of
MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA)
measurements and the angle of arrival (AOA) information to locate MS when three base
stations (BSs) are available. Artificial neural networks (ANN) are widely used techniques in
various areas to overcome the problem of exclusive and nonlinear relationships. When the MS
is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA
circles (and the AOA line), based on various neural networks, to estimate the MS location in
non-line-of-sight (NLOS) environments. Simulations were conducted to evaluate the
performance of the algorithm for different NLOS error distributions. The numerical analysis
and simulation results show that the proposed algorithms can obtain more precise location
estimation under different NLOS environments.
Guo (2020) states that in a wireless communication system, wireless location is the
technique used to estimate the location of a mobile station (MS). To enhance the accuracy of
MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA)
measurements and the angle of arrival (AOA) information to locate MS when three base
stations (BSs) are available. Artificial neural networks (ANN) are widely used techniques in
various areas to overcome the problem of exclusive and nonlinear relationships. When the MS
is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA
circles (and the AOA line), based on various neural networks, to estimate the MS location in
non-line-of-sight (NLOS) environments. Simulations were conducted to evaluate the
performance of the algorithm for different NLOS error distributions. The numerical analysis
and simulation results show that the proposed algorithms can obtain more precise location
estimation under different NLOS environments.
Albers (2012) states that routing algorithm for large scale communication network with
autodetonation problem is proposed in this paper. The proposed approach consists of three
procedures: recursive Hopfield neural network for obtaining the routing order between given
source and multiple destinations, a screening procedure for localizing the problem and
minimizing the computational effort along with depth-first search method, and an improved
version of Hopfield neural network for routing in the large-scale communication networks.
The results show improvements in both computational performance and solution optimality
by the proposed approach over conventional approaches.
Zhu B (2019) stated that in today's world of hackers and malware, resilience and security
in control systems like SCADA and nuclear plants are a pertinent problem. Critical
infrastructure computer systems that regulate physical processes are not exempt from the risk
of cyberattacks and could possibly be weak points. An intrusion detection system's security
can be considerably increased by making it specifically fit for critical infrastructures. This
study introduces the IDS-NNM, an intrusion detection system based on neural networks. This
work's main contributions are: 1) the use and analysis of real network data (data gathered
from an existing critical infrastructure); 2) the creation of a specific window-based feature
extraction technique; 3) the creation of a training dataset using randomly generated intrusion
vectors; and 4) the application of a combination of two neural network learning algorithms,
4
error-back propagation and Levenberg Marquardt, for modelling normal behaviour. On never-
before-seen network data, the proposed algorithm was assessed. The IDS-NNM algorithm
demonstrated its ability to detect all intrusion attempts that were present in network traffic
without issuing any erroneous alerts.
Linda(2009) stated that due to its excellent generalisation capabilities, deep learning has a
wide range of applications in the fields of natural language processing and image processing.
For jointly optimising the transmitter and receiver in the communication physical layer under
fading channels, we propose a unique neural network topology in this research. We construct
a convolutional autoencoder to perform the functions of modulation, equalisation, and
demodulation all at once. According to various channel conditions, the suggested system may
create various mapping schemes from input bit sequences of any length to constellation
symbols. The simulation findings demonstrate that, in terms of time complexity and bit error
rate for fading channels, neural network-based systems perform better than conventional
modulation and equalisation methods. To further boost performance, the proposed approach
can be integrated with additional coding strategies. Furthermore, compared to conventional
communication techniques, the suggested system network is more resilient to channel
variation.
Farsad (2018) stated to look at deep learning-based detection and demonstrate that good
detectors may be trained without being aware of the underlying channel models. In addition,
we show that it is possible to train detectors without channel state information when the
channel model is available (CSI). In specifically, a method for detection known as a sliding
bidirectional recurrent neural network (SBRNN) is suggested, in which the detector estimates
the data in real time as the signal stream enters the receiver following training. Using the
Poisson channel model, which is applicable to optical and molecular communication systems,
we assess this technique as well as various neural network (NN) topologies. Additionally, we
assess how well this detection technique performs when used with data provided through a
molecular communication platform, where it is challenging to analytically analyse the channel
model. We demonstrate the computational efficiency of SBRNN and its ability to carry out
detection under different channel circumstances without being aware of the underlying
channel model. Additionally, we show that the proposed SBRNN detector outperforms various
NN detectors that have previously been proposed as well as a Viterbi detector with a flawed
CSI in terms of bit error rate performance. Finally, we demonstrate that the SBRNN may
operate effectively in rapidly varying channels, where the coherence time is comparable to the
period of one symbol.
Xu L (2020) stated that an essential component of the mobile Internet of Things is
wireless connectivity (IoT). N-Nakagami fading channels are a more accurate description for
real-world mobile communication systems than N Rayleigh and 2-Rayleigh fading channels.
The performance assessment of mobile IoT systems takes into account the average bit error
probability (ABEP). The performance of mobile IoT systems utilising selection combining is
improved in this article using cooperative communications. The signal-to-noise ratios (SNRs)
of the direct link and end-to-end link are taken into account to calculate the ABEP. The
cumulative distribution function, which is utilised to create closed-form ABEP expressions, is
5
obtained from the probability density function (PDF) of these SNRs. The Monte-Carlo
simulation supports the theoretical findings. On the ABEP performance, the effects of fading
and other variables are investigated. These findings can be used to assess how well complex
environments, including mobile IoT and other communication systems, work. It is crucial to
forecast the ABEP performance in order to allow active complicated event processing in
mobile IoT. As a result, a neural network-based back-propagation (BP) algorithm for
predicting ABEP performance is suggested. To create training data, we employ the theoretical
findings. We put the support vector machine (SVM), BP neural network, linear regression, and
extreme learning machine (ELM) approaches to the test. The simulation results show that our
method can consistently produce higher ABEP performance prediction results when
compared to LR, SVM, and ELM methods.
Hu G (20221) stated that a high-tech augmentative and alternative communication device
can be used by people with complicated communication needs to communicate with others.
Currently, to evaluate the performance of augmentative and alternative communication users,
researchers and clinicians frequently employ data recording from high-tech augmentative and
alternative communication devices. However, when many users access the device, current
automatic data logging systems are unable to distinguish between the authorship of the data
log. The veracity of the data logs is compromised by this problem, which also makes
performance analysis more challenging. As a result, this study offers a system that processes
movies using a deep neural network-based visual analysis method to identify various
augmentative and alternative communication users during practise sessions. This strategy has
the potential to greatly boost the outcome measurements for augmentative and alternative
communication as well as the reliability of data logs
Chen S (1993) stated to look at how a radial basis function network can be used to equalise
digital communications channels. It is demonstrated that the radial basis function network can
be used to create the Bayesian equaliser since it has an identical structure to the best Bayesian
symbol-decision equaliser solution. Using a straightforward and reliable supervised clustering
approach, the Bayesian equalisation solution can be quickly realised by training a radial basis
function network. A decision-directed variant of the clustering technique allows the radial
basis function network to follow a slowly changing environment while data is being
transmitted. In addition, the clustering approach offers automatic distortion compensation for
nonlinear equipment and channel distortion. Computer simulations are used to display the
outcomes of the analysis.
Feng J (2003) stated that he efficient neural network algorithm for optimization of routing
in communication networks is suggested. As it was known from literature different
optimization and ill-defined problems may be resolved using appropriately designed neural
networks, due to their high computational speed and the possibility of working with uncertain
data. Under some assumptions the routing in packet-switched communication networks may
be considered as optimization problem, more precisely, as a shortest-path problem. The
Hopfield-type neural network is a very efficient tool for solving such problems. The suggested
routing algorithm is designed to find the optimal path, meaning, the shortest path (if possible),
but taking into account the traffic conditions: the incoming traffic flow, routers occupancy, and
6
link capacities, avoiding the packet loss due to the input buffer overflow. The applicability of
the proposed model is demonstrated through computer simulations in different traffic
conditions and for different full-connected networks with both symmetrical and non-
symmetrical links. This work addresses the channel-distortion problem and proposes a
technique for channel equalization in chaos-based communication systems. The proposed
equalization is realized by a modified recurrent neural network incorporating a specific
training (equalizing) algorithm.
Koska (1994) stated to demonstrate a novel Gaussian kernel-aided deep neural network
(GK-DNN) equalizer that can effectively compensate for the high nonlinear distortion of
underwater PAM8 visible light communication (VLC) channels. The application of a Gaussian
kernel can reduce the necessary training iterations to 47.06%, enabling it to outperform the
traditional DNN equalizer. At the same time, a novel design strategy with respect to the
structure of the GK-DNN equalizer is proposed, which can effectively save computing
resources and reduce the data volume of the necessary training data set. By using the GK-DNN
equalizer, a 1.5 GbpsPAM8 VLC system over 1.2-m underwater transmission is successfully
demonstrated.
Ibnkahla (1996) stated that additive fuzzy system can uniformly approximate any real
continuous function on a compact domain to any degree of accuracy. An additive fuzzy system
approximates the function by covering its graph with fuzzy patches in the input-output state
space and averaging patches that overlap. The fuzzy system computes a conditional
expectation E|Y|X| if we view the fuzzy sets as random sets. Each fuzzy rule defines a fuzzy
patch and connects common sense knowledge with state-space geometry. Neural or statistical
clustering systems can approximate the unknown fuzzy patches from training data. These
adaptive fuzzy systems approximate a function at two levels. At the local level the neural
system approximates and tunes the fuzzy rules. At the global level the rules or patches
approximate the function. Neural networks are suitable to give results to compound problems
in signa l processing and communications due to their parallel distributed architecture, non-
linear processing, and capacity of conception and literacy. This paper provides an outline of
the operations of neural networks to digital communications and signal processing. It shows
new results regarding identification of digital satellite channels equipped with nonlinear
memoryless devices (travelling wave tubes (TWT))
Xin M (2019) stated that communication is converting to a wireless world. Any wireless
communication system requires radio frontends (transceivers) in order to link higher layer
signals to the air interface. Transceivers with high flexibility supporting many of frequencies,
standards and signal requirements are needed for increasing standard and technology
diversity. The challenges tor transceiver designs are not made easier by design to cost, the
demand for highest energy efficiency and MIMO systems. A change in paradigm can help face
these challenges for future systems. This work explores the use of neural networks for signal
processing, impairment mitigation, control and optimization in transceiver systems. The wide
applications of neural networks in image processing are characterised into a novel two-
dimensional taxonomy for image processing algorithms. One dimension states the type of task
performed by the algorithm: pre-processing, segmentation, data reduction or feature
7
extraction, image understanding, object recognition, image understanding and optimisation.
The other dimension captures the abstraction level of the input data processed by the
algorithm: local feature-level, pixel-level, object-level, structure-level, object-set-level and
scene characterisation. Each of the six types of tasks poses specific constraints to a neural-
based approach. These specific conditions are discussed in detail. A conflation is made of
undetermined problems related to the operation of pattern recognition ways in image
processing and specifically to the operation of neural networks. Eventually, we present an
outlook into the future applications of neural networks and relate them to new developments.
Wen H(2018) stated that on the basis of the analysis of the error backpropagation
algorithm, an innovative training measure of depth neural network for maximum interval
minimum classification error is proposed. At the same time, the cross entropy and M3CE are
analysed and combined to acquire better results. Lastly, we tested our proposed M3 CE-CEc on
two deep learning standard databases, MNIST and CIFAR-10. The experimental results
demonstrate that M3 CE can augment the cross-entropy, and it is an active supplement to the
cross-entropy criterion. M3 CE-CEc has received good results in both databases. Because of its
nonlinear processing, parallel distributed design, self-organization, ability for learning and
generalisation, and effective hardware implementation, neural networks (NNs) are able to
provide answers to challenging issues in digital communications. The paper provides a
summary of NNs' uses in digital communications, including channel equivalence and
identification, coding and decoding, vector quantization, image processing, nonlinear filtering,
spread spectrum applications, etc. Finding the right architecture for neural network
techniques that produces the greatest outcomes is the main challenge. The article
demonstrates how to select neural network topologies and how to integrate neural network
algorithms with other methods such as adaptive signal processing, fuzzy systems, and
evolutionary algorithms using a number of examples.
Vicen R ((2018) stated that the study examines mathematical methods used to
comprehend neural network algorithms' learning and convergence behaviour in its last
section.Nonlinear adaptive filters based on a variety of neural network models have been used
successfully for system identification and noise-cancellation in a wide class of applications. An
important problem in data communications is that of channel equalization, i.e., the removal of
interferences introduced by linear or nonlinear message corrupting mechanisms, so that the
originally transmitted symbols can be recovered correctly at the receiver. In this paper we
introduce an adaptive recurrent neural network (RNN) based equalizer whose small size and
high performance makes it suitable for high-speed channel equalization. We propose RNN
based structures for both trained adaptation and blind equalization, and we evaluate their
performance via extensive simulations for a variety of signal modulations and communication
channel models. It is shown that the RNN equalizers have comparable performance with
traditional linear filter-based equalizers when the channel interferences are relatively mild,
and that they outperform them by several orders of magnitude when either the channel's
transfer function has spectral nulls or severe nonlinear distortion is present. In addition, the
small-size RNN equalizers, being essentially generalized IIR filters, are shown to outperform
multilayer perceptron equalizers of larger computational complexity in linear and nonlinear
8
channel equalization cases. Learning Vector Quantization (orLVQ) is a type of Artificial Neural
Network which also inspired by biological models of neural systems. It is based on prototype
supervised learning classification algorithm and trained its network through a competitive
learning algorithm similar to Self-Organizing Map. It can also deal with the multiclass
classification problem. LVQ has two layers, one is the Input layer and the other one is the
Output layer. The architecture of the Learning Vector Quantization with the number of classes
in an input data and n number of input features for any
Bouder C (2000) stated that the Convolutional neural network (CNN) driven by image
recognition has been shown to be able to explain cortical responses to static pictures at
ventral-stream areas. Here, we further showed that such CNN could reliably predict and
decode functional magnetic resonance imaging data from humans watching natural movies,
despite its lack of any mechanism to account for temporal dynamics or feedback processing.
Using separate data, encoding and decoding models were developed and evaluated for
describing the bidirectional relationships between the CNN and the brain. Through the
encoding models, the CNN predicted areas covered not only the ventral stream, but also the
dorsal stream, albeit to a lesser degree; single-voxel response was visualized as the specific
pixel pattern that drove the response, revealing the distinct representation of individual
cortical location; cortical activation was synthesized from natural images with high-
throughput to map category representation, contrast, and selectivity. Through the decoding
models, fMRI signals were directly decoded to estimate the feature representations in both
visual and semantic spaces, for direct visual reconstruction and semantic categorization,
respectively. These results corroborate, generalize, and extend previous findings, and highlight
the value of using deep learning, as an all-in-one model of the visual cortex, to understand and
decode natural vision.
Kechriotis (1994) stated that Structure noise from inhomogeneous micro-structures
makes the detection of flaws present in highly scattering materials difficult. Several techniques
have been applied to improve the signal-to-noise ratio (SNR) in order to make flaw detection
easier. Linear filtering does not provide good results because both structure noise and flaw
signal concentrate energy in the same frequency band. Non-linear filtering can be used to
reduce the structure noise of ultrasonic signals. Therefore, neural networks are applied in this
work for this purpose. In order to use neural networks for non-linear filtering, dynamic
structures must be applied. The easiest way to implement a neural network with the capability
of processing temporal patterns is to consider them spatial ones, applying the signal into a
tapped delay line of finite extension, that is the input of a static neural network (for example, a
multi-layer perceptron). In this work, a dynamic neural network has been built to filter
ultrasonic signals with structure noise, and has been trained with the real-time back-
propagation algorithm, using as inputs 3000 synthetic ultrasonic signals of 896 samples each.
Target signals for training are the same as the ones used as inputs but without noise. The
neural network is trained in order to generate as output the target signal when the noisy input
one is applied. For testing the performance of the non-linear filter, a new set of 500 noisy
signals has been used. The SNR improvement is about 6 dB average. The results show that this
non-linear filtering method is quite useful as pre-processing stage in flaw detection systems.In
9
the context of spectrum surveillance, a method to recover the code of direct sequence spread
spectrum signal is presented, whereas the receiver has no knowledge of the transmitter’s
spreading sequence. The approach is based on an artificial neural network which is forced to
model the received signal. Experimental results show that the method provides a good
estimation, even when the signal power is below the noise power.
Result Analysis
The pie chart represents which age group has given the most responses to the form.
We can see that 42.1% of the responses have come from the age group of 13-18 and the
rest of the responses have come from the 19-59 age group.
The form is an important resource for people in the age group of 13-18 to contribute their
opinions and also be able to get involved in the community. This will help them gain more
experience and it will help improve the community.
This bar graph shows the percentage of people who are familiar with the concept of neural
networks. The target group was asked whether they had some knowledge of it, a basic
understanding of it, or had never heard of it. As we can see from the graph that 10.5% of the
responders are barely familiar, 26.3% is a bit more, 42.1% have a basic idea of the concept,
21.1% are well informed about the concept. This shows that most people are not too familiar
with these concepts. Thus, awareness regarding the concepts of neural networks must be
increased.
10
The pie chart is a visual representation of the importance that people think neural
networks have with respect to communication. We can see that 10.5% think it is very
important, 52.6% think it is important and 26.3% think it holds little importance while the
rest believe it does not hold much importance at all. It is evident that majority of the people
agree that neural networks can be used to improve communication.
This pie chart represents the possibility of further development of digital communication
using neural networks. As we can see, 63.2% of the people agree that further advancements
can be done in the field of digital communication using neural networks, 10.5% people feel
neural networks cannot contribute to any developments in digital communication while
26.3% of the people are not too sure about this and feel that the current level of digital
communication may remain unchanged.
This bar graph provides an overview of people’s experience with the previously used
methods to improve their communication abilities. We can see that cumulatively 21% of the
people did not have a very good experience with the methods they used. A majority of the
people, i.e., 57.9% had a satisfactory experience while 21.1% were quite satisfied with the
methods they used.
This shows that there is a high scope for improvement in the methods that people use to
enhance their communication skills and neural networks can probably contribute to this.
11
This pie chart shows whether we can use neural networks to improve communication. As
you can see, 68.4% of people think that it can improve communication, while 5.3% of people
think that it cannot improve communication, while 26.3% of people are not sure about the role
neural networks will play in the improvement of communication.
This pie chart shows that 47.4% of people use communication-based apps to learn new
languages; 26.3% of people use them to become more fluent in universal languages; and
26.3% of people use them to improve their vocabulary; while no one uses communication-
based apps to improve their pronunciation.
This pie chart shows that 42.1% of people use apps to improve their communication skills,
and 42.1% of people do not use any apps, while 15.8% of people are not sure whether they
have used any apps or not.
This pie chart shows that 11.1% of the people strongly agree and 77.8% of the people
agree that neural networks can positively improve communication. Rest 5.6 % people are
strongly against this idea and 5.6% are natural about this.
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According to the above pie chart, 55.6% of the crowd knows about the implementation of
neural networks in improving communication. The rest don't have any idea regarding this
concept.
In terms of the advantages of Neural Networks in Digital Communication, 27.8% of people
think that it has great speed, 16.7% of people think that it will solve uncertain data, 44.4% of
people think that it has all the above-mentioned advantages, and the rest, 11.1% of people
think it helps solve data trafficking.
The above graph represents the frequency of people using different applications, which
helped them to improve their communication skills. The majority of people use Duolingo while
the rest use Grammarly and social media platforms such as Bumble, Twitter, Google Translate,
etc., and a few don't know about examples of such applications.
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The above pie chart represents that half of the people agree that such programs using
neural networks should be implemented in schools/colleges/offices to improve the skills of
individuals. In fact, 27.8% of the population strongly supports this decision. The rest think that
this might not be the correct solution.
This bar graph illustrates how probable it is for individuals to use an app if it has been
recommended by a professor to help them improve their knowledge of universal languages.
6.3% of respondents indicated that they were not really interested. 31.3% expressed some
curiosity, 56.3% expressed a genuine interest, while 6.3% expressed the greatest level of
interest.
This pie chart shows that 81.3% of the respondents agree that neural networks are used to
mimic the way the human brain operates, while the rest do not agree with it.
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This graph illustrates the accuracy with which an individual can judge their own
communication skills. 56.3% feel they can judge their skills with an average efficiency of 35%,
which proves that most people require an outside source such as communication apps to
judge their efficiency.
There are 3 major types of neural networks in total. This has been answered correctly by
50% of the people. It shows that while people are aware of neural networks, the majority are
not too well versed in them.
This bar graph depicts that most people think that improving their communication skills
would greatly benefit them, while only 12.5% and 25% of people think it would not benefit
them too much or would benefit them in an average capacity, respectively.
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This pie chart shows that 62.5% of people think that there is a need for a better system to
enhance their communication skills; 18.8% of people think that there is no need for a better
system; and 18.8% of people are not sure about that.
This pie chart shows that 43.8% of people think that communication skills play an
important role in an individual’s personal life, while 56.3% of people think that
communication skills play a more important role in an individual’s professional life.
This pie chart shows that 18.8% of people prefer to learn a new language through a
communication app. 50% of the population wants to learn a new language organically. 18.8%
of people want to learn a new language, while 12.5% of people don’t want to learn any new
language.
Conclusion
Overall, after a good retrospection of the topic of” Communication using Neural Networks" and
going through the public analysis and transcoding results, we come to the conclusion that our
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target group, which will benefit the most from this technology, lies between the age groups of
18-55. They will be using this technology on their smart devices such as laptops, computer
systems, phones, and online social media networking sites. However, people are not very
familiar with this concept and need to be introduced to it more proficiently. Most of the
population agree that neural networks are very important for communication, and we have
already seen examples of this enormous networking through applications such as Duolingo
and social media sites, such as Twitter, Instagram, etc. Moreover, people have hope that neural
networks have the potential to improve communication. According to data analysis, the most
common reason for people to use communication-based apps is to improve their
communication skills, vocabulary, fluency and pronunciation.
Thus, in conclusion, neural networks can be an integral part of the future of
communication and can help several people enhance their communication skills.
References
1. Farsad, N. and Goldsmith, A., 2018. Neural network detection of data sequences in
communication systems. IEEE Transactions on Signal Processing, 66(21), pp.5663-5678.
2. Ibnkahla, M., 2000. Applications of neural networks to digital communications–a survey.
Signal processing, 80(7), pp.1185-1215.
3. Eriksson, T.A., Bülow, H. and Leven, A., 2017. Applying neural networks in optical
communication systems: Possible pitfalls. IEEE Photonics Technology Letters, 29(23),
pp.2091-2094.
4. Guo, J., Wang, J., Wen, C.K., Jin, S. and Li, G.Y., 2020. Compression and acceleration of neural
networks for communications. IEEE Wireless Communications, 27(4), pp.110-117.
5. Albers, H.E., 2012. The regulation of social recognition, social communication and
aggression: vasopressin in the social behavior neural network. Hormones and behavior,
61(3), pp.283-292.
6. Principe, J.C., Ibnkahla, M., Sulyman, A.I. and Cao, Y., 2018. Neural Networks and Adaptive
Signal Processing. Circuits, Signals, and Speech and Image Processing, pp.22-1
7. Zhu, B., Wang, J., He, L. and Song, J., 2019. Joint transceiver optimization for wireless
communication PHY using neural network. IEEE Journal on Selected Areas in
Communications, 37(6), pp.1364-1373.
8. Linda, O., Vollmer, T. and Manic, M., 2009, June. Neural network-based intrusion detection
system for critical infrastructures. In 2009 international joint conference on neural
networks (pp. 1827-1834). IEEE
9. Farsad, N. and Goldsmith, A., 2018. Neural network detection of data sequences in
communication systems. IEEE Transactions on Signal Processing, 66(21), pp.5663-5678
10. Xu, L., Wang, J., Wang, H., Aaron Gulliver, T. and Le, K.N., 2020. BP neural network-based
ABEP performance prediction for mobile Internet of Things communication systems.
Neural Computing and Applications, 32(20), pp.16025-16041.
11. Hu, G., Chen, S.H.K. and Mazur, N., 2021. Deep neural network-based speaker-aware
information logging for augmentative and alternative communication. Journal of Artificial
Intelligence and Technology, 1(2), pp.138-143.
17
12. Chen, S., Mulgrew, B. and Grant, P.M., 1993. A clustering technique for digital
communications channel equalization using radial basis function networks. IEEE
Transactions on neural networks, 4(4), pp.570- 590.
13. Kojić, N., Reljin, I. and Reljin, B., 2006. Neural network for optimization of routing in
communication networks. Facta universitatis-series: Electronics and Energetics, 19(2),
pp.317-329.
14. Feng, J., Tse, C.K. and Lau, F.C., 2003. A neural-network-based channel-equalization
strategy for chaosbased communication systems. IEEE transactions on circuits and
systems I: fundamental theory and applications, 50(7), pp.954-957.
15. Chi, N., Zhao, Y., Shi, M., Zou, P. and Lu, X., 2018. Gaussian kernelaided deep neural network
equalizer utilized in underwater PAM8 visible light communication system. Optics express,
26(20), pp.26700-26712.
16. Kosko, B., 1994. Fuzzy systems as universal approximators. IEEE transactions on
computers, 43(11), pp.1329-1333.
17. Kosko, B., 1994. Fuzzy systems as universal approximators. IEEE transactions on
computers, 43(11), pp.1329-1333.
18. Ibnkahla, M. and Castanie, F., 1996. Neural Networks for Communications and Signal
Processing: Overview and New Results. Signal Processing in Telecommunications, pp.358-
373.
19. Jueschke, P. and Fischer, G., 2017, September. Machine learning using neural networks in
digital signal processing for RF transceivers. In 2017 IEEE AFRICON (pp. 384-390). IEEE.
20. Egmont-Petersen, M., de Ridder, D. and Handels, H., 2002. Image processing with neural
networks— a review. Pattern recognition, 35(10), pp.2279-2301.
21. Xin, M. and Wang, Y., 2019. Research on image classification model based on deep
convolution neural network. EURASIP Journal on Image and Video Processing, 2019(1),
pp.1-11.
22. Ibnkahla, M., 2000. Applications of neural networks to digital communications–a survey.
Signal processing, 80(7), pp.1185-1215.
23. Kechriotis, G., Zervas, E. and Manolakos, E.S., 1994. Using recurrent neural networks for
adaptive communication channel equalization. IEEE transactions on Neural Networks,
5(2), pp.267-278.
24. Wen, H., Shi, J., Zhang, Y., Lu, K.H., Cao, J. and Liu, Z., 2018. Neural encoding and decoding
with deep learning for dynamic natural vision. Cerebral cortex, 28(12), pp.4136-4160.
25. Vicen, R., Gil, R., Jarabo, P., Rosa, M., Lopez, F. and Martınez, D., 2004. Non-linear filtering of
ultrasonic signals using neural networks. Ultrasonics, 42(1-9), pp.355-360.
26. Bouder, C. and Burel, G., 2000. Spread spectrum codes identification by neural networks.
Systems and control: theory and applications, pp.257-262
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CHAPTER 2
ARTIFICIAL INTELLIGENCE AND MACHINE LEARING IN E-LEARNING
Siri R Kulakarni (21BCE2351), Ishita Singh (21BCE2448), Ojasvi Bhushan (21BCE0619)
Girish Ashok Wagh (21BKT0006)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
Artificial Intelligence (A.I) systems offer effective (AI) support for online learning and teaching, including
personalized learning which is machine learning "basically, automating instructors’ routine tasks, and
powering adaptive assessments and machine learning. Education is a form of personalized learning. The
goal of introducing AI and ML systems in e-learning and teaching by Improving efficiency and effectiveness
helps both students and teachers in many ways. A questionnaire will be sent to students regarding the
personalization of e-learning wing AI and ML. The data will be analyzed by the response of 50 students.
The data will show that students will have a significant positive response regarding personalized attention
in eLearning. The main motive of this survey will be to investigate the advantage of introducing AI and ML
in e-learning platforms.
Introduction
Artificial Intelligence and machine learning is growing very fast in ed tech ai and ml are the
key to modernizing it. Can AI and ml help in learning? The answer is yes! how will be
explained in the research article done by our team?
AI and ml can help in making things more user-friendly and help in the selection of the
best course out of the available courses. AI is the ability of machines that replicate intelligent
human behaviors like analyzing and making decisions. Machine learning and extended
application of ai which provides systems to learn from experience without being programmed
to perform a particular task AI and ML can help by taking a step towards predictive analysis,
process efficiency is not a far-sighted dream, etc.
AI and ML are very commonly heard terms these days. They have become key drivers of
today’s technological development. AI and ML are used in many fields these days. They are
commonly used in E-commerce, self-driving cars, navigation, social media, Marketing, Virtual
reality experience, metaverse, robotics, healthcare, agriculture, etc. Before learning about the
applications of AI and ML in E-Learning, we must understand what AI and ML means.
IBM says "Artificial Intelligence (AI) leverages computers and machines to mimic the
problem-solving and decision-making capabilities of the human mind". Unlike the natural
intelligence exhibited by animals, including humans, robots can exhibit artificial intelligence
(AI), which is intelligence.
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Machine learning (ML) is a branch of research that focuses on comprehending and
developing "learning" techniques, or techniques that use data to enhance performance on a
certain set of tasks. It is seen as a part of artificial intelligence.
The main advantage of incorporating AI and ML in E-Learning platforms is personalized
learning. The other advantages are advanced analysis of learner performance, chatbots,
deeper engagement with VR, and many more.
The use of artificial intelligence in education is currently a hotly debated issue. Whether or
not AI should be utilized to educate pupils is a contentious issue. Many claim that instructors
will be replaced by AI, eliminating the human component of education. However, using AI in
education has a lot of benefits. AI can grade essays and papers far more swiftly than humans
can. In turn, this will provide teachers more time to work with students on honing their critical
analysis and thinking abilities. Additionally, it would allow teachers to focus on certain
students who might benefit from their guidance. Insights into student learning preferences
and practical feedback for students who require more practice with particular subjects or
skills are two more ways that AI might support human teachers.
To provide each student with a customized educational experience, machine learning in
education is a type of personalized learning. The students are given direction for their learning
in this setting, are free to learn at their own pace, and choose what to learn.
A staggering 270% surge in the past four years can be seen in the 2019 Gartner C10
Surrey, which found that 37% of organizations with employees aged 18 and older had
deployed some sort of. Additionally, according to the same assessment, 80% of newly
emerging technologies will be Al-based by 2021. Instead of using a one-size-fits-all strategy,
e-learning platforms that use artificial intelligence may tailor the information to the needs and
prior knowledge of the student. A data-driven strategy called personalized learning, also
known as adaptive learning, continuously monitors "each student's performance, utilizing
machine learning algorithms to forecast outcomes and adjust content to each student's skills
and preferences. Therefore, the platform will continue to modify the content and levels based
on the student's success until they have fully understood the topic. Making tailored learning
paths for each student with pertinent topics increases time efficiency as well as levels and
student motivation.
Distance learning, also known as e-learning, is a defined framework for processing and
learning that makes use of the internet to enable learning to be done remotely while
communicating electronically. The growing popularity of online learning and learners has
necessitated the extension of traditional e-Learning interface configuration beyond the core of
the vision channel to include intelligent claims as well as exciting elements. This can be done
easily using AI and ML and e-learning AI office effective support for online teaching and
learning including personal rising learning which is machine learning. This can be done easily
using AI and ML and e-learning AI office effective support for online teaching and learning
including personal rising learning which is machine learning. So, both e-learning and AI will go
hand and hand with education transformation ML. ML is a brought up-set of AI based on the
capability of machines to learn from data without being programmed by a human. Deep
machine learning is not exactly AI but rather AI method that teach the computer to
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independently find solution to various problems. Computers do analytic work and determined
patterns faster than humans using preloaded data and special algorithm it is even better than
setting up an automation system for iterative task performance.
Literature Review
According to Williamson in 2018, Universities are increasingly being organized and governed
using digital data. Data about higher education may be gathered, processed, and disseminated
thanks to sophisticated new data infrastructures with both human and nonhuman players and
the assistance of political, economic, and social factors. Instead of only being seen as
technological initiatives to advance the enterprise, HE data infrastructures should be seen as
useful relays of political objectives. In the UK's higher education system, this essay focuses on
a big ongoing data infrastructure project. It also looks at how these technologies integrate with
political demands for market reform. The infrastructure's sociotechnical networks of
enterprises, software applications, industry standards, dashboards, and visual analytics are all
investigated. The research focuses on how He is being redefined by the political project of
marketization while also going through reform to reach the idealistic ideal of the "smarter
university."
In 2018, Ilkka stated that the current state of artificial intelligence (AI) and any potential
impacts it may have on teaching, learning, and education are discussed in this study. It
provides conceptual support for well-informed research, policy-oriented work, and forward-
thinking initiatives that address the opportunities and challenges brought on by current
breakthroughs in AI. Although the report is aimed at policymakers, it also contains valuable
information for those developing AI technology and researchers who are examining how AI is
influencing the economy, society, and the future of education and learning.
According to Tuomi in 2018, this paper discusses artificial intelligence's (AI) present stage
of development and prospective effects on education, learning, and teaching. It provides the
theoretical underpinnings for informed policy-oriented work, research, and forward-looking
initiatives that address the benefits and difficulties brought about by recent advancements in
AI. The paper makes contributions that will be of interest to researchers and developers of AI
technology who are examining the effects of AI on the economy, society, and the future of
education and learning, even though it is primarily intended for policy makers.
In 2019, Zawacki-Ritcher stated that, according to a number of international assessments,
artificial intelligence in education (AIEd) is one of the more recent fields of educational
technology. Despite being accessible for close to 30 years, educators are still confused about
how to use it pedagogically on a broader scale and how it might actually have a big impact on
teaching and learning in higher education. This study seeks to provide a summary of the
literature on AI applications in higher education through a systematic review. Out of 2656
initially found publications for the years between 2007 and 2018, 146 articles were included
in the final synthesis using precise inclusion and exclusion criteria. The descriptive findings
show that STEM and computer science-related subjects are most commonly represented in
AIEd articles, and that empirical research most frequently used quantitative approaches. The
findings are categorized into four groups of AIEd applications in institutional and
21
administrative services, academic support services, assessment and evaluation, and adaptive
systems and personalization: 1. profiling and prediction, 2. assessment and evaluation, 3.
adaptive systems and personalization, and 4. intelligent tutoring systems. The findings draw
attention to the almost total absence of critical reflection on the challenges and risks
associated with AIEd, the shaky connection to theoretical pedagogical perspectives, and the
need for more research on the ethical and pedagogical approaches to AIEd implementation in
higher education.
According to Rosemary Luckin in 2019, we have gained a tremendous deal of knowledge
about human learning through interdisciplinary study in the learning sciences, and as a result,
we are better able to instruct and train individuals. It is now necessary to better guide the
development of Artificial Intelligence (AI) technologies for use in training and education using
the same body of research. In this work, we utilize three case studies to show how learning
sciences research may guide the careful analysis of rich, varied, and multimodal data so that it
can be used to support teachers and scaffold students. We are better equipped to create AI
algorithms that can analyses rich educational data quickly as a result of our improved
understanding of how to best inform data analysis through the use of learning sciences
research. We may then use these AI algorithms and technologies to provide learners with
scaffolding that is quicker, more sophisticated, and individualized. However, most commercial
AI developers have minimal knowledge of the study of learning sciences, and frequently have
much less knowledge of teaching or learning. We contend that inter-stakeholder partnerships
involving AI developers, educators, and researchers are necessary if we are to guarantee that
AI technologies for use in education and training embody such prudent analysis and learn in a
way guided by the learning sciences.
According to Davies in 2020, The usage of a customized learning route is one of the best
techniques for archiving the best eLearning results. The use of artificial intelligence (AI) and
machine learning (ML) is one of the most important advances in modern eLearning since it
enables flexible learning and conducts process customization based on the particular needs of
each user. Artificial intelligence (AI) technologies are the most effective at analyzing each
learner's unique needs and creating a learning path with tailored instructional materials. One
possible result of incorporating ML and AI into the eLearning process is the usage of AI-
powered chatbots. Chatbots have the potential to significantly simplify the learning process by
linking students with the materials they require that have already been tailored to their
specific learning needs. By offering responses customized to each learner's specific needs
within the eLearning system, chatbot integration bridges the real-time consultation gap that is
present with offline courses but not with online courses. For modern software engineers,
creating a chatbot is an easy task. It is difficult to understand a chatbot's behavior and source
language, which calls for the development and use of new analytic models and algorithms.
This study presents a technique for developing a chatbot for an e-learning system that may
personalize consulting materials according to the preferences of the learner.
According to Alyahyan in 2020, Student achievement in educational institutions is
important since it is usually used as a performance indicator. At-risk pupils' achievement can
be markedly raised with the use of preventative measures and early detection. Recently,
22
prediction-related machine learning techniques have been heavily employed. Despite
numerous examples of success in the literature, educators who have a background in
"computer science," or more precisely "artificial intelligence," are more likely to be able to use
these techniques. In order to use data mining technologies successfully and economically,
many decisions must be taken, such as how to define student success, which student traits to
emphasize, and even which machine learning method is most appropriate for the specific issue
at hand. This initiative aims to provide a step-by-step guide for educators who wish to forecast
student progress using data mining approaches. A review of the literature has been done in
order to do this, and the state-of-the-art has been organized into a systematic approach where
potential decisions and parameters are completely covered and supported by arguments.
This initiative will increase educators' access to data mining tools, enabling maximum
potential for their usage in the educational sector.
In 2020, Renz stated that as a result of the ongoing datafication of our social reality, new
data-based business models have been developed. This increase is also visible in the education
sector. A growing number of educational technology (EdTech) companies are introducing
data-based teaching and learning solutions into the conventional education sector,
permanently altering the market. Nevertheless, despite the current market dynamics, there
are very few business models that take advantage of the potential of Learning Analytics (LA)
and Artificial Intelligence (AI) to create adaptive teaching and learning routes. The key
subjects of this study, which focuses on EdTech companies, are the factors that influence
data-based teaching and learning paths at the moment. According to the findings, learning
analytics (LA) are incorporated into EdTech firms' current business models on three different
levels: basic learning analytics, learning analytics and algorithmic or human-based
recommendations, and learning analytics. The discourse analysis demonstrates the
fundamental differences between the cutting-edge concept of education and information
transfer and the traditional educational ideal. The debate over AI-based learning systems is
motivated by the need for flexibility and individualization, but the lack of data sovereignty,
ambiguity, and lack of data understanding are also impeding the development and use of
workable solutions.
According to Guan in 2020, after examining twenty years' worth of educational research,
they discovered 400 research articles on the application of AI and DL techniques in teaching
and learning. The growth of AI and DL research themes in the leading scholarly journals was
examined by a computerized text analysis. Due to the field's dynamism, they carry out this to
determine the most common terms associated with AI-enabled pedagogical adaptation
research in each decade. By examining the main research subjects and historical trends from
2000 to 2019, we demonstrate how some study topics appear to have weathered the test of
time while others have experienced peaks and troughs as sophisticated technologies in
education evolve over time. What’s more is that their analysis highlights new patterns and
paradigm shifts that are gaining prominence in the field of educational research. The results,
for instance, show a decline in research on conventional tech-enabled instructional design and
an increase in learning analytics and student profile models. The results of this study open a
dialogue regarding the benefits and drawbacks of tailoring education with AI and DL.
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In 2021, Orozov stated that their report presents a study on machine learning that uses
visual data. The basic goal is to design and develop a Programme that, using facial coding
system (FACS) developed by Ekman and Friesen, can identify different human emotions from
facial photographs. The ML. Net framework implements a method for multi-class classification
based on an ML agent of the Supervised Learning kind. After being trained, the model can
recognize the emotional state of a person in a provided image (photo). The created application
will be used in an electronic learning environment. Changes in learners' emotional states are
desired in order to assist them with the cognitive demands placed on them during the learning
process.
According to Hahn in 2021, the uptake of online learning now heavily relies on automated
evaluation and feedback mechanisms. These techniques include multiple-choice tests and
machine learning-based essay grading (ML). Massive Open Online Courses (MOOCs) wouldn't
be viable without them as a learning environment. This technique has given rise to numerous
fascinating fields of research, such as the formulation of queries on the precision and accuracy
of ML sorting algorithms. The use of automated assessment and feedback as learning tools is
examined in this research using data from 125 studies that were published between 2016 and
2020 in peer-reviewed journals and conferences. This report gives a broad overview of the
trends, obstacles, and unresolved problems in this field of study. The findings indicate that
automatic grading and feedback have several advantages. The ability to scale the number of
students without increasing the number of teachers proportionately, an enhanced learning
experience for students by reducing the time between submitting work for grading and
receiving feedback, and eliminating bias in grading are the three most significant advantages.
It's incorporated. However, there are certain downsides to these methods. The fundamental
issue is the discouragement of coming up with creative solutions that are different from or do
not fit what is anticipated. Another issue is that students could be taught how to respond to
questions rather than how to understand ideas. If there is a correct answer, the answer may be
leaked on the Internet, making it easier for students to avoid solving the problem. Collectively,
each of these shortcomings represents an opportunity to look for ways to improve the
technology for using these tools. Students will find it simpler to avoid solving the problem if
there is a right answer because the solution might be released online. When considered as a
whole, each of these flaws offers a chance to consider how the technology for employing these
tools can be enhanced.
In 2021, Zhang stated that their article provides an in-depth examination of selected
empirical research on artificial intelligence in education (AIEd) published in 1993-2020, as
collected in the Web of Sciences database and selected AIEd-specialized publications, from
various educational perspectives. Various methods, including categorical meta-trends analysis,
content analysis, and selected bibliometrics, were used to thoroughly analyse 40 empirical
studies in total. This article summarizes the current state of AIEd research, highlights a few
AIEd technologies and applications, discusses the proven and potential educational benefits of
these technologies, bridges the knowledge gap between AIEd technological advancements and
their educational applications, and offers specific examples and inspirations for both AIEd
technology developers and educators leading the charge on AI innovations in education. Rich
24
discussions are also provided on both practical applications and potential directions for future
study. The creation of AIEd calls for significant efforts to solve privacy and AI ethics concerns
as well as interdisciplinary and transdisciplinary collaboration in vast, protracted research
and development projects.
In 2021, Seo stated that Artificial intelligence (AI) technologies effectively support online
learning and teaching by automating boring tasks for teachers and facilitating adaptive
evaluations. Despite how appealing the potential for AI is, it is not yet apparent how AI
systems will affect the customs, expectations, and culture that surround interactions between
students and teachers. Learner-instructor contact has a substantial impact on student
satisfaction and learning outcomes in online learning (including communication, assistance,
and presence). It is critical to comprehend how students and instructors view the influence of
AI systems on their interactions in order to spot any gaps, blockages, or other impediments
preventing AI systems from reaching their full potential and jeopardising the safety of these
interactions. In order to meet this demand for forward-thinking assessments, we used Speed
Dating with storyboards to gauge the genuine thoughts of 12 students and 11 teachers on
various use cases of possible AI systems in online learning. Results show that participants see
the implementation of AI systems in online learning to enable scaled individualized learner-
instructor interaction, but at the risk of going against social norms. Even though AI systems
have been praised for improving both the quantity and quality of communication, for
providing large-scale settings with just-in-time, tailored support, and for fostering a sense of
connection, there have been some concerns raised about issues with accountability, agency,
and surveillance. These conclusions have implications for how AI systems ought to be
developed to guarantee explain ability, human interaction, and thorough data collection and
presentation. The study's overall contributions include the creation of technically feasible AI
system storyboards that support learner-instructor interaction positively, the use of speed
dating to gather students' and instructors' AI system concerns, and the suggestion of practical
applications for maximizing the positive effects of AI systems while minimizing the negative
ones.
According to Valentin in 2021, Information technology has revolutionized the way people
travel, schedule their time, and get information. Data management and development
procedures gave rise to mechanisms like artificial intelligence (AI) and machine learning (ML).
Many diverse industries, including education, have identified the use of these processes in
business as a trend that will change the game. As a result, educational platforms and
applications are better matched to the requirements and expertise of learners, increasing the
effectiveness of instruction. As a result, higher education and e-learning institutions have a lot
of potential for using AI and ML (HEI). Consequently, the article's objective is to assess its
potential and application areas in higher education through secondary research, document
analysis (literature review), content analysis, and primary research (survey). Multiple
academic, scientific, and commercial sources were employed as reference points for this study
to provide a bigger image of the research topic. To gather data and information on the level of
understanding of AI and ML possessed by the student population, a survey of 103 students in
the Republic of Serbia was also conducted. The purpose of this study was to better understand
25
the prospects and problems associated with AI and ML in HEI. The study addresses important
themes such as general knowledge and research base perspectives on AI and ML in HEI, best
practices for using AI and ML in HEI, student knowledge of AI and ML, and student attitudes
about AI and ML opportunities and obstacles in HEI. The Correlation Matrix was provided,
followed by the Composite Reliability, as part of statistical analysis to determine whether the
indicators were deemed reflexive and, in this case, belonged to the same theoretical
dimension. Regression analysis was then used to assess the outcomes. The findings showed
that AI and ML are crucial technologies that improve learning, particularly through students'
talents, collaborative learning in higher education, and a welcoming research environment.
In 2021, Divyansh Rana stated that for the benefit of school-going pupils, this study
compares modern technologies currently being employed in the field of education. This study
focuses on the efficacy of the tools and technologies being utilized often in Indian school
systems. The impact of the various characteristics on students was also evaluated from an
educational and technological standpoint in the research.
According to Alexander Huls in 2021, Cyberattacks on K–12 institutions were a major
worry even before the pandemic. The threat has only grown as remote learning has become
more popular. The exposed edges of the network have dramatically increased as a result of
supporting digital transformation projects and a remote work style, according to Bob Turner,
field CISO of higher education at Fortinet. At the same time, malware, ransomware, and other
threats continue to pose a hazard to schools by taking advantage of endpoint devices that are
not always properly protected. An assault may have lasting ramifications. According to IBM's
"2021 Cost of a Data Breach Report," identifying and containing a data breach can take an
average of 287 days, and the longer it takes, the more expensive it is to do so. Machine
learning-enhanced endpoint protection is a new solution that K–12 institutions have
discovered. Machine learning is a form of artificial intelligence that makes use of powerful
computing resources and algorithms that have been trained on a lot of data. It gains a
thorough understanding of how to use that knowledge to monitor and provide insights at a
scale that is beyond human capacity.
In 2022, Wijayawardena stated that one of the key responsibilities directly assigned to
online platforms under COVID-19 is education. The use of electronic learning in Sri Lanka's
secondary school system is covered in the study. Students and teachers can access
information, resources, and tools through an E-Learning system, which is a Learning
Management System that includes a variety of online activities. The proposed system's three
main functions are the chatbot, final grade prediction, and student weak area prediction. A
recent study found that chatbots are increasingly prevalent in many different apps,
particularly those that offer the user intelligent support. Because of this, these systems
typically use Chatbots to speed up the aid process because they can quickly and accurately
answer the user's questions. The use of a Chatbot prototype in the educational setting is
covered in this study as a means of assisting pupils. The first goal was to develop a special
architectural and communication model that would help students get the appropriate
answers. The system depends heavily on the component that forecasts final grades. Because
when grades are assigned based on marks, students can examine and work on their weak
26
areas. This will be advantageous for both teachers and students. Weak area prediction also
heavily relies on the capacity to recognize each topic's weak areas and develop personalized
student progress plans that account for each student's weak subjects and subject areas.
Students are encouraged to acquire higher grades more readily since this portion is largely
focused on students' weak areas and strengthens those weak areas by providing a variety of
learning tasks. These are the system's essential elements, which work together to make it an
effective e-learning platform for both teachers and students.
In 2022, Murtaza stated that through a customizedeLearning system, users can learn more
effectively. Instead of providing each learner with the same content as in a standard e-learning
system, a personalized learning system gives them their own learning materials and
assessments. Personalization chooses the best information for each learner based on their
level of comprehension and preferred learning styles using methodologies that depend on
Artificial Intelligence (AI). This study discusses the requirements and challenges for a
customized e-learning system. The study focuses on outlining four research questions:
defining critical elements of customized learning, outlining state-of-the-art research in the
area, utilizing the benefits of AI in customized learning, and determining future research
objectives. The study carefully examines current research publications in order to offer
solutions to these problems. It provides a comprehensive study of the choices for offering
customized e-learning solutions. It goes into great detail about a number of learning theories
and models, which are crucial for providing individualized training. It proposes a helpful
framework that can offer each learner tailored online training. The suggested structure is
composed of five modules: the Data Module, the Adaptive Learning Module, the Adaptable
Learning Module, the Recommender Module, the Content, and the Assessment Delivery
Module. Our analysis also highlights crucial topics for further research. The paper provides an
overview of the requirements for such a system, its approach, and the problems that need to
be handled. Academicians and researchers will find it useful.
According to Munir in 2022, The use of artificial intelligence and machine learning
techniques has exploded over the past several years across all disciplines as a result of the
ever-increasing volume of data and the growing requirements of higher education, such as
digital education. A lot of data about students in digital education is available in online
educational information systems, which is similar to this. This educational data can be utilized
in conjunction with machine learning and artificial intelligence techniques to improve digital
education. This work has two important contributions. The investigation starts by doing a
thorough and repeatable process of literature review. Second, the paper summarizes and
elucidates the key points made in the literature regarding the use of AI-based algorithms in
digital education. The study's findings are summarized in six categories that relate to the use
of computers in digital education. According to the data gathered for this study, machine
learning and deep learning techniques are used in a number of digital learning domains. Using
intelligent tutors is one of these themes, along with dropout and performance projections,
analytics, group-based learning, automation, and adaptive and predictive learning. The
employment of artificial neural network and support vector machine techniques, as well as
27
random forest, decision tree, naive Bayes, and logistic regression algorithms, appears to be
prevalent among all the themes that have been identified.
In 2022, Gazzawe stated that for more than 20 years, e-learning has been regarded as
being more flexible and quicker than other traditional ways, especially when it comes to
knowledge development. Parallel to this, e-learning now has a strong foundation to stand on
thanks to the advancement of information technology applications, such as mobile
applications and artificial intelligence (AI). Particularly in the area of education, e-learning
advancements can be found to be particularly useful. Machine learning, which is viewed as a
form of personalized learning that enables students to create their own experiences, might be
used to provide each student a specific unique experience. Despite the fact that online and AI-
enabled mobile applications are among the most popular e-learning platforms and may be
used to measure a variety of factors and make predictions about the quality of e-learning, we
cannot ignore the complexity of use. This study shows how machine learning impacts how well
consumers can assess the course and its contents' ease and clarity. This analysis, which builds
on a previous study, examines user preferences to pinpoint the realities and complexity
around web and mobile applications incorporating AI. The second phase, which is described in
this study, involved data collection from two user groups (aged 21 to 30), with the goal of
examining user preferences when utilizing an application. In light of their greater potential for
development and improvement, web-based applications have a more promising future for e-
learning than mobile ones, claims the paper. The conceptual framework described in the
paper's conclusion operates as a machine that stimulates various kinds of information and
uses e-learning tools to support artificial intelligence methods. Future research on the
consequences of AI-enabled e-learning for costs, quality, and usability in the educational
industry can be built on the solid basis provided by this work.
According to Kadduora in 2022, Exams and evaluations have a significant influence on
every student's life because they determine their possibilities for the future and for a
profession. Every aspect of life has been negatively impacted by the COVID pandemic,
including academia. Face-to-face real-time exams and regularly planned classroom training
were impractical since they would not be able to guarantee safety and prevent widespread
infection. During these trying times, technological advancements intervened to enable
students to continue their studies uninterrupted. Machine learning is necessary for the real-
time online conversion of educational institutions to the digital age. While the area was under
lockdown, machine learning techniques allowed for online instruction and testing. A rigorous
study of how machine learning functions in lockdown test management systems was
conducted using 135 papers from the previous five years that were analyzed. Throughout the
whole exam cycle, including exam administration, grading, and pre-exam planning, the
significance of machine learning was evaluated and addressed. Whether they were supervised
or unsupervised, the machine learning algorithms were identified and categorized in each
phase. Exam fundamentals including authentication, scheduling, proctoring, and fraud or
cheating detection are all carefully explored using machine learning approaches. The main
characteristics, such as identifying at-risk students, adaptive learning, and student monitoring,
are incorporated for a greater understanding of how machine learning functions in exam
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preparation. Following that, its management of the post-examination procedure is covered.
The review concludes by examining the issues and difficulties that machine learning poses for
the examination system as well as possible solutions.
In 2022, Koć-Januchta stated that the swift adoption of instructional technology in higher
education aims to increase the efficacy and engagement of learning. The cognitive load
hypothesis also draws attention to the constraints of human cognitive architecture and urges
educational tool designers to provide instructional materials that fully utilize students'
cognitive capacities. We investigated how college students learned from a digital biology
textbook supplemented by AI that includes a 5000-concept knowledge base and algorithms
that support question-and-answer sessions. The study aimed to define three sub-types of
cognitive load (intrinsic, germane, and extraneous) and their relationships with learning gain,
self-regulated learning, and usability perception when students interacted with the AI-
enriched book throughout an introductory biology course. We found that students had an
effective pattern of learning, with relevant cognitive load being significantly higher than both
intrinsic and extraneous loads, indicating that they were actively involved in learning
throughout the investigation. An important correlation with germane load and accessing
related recommended questions suggests that the AI-book may support deep learning. The
findings also showed that perceived non-optimal design, which takes cognitive resources away
from meaningful processing, was linked to lowered learning gains. Students had substantially
better than negative opinions of the AI-book, though. The findings open up new avenues for
investigating various types of cognitive burdens in relation to higher education coursework
using cutting-edge digital tools. The outcomes emphasize the value of a seamless integration of
instructional technology with human cognitive architecture.
According to Salas-Pilco in 2022, the use of artificial intelligence (AI) in a range of
industries, including law, banking, and medical, has attracted a lot of research interest in the
last ten years. Recently, research has begun to focus on the great potential of using AI in
education. It is consequently necessary to do a thorough analysis of the literature on AI in
education. The use and uses of it in higher education institutions in Latin America are
examined in this article. This review, which begins by identifying the research devoted to
educational innovations made feasible by the use of AI technology, analyses AI applications in
three aspects of education: learning, teaching, and administration. Each study is reviewed in
terms of the main educational subject, the AI techniques (such as machine learning, deep
learning, and natural language processing) that were used, and the tools and algorithms that
were used. Predictive modelling, intelligent analytics, assistive technology, automatic content
analysis, and image analytics are the main applications of AI in education, according to the
research. Another indication that AI applications aid in the provision of high-quality education
is their usage to address important educational issues, such as identifying students who are at
risk of dropping out. The key findings from the analysis of the application of AI technology in
higher education in the Latin American context are presented as the essay comes to a close.
In 2022, Galvis stated that This study seeks to aid academics interested in non-face-to-face
forms of higher education in making decisions about the use of digital and educational
technologies. ET can be promoted within the scope of their organizations (DET). In order to
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help students, develop abilities that will be valuable for both their personal and professional
development, this organizational change involves the use of flexible instructional strategies
based on technology. In light of this, in 2018 we identified and followed six leading higher
education institutions across three continents that have long been performing technology
supported educational innovation initiatives. Two of the analyzed experiences use eLearning
as an addition to the face-to-face modality, one employs learning, and the remaining
experiences combine eLearning and learning. The meta-analysis of the cases was carried out in
2019 in accordance with recommendations from (Stake in The Art of Case Study, Sage
Publications Inc., 1995) and qualitative research that seeks to comprehend the examples from
three dimensions: education, technology, and organization. We identified what each one does,
how they do it, and what success criteria need to be taken into account. Due to the fact that the
data was gathered before the 2020 pandemic and that this problem created structural
inequalities in society and higher education, it was deemed necessary to check the pulse of the
ET mediated with DET at three of the six institutions studied by the end of 2020. The goal was
to improve the meta-conclusions analysis and learn from the choices made when settings,
resources, and techniques had to be changed forcibly in order to continue offering high-quality
higher education. We defined what each one performs, how they do it, and what success
factors must be taken into consideration. The data was acquired prior to the 2020 pandemic,
and because this issue led to structural inequities in society and higher education, it was
thought important to check the pulse of the ET mediated with DET at three of the six
institutions analyzed by the end of 2020. The objective was to enhance the meta-conclusions
analysis and gain knowledge from the decisions taken when environments, resources, and
instructional methods had to be forcibly altered in order to maintain the provision of high-
quality higher education.
Result Analysis
The graph represents how often vit Vellore students use online platforms to study. As we
can see 43.3% of students highly use online platforms to study, while 43% study online. 13.3%
study from online and offline both. This indicates that maximum student’s study on online
platforms while some study from online and offline both. There are 0 % of students who don't
study from online platforms hence this proves that online platforms are used most.
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40% of students always make notes while studying on online sites 23.3% students do
make notes usually while another 23.3% make notes not very often while 13.3 % only note
down the important points. Therefore, this explains how people make notes while studying
online.
When it comes to the aspect of peoples experience in an online learning platform which
hasn’t implemented AI or ML in its interface, it can be seen that 17.2% of people’s experience
were really good. 44.8% found online learning platforms good. 31% of people found it neutral
and 6.9% of people found it bad. It can be found that more than half of the people in the survey
found online learning as a good option. Improvement in such a domain is absolutely necessary
and AI and ML will definitely help.
In the survey, people were given 4 features which can be implemented in e-learning
platforms using AI and ML. Out of them, 43.3% people chose personalized learning as an
advantage over normal e-learning platforms. Personalized Mistake Correction was chosen by
36.7% of the people. Chatbot and Improvised grading systems were each chosen by 10% of the
people respectively. This shows that the majority likes the learning process and mistake
correction to be personalized.
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People were asked whether they believe that AI and ML would really help their
understanding. 90% of the people agreed that it is really going to improve their understanding
while studying and 10% disagreed. This shows that the public is aware of the benefits of AI
and ML in e-learning and do not think of it as a disadvantage or a barrier in the learning
process. This also shows that the online learning platform which will introduce AI and ML
benefits will surely get support in the market.
When it comes to the aspect of peoples in enhancing the knowledge of students as well as
teachers it can be seen that 53.3% of people’s experience gave 4 ratings. 23.3% gave 5 rating.
16.7% of people found it neutral or 3 rating and 6.7% of people found it bad or 2 rating. It can
be found that it helped in increasing the knowledge.
In the survey, people were given 4 software options which can will need in e-learning
platforms using AI and ML. Out of them, 10.3% people chose elucidat.20.7% people chose
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Adobe Captivate.48.3% chose both the options and 20.7% didn’t choose any option This shows
that the majority likes both the tools.
Most of the companies do not have any ai projects underway as it is a new concept and
requires time. As stats show 82.1% companies have no AI projects underway.13.4%
companies do not have any confirmed AI projects underway. They might have some ideas but
they're not in action right now.And the remaining companies are the only one ones which have
AI projects underway. We can clearly say that AI is a new technology and most companies are
not investing time towards it.
E learning is a vital part of education in today's society. Most students have e-learning as a
part of their everyday life. We know due to the corona pandemic the times have changed and e
learning has become of great significance. According to 40% people the e learning course
should be 6 weeks long, while 26.7 % people think the course should be 3 weeks long.
Approximately 20% of people think that e-learning courses should carry as long as 2 weeks
whereas 13.3 % people also think that the course should be longer than 6 weeks.
Conclusion
Education is one of the most powerful weapons. E-learning has opened a new era in learning
and teaching. Using AI and ML in e-learning platforms would open many doors in
improvement of the education system as a whole. This survey aimed at studying people's
responses on the concept of AI and Ml, problems faced by students in an e-learning platform,
and rectifying them by improving the system using AI and ML. It was found that people were
very open-minded about introducing AI and ML in e-learning platforms and also about the
concept of e-learning as a whole. It was also found that people did not find the introduction of
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AI and Ml as a threat to the traditional learning process. Hence it can be concluded that
implementation of AI and ML in e-learning can be very much beneficial in e-learning platforms.
References
1. Alyahyan, E. and Düştegör, D., 2020. Predicting academicsuccess in higher education:
literature review and bestpractices.International Journal of Educational Technology in
Higher Education, 17(1), pp.1-21.
2. Davies, J.N., Verovko, M., Verovko, O. and Solomakha, I., 2020, June. Personalization of e-
learning process using ai-powered chatbot integration.In International scientific-practical
conference (pp. 209-216).Springer, Cham.
3. Galvis, Á.H. and Carvajal, D., 2022. Learning from success stories when using eLearning and
bLearning modalities in higher education: a meta-analysis and lessons towards digital
educational transformation. International Journal of Educational Technology in Higher
Education, 19(1), pp.1-31.
4. Gazzawe, F., Mayouf, M., Lock, R. and Alturki, R., 2022. The Role of Machine Learning in E-
Learning Using the Web and AI-Enabled Mobile Applications.Mobile Information Systems,
2022.
5. Guan, C., Mou, J. and Jiang, Z., 2020. Artificial intelligence innovation in education: a
twenty-year datadriven historical analysis. International Journal of Innovation Studies,
4(4), pp.134-147.
6. Hahn, M.G., Navarro, S.M.B., Valentín, L.D.L.F. and Burgos, D., 2021. A systematic review of
the effects of automatic scoring and automatic feedback in educational settings.IEEE
Access.
7. Ilkka, T., 2018. The impact of artificial intelligence on learning, teaching, and
education.European Union.
8. Kaddoura, S., Popescu, D.E. and Hemanth, J.D., 2022. A systematic review on machine
learning models for online learning and examination systems. PeerJ Computer Science, 8,
p.e986.
9. Koć-Januchta, M.M., Schönborn, K.J., Roehrig, C., Chaudhri, V.K., Tibell, L.A. and Heller, H.C.,
2022. “Connecting concepts helps put main ideas together”: cognitive load and usability in
learning biology with an AI-enriched textbook. International Journal of Educational
Technology in Higher Education, 19(1), pp.1-22.
10. Kuleto, V., Ilić, M., Dumangiu, M., Ranković, M., Martins, O.M., Păun, D. and Mihoreanu, L.,
2021. Exploring opportunities and challenges of artificial intelligence and machine
learning in higher education institutions.Sustainability, 13(18), p.10424.
11. Luckin, R. and Cukurova, M., 2019. Designing educational technologies in the age of AI: A
learning sciences‐driven approach.British Journal of Educational Technology, 50(6),
pp.2824-2838.
12. Munir, H., Vogel, B. and Jacobsson, A., 2022. Artificial Intelligence and Machine Learning
Approaches in Digital Education: A Systematic Revision. Information, 13(4), p.203.
13. Murtaza, M., Ahmed, Y., Shamsi, J.A., Sherwani, F. and Usman, M., 2022. AI-based
Personalized E-Learning Systems: Issues, Challenges, and Solutions. IEEE Access.
34
14. Orozov, B.I. and Orozova, D.A., 2021. An AI Application in E-Learning.In ERIS (pp. 76-80).
15. Renz, A. and Hilbig, R., 2020. Prerequisites for artificial intelligence in further education:
identification of drivers, barriers, and business models of educational technology
companies. International Journal of Educational Technology in Higher Education, 17(1),
pp.1-21.
16. Salas-Pilco, S.Z. and Yang, Y., 2022. Artificial intelligence applications in Latin American
higher education: a systematic review. International Journal of Educational Technology in
Higher Education, 19(1), pp.1-20.
17. Seo, K., Tang, J., Roll, I., Fels, S. and Yoon, D., 2021. The impact of artificial intelligence on
learner– instructor interaction in online learning.International Journal of Educational
Technology in Higher Education, 18(1), pp.1-23.
18. Wijayawardena, G.C., Subasinghe, S.G.T., Bismi, K.H. and Gamage, A., 2022, April. AI and
Machine Learning Based E–Learning System For Secondary Education. In 2022 IEEE 7th
International conference for Convergence in Technology (I2CT) (pp. 1-6).IEEE.
19. Williamson, B., 2018. The hidden architecture of higher education: building a big data
infrastructure for the „smarter university‟. International Journal of Educational
Technology in Higher Education, 15(1), pp.1- 26.
20. Zawacki-Richter, O., Marín, V.I., Bond, M. and Gouverneur, F., 2019. Systematic review of
research on artificial intelligence applications in higher education–where are the
educators?International Journal of Educational Technology in Higher Education, 16(1),
pp.1-27.
21. Zhang, K. and Aslan, A.B., 2021. AI technologies for education: Recent research & future
directions. Computers and Education: Artificial Intelligence, 2, p.10002
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CHAPTER 3
COMPUTER ASSISTED LANGUAGE LEARNING
Nimisha Kumari (21BCI0146), Akshwin T (21BCE3174)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
In education in general and English language instruction in particular, information and communication
technology has expanded more quickly. Because of its positive effects on the teaching and learning
processes, behaviorists recommend the use of this media. The use of computer-assisted language learning
has been introduced, despite the fact that many teachers and students lack the necessary proficiency. This
is because the curriculum mandates that teachers use the media to their advantage. In fact, integrating the
media presents a number of challenges for both teachers and students. Computer Assisted Language
Learning, or CALL, is a technique of interactive training that aids students in achieving their learning
objectives at their own pace and skill level. In this approach, computer technology is employed throughout
the teaching and learning processes, including the presentation, practice, and feedback phases. The aim of
this research is to investigate and understand how CALL can help in teaching English and how it helps
make the learning process better. The study was conducted on graduate students and undergraduate
students of VIT University and can be extended to the students of other colleges as well. The study sample
consists of 65 students. To collect the data, the sample body was given a questionnaire through Google
forms and this report represents the result of the questionnaire. In general, the results show that CALL
technique is quite effective while learning English and as it makes the learning process more interactive,
students grasp the concepts quickly with the help of this technique. It can be inferred that the CALL
techniques making the learning process self-paced, makes the students more comfortable and hence
increases their interest. It is concluded that CALL techniques make the learning process better and it can be
employed to teach languages like English, French etc.
Introduction
In this modern era, computer has become a part of our daily life. Computer is paying an
important role in almost the fields such as medicine, finance, education, sport, communication
and so on. Among these fields, Education is such an important field which can determine the
development of a country. Another important field is the communication. Communication is a
integral part of the human society. But there are lot of languages in the world. So, there is a
barrier created between people in different regions of the world.
This barrier can be broken by providing an opportunity for the people to learn a language
at their ease. Here comes the intersection of the technologies in two different fields. The
computer technology can be combined with communication and education to provide
education of language with the help of the computers. This process is called Computer -
Assisted Language Learning.
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With Computer assisted language learning, teachers can help the students can learn more
vocabulary and grammar by making them watch videos and even search the internet using
their target language. It also helps students to use that target language in a better way, which
helps them learn it more naturally than just memorization. The words and rules of the
language become something more useful to them, so they’re able to remember them better.
Students who learn visually can benefit by seeing an image or an example of the terms used in
class. Thus, Computer assisted learning can help to greater extent.
Listening is a vital part of learning any language. CALL helps in this part by enabling
everyone to play music or record conversations, so the students can listen to the language
which is used. The development that has occurred in today’s technology has enabled people all
over the world to connect from place to place. This plays an important role for the people who
cannot afford to go to offline for getting the education and to learn lot off skills. Today most of
the skills are learned in online in platforms such as Udemy, Coursera, Linked in Learning,
YouTube and so on.
Today CALL is implemented in lot of places and different sector of industries. It helps in
developing skills. The Business corporation companies indulge CALLs in their working sector
to improve the working of the employees and do good in the market. Software and Internet
related activities are the two main parts of technologies employed in computer assisted
language learning. The software which is used in a CALL setting is modified for or specifically
created for the study of foreign languages. The majority of language textbook publishers
provide some kind of educational software, either to supplement textbook or to serve as the
only resource for independent study.
Online software, computer-mediated communication which helps the learner interacts
with other people via the computer and apps that combine the two features are only a few
examples of the diverse range of internet activities. These days, there are so many and a wide
variety of websites that are geared toward foreign language learners, especially those learning
English, that it can be very challenging to know where to start.
Literature Review
Levy, M [1997] stated that the term "search for and research of computer applications in
language teaching and learning" can be used to describe Computer-assisted language learning,
The term CALL is relatively new; it has been acknowledged in academic literature over around
the past 30 years. The article, which is inter linked in nature, emerged from early attempts to
use computers for teaching or instructional purposes across a wide range of subject areas. As a
result of the depth of knowledge and breadth of application in language learning, the area of
study has since become more specialized. The creation of the computer and its subsequent
advancement have made CALL possible. As a result, the type of CALL at any given moment
mostly reflects how far along technology is in its progress. The pace in which technology has
developed has been excellent and amazingly sustained. The quick and continuing discovery of
new built technologies into education field has slowed down the capacity of developers and
teachers to evaluate.
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Lee, K.W. [2000] presented that the number of teachers using CALL has significantly
expanded in the past years, and various articles were created regarding how technology is
used in education in the 21st century. We have entered a new information age in which the
connections between technology and TEFL have already been made, even though the
Internet's potential for educational application has not yet been completely exploited and the
typical school still uses computers sparingly. Beginning in the early 1990s, the introduction of
word processors in schools, colleges, and universities began to have an impact on education.
There has been a substantial increase in quantity of teachers adopting CALL in recent years,
and numerous articles have been written about the way in which the technology is employed
in education in 21st century. Though Internet's opportunity for educational application has
not been fully realised that the schools still employ computers sparingly, we have entered into
a new era of information in which technology and TEFL link is formed. The usage of word
processors in schools and universities started to have an effect on education.
Nazlı Gündüz [2005] in the article titled “Computer assisted languagelearning” states that:
The CALL, its advantages and disadvantages, internet, the WorldWide Web and studies
pertaining for the use of computers inlanguage instruction will all be covered in this article's
review of computers. It also seeks to provide novices some background on how the Internet is
used inlanguage lessons nowadays. It explains some of the most popular categories ofonline
works that are used today, the prerequisites for utilizing Internetfor learning the language,
and a few simple exercises you can modify for your lessons. CALL does not refer to a teacher
using the computer to preparehis or her own lesson plans, a class list, or a worksheet. Any
piece of computerhardware, such as the computer the keyboard, the monitor the disc-drive,
and the printer, is referred to as hardware. The sets of instructions that must be loaded into
the computer for it to function are referred to as computer programmes.
Altun, E [2006] states that to discern the effects of computer assisted language on English
learning. There were two types of researches conducted, namely Traditional English
commands and computer assisted English commands. At the end, the results showed that the
students who were given the computer assisted learning showed great attitude towards
learning. But the research is advised for researchers to see the variations in measurements
and trends in recordings.
Bax.S[2006]in the article titled “Making CALL work: Towardsnormalization” states that:
The ultimate goal of CALL practitioners is to achieve "normalisation," or the complete
integration of computers into education. The discussion of barriers to normalisation and
strategies for overcoming them in this article is based ona qualitative research study
conducted in two EFL contexts. It lists many essential characteristics that are important in
normalisation and connects the results to earlier research on the useof Call in the field of
language instruction. The debate and conclusions should be helpful to individuals who want to
make computer technology more commonplace in their own contexts for teaching foreign
languages as well as to those who want to do qualitative research on the efficacy of Call-in
various contexts.
Bush, M.D [2008] stated that it can be difficult to learn a second language, butadvocates of
computer-assisted language learning (CALL) have long promised that it will geteasier.
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Research has shown the benefits of CALL, as noted in the CALICO Journal and in other
scholarly settings. However, many teachers continue to rely primarily on the textbook alone,
despite the fact that textbook publishers make a lot of effort to provide computer-based
ancillaries with many of their products. Given the cutting-edge hardware and software
capabilities of modern delivery systems, which were previously inconceivable but are now
both available and inexpensive, this situation is nothing short of remarkable. Is the attempt to
implement CALL a fruitless endeavour, or is it finally only a matter of time before This
articlecontains overview of CALL, including a glimpse at both its pedagogical limitations and
strengths and a sketch of research and development efforts that will help teachers,
researchers, and developers move CALL to the next level.
Jia, J [2009] states that computer Simulation in Educational Communication if focussing on
creating virtual chatbot which can chat with the language learners. It gives output based on
the learners input and dialogue context. The languages are expressed in the form of NLML.
NLML can be obtained automatically by parsing the text or with the help of GUI editors. This
article consists of system architecture and technologies that underlie behind it and the
educational application results.
Healey. D [2009] in the article titled “Computers and language learning:an overview”
states the modern age hasproven an explosion of hobby in the usage of computer systems for
language coaching and learning. A decade ago, using computersystems withinside the
language study room changed into a challenge best to aleastquantity of specialists. But, with
the discovery of multimedia computing and the Internet, the position of computer in language
training has changed out to be a critical trouble confronting massive numbers of language
instructors at some stage in the world. This article will offer a top-level view of modern-day
coaching practices and studies associatedwith the makes use of computer systems withinside
the language study room.
It may be divided into four most important parts: (1) a quick record of Computer-assisted
language learning (CALL), (2) a survey of modern-daypractices, studies, (3) aprospectus
towards the twenty first century, and (four) a listing of sources forsimilar
information.Shdeifat, S [2009] sought to determine how employing an English language
education software programme affected secondary students' academic performance in Jordan.
Students are divided categorised into four experimental groups and four control groups for
study's sample. A software application for teaching the passive voice as well as an
accomplishment test served as the study's tools. The impact of the educational programme on
the students' achievement in the passive voice was examined using an analysis of covariance.
The study's results showed that: 1. There were statistically important differences between the
achievement marks of the students in grammar that may be attributable to the teaching
approach.The experimental group of students benefits from this difference. 2. The mean
accomplishment scores for grammar among the students showed statistically important
gender-related differences. Students who are masculine benefit from this distinction. 3. The
grammar achievement mean scores of the pupils varied statistically significantly (p 0.05)
depending on the students' course of study. The students in the scientific stream will benefit
39
from this differential. It was advised that TEFL teachers employ CAI lessons in their training in
light of the study's findings.
Carol A. Chapelle [2009] in the article titled “The spread of computer-assistedlanguage
learning” states that it is becoming difficult to differentiate between CALL and other language
materials as there has been a quick spread of language materials and curricula. It is stated that
reflection on CALL assessment-related issues can provide some useful lessons about materials
evaluation given the importance that instructors, researchers, and administrators have put on
evaluating CALL. He focuses in particular on the opportunities for professionals to re-evaluate
presumptions made about comparative research, use applied linguistics research perspectives
and methodologies when evaluating materials, andincorporate critical viewpoints that look at
the chances of materials giving language learners to engage in language and cultural studies
Chapelle [2010] experiments on this study makes the case that it is challenging to discern
a clear separation computer-assisted language learning and other language materials due to
the vertical expansion of CALL. The author contends that considering the importance that
educators, academics, and administrators have given to evaluating CALL, we can learn some
important lessons about how to evaluate materials. The author focusses on the opportunities
for professionals to revaluate presumptions made about comparative research, incorporate
viewpoints that look for the chances that materials give the language learners to focus in
language learning, and create research perspectives and methodologies from materials
evaluation.
Garrett [2009] stated “Technology in the Service of Language Learning: Trends and Issues"
examines how technology is currently used to make teaching and evaluating second languages
easier. The bond between theory, pedagogy, physical infrastructure, copyright issues, efficacy,
categories of software (such as authentic materials engagement, tutorials, communication uses
of technology), and evaluation are some of the changes that have occurred for the past decades
with regard to a few topics from the 1991 article. Other topics covered in this article include
evaluation. The most difficult problems CALL based scholarship and practise today are then
discussed, including the need to rethink online learning, grammar instruction, social
computing, professional development and teacher training, CALL research, and newly created
demands in language education (on the findings of the Modern Language Association's 2007
report and Jackson & Malone, 2009). This work includes an appendix with information sources
links for CALL practice and research, same as the original 1991 essay. In order to facilitate
secondary language acquisition and to promote the technology use in CALL research, fresh
initiatives are required. A few examples include funding for institutional language centres,
streamlining the operations of CALL-specific professional organisations, and establishing a
national CALL centre.
Chapelle, C.A. [2010] experimented and found in the research, it is claimed that it
ischallenging to distinguish clearly between CALL and other materials because of the vertical
expansion of CALL, or its distribution throughout language materials. I contend that
contemplation on CALL assessment-related difficulties can provide some useful insights into
the evaluation of materials given the emphasis that instructors, researchers, and
administrators have placed on evaluating CALL. I focus on the opportunities that are available
40
for the professionals to re-think their beliefs on comparative research, use applied linguistics
research perspectives and methodologies when evaluating materials, and incorporate critical
viewpoints that look at the chances that materials give language learners to engage in
language and cultural learning.
Razak, N.Z.B. A [2012] states that the CALL is evaluated on the learner’s performance and
the positive outcome. The ideology of 30 postgraduate students in the Malaysian university
towards computer assisted learning was assessed based on the questionnaire and vocabulary
tests. The results showed that it had a positive effect. This will help in integrating computers
into design of EFL course.
Stockwell, G. ed [2012] explained that in the past few years, the area of CALL has been
discussed in books, journals, and academic conferences. There are multiple peer-reviewed,
international English-language journals in the area, with papers coming from the US, Europe,
Asia, as well as a large number of additional publications. Since its inception more than 50
years ago, CALL practitioners have had access to a wider variety of technology based on
various pedagogies and philosophies. The variety of variables might seem daunting to teachers
who are new to the subject as well as to those who have made a name for themselves in a
particular area of the field, despite the fact that the potential for variety and diversity that this
expansion in range may provide is encouraging. The diversity we observe in CALL may include
diversity in the technology utilized, diversity in the settings in which CALL is used, diversity in
the pedagogies used, diversity in the users of CALL, and diversity in the research and analysis
techniques. Each of these differences has the ability to alter how we perceive, employ, and
even assess CALL.
Pirasteh, P [2014] aimed to look at the effect of employing CALL for the student’s ability to
learn grammar in Iran. 80 students were separated randomly into two experimental and two
groups for study's sample. Conjunctions (coordinating, correlative, and transitional) were
taught using an online educational tool and an accomplishment test in this study. According to
the study's conclusions, the instructional approach used in the classroom caused notable
changes in the performance scores of the students in grammar. The students in the
experimental group benefited from this differential. Additionally, there were notable
disparities in the pupils' mean grammar success scores based on gender. In both the groups,
the post test results showed that female students did better than male students. The results of
this study suggest that teachers incorporate CALL teachings into their curriculum.
Kaburise, P [2014] states that most support courses can only focus on one facet of
academic literacy (AL), which is a broad concept. Due to its importance in tertiary success,
supporting academic language literacy has drawn some attention. In response to issues with a
language support course called English Communication Skills, the University of Venda
(UNIVEN) conducted a computer-assisted language learning (CALL) project (ECS). Blended
learning, which combines lecturer and CALL instruction, was suggested as one remedy for the
argument that ECS did not significantly contribute to linguistic development. The goal of the
research was to use computer software called MySkillslab to reinforce some reading skills in a
group of first-year students. Reflections on the conceptual and practical ramifications of such a
project are made in the paper's conclusion.
41
Kaburise, P [2014] states that most support courses can only focus on one facet of
academic literacy (AL), which is a broad concept. Due to its importance in tertiary success,
supporting academic language literacy has drawn some attention. In response to issues with a
language support course called English Communication Skills, the University of Venda
(UNIVEN) conducted a computer-assisted language learning (CALL) project (ECS). Blended
learning, which combines lecturer and CALL instruction, was suggested as one remedy for the
argument that ECS did not significantly contribute to linguistic development. The goal of the
research was to use computer software called MySkillslab to reinforce some reading skills in a
group of first-year students.Reflections on the conceptual and practical ramifications of such a
project are made in the paper's conclusion.
Hashmi, N.A. [2016] observed how many Arab students are choosing to study English as a
foreign language at higher education institutions thanks to CALL. It significantly affects their
academic careers, particularly the teaching-learning process in the classrooms. Computer
technologies have been introduced in the classrooms for the students' appeal because they are
thought to be useful in increasing student learning and addressing specific educational issues.
For effective teaching and learning results, Saudi Arabia's higher education institutions,
students, and Faculty have made the choice to do their great to include computer systems and
other relevant tech into their EFL classes. Thus, when it comes to teaching languages in Saudi
Arabia, computers have taken centre stage and are crucial.
Fan, Y [2016] states that a randomized trial in conducted in elementary school on effective
CALL where English is taken as main language. The trial showed that the oral proficiency is
very limited. Gradually the proficiency has increased in 25 weeks. The trial also shows that
exposure to the English is not only the factor for efficiency in English. The guidance through
proper instructor Is also required for good English. This also helped in determining the cohort
effect in learning English.
Rachmawati, U. [2016] states that English language instruction in particular, information
and communication technology has expanded more quickly. Because of its positive effects on
the teaching and learning processes, behaviourists recommend the use of this media. The use
of CALL has been introduced in the Indonesian context, despite the fact that many teachers
and students lack the necessary proficiency. This is because the curriculum mandates that
teachers use the media to their advantage. In fact, integrating the media presents a number of
challenges for both teachers and students.As a result, the writer in this article conducts a
theoretical analysis of the prospects and difficulties associated with the use of CALL
acquisition in the teaching of English. To hasten the success of EFL teaching and learning, all
parties participating in teaching and learning should be aware of the advantages and
drawbacks of media use.
Rusetskaya, M.N [2017] in the article titled “Computer assisted language learning” states
that: In the context of learning Russian as a foreign language, the study investigates the
efficacy of a computer-assisted language learning (CALL) technique for theimprovement of
non-reciprocal listening skills (RFL). The impact of CALL on the growth of listening skills has
been thoroughly explored based on a case study of teaching other languages (particularly
English), but this is the first time a study of this kind has been conducted in the context of
42
teaching the Russian language. The intervention study involved the RFL students (N=68) and
teachers (N=7) of the Russian Preparatory Department. A control group and an experimental
group were created with the pupils. A combination of qualitative and quantitative
methodologies was used to perform the study. Theresearchers cantered the eye on forms of
listening: listening for widespread facts and selective listening. As the listening competence,
and mainly instructional listening proficiency, is significantly vital for the scholars of
thepreparatory department, the researchers' goal changed into to analyse methods of
enhancing listening talents with one-of-a-kind tactics of the usage of CALL. The trying out and
evaluation substances have been advanced and the data changed into accumulated for every
sort of listening. In addition, the scholars of the experimental organization have been surveyed
to pick out them reviews from the usage of CALL withinside the classroom. The study’s
findings allowed concluding approximately the effectiveness of CALL utility for growing
listening for the element skills, while withinside the widespread listening no substantial
impact changed into found. In addition, the have a look atdiscovered particular complexities
withinside the utility of Call-in coaching listening in Russian.
Shah, S.H..R [2021] states that the purpose of the research is for computer assisted English
language learning technology in universities. Computer assisted English language learning is
very popular method to teach and learn foreign languages. This method is used both in student
and teachers. Among all the skills, listening skill is improved using CAELL technology. This
makes easy for the students to learn and teachers to teach. But one drawback is this program
is not known to lot of people due to lack of facilities.
Su, F., 2021 in stated that Computer-assisted language learning (CALL) is a vibrant,
interdisciplinary subject with expanding research potential and topic diversity because to
thedevelopment of educational technologies and digital devices. Understanding the past and
future of the CALL field depends on answering questions like "what issues and technologies
draw the interest of the CALL community?" "How have these topics and technologies
evolved?" and "what is the future of CALL." The current review looked at the state, trends, and
key topics in CALL research from 1,295 publications published over the last 25 years,
concluding in 2020. It did this by combining bibliometrics, structural topic modelling, the
Mann-Kendall trend test, and hierarchical clustering. Significant findings showed that Social
Sciences Citation Indexed journals, including Computer Assisted Language Learning. Most of
the field's advancements came from Language Learning & Technology and ReCALL. The most
popular subjects were blended learning, project based learning, and mobile-assisted language
learning. Wiki-based learning, mobile-assisted language learning, seamless learning, virtual
worlds, and virtual reality are among the subjects attracting growing study interest.
Furthermore, the growth of mobile technology, video games, and virtual worlds continue to
draw attention to study. In the end, the review demonstrated how academics and educators
are integrating various technologies, including the combined use of mobile technology and
glosses/annotations for vocabulary learning, and their application into various contexts, one
of which is the integration of digital multimodal composing into blended project-
basedlearning.
43
Wild, C. [2022] examined how much technology use has ingrained itself into
Englishlessons at secondary schools throughout Malaysia and the function that context and
community play in the process of normalisation. In order to learn more about how English
language teachers use technology in their classes, a qualitative research methodology was
used, which included online questionnaires and interviews. The study's findings suggest that
the environment is becoming more normalised to some level, with the degree of normalisation
being highly influenced by both contextual circumstances and how the teaching community
functions. Additionally, the study contends that normalisation should be seen as a more
intricate, dynamic, context-dependent, and community-based term than has previously been
acknowledged. Because of this, the policy makers, school administrators, and instructors
working towards incorporating and normalising technology inteaching and learning.
Lin, M.F [2022] stated that the goal of this study is to create a brand-new vocabulary
learning mechanism (VLM) for the previously created video-annotated learning and reviewing
system (VALRS), which will enable learners to recognise unfamiliar or unknown words while
watching the video and generate customised input enhancement from English subtitles for
vocabulary learning. The VALRS with VLM (VALRS-VLM) is expected to aid students in
improving their English listening comprehension, namely in the understanding of the meaning
of vocabulary words and oral sentences as well as the recognition of speech sounds of
particular vocabulary words. The purpose of this study was to compare the outcomes of
English listening comprehension performance and technology acceptance between the
experimental group using the VALRS-VLM and the control group using the VALRS without the
VLM in order to investigate the learning effectiveness and learners' experiences of the newly
developed VLM. The purpose of this study is to develop a new vocabulary learning mechanism
(VLM) for the previously developed video-annotated learning and reviewing system (VALRS).
This mechanism will allow learners to recognise unfamiliar or unknown words while watching
the video and generate individualised input enhancement from English subtitles for
vocabulary learning. The VALRS with VLM (VALRSVLM) is intended to support students in
enhancing their English listening comprehension, namely in the understanding of the meaning
of vocabulary words and oral sentences as well as in the recognition of speech sounds of
specific vocabulary words. Comparing the results of English listening comprehension
performance and technology acceptance between the experimental group using the VALRS-
VLM and the control group utilising the VALRS without the VLM was the goal of this study in
order to investigate the learning effectiveness and learners' experiences of the newly
developed VLM.
Result Analysis
What is your Occupation?
44
Students play an important role in the country. The above pie chart represents the percentage
of students who participated in the pole.The pie chart shows that the people who participated
in the pole are 100% students. From the above analysis it can be seen that only students have
replied to the form that has been circulated. All the responses are from the students only.
Have you ever used an Online English Language Learning Software?
The Online English learning software play an important role in learning the language. The
above pie chart represents the early experience of usage of any software in learning the
language. 56% people has not used any English learning software and 44 % people has used
English learning software. From the analysis, it can be seen that majority of people has not
used any software in learning English.
If you are a student, whatis your Year of Study?
The form was circulated to the students. The above pie chart represents the year of
studying of the students in the university.
From the bar diagram, it is clear that 100% people are form second year. From the analysis
it is clear that reply has been received only from second year students.
Is English your First Language?
Many people learn only their first language and they don’t have interest in learning other
languages. But today English has become a very important language in world to communicate
45
with the person all over the world. The above pie chart represents the percentage of people
whose first language is English.
Only 32% people’s first language is English and rest 68% people’s first language is not
English. From the above analysis, it can be seen that majority of people needs computer
assisted language learning to become fluent in English
How will you Rate the Process of Learning a Language Online?
The graph above depicts the ratings given by the students to the process of learning a
language online on a scale of 1 to 5. 0% of the respondents or none of the respondents have
rated the process of learning a language online as 1. 4.3% of the respondents have rated the
process of learning a language online as 2. 17.4% of the respondents have gone with the rating
of 3. 60.9% of the students have rated the process learning a language online as 4. Last but not
least, 17.4% of the respondents have gone with the rating as 5. We can observe from the graph
that equal number of people have rated the process 3 and 5. While most of the respondents
have gone with the rating of 4.The least being the rating 1 with zero rates. 2 being the second
last in the comparison while 4 being the first. Researchers found that the students who rated 4
and 5 are happy with learning the languages online as they can learn it anywhere from
teacher/software based on any part of the globe. Overall, the student community is shifting
towards learning the language online.
What is your Age Group?
The given chart shows the age distribution of the subjects on which the survey was
conducted. As it is quite clear from the chart that none of the subject is from the age group of
below 13 years. 88% of the respondents are from the age group of 13-19 years. 12% of the
respondents belong to the age group of 20-59 years.
Last but not least none of them belong to the age group of 60+ years. It is clear from the
analysis that a major part of the subjects is belonging to the age group of 13-19 years. These
are the students with more access to technology and they are better equipped with the
technical aspects of education for example using CALL.
46
Have you ever used an Online Language Learning Software?
The above pie chart shows the distribution of students who have ever used an online
language learning software or not. As the graph reads, 72% of the respondents are using or
have used some online language learning software while on the other hand 28% of the
respondents haven’t used any online language learning software ever in their lifetime. It is
clear that there is a huge difference in the number of students who have used the online
language learning software and the students who haven’t. The major part of the subjects is
belonging to the group who have learnt some language(s) like English, French, German,
Japanese online. Researchers found that the most of the people group of students who have
not learnt any languages online are struggling to figure out which platform is best and most
easy to use for learning a languageonline.
Are you Aware of Computer Assisted Language Learning (CALL)?
The above graph depicts the distribution among the students who are aware of Computer
Assisted Language Learning and who are unfamiliar with Computer Assisted Language
Learning. As the chart goes, 56% of the respondents are aware about the Computer Assisted
Language Learning technology and about 44% of them are not aware about it. 56 and 44 are
quite comparable numbers. They are almost half-half of the total chart. It can be concluded
that it is the need of the hour to make students aware about this awesome technology of
learning a language online.
47
How Strongly do you Agree or Disagree that the Computer Assisted Language Learning
can Revolutionize the Learning Process?
The graph above shows the distribution of people about how much they agree or disagree
that Computer Assisted Language Learning can revolutionize the process of learning. 16.7% of
people strongly agree. 16.7% of people agree but not that strongly. 29.2% of people are
neutral towards it. 29.2% people disagree and 8.3% people strongly disagree. The difference
between the respondents who strongly agree and just agree is 0. The difference between the
people who strongly agree and are neutral is 12.5%. The least selected option is strongly
disagreed. The not so huge difference between the no. of respondents who strongly agree,
agree and are neutral towards the belief the Computer Assisted Language Learning can
revolutionize the learning process ensures the fact that CALL Process is the future of the
education system. The fact that the least responses are in favor of strong disagreement
ensures the bright future and applications of CALL.
What Software or Platforms have you used?
Upon conducting the survey, it is found that a lot of different platforms for language
learning online are popular among the students. The most famous is the app ‘Duolingo’ which
provides very simplified and fun way of learning English with useful exercises and games, self-
assessment is also present on the platform to assess your own performance. Grammarly,
YouTube, Udemy, geeks for geeks were among the ones also popular and efficient as per the
students, other less popular options are also preferred by some.
Do you know the Basic Working of a Computer System?
48
Technology, easy and readily access to computer and internet is the basic requirement for
CALL. Being equipped with basic knowledge about the working of computer comes handy
while learning something new online. As expected, more than 95% of the students are well-
equipped with computers and use them on a daily basis, hence this is an important factor for
the success and efficiency of CALL.
Does your Computer have a Good Internet Speed?
As discussed, internet is the key to facilitate CALL globally and for it to be a more common
and popular means of learning English. For easy access of such platforms anytime and
anywhere, a good and stable internet connection is a must. Hence, it’s a very important
question and the responses suggest that about 84% of the students who took the survey have
a decent internet connection and will have no problem while accessing various platforms that
support CALL.
Does your School/College take CALL Sessions?
Even today when technology has advanced so much and the primitive education is
transforming. Old methods of teaching are being replaced with the new, better methods with
less labour work and more understanding of the topic. yet there are many institutions that are
still stuck on the old teaching styles. As per the responses of the students, it is found that
around 54.2% students said their institutions incorporate computer assisted language
learning online platforms whereas 45.8% do not indulge in online learning or take help or
resources online to easy the process of teaching and learning.
What Software or Platforms have you used?
49
Upon conducting the survey, it is found that a lot of different platforms for language
learning online are popular among the students. The most famous is the app ‘Duolingo’ which
provides very simplified and fun way of learning English with useful exercises and games, self-
assessment is also present on the platform to assess your own performance. Grammarly,
YouTube, Udemy, Geeks for Geeks were among the ones also popular and efficient as per the
students, other less popular options are also preferred by some.
Do you know the Basic Working of a Computer System?
Technology, easy and readily access to computer and internet is the basic requirement for
CALL. Being equipped with basic knowledge about the working of computer comes handy
while learning something new online. As expected, more than 95% of the students are well-
equipped with computers and use them on a daily basis, hence this is an important factor for
the success and efficiency of CALL.
Does your Computer have a Good Internet Speed?
As discussed, internet is the key to facilitate CALL globally and for it to be a more common
and popular means of learning English. For easy access of such platforms anytime and
anywhere, a good and stable internet connection is a must. Hence, it’s a very important
question and the responses suggest that about 84% of the students who took the survey have
a decent internet connection and will have no problem while accessing various platforms that
support CALL.
Do you Recommend Computer Assisted Language Learning through Online Platforms?
50
Through the above pie-chart, the views of the respondents are reflected regarding the
recommendation of Computer Assisted Language Learning through online platforms. About
25% of the respondents denied recommending CALL while 75% recommend Computer
Assisted Language Learning through online platforms to enhance the language learning
process. The number of people who recommend CALL through online platforms, are greater in
percentage than the respondents who don’t. A decent number of respondents believe that
Computer Assisted Language Learning through online platforms is good and is necessary,
whereas a small fraction of respondents does not recommend CALL through online platforms.
What Platforms do you Suggest?
The pie chart depicts the recommendation of the responders on the platforms that could
be accessed for Computer Assisted Language Learning. The graphical representation depicts
the online platforms most popular amongst students that could be significant in learning a
language through CALL. About 22.4% of the respondents recommend using Cambly, 22.3% of
these respondents recommend it to be Duolingo; 16.8% of the respondents feel that people do
not recommend a specific platform to use, 11.6% of the respondents suggest Teams, 11.2%
suggest Udemy and 16.7% of the respondents recommend people to use YouTube for
Computer Assisted Language Learning. The number of people who recommend that people
should use Cambly and Duolingo, are greater in percentage than the others. A decent number
of respondents suggest YouTube, almost a similar percentage of respondents suggest Teams
and the least number of people think the people recommend user to use Udemy for CALL.
Do you think that CALL is the Need of the Hour?
Through the above pie-chart, the views of the respondents are reflected regarding the
statement that CALL is the need of the hour. 45.8% of the respondents have strongly agreed
that CALL is, 25% have agreed, 20% have a neutral opinion. From this it can be inferred that
majority people believe that language learning through computers or CALL is the need of the
51
hour. As the majority of people strongly agree that CALL is significant in imparting language
learning and a decent count agrees with the statement raised and none of the respondents
disagree, from the above analysis it is observed that the majority of the respondents believe
that Computer Assisted Language Learning is the need of the hour by providing people an
opportunity to learn a language at ease.
Conclusion
After conducting the research successfully, some of the conclusions that come up surely point
towards the success of CALL. In the near future, it can be a big hit. With various such platforms
coming up, online teaching and learning is such easier, hassle free than the primitive methods
of education.
From the survey, it can be concluded that most of the students in the age group 13-19
years are familiar with the working of computer and have experienced some online learning
platform to learn English. In the recent years, with the shift from entirely offline to hybrid
(offline and online) level of teaching, students are aware of CALL and its functioning.
Numerous students have benefitted from using various available online resources, the
most popular among them was “Duolingo” and “YouTube” where it facilitated translation from
English to other languages and vice versa for better understanding. Even some of the schools
and colleges incorporate CALL and the students found it more useful than the contemporary
methods of teaching.
As per the opinions and views of students, CALL is a great initiative and in the coming
times, it will be the go-to measure to learn anywhere and anytime, CALL is the need of the
hour. students in remote areas with harsh conditions aren’t able to attend school regularly but
with the help of CALL the process of learning will not be halted.
A lot of platforms already exist while the new ones are also coming up, it should be made
easily accessible to every student for an interesting and innovative process of learning.
References
1. Levy, M., 1997. Computer-assisted language learning: Context and conceptualization.
Oxford University Press.
2. Warschauer, M. and Healey, D., 1998. Computers and language learning: Anoverview.
Language teaching, 31(2), pp.57-71.
3. Lee, K.W., 2000. English teachers’ barriers to the use of computer-assisted language
learning. The internet TESL journal, 6(12), pp.1-8.
4. Gündüz, N., 2005. Computer assisted language learning. Journal of languageand linguistic
studies, 1(2), pp.193-214.
5. Ates, A., Altunay, U. and Altun, E., 2006. The Effects of Computer Assisted English
Instruction on High School Preparatory Students' Attitudes towards Computers and
English. Online Submission, 2(2), pp.97-112.
6. Chambers, A. and Bax, S., 2006. Making CALL work: Towards normalization.System, 34(4),
pp.465-479.
52
7. Bush, M.D., 2008. Computer-assisted language learning: From vision to reality? CaLICO
Journal, 25(3),pp.443-470.
8. Naba'h, A.A., Hussain, J., Al-Omari, A. and Shdeifat, S., 2009. The effect of computer assisted
language learning in teaching English grammar on the achievement of secondary students
in Jordan. Int. Arab J. Inf. Technol., 6(4), pp.431-439.
9. Jia, J., 2009. CSIEC: A computer assisted English learning chatbot based on textual
knowledge and reasoning. Knowledge-Based Systems, 22(4), pp.249-255.
10. Garrett, N., 2009. Computer‐assisted language learning trends and issues revisited:
Integrating innovation. The modern language journal, 93, pp.719-740.
11. Chapelle, C.A., 2010. The spread of computer-assisted language learning.Language
teaching, 43(1), pp.66-74.
12. Chapelle, C.A., 2010. The spread of computer-assisted language learning. Language
teaching, 43(1), pp.66-74.
13. Chapelle, C.A., 2010. The spread of computer-assisted language learning. Language
teaching, 43(1), pp.66-74.
14. Mahmoudi, E. and Razak, N.Z.B.A., 2012. Attitude and students’ performance in computer
assisted English language learning (CAELL) for learning vocabulary. Procedia-Social and
Behavioral Sciences, 66, pp.489-498.
15. Stockwell, G. ed., 2012. Computer-assisted language learning: Diversity in research and
practice. Cambridge University Press.
16. Kaburise, P., 2014. Practicalities of a Computer-assisted Language Learning Project.
International Journal of Educational Sciences, 7(3), pp.747-754.
17. Pirasteh, P., 2014. The effectiveness of computer-assisted language learning (CALL) on
learning grammar by Iranian EFL learners. Procedia-Social and Behavioral Sciences, 98,
pp.1422-1427.
18. Hashmi, N.A., 2016. Computer-assisted language learning (CALL) in the EFL classroom and
its impact on effective teaching-learning process in Saudi Arabia. International Journal of
Applied Linguistics and English Literature, 5(2), pp.202-206.
19. Rachmawati, U., 2016. Computer Assisted Language Learning (CALL) as EFL teaching and
learning media in Indonesia: Opportunity and challenges. Edulingua: Jurnal Linguistiks
Terapan Dan Pendidikan Bahasa Inggris, 3(2).
20. Alvarez-Marinelli, H., Blanco, M., Lara-Alecio, R., Irby, B.J., Tong, F., Stanley, K. and Fan, Y.,
2016. Computer assisted English language learning in Costa Rican elementary schools: An
experimental study. Computer Assisted Language Learning, 29(1), pp.103-126.
21. Lebedeva, M.Y., Koltakova, E.V., Khaleeva, O.N. and Rusetskaya, M.N., 2017.Computer-
assisted language learning for the development of listening skills: Acase study of pre-
university Russian as a foreign language. International Journalof Applied Linguistics and
English Literature, 6(1), pp.257-265.
22. Rajput, S.N. and Shah, S.H.R., 2021. Computer-assisted English language learning
technology for undergraduate university students. Computer, 1(1).
23. Chen, X., Zou, D. and Su, F., 2021. Twenty-five years of computer-assisted language
learning: A topic modelling analysis. Language Learning & Technology, 25(3), pp.151-185.
53
24. Balchin, K. and Wild, C., 2022. Exploring the role of context and collaboration in
normalising technology use in English language teaching in secondary schools in Malaysia.
Computer Assisted Language Learning, 35(7), pp.1437-1457.
25. Chen, C.M., Li, M.C. and Lin, M.F., 2022. The effects of video-annotated learning and
reviewing system with vocabulary learning mechanism on English listening
comprehension and technology acceptance. Computer Assisted Language Learning, 35(7),
pp.1557-1593.
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CHAPTER 4
IOT IN EDUCATOIN ESPECIALLY ESL CLASSROOMS
Manya Chalana (21BCE0682)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
The internet has exponential expansion and growth. During the span of two decades, the net is boosted
thereby connecting the human population around globe. Nowadays due to the revolution of the internet, a
large variety of devices communicate using the internet as a source as well as bringing about the Internet
of Things (IoT). With the extreme and drastic evolution of the Internet of Things, physical environment is
becoming advanced, and are interconnected than before. This changes the way we exist by enhancing
sustainability, efficiency, exactitude and economy in multiple aspects of lives of humankind. IoT has
managed to unfold multiple industry sears such as retail, manufacturing, healthcare and education. The
introduction of IoT in education gives rise to numerous application that can intensify student safety, offer
communication channels for global students and assist disabled pupils. The IoT has the potential to change
education by downright changing how schools, colleges and universities gather data interface with users
and automate operations. When Internet of Things is coalesced with technologies such as user mobility and
data analytics, it brings a new nuance in education. With this approach, education can become more agile
and the quality of education will most probably improve.
IoT in education epically ESL classrooms plays an integral part not only for the student but also for the
teachers in the process of gaining and imparting knowledge and skills. IoT makes classrooms more
interactive, vibrant and advanced for learning and teaching. IoT provides an effective stimulus for students
to express their feeling and makes a difference in a student’s life.
After the pandemic, the usage of IoT in classrooms have become most prevalent and the students have
adopted the usage gradually “Smart lesson” plans, devices connected to the cloud, smart boards and so on
have impacted the lives of the students and the teachers. In totality IoT has made a drastic impact on the
education sector and ESL classrooms’
The points highlight how IoT can transform education:
There are certain IoT products available in the market which can have a great impact on e-learning
examples being smart boards and digital-highlighters.
RFID chips can be used to track any physical object, even plants and animals and gather the information
about these objects, store in the cloud.
QR codes are becoming popular nowadays. These codes can be embedded in books to access any additional
resources or students can embed them in their offline work which can be linked to an online portfolio of the
project.
While the rise of cloud-based technologies along with data mining and big data analytics, the future of IoT
seems to be promising and with it, the applications it is going to provide. Thus, the above discussed points
are just some of the numerous possibilities in which IoT can benefit e-learning, technological
advancements coupled with imagination are the only limits!
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Introduction
IoT is a collection of thousands of wireless networks that are interconnected for the purpose
of gathering, transmitting, and receiving various kinds of information.
To make conducting business easier, it is expanding its quality into virtual space. For data
sharing and receiving, the majority of electronic appliances, gadgets, and software-based
equipment are connected to one another.
To make the most of technology, the education sector is modifying IoT devices and
associated services. This approach aids in making education more participatory, accessible to
all people, and interactive. Additionally, it makes interactive learning possible, ensures the
safety of the educational facilities, boosts productivity, offers real-time learning experiences,
allows for close supervision, etc.
IoT will become more significant and capable of providing more insights when it is
integrated into regular teaching techniques. Overall, we may conclude that IoT is just
converting traditional schooling to a digital paradigm. Along with greater effectiveness, this
also offers numerous additional advantages.
Literature Review
Aldowah (2017) states that the educational process will be significantly impacted by
technologyin the upcoming years. The Internet of Things reaffirms the critical role in the
affairs ofinformation, communication technologies and societal advancement. With IoT
support,institutions may improve outcomes in learning by offering luxurious educational
opportunitiesimproving efficiency in operations, and gaining hands on and real-time, insight
into the performance of the student. Finding out possibilities of IoT in higher education is the
goal for this project. ForIoT systems and technologies to reach their full potential, efforts are
required. Considering this, thisessay presents research on how the Internet of Things is
affecting universities, specifically. IoThas the potential to significantly modify how colleges
operate and enhance pupil literacy innumerous disciplines and at any position. Universities
and many educational institutions cangreatly benefit from it; if the case follows being well-
prepared to enable extensive and triumphant implementation byleadership, employees, and
scholars. Researchers and pupils are in a distinct position to pioneerthe development of
Internet of Things systems, bias, operations, and services. Additionally, afew research groups
and businesses have given confirmations regarding the futurity of IoT inhigher learning over
the past decades in this paper. Then again, IoT likewise brings a lot ofhurdles to education.
Consequently, the paper presents the point of view on thedifficulties of Internet of Things in
advanced education.
LaPlante et., al., perception stated that the IoT have benefits and obstacles in
education.With around 20 billion internet-connected devices to be deployed within 2020, the
usage of Internet ofThings is spread over various branches of the economy. Due to the
omnipresence of IoT devices, placesof learning like schools and so on want IoT to go hand in
hand with education. As the demand for IoTrises within the educational sector, it is
compulsory to learn about IoT along with the functions such asdecision making and sensing
that help and creates hurdles in the teaching process especially for faculty, students and staff
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inaddition to classrooms and laboratory. There were various significant additions to inculcate
IoT intoeducation, the need of united and logical views on this matter is required. Therefore,
the motive is toget the views united, and we have started mapping available published studies.
This study shows theadvantages and disadvantages of IoT in education. Many mapping views
extracted from studies havebeen provided as well as the summary, but the already inculcated
methods and research questions needto be investigated.
M Bagheri and SH Movahed (2016) state that education has seen a significant
transformation as aresult of IoT, that enables communications based betweenphysical devices,
sensors, and controllers. By installing sensors in items and coordinatingdistributed computing,
expanded verisimilitude, habiliment advances and big data in the sector, variousboundaries of
instructive climate that may be estimated as well as dissected to give helpful data.
Theconnection between individuals and the environment in educational organizations has also
changedas a result. In this exploration considering the new IoT in schooling, we can order
utilization of Internet of Things in training into various gatherings: energy the board as well as
constant environmentchecking, observing understudy's medical care, study hall access control
and further developinginstructing and learning. We will look at and analyse how the Canvas
Business Model has beenincorporated into these enterprises, changing the Education Business
Model and introducing newestimate postulations.
Malik et., al., perception stated that Internet of Things has various roles in the educational
domain. The Internet of Things is advancing at a rapid rate due to many ‘connected things.’
Usage of Internet of Things in education domain is equivalent to a new beginning for
enhancement in both teaching and learning process as well as the infrastructure of
institutions. The benefits and uses of IoT in the field of education are covered in this study
paper. Additionally, it seeks to lay out the studies, challenges, and long-term effects of IoT in
education.
Al-Emran, Iqbal Malik and Al-Kabi (2020) state that the most difficult platform for defining
thecorrelation of physical objects in the near future is the Internet of Things (IoT). To assess
andsummarize the utilization of IoT and its applications in many sectors, numerous evaluation
studies have been conducted. However, the implementation of IoT in education is not given a
thoroughreview study by research. Accordingly, the principal motivation behind this study is
to highlight the recent development of using IoT applications in training and present many
opportunities and challenges to upcoming preliminary exams. All the more explicitly, the
possibilities for implementingwearable technologies, green IoT, medical education and
training, vocational education andtraining, and IoT in education are all summarized in this
review research. It is presumed that thereception of IoT and its applications in non-industrial
nations is still in its beginning phases andfurther exploration is profoundly energized.
Vairinhos et., al., perception stated that IoT in education is a powerful tool and has scope in
the current scenario as well as the future. The objective of this paper is to discuss and examine
the scope and challenges of IoT in the education sector based on literature, projects and
recognition of technology. Open data, into textbooks, called smart books in this context, shows
the amalgamation of IoT technologies, which is also discussed. In regard to open data,
combination of data sources is shown in relation to open data, and possibilities for their fusion
57
in manuals are also covered. Finally, the Internet of Things presents the scope to leverage
updated data sources, there is still much work to be done in the field of education.
Ana-Maria Suduc, Mihai Bîzoi and Gabriel Gorghiu (2018) state that the Internet of Things
(IoT) may dramatically improve human lives in a variety of contexts, including smart cities,
smart surroundings, smart water, smart metering, security and emergency, retail, logistics,
industrial control, agriculture, home automation, eHealth, and education. For instance, in the
development and lodging area, savvy structures might coordinate IoT advancements to build
productivity, security, and solace for occupants. In industry, clever wristbands might robotize
timing in also, out to definitively record how much time spent working. IoT technology may be
utilized in "smart cities" to generate street lights with intelligent and weather-responsive
illumination, to produce real-time sound monitoring in various city regions, to monitor
parking spot availability in the city, etc. The Internet of Things (IoT) technologies offer schools
several opportunities in the field of education, including the ability to gather and utilize
information to improve student learning, assist in achieving learning objectives, and better all
aspects of school operations. It is imperative to prepare the future generation for these
changes since the IoT area is anticipated to expand rapidly over the next years. The article
summarizes the results of a survey conducted among college students majoring in technical
specialties to learn more about their perspectives on various IoT technology-related issues as
well as their expertise and interest in the field.
Bakla et., al., perception stated that Internet of Things is a new concept and seems to have
a great influence in the process of learning and teaching. Moreover, this attractive term has
gained momentum in the education sector but there remain doubts regarding the complexity
of it and the usage/working of it in teaching and learning processes among teachers as well as
students. The objective of this study is to find IoT in instruction and give an interpretation of
the working of it. It makes a demarcation of the application of Internet of Things in
managemental and instructional levels in the educational sector. In the present time, teachers
seem to be in favour of IoT in education, but a few suggestions have been put forward to use
IoT in domains like administration, leaving little space for debates catering to the future scope
for the usage of IoT in the classroom. Henceforth, the study shows the advantages and
challenges, mainly with respect to technology like digital devices and the Internet.
S Pervez, S ur Rehman and G Alandjani (2018) state that the traditional and classical
methods of instruction in the classroom are no longer appealing and effective for students in
the 21st century due to the enormous growth and accumulative significance of technology in
all aspects of life. Little contraptions are acquiring wide fame with the rise of the Internet of
Things (IoT), especially among students who employ wearable technology with tiny sensors to
link to learning systems. Present day intuitive gadgets are outfitted with IOT sensors that
allow them to link to users' devices and grant them restricted admittance to download
information as founded on sorts of records they are utilizing. With the ability to link objects to
the Internet, the Internet of Things is altering many aspects of our daily life. The web-based
learning framework with the assistance of Internet has well established itself into our schools,
and e-learning has turned into a typical practice in present day tutoring frameworks. Be that
as it may, there are many IoT applications in education, and the ramifications for this
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disruption will have far-reaching effects. It offers several advantages to the society and system,
much to how mobile technology has become so popular. Moreover, the IoT permits schools to
work on the wellbeing by following of distinct advantages, and upgrading admittance to data
which works with instructors to make "smart lesson plans". The understudies, especially in
schools/colleges, are logically getting away from paper books in favour of IPADs and tablets
that include interactive programmes with built-in visuals and simulations that allow for time
and location flexibility. In order for instructors and students of the present to benefit from the
handling of information, which demonstrates various learning patterns and with progress
proportion of those implemented tactics, this study discusses all IoT components with their
degree of efficiency. In addition, we may discover areas that could have development
depending on factors like age, category, geography, etc. The findings will support decision-
makers and offer the best instruction model for enhancing a certain platform for a specific
group, using more customized methodologies. This will be finished by an investigation on Big
Data, produced by these IOT gadgets and assortment of information will keep on venturing
into new regions that have up until recently never been accessible for examination. The
Internet of Things is made up of interactions between educators and students through media
platforms, process automation, and the compiling of data from many sources (IoT). This
computerized change will uncover new bits of knowledge that guarantee to meaningfully have
an impact on the manner in which we think, learn and execute things in our reality and all the
more explicitly later on schooling system.
Jeon et., al., perception stated that IoT is a smart and a secure way for schools to monitor
and be vigilant. One approach to build society, provide for welfare and prosperity, and provide
for human resources is through the education sector. Safety and privacy in educational
institutions is a major concern due to the prevalence of violent and terrorist interventions.
Technology has been included with effective learning methods to improve the cognitive
development, however safety within or beyond educational institutions has been
compromised. By applying clever monitoring and sensing tools, sophisticated technology has
been implanted. The aim of this article is to examine the fixes offered by Internet of Things
(IoT) created with schools in mind to offer cutting-edge and secure learning methods. The
paper puts forward Secure system for the Internet of Schools Things (S-IoST) for institutions
with cutting-edge technology built on 5 G cellular systems, sensor technologies, intelligent
transportation systems, and IoT networks. The said system puts forward a safer alert system
and encourages the consumer at school and on their way to their place of abode. The
aforementioned system evaluates based on a number of factors, including data delivery,
reaction alerts, and timing.
The phrase "Internet of Things" (IoT) refers to networking innovations that allow for the
connection and communication of real-world devices over the internet. The phrase "things"
refers to all related objects collectively. Almost every field, including healthcare, business,
transportation, agriculture, management, and education, can benefit from the interconnection
of various products via the internet that sends and receives information. With an emphasis on
e-learning, the Internet of Things (IoT) will be discussed generally, along with some of its
59
applications. A smart learning approach that uses gamification and the IoT is presented as the
study's conclusion.
The phrase "Internet of Things" (IoT) is used in networking to refer to developments in e-
learning technology. It is obvious that the invention of the internet has made it easier and
more convenient than ever to stay up to date on international happenings. Everyone is aware
that there are means of communication available to individuals everywhere. Any item with an
internet connection is considered a thing. A certain type of connectedness of various things
can perform its purpose through the information that may be employed for receiving and
disseminating evaluated data through the internet. It is claimed to be knowledgeable in nearly
every field, which can be decided in a number of different methods for the implementation of a
wide variety of application formats. There are numerous categories, with a few examples
including management, business, transportation, agriculture, and healthcare. The Internet of
Things is specifically and mostly mentioned in this article in a general manner (IoT). It is
claimed that e-learning has become more of a focus as a source of knowledge for its users.
Smart learning technologies like the IOT can be used in conjunction with e-learning
methodologies to exhibit and demonstrate smart ways.
According to Li et al., the study provides an overview of the Internet of Things based on
technology utilised in education and includes its definitions and status. Additionally, we go
over the benefits of IoT in education, which mostly revolve on a greater demographic reach,
real-time usage, and freedom. The concept of mobile education, which is the fundamental
foundation of IoT in education, is now put forth. The benefits and drawbacks of mobile
learning are then examined. Thus, issues like adaptability and growth in a possible cloud-
based mobile education framework are also covered.
According to Politopoulos et al., gamification and the Internet of Things will have a fresh
impact on the educational space. Gamified features on game engines give room for the
development of creative virtual jobs and a variety of fun learning opportunities. Real-time data
visualisation is possible with IoT. It is feasible to create non-virtual and secure settings with
non-virtual life data and triggering systems in conjunction with all of these sectors, allowing
students to experience learning on a completely new level.
According to Charles et al., the purpose of the paper is to understand pre-service teachers'
perspectives on a specific IoT (Internet of Things) technology. Google Assistant is the main
focus of this essay. Even while there are teaching aids in many classes, especially those for
special education, the use of Intelligent Personal Assistants (IPAs) in educational institutions
offers services as teaching aids similar to those found in a traditional classroom setting. The
research addresses the background information and perspectives of pre-service teachers on
the use of voice assistant technology in their ongoing specialised work or future classrooms.
The goal of the study, according to Enescu et al., is to demonstrate the Internet of Things,
the most recent IT&C (Information Technology and Communications) idea (IoT). It is
suggested that study be done to explore the implications of incorporating the Internet of
Things (IoT) in higher education after a brief introduction to its foundations. Additionally,
there are a number of concrete methods for integrating IoT elements into academia, namely in
the areas of bettering teaching and learning. We experiment that the ideal technical remedy
60
for the education domain is IoT platforms with real-time, restricted-vicinity service provision
using Cloud Computing services. Important IT&C firms built and inculcated projects in this
field.
According to Raj et al., the term "Internet of Things" (IoT) refers to cutting-edge
networking technology that works hand in hand with real-world structures that can be
connected to communicate with one another online. "Things" refers to the interconnected
structures. There are several applications for connecting various objects over the internet with
the ability to send and receive information in every industry, including healthcare, business,
transportation, agriculture, management, and education. The application of IoT in relation to
e-learning is examined in this study. The paper concludes by presenting a concept for smart
education using the Internet of Things and gamification of e-learning.
The Internet of Things (IoT) is a term used to describe technological advancements in e-
learning in the networking space. By staying updated about all-encompassing events, the
Internet of today makes it simple to stay linked to events taking place in the actual world. We
are all aware that we communicate with one another on a global scale. Internet-connected
objects are referred to as "things." The Internet connects objects in a specific way through data
that may be used to send and receive analysed data, which is what causes it to be thus. It is
said to have specialisation in practically any field and to be able to implement many
application formats depending on how it is defined. The broad categories can include things
like management, business, transportation, agriculture, and education. The Internet of Things
is explicitly and mostly discussed in this article (IoT). E-learning is highlighted particularly as a
source of information for readers. Smart Techniques can also be expressed in e-learning
techniques by employing Smart Learning as his IOT.
This study introduces a virtual learning environment for the Internet of Things. The
perceptual layer, the operational and analytical layer, and the cognitive layer are the three
levels that make up spatial components. Later, more on this. This area has the benefit of
efficiently supporting students with impairments by fusing the virtual world with the actual
campus of the university. A hypothetical situation is used to illustrate this new option. VeLS is
also expanded to include standard architectures that can be customised for fresh IoT
applications. Three formal tools, AmbiNet, TNet, and ENet, provide "things" virtualization in
the reference architecture. I'll also briefly touch on my plans for the future.
Previous studies have emphasised the learning dissatisfaction in traditional education,
which is a major concern for higher education institutions (HEIs). This is especially true in
view of the numerous concerns academics have expressed over the declining quality of
educational learning. In this study, we conducted a literature review to determine how student
learning styles and the Internet of Things (IoT) affect learners' expectations for learning
outcomes (LO) in higher education (LS). Educators can use IoT to enrich their curriculum
utilising her free LS and LO after reading the research review indicated in this article while
this phase is still being developed. In order to show how IoT and LS promote the achievement
of LO and enable university instructors to reach more students through e-learning settings, the
study's model was also looked at in the context of e-learning. I can do this by employing the
61
multidisciplinary model put forth in this paper. The implications for theory and practise are
also covered.
Students' lives all throughout the world have changed as a result of the new coronavirus's
outbreak. To stop the coronavirus from spreading, the following international criteria
mandate that all educational institutions operate remotely. The Internet and web-based
technologies have gained popularity as platforms for creating and implementing distance
learning courses in virtual classrooms. The teaching and learning process is changing as a
result of the use of programmes known as E-Learning Motivation Systems (E-LMS), which
were created expressly to boost the efficacy of e-learning. The goal of this article is to discover
and recommend low-cost, powerful, and adaptable platforms. The platform is intended to keep
track of early information regarding student access to and engagement in online learning
environments and activities. The first case study was carried out at Wasit University's
Electrical Engineering Department. The findings of the evaluation demonstrate that E-LMS
Motivation is a useful tool for supporting educators in educational monitoring and student
performance analysis, greatly enhancing rates of student retention and promotion.
The advantages of e-learning in smart cities are highlighted in this article by the scientific
research that backs them up. This paper investigates a theoretical analysis. IoT is an emerging
technology that is flourishing in the realm of computing and technology. Along with the IoT
concept, smart city development is accelerating. One of the fundamental elements, e-citizens,
is crucial for developing community and building smart cities. It goes without saying that a
new class of citizen (the "ecitizen") in smart cities can play a significant role if given sufficient
e-education. These problems might grow into imaginative and enterprising participants who
can guarantee that the educational objectives of contemporary communities are met. The e-
education component is reinforced by using effective e-learning on the Internet of Things (IoT)
campuses in smart cities. This essay examines the projected advantages of e-learning while
concentrating on the requirement of adopting IoT technologies on campuses in smart cities.
The report gives a thorough analysis of smart cities and highlights the remarkable benefits of
online learning. The last sentence might be used as a clear topic for further research by smart
city experts.
IoT is a new technology that has recently seen rapid development in the computing
industry. In order to maintain a nice environment for successful e-learning in the digital age,
our college campus needs IoT technology. On our classic, traditional college campus, there is
no usage of any modern technology for e-learning activities. This essay focuses on the
significance of integrating IoT technologies in learning environments that use online
instruction. In the near future, make big changes for students in i-Campus environments that
are greatly facilitated by IoT.
This paper describes the Virtual eLearning Space as an ecosystem for the Internet of
Things. Three layers—a sensory layer, an operational and analytical layer, and a cognitive
layer—are used to organise the space's components. By combining the virtual and actual
worlds of the university campus, the space successfully serves students with disabilities,
which is one of its advantages. An example is given to show how this new opportunity works.
VeLS is enhanced concurrently to serve as a reference architecture that can be altered for
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brand-new IoT applications. The reference design supports virtualization of "things" using
three formal tools: AmbiNet, TNet, and ENet. Future directions are also briefly mentioned.
Due to the alternatives the internet provides, more people are using e-learning courses,
and several research efforts have been made to create e-learning systems. Up till now, many
e-learning platforms have been created and used. The rate of e-learning completion in these
systems is, however, low. One of the causes is a loss of excitement and motivation for studying.
In this work, we build and use a Raspberry Pi running Raspbian as an IoT-based testbed for
e-learning. We compare the performance of Optimised Link State Routing with the Wired
Equivalent Privacy (WEP) protocol in an indoor setting (OLSR). For evaluation, we considered
throughput, latency, and jitter measures. The experiment's results show that communication
between testbed nodes was smooth.
Results Analysis
The pie chart represents what IoT stands for. As per the observations, 90.9% of the
respondents say that IoT stands for Internet of things, 4.5% of the respondents say that IoT
stands for International of Things, 3% of the respondents say that IoT stands for Internet of
Thoughts while 1.5% of the respondents say that IoT stands for Internet of Thinks. Hence as
Internet Things received the maximum amount.stands for Internet of Things votes, IoT stands
for Internet of Things.
This pie chart represents how helpful IoT in education is in especially in ESL classrooms.
19.7% respondents strongly that the usage of IoT in ESL classrooms is helpful whereas 30.3%
respondents are neutral. On the other hand, 50% agree on the fact that IoT in ESL classrooms
actually help students. It is observed that majority of the respondents think that IoT is helpful
for students especially in ESL classrooms.
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The pie chart represents how many respondents have experienced IoT in ESL classrooms.
As per observations, 74.2% of the respondents have experienced IoT in ESL classrooms, while
25.8% of the respondents have yet to experience IoT in ESL classrooms.
The pie chart represents how interested respondent is in the field of IoT. 27.3% believe
that they are very interested in this field whereas 37.9% Believe that they are fairly interested
in this domain. About 34.8% are convinced that they are somewhat interested in IoT. The
majority seems to be fairly interested in this area.
By selecting which assertion regarding the Internet of Things is untrue, the pie chart
illustrates how well-versed the respondents (students at VIT Vellore) are have the idealogy
that IoT. As per choices "it slows down the communication between student and teacher" is
untrue, 57.6% of the students selected the right response, while 42.4% selected one of the
incorrect responses. Even if the majority of students are aware with the idea of the Internet of
Things, there are still some who are not. The researchers came to the conclusion that while IoT
is a widely utilised or recognised concept, a tiny percentage of individuals are not entirely
familiar with it.
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The diagram represents the rate of usage of usage of IOT in ESL classrooms from personal
experience of the respondents. 43.9% of the respondents believe that their experience was
average(3/5). 36.4% of the respondents have an opinion that their experience was good(4/5).
12.1% of the respondents are convinced that the their experience was perfect(5/5).3% of the
respondents had a below average(2/5) experience and 4.5% had a poor(1/5 )experience.
Majority of the respondents believe that they had an average experience with the usage of IoT
in ESL classrooms from their personal experience.
The pie chart represents how many people feel that there is more than one way to involve
IoT in education by using smartphones and digital materials. 97% of the respondents believe
that there is more than one way to involve IoT in education by using smartphones and digital
materials whereas 3% of the respondents believe that it is not possible.
The bar graph represents which IoT device is preferred in smart classrooms. 77.3% of the
respondents prefer smart boards, 48.5% of the respondents prefer online/recorder lectures
while 36.4% of the respondents prefer to use tablets in their smart classrooms. Majority of the
respondents prefer to use smart boards than any other IoT device in their smart classrooms.
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This graph illustrates the results of a survey in which people above the age of 18 were
asked about their recent experience with a smart classroom maximum number of people rated
their experience (4/5) and (3/5). About (15.2%) of the people have rated their experience as
very good by rating it 5/5. However, a small fraction of people has rated that their experience
of a smart class was not up to their expectations.
The pie chart represents how much percentage of the respondents enjoy E-learning
experience in classrooms. 72.7% of the respondents enjoy E-learning in classroom, whereas
9.1% do not enjoy E-learning in classroom and 18.2% prefer not to share their opinion We can
see that majority of the respondents agree that they enjoy E-learning experience and only a
minimal percentage of the respondents think they do not enjoy E-learning in classroom.
The percentage of students of VIT Vellore who have utilized any online learning resources
is shown in the pie chart. 86.4% of the respondents (students) have used web-based
learning tools, whereas 13.6% students have not used any such tools. It has been shown
that most students utilize some type of web-based learning tool on a daily basis. The
researchers came to the conclusion that while many students have found using web-based
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learning tools to improve their learning process, others of them have not yet investigated
these choices.
The graph illustrates the results of the question “How often do you come across smart
classrooms which use IoT and E-Learning?” which was asked by our audience during a survey
conducted on IoT.
Maximum no of our respondents (19.7%) believes that 7 out of 10 times they came across
smart classrooms which use IoT and E-Learning. 15.2% of the people believe that 9 out of 10
times they have encountered smart classrooms. 4.5% of the audience believes that they
encounter IoT in every classroom they visit. However, a small amount (1.5%) of our audience
also believes that out of 10 only 3 times they have encountered the use of IoT in classrooms.
The frequency with which VIT Vellore students use web-based learning resources, which
has enhanced their educational experience, is seen in the pie chart. It was discovered that 47%
of respondents agreed with this statement, 33.3% of respondents agreed strongly, and 18.2%
of respondents had a neutral opinion. Additionally, a minor percentage of 1.5% of the students
disagree with this assertion. The majority of pupils, it has been found, think that using these
online learning resources improves their educational experience. The researchers come to the
conclusion that even if employing these tools has been useful, some students are either
unaware of them or have had negative experiences with them.
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The pie chart represents how much percentage of the respondents agree that content in E-
learning should be made available in different languages. 45.5% strongly agree that the
content has to be made available in different languages, whereas 37.9% agree to the same, and
15.2% of the respondents is fine with common language. Only a minimal of 1.4% disagree for
this. We can see that majority of the respondents agree for the content to be made available in
different languages, and very few think it shouldn’t be made available in separate languages.
This graph illustrates the extent of IoT device usage in the modern era. Regarding the
utilization of IoT, 9.1% of the students picked a score of 5 out of 5, followed by 27.3% who
chose 4, 53% who chose 3, 10.6% who chose 2, and 0% who selected 1. The majority of
students, it is seen, think that although we use IoT frequently, it is not always available;
nonetheless, some students decided that we use IoT less frequently as their response. The
researchers came to the conclusion that although IoT is widely utilized today, more education
and awareness about it is still required if it is to be adopted globally.
The pie chart represents how many people believe that IoT can change the future of
education. As observed, 93.9% of the respondents are convinced that IoT can change the
future of education whereas 6.1% of the respondents do not believe so.
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Conclusion
The paper examines numerous Internet of Things uses in the area of education. Ideas are put
forth by several writers on the application of IoT resources in the sectors of education were
highlighted. Universities can overcome several issues, including managing vital resources,
enhancing information access, developing better planning, and creating safer campuses,
thanks to the development in technology. IoT systems have the prospective to significantly
improve higher learning by energizing the faculty and staff, encouraging the students, and
accelerating the learning process. Finding the prospective of IoT in higher learning and
leveraging the advantages were goals of this study. Additionally, studies may be conducted in
the context of some cutting-edge IoT-specific solutions that have the potential to be helpful for
education.
References
1. Kassab, M., DeFranco, J. and Laplante, P., 2020. A systematic literature review on Internet
of things in education: Benefits and challenges. Journal of Computer Assisted Learning,
36(2), pp.115-127.
2. Gul, S., Asif, M., Ahmad, S., Yasir, M., Majid, M., Malik, M.S.A. and Arshad, S., 2017. A survey
on role of internet of things in education. International Journal of Computer Science and
Network Security, 17(5), pp.159-165.
3. Moreira, F.T., Magalhaes, A., Ramos, F. and Vairinhos, M., 2017, June. The power of the
internet of things in education: an overview of current status and potential. In Conference
on smart learning ecosystems and regional development (pp. 51-63). Springer, Cham.
4. Bakla, A., 2019. A critical overview of Internet of Things in education. Mehmet Akif Ersoy
Üniversitesi Eğitim Fakültesi Dergisi, (49), pp.302-327.
5. Qureshi, K.N., Naveed, A., Kashif, Y. and Jeon, G., 2021. Internet of Things for education: A
smart and secure system for schools monitoring and alerting. Computers & Electrical
Engineering, 93, p.107275.
6. Aldowah, H., Rehman, S.U., Ghazal, S. and Umar, I.N., 2017, September. Internet of Things in
higher education: a study on future learning. In Journal of Physics: Conference Series (Vol.
892, No. 1, p. 012017). IOP Publishing.
7. Pervez, S., ur Rehman, S. and Alandjani, G., 2011. Role of internet of things (IoT) in higher
education. Education, 2011.
8. Suduc, A.M., Bîzoi, M. and Gorghiu, G., 2018. A Survey on IoT in Education. Romanian
Journal for Multidimensional Education/Revista Romaneasca pentru Educatie
Multidimensionala, 10(3).
9. Al-Emran, M., Malik, S.I. and Al-Kabi, M.N., 2020. A survey of Internet of Things (IoT) in
education: Opportunities and challenges. Toward social internet of things (SIoT): enabling
technologies, architectures and applications, pp.197-209.
10. Bagheri, M. and Movahed, S.H., 2016, November. The effect of the Internet of Things (IoT)
on education business model. In 2016 12th International Conference on Signal-Image
Technology & Internet-Based Systems (SITIS) (pp. 435-441). IEEE.
11. AjazMoharkan, Z., Choudhury, T., Gupta, S.C. and Raj, G., 2017, February. Internet of Things
and its applications in E-learning. In 2017 3rd international conference on computational
intelligence & communication technology (CICT) (pp. 1-5). IEEE.
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12. Soni, V.D., 2019. IOT connected with e-learning. International Journal on Integrated
Education, 2(5), pp.273-277.
13. Pei, X.L., Wang, X., Wang, Y.F. and Li, M.K., 2013. Internet of things-based education:
Definition, benefits, and challenges. In Applied Mechanics and Materials (Vol. 411, pp. 2947-
2951). Trans Tech Publications Ltd.
14. Pappas, G., Siegel, J., Vogiatzakis, I.N. and Politopoulos, K., 2022. Gamification and the
Internet of Things in Education. In Handbook on Intelligent Techniques in the Educational
Process (pp. 317-339). Springer, Cham.
15. Jean-Charles, A., 2018, March. Internet of things in education: Artificial intelligence voice
assistant in the classroom. In Society for Information Technology & Teacher Education
International Conference (pp. 883-885). Association for the Advancement of Computing in
Education (AACE).
16. Banica, L., Burtescu, E. and Enescu, F., 2017. The impact of internet-of-things in higher
education. Scientific Bulletin-Economic Sciences, 16(1), pp.53-59.
17. Doychev, E., Stoyanova-Doycheva, A., Stoyanov, S., Glushkova, T. and Ivanova, V., 2020. An
IoT Virtual eLearning Space. In Transactions on Computational Collective Intelligence XXXV
(pp. 148-169). Springer, Berlin, Heidelberg.
18. Razzaque, A. and Hamdan, A., 2020, April. Internet of things for learning styles and
learning outcomes improve e-learning: A review of literature. In The International
Conference on Artificial Intelligence and Computer Vision (pp. 783-791). Springer, Cham.
19. Jasim, N.A., AlRikabi, H.T.S. and Farhan, M.S., 2021, September. Internet of Things (IoT)
application in the assessment of learning process. In IOP Conference Series: Materials
Science and Engineering (Vol. 1184, No. 1, p. 012002). IOP Publishing.
20. Bayani, M., Leiton, K. and Loaiza, M., 2017. Internet of things (IoT) advantages on e-
learning in the smart cities. International Journal of Development Research, 7(12),
pp.17747-17753.
21. Veeramanickam, M.R.M. and Mohanapriya, M., 2016. IoT enabled futurus smart campus
with effective e-learning: i-campus. GSTF journal of Engineering Technology (JET), 3(4),
pp.8-87.
22. Doychev, E., Stoyanova-Doycheva, A., Stoyanov, S., Glushkova, T. and Ivanova, V., 2020. An
IoT Virtual eLearning Space. In Transactions on Computational Collective Intelligence
XXXV (pp. 148-169). Springer, Berlin, Heidelberg.
23. Oda, T., Matsuo, K., Barolli, L., Yamada, M. and Liu, Y., 2017. Design and implementation of
an IoT-based e-learning testbed. International Journal of Web and Grid Services, 13(2),
pp.228-241.
24. Abdelhady, G.A. and Mouez, M.A., 2020, September. Survey on IoT based education system,
case study: MSA university. In 3rd Smart Cities Symposium (SCS 2020) (Vol. 2020, pp. 498-
502). IET.
25. Fagroud, F.Z., Ajallouda, L., Lahmar, E.H.B., Toumi, H., Zellou, A. and El Filali, S., 2021,
January. A brief survey on Internet of Things (IoT). In International Conference on Digital
Technologies and Applications (pp. 335-344). Springer, Cham.
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CHAPTER 5
USE OF TECHNOLOGY AND ANALYSIS TO FIND PROBLEMS AND
SPREAD AWARENESS FACED BY SPEECH IMPEDIMENT PATIENTS
Moulik Tejpal (21BCE0213), Ambaliya Kaushal (21BCI0332)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
Communication problems involving hearing, speech, language, and fluency are referred to as speech
disabilities. A speech recognition system is presented to differentiate between a normal speaker and a
person with a speech handicap. Stuttering is the speech impairment that is the subject of this study, which
is done on both normal-speaking and stuttering female speakers. There are numerous reasons for speech
difficulties. Motor Neurone Disease (MND), Parkinson's disease, and multiple sclerosis are the three main
neurological degenerative diseases that cause severe speech impairments; stroke and cerebral palsy are
examples of non-progressive ailments that cause these impairments. Another illness that may affect speech
is vocal cord cancer, which requires laryngectomy.
Speech-based assistive technology interfaces are uncommon and frequently superseded by other types.
They are aiming at a market that is not seen to be appealing, and voice technologies are still not widely
used. The business community still believes that they pose some performance hazards, particularly Speech
Recognition systems. Speech has a tremendous potential to improve inclusion and quality of life for larger
groups of users with special needs, such as people with cerebral palsy and older people living at home, as it
is the most fundamental and natural form of communication. In this position paper, the authors make the
case for the need of making speech the default interface for assistive technologies. The following are some
of the key defences for speech recognition technology. Since there are more elderly and disabled people,
there is a growing market for embedded speech in assistive technologies; speech technology is already
developed enough to be used, but it needs to be customized for people with special needs.
Introduction
To live lives that are as productive as possible, many people with hearing loss may require
rehabilitation. As a result, individuals require a range of assistive devices that give them better
access to information and improve their communication skills in a number of settings. Most
gadgets either offer audio amplification or alternative methods of information access via
vibration and/or vision. Three broad categories can be used to classify these technologies.
There are subcategories depending on various uses of the technology or target audiences
within each primary category. These devices' main objective is to increase information
accessibility to a level as close as possible to that experienced by people without speech and
language problems.
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Exploring ideas and concerns that are crucial to take into account while seeking to help
people who use a range of augmentative and alternative communication systems get past
speech and/or language difficulties that prevent them from learning to read and write. An
initial foundation for creating more efficient methods of promoting literacy development and
addressing literacy-learning issues in a complex and varied population is provided by a
conceptual model of the literacy-learning process that represents current theoretical
understanding. The link between spoken and written language development in the general
population and its consequences for those with severe congenital speech abnormalities are
also covered.
There are numerous reasons for speech difficulties. Motor Neurone Disease (MND),
Parkinson's disease, and multiple sclerosis are the three main neurological degenerative
diseases that cause severe speech impairments; stroke and cerebral palsy are examples of
non-progressive ailments that cause these impairments. Another illness that may affect speech
is vocal cord cancer, which requires laryngectomy. MND, often referred to as Lou Gehrig's
disease or Amyotrophic Lateral Sclerosis (ALS) in the US, is a crippling neurological condition
brought on by the degeneration and death of the major motor neurons in the brain and spinal
cord. Due to the increased muscle weakness brought on by this, movement is lost, and
swallowing, breathing, and speaking become difficult. The ability to talk is lost in about 75% of
MND patients by the time of their death. MNDs come in four different flavours. Progressive
Bulbar Palsy and ALS are most common in those over 60. Primary Lateral Sclerosis usually
develops around age 50. Progressive muscular atrophy typically begins before the age of fifty.
In Scotland, United Kingdom, about 100 new cases of MND are diagnosed each year
The multimedia speech therapy system must be able to be used to deliver tailored speech
treatment for various difficulties and for various ages, according to numerous research. High
inter-speaker and internal variability must be supported by speech recognition technology. He
must be able to analyse the visual signal of the patient's speech and provide visual and audio
feedback in addition to displaying text on the screen, recording voice-read text, analysing
recorded speech signals, performing speech recognition, including identifying speech
abnormalities and monitoring disease progress. This suggests that creating effective
multimedia speech treatment software requires synchronising diverse media. Time-frequency
analysis and neural networks with the incorporation of image data are proposed to
accomplish speech recognition and recognition tasks.
For those with speech impairments, computer-based speech therapy systems or virtual
speech pathologists (VSTs) are presented as an alternative to the technology already in use.
This project has been organised using the PRISMA framework. Although there is no set
roadmap for how these systems should be designed, implemented, customised, and evaluated
for various language disorders, advancements in voice technology and an increasing number
of successful real-world projects in this area point to a thriving VST market in the near future.
This systematic review's emphasis is on phonology and speech impairments. All of the
experiments that were chosen incorporated computer intervention in the form of VSTs that
corrected pronunciation or phonetic issues, followed by qualitative or quantitative
evaluations.In general, articles describing technical elements had poor research design, while
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publications not describing technical elements did not describe the technical aspects
employed in their VST. It is underlined that the virtual therapist should not oversee the
intervention but rather serve as a means of implementing the speech-language pathologists'
planned intervention. According to the publications we've evaluated, VSTs are extremely good
at training people with different speech problems, but there isn't any agreement that they are
more effective than speech-language pathologists in terms of rehabilitation outcomes
Result Analysis
We observed that most of the people who were a part of our questionnairewere male.
Around 70 percent of our responses were male, leaving the female responses being around 30
percent. This depicts the participation willingness in accordance with gender.
18.2% belong to age group 13 to 18yr
81.8% belong to age group 19 to 59yr
Majority of our responses were from 19 to 59 age group.
Since speech impairment cases are increasing in children's that is the reason our target
audience for research were younger people.
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That is why the responses we received, also belonged to 13 to 59yr.
59.1% of the responses said they are not associated with any speech impediment user.
40.9% the responses said they are associated with any speech impediment user.
Majority of the people who took our survey were not associated with any speech / hearing
Impediment user
Although there has been a rise in the count of speech impediment cases but still the count
is nothing compared to our Population. We still managed to get 40.9% of the Surveyors being
associated with Speech/Hearing Impediment user.
People of various regions and localities participated in the questionnaire. Around 82
percent of them belong to the urban localities while the rest belong to rural areas.
The means of social participation are lesser in rural areas when compared to their urban
regions, which is clearly indicated by our study.
The severity of a disorder is a component upon which most of the treatment is decided.
Our questionnaire suggests that on a scale of 1-5, around 50 percent suffer from mild
disorders. 43 percent of them suffer from a little severe disorder. Around 7 percent people
suffer from very severe disorders.
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59.1% of the responses said they are not aware of any speech therapy Sessions.
40.9% the responses said they are aware of any speech therapy Sessions.
Majority of the people who took our survey were not aware of any speech therapy
Sessions.
34.1 percent people rated it 1
0percent people rated it 2
31.8 percent people rated it 3
22.7 percent people rated it 4
11.4 percent people rated it 5
Speech or hearing therapy sessions often considered help the most in a disorder's
development to cure. Our questionnaire suggests differently.
61.4% - Yes
11.4% - Maybe
27.3% - No
Generally, more than 60% of the people were already aware of speech impediment
application technology, more than a quarter of the whole percentage had absolutely no idea of
existence of any such tech and the rest had just heard about it here and there in conversations
but are not fully knowledgeable themselves.
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As we can clearly see from the results obtained by the survey conducted, Mobile
Applications are more preferable (61.4%) than physical aid devices (40.9%) than web
applications (29.5%).
This shows how much value the comfort of user experience holds in this sector of speech
impediment. A user will always prefer using a digital handy version of a technology (software)
than having the burden of carrying a physical device when given the choice.
When it comes to software’s, web applications and not so compatible certain operations
such as vibrations and gyro sensor, which mobile application can easily access and hence can
be programmed better in terms of the number of features the technology is capable of
performing in the near future.
54.5% rated 1/5
27.3% rated 2/5
11.4% rated 3/5
0%rated 4/5
6.8%rated 5/5
Only technically development of a problem is not enough but unity and support towards
the needy is appreciated and would help reach our vision of solving this issue at a much faster
rate.
6.8%rated 1/5
0%rated 2/5
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38.6%rated 3/5
31.8%rated 4/5
22.7%rated 5/5
Said that, how do the impaired seek mental peace and support? Therapy is one good
option, but unfortunately, these sessions which are supposed to comfort and understand the
patients, have not been effective and this is directly backed by the feedback result of therapy
sessions in the conducted survey. More awareness should be spread in terms of speech
impairment so a lot more understanding can happen resulting in much effective therapy
sessions.
6.8%rated 1/5
0%rated 2/5
31.8% rated 3/5
38.6% rated 4/5
22.7% rated 5/5
Majority of our users said and concluded that living with an impaired individual takes a
toll, as over 95% of the responses showcased the scale on which it has affected them or a
person close to them. Dealing with speech impairment is a sensitive topic as it showcases how
hard it makes communication between people due to their speech impairment.
93.2 % of our users assumed the need for greater awareness, compared to the 6.8% who
says there is enough awareness for the problems and issues of speech impairments, this shows
the public willingness to invest in good campaigns for the people suffering with problems as
summarized by our collected data.
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43.2% rated 1/5 (healthy manner)
27.3% rated 2/5
29.5% rated 3/5
0%rated 4/5
0%rated 5/5 (aggressive manner)
Questionnaire suggests that people with speech/hearing disorders are usually treated
with respect. There is only a small group of people who treat people with impairments as
outcasts.
0%rated 1/5
27.3% rated 2/5
31.8% rated 3/5
0%rated 4/5
40.9% rated 5/5
Majority of our users reported that medical services, and sessions were available to them.
A correlation was found between rural users and urban users,where rural users were the ones
that rated speech therapy sessions and services were lesser in number to them than urban
ones. Hopefully with assistive technology via mobile apps we are able to change this
percentage.
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The proportion of persons who feel worse about their impairment on certain days
compared to typical days is shown in the pie chart. It was shown that around 46% of persons
do not notice changes in the severity of the obstruction. 32% of participants were unclear
whether they experienced varying degrees of impairment on various days. 23% of
respondents said their impaired state was worse some days than other.
The intensity of a surrounding’s impact on the conditions is depicted in above pie chart.
Approximately 61 percent of respondents thought their environment had no effect on how
their surrounding conditions were, whereas 39 percent thought it did. We can relate it to the
46 percentage of people who said that their impairment doesn’t worsen on some days. So,
these people don’t are not affected by the change in the surroundings too.
The happiness of people with regard to governmental regulations for those with
conditions to drive is shown in the pie chart. It was discovered that roughly 71% of people
disliked of the laws. It may be because RTOs do not issue driving licenses to those who have
hearing impairments. However, about 29% of people said they were happy with the laws.
The severity of the academic consequences individuals experienced because of the
disorder is mentioned in the above pictorial representations. On a scale of 1 to 5, the
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seriousness of the consequences is specified. The majority of respondents gave 4 as a response
which means that they had significant academic challenges. 32% of respondents had mild
academic consequences. 11 percent of the population reported no issues with their diseases
affecting their ability to study. Approximately 7% of respondents had severe academic effects
as a result of their impairment.
Conclusion
These results provide further evidence of the long-term effects of language disorders.
Presented data indicates continuous difficulties for students entering school with expressive
language disorders, especially those whose language disorders are characterized by non-
developmental error processes procedure Effects were evident in tasks measuring
phonological awareness, reading accuracy, and spelling (skills that rely on good phonological
processing skills and clear underlying phonological representations). Poor reading
comprehension was also noted. These results have implications for early detection of people at
risk. In addition, interventional approaches to expressive infants who exhibit these error
patterns should address potential phonological weaknesses and develop phonological
recognition skills. Hearing loss has a significant negative impact on the quality of life of older
people who are restorable with hearing aids. Early detection of hearing loss in childhood was
associated with higher language scores, but not with speaking in middle age.
References
1. Wright., et., al., 2001. Relationships among speech perception, production, language,
hearing loss, and age in children with impaired Hearing.
2. Davis, A.C., et., al., 1983. Hearing disorders in the population: first phase findings of the
MRC national study of hearing. In Hearing science and hearing disorders (pp. 35-60).
Academic Press.
3. Creer, S., et., al., 2013. Building personalized synthetic voices for individuals with severe
speech impairment. Computer Speech & Language, 27(6), pp.1178-1193.
4. Rong, P., et., al., 2021. A Novel Hierarchical Framework for Measuring the Complexity and
Irregularity of Multimodal Speech Signals and Its Application in the Assessment of Speech
Impairment in Amyotrophic Lateral Sclerosis. Journal of Speech, Language, and Hearing
Research, 64(8), pp.2996-3014
5. Qin, Y., et., al., 2019. Automatic assessment of speech impairment in cantonese-speaking
people with aphasia. IEEE journal of selected topics in signal processing, 14(2), pp.331-
345.
6. Georgopoulos, V.C., 1999, June. An investigation of audio-visual speech recognition as
applied to multimedia speech therapy applications. In Proceedings IEEE International
Conference on Multimedia Computing and Systems (Vol. 1, pp. 481-486). IEEE.
7. Chen, Y.P.P., Johnson, C., Lalbakhsh, P., Caelli, T., Deng, G., Tay, D., Erickson, S., Broadbridge,
P., El Refaie, A., Doube, W. and Morris, M.E., 2016. Systematic review of virtual speech
therapists for speech disorders. Computer Speech & Language, 37, pp.98-128.
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8. Kleffner, F.R., 1973. Hearing losses, hearing aids, and children with language disorders.
Journal of Speech and Hearing Disorders, 38(2), pp.232-239.
9. Salvi, R., Ding, D., Jiang, H., Chen, G.D., Greco, A., Manohar, S., Sun, W. and Ralli, M., 2018.
Hidden age-related hearing loss and hearing disorders: current knowledge and future
directions. Hearing, balance and communication, 16(2), pp.74-82.
10. Margolis, R.H. and Saly, G.L., 2007. Toward a standard description of hearing loss.
International journal of audiology, 46(12), pp.746-758.
11. Yamagishi, J., Veaux, C., King, S. and Renals, S., 2012. Speech synthesis technologies for
individuals with vocal disabilities: Voice banking and reconstruction. Acoustical Science
and Technology, 33(1), pp.1-5.
12. Teixeira, A., Braga, D., Coelho, L., Fonseca, J., Alvarelhão, J., Martín, I., Queirós, A., Rocha, N.,
Calado, A. and Dias, M., 2009, June. Speech as the basic interface for assistive technology. In
DSAI 2009-Proceedings of the 2th International Conference on Software Development for
Enhancing Accessibility and Fighting Info-Exclusion
13. Olaosun, A.O. and Ogundiran, O., 2013. Assistive Technology For Hearing and Speech
Disorders. Assistive Technology, 3(17).
14. Hawley, M.S., Cunningham, S.P., Green, P.D., Enderby, P., Palmer, R., Sehgal, S. and O'Neill,
P., 2012. A voice-input voice-output communication aid for people with severe speech
impairment. IEEE Transactions on neural systems and rehabilitation engineering, 21(1),
pp.23-31.
15. Prelock et al., 2008. Speech-language impairment: how to identify the most common and
least diagnosed disability of childhood. The Medscape Journal of Medicine, 10(6), p.136.
16. Matoušek et al., 2020. Speech and web-based technology to enhance education for pupils
with visual impairment. Journal on Multimodal User Interfaces, 14(2), pp.219-230.
17. Foley, B.E., 1993. The development of literacy in individuals with severe congenital speech
and motor impairments. Topics in language disorders.
18. Bishop, D.V., 2006. What causes specific language impairment in children? Current
directions in psychological science, 15(5), pp.217-221.
19. Bernhardt et al., 2005. Ultrasound in speech therapy with adolescents and adults. Clinical
Linguistics & Phonetics, 19(6-7), pp.605-617.
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CHAPTER 6
ENGLISH LEARING AND TEACHING METHODOLGY USING
DEEP LEARING
Ishita Jindal (21BCB0061), Vansh Dalal (21BCE0635), Aditi Singh (21BCE0349),
Prajwal Sinha(21BCE0713), Prateek(21BCE2522)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
Deep learning is a learning method which deals with higher order thinking and emphasizes the learner’s
ability to understand the learning content. The aim of this thesis is to find the solution to the shortcomings
to the existing teaching methodology and implement deep learning to improve the teaching and learning
of English as a language. The research targets the students of VIT-Vellore university as an audience of data
collection, taking 65 students from various branches for analysis. An online survey was conducted using
Google forms to collect the required data, where questions were mainly focused on their views of the
current teaching method, deep learning as a concept and implementing deep learning into the current
education system. To make sure the form had good outreach, it was circulated via WhatsApp messages,
word of mouth and emails. People are expected to have some degree of knowledge about deep learning as a
concept and its effectiveness to teach and learn English as a language. The collected data was then
analysed thoroughly using various methods such as pie charts and other graphical representations, tables
and excel spreadsheets. It was observed that students while lacking basic knowledge o f deep learning were
open to have it implemented but feel a mix of traditional and modern methods must be used without one
overpowering the other.
Introduction
According to statistics, English is spoken as an official language by over 430 million people in
Asian nations like India, where it is the primary language of over 350 million people and
taught in over 118 countries. This makes English is the most widely spoken language in the
world. It is also the top most profitable language in the CSA rankings. It currently has 1,348
million speakers, commands 43.9% of the eGDP and 27.7% of the online population making it
an incredibly useful language to learn.Learning the English language can help you speak
efficiently with people from all around the world, which will make travelling much simpler and
teach you more about various cultures. Nearly every element of our life demonstrates the
value of the English language. This is particularly true in the business sector, where English is
the most widely spoken language. As a result, most companies will require candidates to have
a specific level of English proficiency throughout the recruiting process. Investing in a good
English language education will considerably improve your job prospects.
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Deep Learning is an approach and an attitude of learning where the learning uses their
high order skills such as ability to analyse, synthesize, solve problems and think in a different
way in order to have long term understanding. It involves critical analysis of new ideas, linking
them to already known concepts, and principles so that this understanding can be used for
problem solving in new unfamiliar contexts. Deep learning promotes understanding and
application of concepts.
The rise of E-learning software in classrooms and educational centres has enabled open
minded environments in classrooms. The popularity of online platforms is offering large
amount of data on how students interrelate with educational software. This data and insight
might have opened new ways of deep learning methods to understand how students can be
trained. This process will personalize the educational atmosphere to the precise needs of the
students.
Many education institutions emphasize only an English only teaching medium, to reinforce
uniformity and a flow of information which is not lost in translation, however with a country
like India, having a diverse population of over 1 billion people and more than two hundred
native languages, it is evident not everyone will be fluent enough in English to understand the
instruction. Sticking to only English leads to misunderstandings and confusion in simple terms
like circle and not only technical terms or jargon. This barrier in communication prevents the
student from connecting with the faculty and the subject. A big jump in the level of language
also poses a problem as they now have to comprehend specific terminologies without knowing
the basics of the language. This further leads to distortion of concepts they might have known
well in their native language leading to students having to relearn these concepts.
The success of deep learning has exceeded our expectations. It outperforms the alternate
approaches to finishing a task with the help of its extensive database. But we cannot be sure, if
the chosen approach is the best and most efficient.
Deep learning is a vast and developing technology, its algorithms are more vulnerable to
failures, due to which, it has discovered and undiscovered limitations. Since it is a
comparatively new technology, it is unable to interpret out-of-scope functions effectively. Any
small addition to a function might lead to major alterations in the algorithm.
Learning with the current deep learning methodology is difficult, specifically the grammar
of any spoken language. As per the existing algorithm, it searches its limited human-annotated
data, with which it ignores the exception in rules or gets confused due to the ambiguity to give
the literal interpretation as output. Deep learning does not have the human exposure to think
out of the box and serves us with results based on already fed data, and with the data missing,
it becomes a lesser useful tool.
Literature Review
Li X (2017) states that due to the rapid growth in students' education and modern information
technology, a convergence has been prevailing between the two. The current teaching
approach differs from the existing educational approach. It integrates technology with college
English teaching. First, the teaching of college English is optimized using the GA-MLP-NN
algorithm so that students may learn and understand more complicated structures. Based on
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S-type recursive function, incremental hidden layer unit neural network is built, increasing the
operation's accuracy. The GA-MLP-NN neural network model is then used to build the spoken
English system. Finally, we assess the model's parameters, create a comparative experiment,
and conduct a questionnaire survey to confirm the validity and viability of the hypothesis,
demonstrating that this approach can handle more complex program and improve students'
English learning experiences by utilizing computer technology.
Ding H (2021) states to examine the in depth learning for the experiment a large group of
students Were taken into consideration where more than half of them served as the reference
group, with the rest being the observation group. This allowed the researcher to compare the
impact of in-depth learning with respect to the current method of education. The observation
group was noticed to have a better performance than the reference group. The deep learning
algorithm is utilized for analysis of the structure of student’s English papers and the
applications can be widely developed. Other effects involve reduction in stress levels, along
with a great increase in learning efficacy.
Guo Y (2021) states that the university has fresh chances for development and problems
due to the quick development of artificial intelligence. The essay examines "smart education"
and the process of developing a teaching model for English college by analysing the ideas of,
deep learning and language education. Deep learning, has widespread opportunities in many
areas, including but not limited to helping overcome individual differences in learning,
customizing materials, and unique assessments. The process must evolve into a different form,
a loop, to develop various niches in the learning process. Data mining technology can be used
to analyse patterns and characteristics. For creating a deep learning-based scoring prediction
model, a system must be constructed to teach English informatics in this new method. Deep
learning can also be used to explore certain academic niches by using methods such as word
embedding and convolutional text networks. This approach can lead to the exploration of new
areas of English which the academic might not have known previously existed and can lead to
a new area of interest and for the academic. The results of the research prototypes provide a
compelling result proving that the online e-learning platform can satisfy the varying and
individual English learning requirements of university students, as well as increase both
teachers' and students' learning efficacy with ease.
Jiang D (2022) states that the English methods had low accuracy and poor effect problems.
The solution to the problem is proposed in the paper using deep learning algorithms. An
ability assessment method is created using these algorithms. This method analyses using a
series of layers namely input, convolution, pooling, and fully deep layer which helps to get the
estimated outputs using back propagations. We set a deep learning model to set the English
teaching and learning ability assessment using fixed data. The current online English
evaluation system in schools is unstable so it is better to adopt a better evaluation system and
better high school teaching is more in-depth practical and theoretical. This article combines
deep learning algorithms and remote supervision which simulates and analyses the
algorithms. The article also evaluates what students are doing in the learning process
analyzing their actions and status. The paper is designed to evaluate effective learning models
and their effect on the target audience.
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Wang T (2022) states that on applying deep learning to an online platform and analyzing
the target by using sets of algorithms. A personalized learning algorithm is applied to help the
learners effectively. The first technique we are using is named “Cluster Mining” which analyses
the target profile and classifies them into various groups and provides them with a suited
content to them for better communication. Association rules are another approach that finds a
correlation between the content for the learners. For an adaptive teacher-student relationship
online, a teacher model implementation can guide the learner and be specific to him regarding
his assessments. For an effective English assessment platform, we use deep mining. We are
hopeful that the results of this study will contribute to the area of research and enhance the
standard of education.
Qu C (2022) stated that a deep-learning based research aids to help the current English
auxiliary system. The deep learning teaching mode for students in college was investigated in
this research. Earlier students had the perception that the finest way to qualify for an English
examination is by memorizing the words with a high frequency which was later changed to
that with active participation and engagement orally is possible to pass the exams. It is
suggested to train our critical ability with the help of logical English problems to boost our
confidence. Through the use of technology, a qualitative and quantitative method was adopted
for the evaluation of practical applications called the offline and cloud model.Two rounds of
loop designs were created for the research which is being improved continuously.This study
aims to improve the accuracy of English speech recognition and provide better evaluation
methods. This work builds on related theories such as deep learning, speech recognition, and
oral practice. As summarized in the literature, recurrent neural networks have formed the
basis of computation and English speech recognition indices are the main basis for building
English speech recognition models. Then, 20 English majors and 5 sets of English sentence
samples were randomly selected for the studies. For further improvement, a criterion for
correcting English language errors was included in the model. According to the survey results,
the average match rate for speech recognition by sample testing reached 91%. The matching
rates of words, phonetics, and timbres for recognition were 89%, 91%, and 86%, respectively.
Therefore, in this study, we investigated the application of a deep learning assessment model
to evaluate oral English teaching.
Xu J (2022) stated that in multimedia English classes, learners stand in front of an
emotionless and indifferent computer screen to feel the enjoyment and emotional stimulation
of interaction, causing resentment and affecting learners' learning effects. The efficiency
English learning and teaching and the presence of emotion in targets can be enhanced by a
teaching system based on deep learning language and facial recognition. The foundation of the
study uses emotion computation and facial expression recognition as the base to recognize the
facial expressions of learners based on emotional states. The method of identifying is tested in
the paper and it states a good recognition effect on the micro-expressions. The English
teaching university faces new development prospects and problems as a result of the quick
development of artificial intelligence. By understanding artificial intelligence and language
education, the idea of "smart education” is initiated. The process of learning language is a non-
linear process which has transformed into an open loop. Considering the data mining
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technology for analysis of characteristics provides a harmonious development language
learning. A scoring prediction model is created by analyzing and designing a model English
teaching and learning system. Embedding and convolution networks are used in the deep
learning algorithms revealing the hidden interest areas in English.
Han Y (2021) stated that the findings of the experimental study demonstrate that the
online e-learning services successfully satisfy the various and individual English learning
needs of university students. The standard of English is gaining attention as the ongoing.
Assessments play a vital role in enhancing English education and teaching. The English
teaching university faces new development prospects and problems as a result of the quick
development of artificial intelligence. By understanding the ideas of artificial intelligence, deep
learning, ecological linguistics, and language education, this study investigates the idea of
"smart education". The language learning process is no longer a linear process but an evolving
open loop, resulting in the harmonious development of various ecological niches in the
language learning process. This is accomplished by relying on the data mining technology of
deep learning to analyze learners' characteristics. In order to create a deep learning-based
scoring prediction model, we analyze and design a system for teaching English informatics in
this work. The deep learning algorithms used in the approach, which include word embedding
and text convolutional networks, can reveal the academics' hidden areas of interest in English.
The findings of the experimental study demonstrate that the online e-learning services
successfully satisfy the various and individual English learning needs of university students.
Ning Y (2016) stated that the study of English education quality is getting more and more
attention as the current reform of English education and teaching continues to grow and
expand. English education assessment is a key initiative to improve the quality of English
education and teaching. Improving the quality of teaching is the main emphasis of raising the
standard of English education. As a result, education management places a high priority on the
creation and growth of the Englisheducation quality evaluation system. This essay includes the
elements of deep learning and is based on a thorough investigation of the state of English
education quality evaluation in universities today. This research builds a deep learning-based
English education quality evaluation model and conceptually compares and contrasts the
training outcomes of the deep learning algorithm and the algebraic algorithm employed in the
model to provide a workable solution for the English education evaluation model. Through
simulation analysis, we may draw the conclusion that the deep learning-based evaluation of
English education proposed in this research has produced positive evaluationfindings.419
students were chosen for the experiment in order to examine the ways in which in-depth
learning is applied and its effects on English teaching for non-English majors in colleges and
universities. 205 students from grade 2018 served as the reference group and 214 students
from grade 2019 served as the observation group, allowing researchers to compare the effects
of examination-oriented education and the impact of in-depth learning. Students in grade
2019 performed significantly better than students in grade 2018 which was statistically
significant. Finally, it is discovered that the intelligent deep learning algorithm is used to
analyze the knowledge structure of non-English speaking students' English papers, and the
application scenarios of the analysis results are widely developed, all of which help to enhance
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the effectiveness of non-English speaking students' English instruction, increase the
effectiveness of their learning, and decrease their stress levels.English is a universal language
making it very significant for economic and cultural exchanges globally. While countries
prioritise the teaching and learning of the English language, many countries don’t have the
resources to teach about the correct pronunciation. Other factors like, the when and where of
class also hinder progress in English. Deep learning can be used to identify and evaluate the
quality of pronunciation along with providing, precise and rapid information about the
pronunciations. Learners can also correct their pronunciation by learning about minor
pronunciation faults on repeated listening, overall bettering the existing process. The deep
learning model used for the process must be able to distinguish between factors like
intonation, speed, and rhythm. It has been seen in tests that only about 13% people fare better
when the pronunciation is manually taught to them as compared to a deep learning model.
Liu Y (2022) stated that the advancements in deep learning have put forth a vast
opportunity to an English medium institution. This report discusses further about the concept
of “smart education” and building a teaching model for colleges by using the concepts of
artificial intelligence, deep learning, and language education. Deep learning performs various
functions like analysing minute differences and customization and visualization of learning.
Teachers perform a major role in smart classrooms and making conceptual assignments. The
language learning process is constantly grows using deep learning which helps to see
individual progress, promotes independent learning. In this paper, a study a deep learning-
based English is done based on informatic teaching system. The model contains deep learning
methods based on word embedding and text convolutional networks, which can be helpful for
the future of academics for English. The research results reflect and prove that the online e-
learning service platform doesn’t only provide the solution for diverse English learning needs
of university students, but it also enhances the learning efficiency of both teachers and
students.
Guo Y (2021) stated that the grammar is a very important part of English teaching.
Following the seq2seq model, deep learning can be used to create a grammar analysis with
attention, word embedding and CNN methods. A prototype algorithm was trained on NUCLE
and tested on Conil-2014.There was a 33.43% improvement as compared to seq2seq.
Following the P and R values of this study and CAMB, the P value has a marked increase of
59.33% and the R value was 8.9% larger. On analysis of a real student’s grammar homework, it
is seen that the algorithm performs well. The positive outcome of the prototype proves its
application in grammar purposes and can soon be implemented in teaching English.
Shi J (2022) stated that the Deep learning for learning English can even be extended to a
mobile environment. Texts can be handwritten using the pre-existing screen input method.
This makes the process more convenient than using an explicit graphics user interface. Then
deep learning is used to develop an interaction depending on the behaviour of the input text.
For recognizing text written interface, the Extended Modified National Institute of Standards
and Technology (EMNIST) dataset and a convolutional neural network (CNN) model can be
used. On connecting the text to a behaviour, finally English language teaching applications are
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created. They facilitate the user for alphabet and word writing using handwritten techniques.
The method can be updated and improved upon depending on user feedback.
Wang T (2022) stated that the objective is to understand the state of the current English
teaching method (CET). A questionnaire is designed to test the student’s vocabulary, then deep
learning is introduced with edge computing into the CET. Based on the when and how a
student learned their vocabulary it is seen that their vocabulary is shallow. Further teachers
follow a teaching method they find appropriate but students find it to be far from perfect.
Implementing deep learning into the CET enhances students’ concentration in class time,
homework submission efficiency, and the overall academic performance. Many students also
believe that new these new teaching methods have made learning English more fun and
interesting. Therefore, adding deep learning to the CET is extremely beneficial.
Guo Y (2021) stated that the recently, according to research which was undertaken by the
scholars has shown that there has been a big shift in ways of English language learning and
teaching from current education in institutions. The scholars strongly suggest that
strengthening or improving language skills are not mutually exclusive to each other. Deep
Learning Theory and Deeper Learning Cycle have provided course elements and the method of
learning languages combined with current educational system by using problem solving and
deep-learning based learning process. It provides an insight making the design and
implementing of a new educational process in learning English language.
Fei B (2022) stated that Technology is a developing tool. It is strengthening different
sectors of society by creating awareness among people by providing access to data worldwide.
It plays a vital role in the process of learning and teaching. Nowadays, technology is used as an
aid to enhance the learning and teaching process. It helps an educator to educate their scholars
with ease. The main focus of this research lies in identifying the use of any new technology to
learn or teach Technology is a developing tool. It strengthens different sectors of society by
creating awareness among people by providing access to data worldwide. It plays a vital role
in the process of learning and teaching. Nowadays, technology is used as aid to enhance the
learning and teaching process. It helps an educator to educate their scholars with ease. The
main focus of this research is to identify a new technology to learn or teach English as a
spoken or written language for skill improvement. This research fixates its attention on the
link between technology and language. It explains classroom learning with technology,
comparisons between the learning methodologies, and suggestions for various techniques for
improvement. It specifies the ways to use technology effectively.
Ji D (2022) stated that the english language skills refer to speaking, writing, and
understanding. Mobile phones have cordially influenced our regular lives. While learning or
teaching, phones help students stay connected to ongoings worldwide. The data was collected
through online and offline surveys using questionnaires. The research shows an excessive time
spent on social networking sites; a few students use the technology effectively for education.
There is a need for teachers and parents to encourage students to be aware of research-based
knowledge, and to be more curious and creative, such that they can gain experience analysing
things on their own.
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Lekawael (2017) stated that the research conducted among students from Indonesia. The
students belonged to a private Senior High School in South Tangerang; they require the help of
technology to learn English outside of class. When the students are given freedom to explore,
they get to acknowledge things to their greatest potential leading to successful learning. A
quantitative and qualitative design was applied in this research which included questionnaires
and semi-structured interviews. Based on the responses in interviews, five students were
selected. The research states learning English with the help of technology boosts self-
confidence, and social aptitude, gaining motivation and awareness. The research's main
expectation was to improve students' English proficiency with the help of information and
communication technology using deep learning.
Ahmadi D (2018) stated that Mobile learning has conventionally emerged as the root of
the teaching and learning process, which can also be English learning and teaching process
using mobile is an exemplary model of the modern learning process. With the new education
system executed, it is noticed that students and teachers have had an improvement in their
skills. The progress has increased knowledge of effectively using technology. A multiprocessor
based on the CCN algorithm proposes the idea to improve the English fluency rate. With the
unavailability of teachers in remote areas, learning concludes through a reciprocating media
platform. The designed model provides an ease to the teacher by helping students understand
with an easier methodology. As per the research, the algorithm makes English learning and
teaching easy with an increase of 10% in accuracy rate.
Result Analysis
80% of respondents tend to have completed their academics in a city, as per thechart.
According to the survey, 3/4th of the survey population has completed their education in a city
and a minority have completed it in a town or a village It concludes that the majority of the
audience belongs to the city.
`
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The chart shows that 40% of people agree with the statement, "Learning and teaching
methods using deep learning will provide research-based knowledge."
It is observed that people having a neutral hold on the statement are slightly lower, as they
are unaware of deep learning as a concept. The people in disagreement with the statement are
found to be minute.The chart all boundedlyfavors learning and teaching using deep learning,
providing research-based knowledge.
The chart depicts the belief in efficient learning outside the classroom.
As per the chart data, we spot that approximately 73 % of people consider that deep
learning can provide efficient learning outside the classroom. The remaining data shows the
uncertainty of people. A few students still adhere to traditional teaching methodology being
efficient, but the ratio of such people is comparatively on the lower end.The target audience is
more inclined to believe that deep learning elevates learning efficiency outside classrooms.
According to the survey, the statistics prefer teaching and learning using deep learning.
On analyzing the graph, it is observed that the need for learning and teaching with deep
learning is favored. But, the necessity of this methodology is denied, since the urgency to
implement is observed in minority. With the greater amount of people favoring teaching and
learning using deep learning, it concludes that this methodology is suitable for introduction for
better understanding of concepts, despite it not being a necessity.
The survey results portray a higher interest in people wishing to learn deep learning
concepts in English methodology. There is a slight variation in people interested in learning
and giving it a try, but the overall data claims a high interest in people towards deep learning
in English. Individuals who are unaware of the concept are hesitant to opt for learning the
deep learning concepts used in English. Since, more than half of the population shows interest
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in learning deep learning concepts related to English. Therefore, it concludes that learning and
teaching students wish to learn a new methodology for teaching and learning English.
It is noticed that more people feel that existing learning and teaching using deep learning
methodology has made a moderate impact.
People dissatisfied with the impact of learning and teaching methodology are negligible
compared to the number of people pleased with it. Therefore, it portrays that the target
audience is benefitted from the learning and teaching methodology using deep learning.
Looking at the statistics, we can say that the maximum responses are from students who
belong to Computer Science branch. This means that the responses to other questions might
be biased more towards the knowledge of a computer science student as compared to
students of other branches like Civil, Chemical, Architecture etc. As deep learning is a part of
the Artificial Intelligence branch which comes under CSE, the output of the research is likely to
have a high rate of accuracy. The variation in branches help us to gain perspective from
students having different knowledge and point of views.
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From the above bar graph, we can see that maximum people are quite interested in
learning the English language.Few people are moderately interested whereas a very few
people don’t value learning English too much. This however shows that a large number of
students consider English as an important language and that they would love to learn it by
various ways for its better use in their life.
From the data above we can observe that 41.5% of the students have a little knowledge
about the deep learning methodology whereas 38.5% are still clueless about the topic. A very
small population of the students is well aware about the concept and a large percentage of
students are quite enthusiastic about the topic even though they don’t have any knowledge
currently. This shows the popularity of the deep learning concept and the vast exposure that it
needs and its demand in the current times.
It is noticed that a vast majority of students strongly believe that deep learning has a major
scope in teaching and learning English whereas about only 30% aren’t quite sure about the
idea. This is definitely something to think about since from the analysis of the above question
we see that mot many students are completely aware about the concept and yet they strongly
support the implementation of the idea. This means that even without complete knowledge
students know the importance and scope of the subject.
According to the survey, about 74% of the population lies int the category of students who
are in the affirmation of the above statement. As for the rest, the majority of students are
neutral about the concept and very small fraction of students are in disagreement of the
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statement. Therefore, this portrays that the target audience knowns how they can be
benefitted from the deep learning methodology in learning and teaching English.
Looking at the statistics we can say that people are not fully satisfied by the current spell
check algorithms with an average range of 3-4 range out of 5. This means that the current
algorithms still need an advancement to their current design in order to have a better user
response towards many English applications in daily life considering correction and spell-
check the major in this analysis. As a whole it shows us the importance of these algorithms.
Referring to the pie-chart students are being neutral towards being given excessive
number of assignments which is not necessary. After being neutral students are also agreeing
with the fact that students are being given necessary assignments which is not needed.
Collectively it shows that assignments are an important part of student’s life.
Referring to the pie-chart student-teacher interaction is said to be the main reason in
order to improve teaching by a teacher followed by practical references. Practical usage is
shown the least which tells us that nobody is willing to communicate in the language they are
willing to learn. The chart also shows that how a teacher-student bond is so important for an
interactive session and better understanding.
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Looking at the current bar graph adaptation to new environment is shown the major
concern in implementation of deep learning followed by excessive knowledge. Malpractice is
also given a concern in the bar graph. This gives us a picture that people are a little bit hesitant
in shifting to newer platforms. Malpractice is also being for sure looking at the bar graph with
everyone eager to obtain a good grade on online platforms.
Looking at the pie-chart people are showing a strong belief in deep learning algorithms for
correction of assignments and a very few populations is giving it a false compliment. This
shows that people are having a belief on these algorithms for corrections such as plagiarism
etc which can be time consuming without a machine.
The chart shows that 36.9% of people think that Deep learning methodology may or may
not be implemented i.e. they are neutral and also 30.8% of people agree that it can be
implemented in current education scenario.
It is observed that people who strongly agree on the implementation of deep learning
methodology are slightly lower . The people in disagreement constitutes 15.4% of the total
responses, because they might be unaware of the fact that how deep learning can change the
current education scenario.
The chart all roundely favors that deep learning methodolgy can be implemented in
current education scenario.
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The survey results portray that people will be consistent in learning English using deep
learning. There are certain percentage of people i.e., 36.9% people who think that people may
or may not be consistent in learning English using deep learning. These people might be
unaware of the fact how deep learning can change current education system. The remaining
data shows disagreement of people, but the ratio of such people is on the lower end.
The chart all boundedly shows that that people agree on the fact that they will be
consistent in learning English using deep learning.
It is noticed that more people feel that existing teaching methods used for teaching English
has made a decent impact.
People dissatisfied with the current teaching methods for teaching English also hold a
certain percentage. Therefore, it portrays that the target audience seem to be neutral on
current teaching methods used for English teaching and they might accept the innovation of
deep learning in English teaching methods.
According to the survey, the statistics shows that people are satisfied with current deep
learning algorithms used in paraphrasing tools. People dissatisfied with the algorithms of
paraphrasing tools are negligible compared to the number of people pleased with it.
Therefore, it portrays that the target audience is benefitted from the deep learning algorithms
used in paraphrasing tools.
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The chart shows that 46.2% of people agree with the above statement.
It is observed that people having a neutral hold on the statement are slightly lower, as they
might not know what changes deep learning can bring in current teaching methodology. The
people in disagreement with the statement are less compared with the ones who agree with
the statement.
The chart all boundedly shows agreement to the above statement.
Our respondents include the students doing B. Tech of which max of the respondents are
from second year and few respondents are from 3rd and 4th year. It concludes that the majority
of the audience are from 2nd year.
As is implied by the pie chart, we see most of the students who took part in the survey
have achieved or are achieving a bachelor’s degree in technology, with the remaining 4.6%
split between their master’s degree and a PhD.
As can be implied from the above chart we see that most of the students who responded to
the survey have little to no knowledge of deep learning. This lack of knowledge of deep
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learning in general inhibits the expression and foundation of deep learning as a tool to help in
educational purposes on a daily basis. This lack of knowledge could be due to various reasons
including but not limited to finding deep learning to be a part of AI and ML which is perceived
as too much of a pain to do.
Deep learning has one major advantage over the traditional method in the sense that the
software provides personalized progress tracking and can be improved upon to even provide
personalised corrections to students. Following this trend, the majority agree that
personalized progress tracking is important and helps each student understand their weak
points however a few feel that the above is not really necessary and the traditional method of
equal measures of education for all is better.
68% of the students are open to try out deep learning methods. They would love to
embrace change and see how the methods work out. Of the remaining, 20% are indifferent to
the change and just want to learn, the remaining 12.3% wish to maintain and are more
comfortable with the traditional method of teaching.
It is believed that teachers will still play an important role for education needs of students
and a symbiotic relationship of both teachers and technology is required for maximum
betterment. A minority believe the teachers will no longer have a major part in the education
system and a well-developed algorithm will eventually be able to replace them. The others are
not sure about the question and feel other factors will also play a part in the same.
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An almost equal split exists between the students willing to test deep learning applications
for betterment and those who would like to know more details before agreeing to any tests.
About 15% of the people would prefer not to participate at all and approximately 10.8%
would look for some sort of compensation for their time and efforts before agreeing to test
these applications.
Conclusion
The research conducted across many fields and branches in VIT-Vellore has led to the
conclusion that there is an in general lack of knowledge about deep learning as a concept, but
students are open to the implementation of deep learning algorithms and methods in the
current teaching method. There are various problems which plagues the current teaching
methods and students wish to get the best from the education system. While a complete
transformation from traditional methodology is not preferred, a symbiotic relationship must
exist between the traditional and future methods of learning. It will take a lot of time and
practice to find this delicate balance and adapt to this system. Hence it can be concluded that,
while deep learning prototypes are ready to be implemented into the system, it must be
perfected over time.
References
1. Li, X., 2017. The construction of intelligent English teaching model based on artificial
intelligence. International Journal of Emerging Technologies in Learning (iJET), 12(12),
pp.35-44.
2. Ding, H., Chen, Y. and Wang, L., 2021. College English online teaching model based on deep
learning. Security and Communication Networks, 2021.
3. Guo, Y., 2021. A Study of English Informative Teaching Strategies Based on Deep
Learning. Journal of Mathematics, 2021.
4. Jiang, D., Pei, Y., Yang, G. and Wang, X., 2022. Research and Analysis on the Integration of
Artificial Intelligence in College English Teaching. Mathematical Problems in
Engineering, 2022.
5. Wang, T. and Gu, Y., 2022. Research on the Design of English Comprehensive Learning
Activities Based on Deep Learning. Mobile Information Systems, 2022
6. Qu, C. and Li, Y., 2022. Oral English Auxiliary Teaching System Based on Deep
Learning. Advances in Multimedia, 2022
7. Xu, J., Liu, Y., Liu, J. and Qu, Z., 2022. Effectiveness of English Online Learning Based on
Deep Learning. Computational Intelligence and Neuroscience, 2022.
98
8. Han, Y., 2021. Evaluation of English online teaching based on remote supervision
algorithms and deep learning. Journal of Intelligent & Fuzzy Systems, 40(4), pp.7097-7108.
9. Song, C., 2022. An Evaluation Method of English Teaching Ability Based on Deep
Learning. Security and Communication Networks, 2022.
10. Ning, Y. and Zhu, X., 2016, September. Deep learning in effective English teaching strategy
of senior high. In 2016 4th International Education, Economics, Social Science, Arts, Sports
and Management Engineering Conference (IEESASM 2016) (pp. 1281-1285). Atlantis
Press.
11.
Liu, Y. and Li, R., 2022. Deep Learning Scoring Model in the Evaluation of Oral English
Teaching. Computational Intelligence and Neuroscience, 2022.
12.
Hao, K., 2020. Multimedia English teaching analysis based on deep learning speech
enhancement algorithm and robust expression positioning. Journal of Intelligent &
Fuzzy Systems, 39(2), pp.1779-1791.
13.
Guo, Y., 2021. A Study of English Informative Teaching Strategies Based on Deep
Learning. Journal of Mathematics, 2021.
14.
Shi, J., 2022. Deep Learning for College English Education Evaluation. Mobile
Information Systems, 2022.
15.
Wang, T. and Gu, Y., 2022. Research on the Design of English Comprehensive Learning
Activities Based on Deep Learning. Mobile Information Systems, 2022.
16. Guo, Y., 2021. A Study of English Informative Teaching Strategies Based on Deep
Learning. Journal of Mathematics, 2021.
17. Xu, Y., 2022. English speech recognition and evaluation of pronunciation quality using
deep learning. Mobile Information Systems, 2022.
18. Zhang, G., 2020. A study of grammar analysis in English teaching with deep learning
algorithm. International Journal of Emerging Technologies in Learning (iJET), 15(18),
pp.20-30.
19. Cho, Y. and Kim, J., 2021. Production of mobile english language teaching application based
on text interface using deep learning. Electronics, 10(15), p.1809.
20. Fei, B., Cai, X. and Huang, G., 2022. Status and strategies of college English teaching using
adaptive deep learning from the perspective of multiculturalism. Frontiers in
Psychology, 13, p.910667.
21. Ji, D., Yang, X. and Wang, W., 2022. Evaluating the Design and Teaching Effect of College
Mobile English Learning Using Deep Learning Technique. Wireless
22. Warni, S., Aziz, T.A. and Febriawan, D., 2018. The use of technology in English as a foreign
language learning outside the classroom: An insight into learner autonomy. LLT Journal: A
Journal on Language and Language Teaching, 21(2), pp.148-156.
23. Lekawael, R.F.J., 2017. The impact of smartphone and internet usage on English language
learning. English Review: Journal of English Education, 5(2), pp.255-262.
24. Ahmadi, D. and Reza, M., 2018. The use of technology in English language learning: A
literature review. International Journal of Research in English Education, 3(2), pp.115-125.
25. Gu, F., 2021. On Deep Learning-Based Synthesis of Language Training and Humanistic
Education in College English Teaching. Open Access Library Journal, 8(6), pp.1-10.
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CHAPTER 7
ROLE OF HUMAN PSYCHOLOGY AND TECHNOLOGY IN
LEARING ENGLISH
Chirantan Jain(21BCE0509), Aditya Vispute (21BCI003), Prakhar Varshney (21BCT0045)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
Communication is the process that allows the humans to exchange information by articulation of sending a
message, whether it be verbal/non-verbal as long as it transmits a thought-provoking idea, gesture, action
etc. Initial communication methods included cave paintings, smoke signals, symbol carrier pigeons and
telegraphs. The technological advancements since made comprises of Machine Learning and Artificial
Intelligence which have been adopted by 75% of the companies today and became a major part of our daily
lives and made the lives simpler. Human psychology plays an important role in learning or speaking a new
language. Scholars often focus on understanding and show the difficulty of learning a foreign language by
personal characteristics, learning settings, learning circumstances etc. The focus in a psychological factor
is on the emotional or spiritual components of a student’s understanding of a second language foreign to
him.
Introduction
The first instances of communication in a more formal form were discovered to be around
3200 BC in ancient Egypt and Iraq. Other civilizations also came up with their own forms of
writing like the Mayans in Central America. Other important addition towards the field of
communication was with the invention of alphabet in what is now Israel and Lebanon.
Technology plays an important role in advancement of both humans as a species and form of
communication which was then limited by scrolls and paintings which only the affluent could
afford is now accessible to all in forms of digital communication styles like texts, SMS, emails,
video calls and also through the more primitive methods like letter writing, memos, notes etc.
these advancements in technology caused the learning processes to simplify and accessible to
the more underprivileged and people with disabilities focusing on specific factors that
influence the learning methods like behavioral perspective, developmental perspective,
cognitive perspective and experimental perspective. The behavioral perspective suggests that
all behaviors are learnt through conditioning. This aspect can be useful in some cases but it
has been criticized for failing to account for emotions, attitude and intrinsic motivations for
learning. The development perspective generally focuses on children and how the learner
acquires new skill and knowledge as they develop. By understanding how children are capable
of at each stage of their growth. This helps the educators to tailor the exact method of teaching
best aimed at a certain age group. he cognitive approach accounts for how things such as
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memory, beliefs, emotions and motivations contribute to the learning process. Use of various
audio-visual devices and projectors based on the receiving audience and provision of various
online courses and various “game-like” educational help apps like Duolingo is also a helping
hand for the people learning a new language.
Psychology is the study of human recognition of behavior and learning. Educational
psychology and its various branches in the field of education where the different teaching
methods, process of thinking, change in learning rate due to changes in environment and the
role of teachers in improving the standards of learning are studied. Through various studies it
is a stated fact that the environment plays an important role in altering the learning rate and
quality of the student.
Not only the external factors like the method of teaching and environment but there are
also other factors which may affect the learning process which is inclusive of the psychological
inhibitors to learning a new language like several diseases and disorders like anxiety, ADHD
and various other inhibitors like self-consciousness and closed mind, fear of vocabulary and
syntax, sudden demand for speaking, fear of failure and short-term memory. People with
anxiety disorders tend to become overwhelmed easily by their feelings and have a negative
reaction to those repressed emotions evoked by it. By avoiding conditions that make them feel
anxious people try to cope these with negative and unpleasant reactions.
Literature Review
Reyes,2018, discovered and put forward the various measures to help resolve the numerous
problems faced by the students who are trained for the skill of speaking a language in the
classroom. These issues comprise of the various psychological and personal behaviors which
may hamper the development and pace of acquiring the skills. In order to learn a new foreign
language, it is important to account for the different personalities, their individual learning
environment. This article truthfully and experimentally puts forward the influence of
biological factors and inevitable role of teachers for successful learning and propagation of the
course analyzing the students of a public school in Bonao, Province of Monseñor Nouel,
Dominican Republic.
Ahmadi D and Reza M,2018 emphasized on how technology is used in learning any form of
language. With the adoption of technology in teaching it improves the language learning
process as it allows the teacher to adapt classroom activities. The research made in this study
focuses on using new technologies in learning a foreign language, discussing various means
through which technology supports English language learners to increase their learning skills.
Through this paper technology and the various aspects related to it like the technological
advancements and integrations which propagates the learning and adaptation along with valid
recommendations for better use of these technologies, assisting the learners in the longer run.
Hao. H (2020) stated in the journal of physics, he looked upon the continuous development
of the propagation of education and research methods where the educational psychology plays
a vital role. The research is based upon the methods of educating the university students
wherein the class was divided into two subgroups which used the experimental and
comparative teaching classes. Questionnaire was then prepared to summarize the effects and
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differences in the teaching methods. Modelling the academic structure according to the human
psychology and different teaching methods is found to be the best way for finding student’s
potential.
Purba N, 2018, in this research paper discussed about the role of psycholinguistics in
learning a new language and how it affects the grasping and perception of the learners for
both spoken and written language. Psycholinguistic approach recognizes learning as a
cognitive process and then looks upon the social framework and ability of the learner. Natural
method, Total Physical response method, and Suggestopedia method are some of the examples
of the methods risen from the psycholinguistic approach. These methods primarily focus on
how a student learns their mother tongue/ first language, second language and looks into the
language perception which is the measure of the cognitive skills of the learner like reading,
listening, writing or speaking, all of which are considered as the four pillars of language
learning. Psycholinguistics through the various methods, helps understand the various
intrinsic and extrinsic barriers raised due to the incapabilities in these four pillars and
primarily assists teachers to consider the use of appropriate method to overcome the problem.
Srebnaja, J, (2020), stated about how the technology has become an important aspect of a
student’s life customizing and providing the teacher and learner a better learning
environment. These technologically aided learning provides for an enhanced system for
acquisition and stimulates quality learning and present practical tools for technologically
mediated learning. Various strategies and technologies like the smart board and YouTube
videos in the secondary schools.
Reyes (2018) intends to gather information on how Psychological Personality Factors
impact learning English as a Second Language. Language proficiency is declining in schools
where ESL is taught in primary education due to the lack of interactive conversational
activities that incorporate learning techniques to improve student skills. Through this Survey,
we hope to find valuable information that will help us tackle the problems students face in
learning English in their classrooms. The progression of studying English is always influenced
by students' interest in the subject. These characteristics, which are significant facets of our
personalities and what distinguishes each of us, are also what psychologists have sought to
study and quantify in terms of the process of learning a foreignlanguage in English. To
understand this, studying and understanding the differentways and environments students
prefer to learn English is essential. In order toillustrate the crucial role of teachers and the
impact of biological elements on pupilsduring the process of teaching and learning a foreign
language, this document placesthis reality in perspective. This research aims to analyze and
study the different psychological factors in students of primary school, a public school in
Bonao, Province of Monseñor Nouel,Dominican Republic, in learning English as a foreign
language. The current study, which examines the psychological aspects of participants'
personalities, will be carried out in the 2018–19 academic year with the new curriculum that
notifies pupils that they must learn English from the fourth to the sixth grades.
Getie and A.S. (2020) intend to gather information on how Psychological Personality
Factors impact learning English as a Second Language. This study looks into the influences on
students' attitudes toward learning EFL in grade 10 at Debremarkos Comprehensive
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Secondary School in Debre Markos, Ethiopia. Out of the total population (1030), we randomly
selected 103 students (10%) for the study. A questionnaire was carefully and methodically
constructed to collect data. Additionally, nine sample students were selected for the focus
group discussion with a few English teachers from grade 10 for the interview. The data were
then subjected to quantitative and qualitative analysis, demonstrating that grade 10 pupils
have good attitudes toward learning EFL. Positive social influences on students' views include
peer groups, parents of learners, and native Englishspeakers. On the other hand, elements of
the educational context, including English language instructors and the physical learning
environment (such as classrooms, seatingarrangements, etc.) had a negative effect on
students' attitudes. The results, however, demonstrated that target language learners have
favorable attitudes toward the other educational context factor, which is the English textbook
for grade 10, indicating that teaching English as a foreign language in the study's context
positively affects students' attitudes. It is feasible to facilitate language learning by reducing
the psychological factors (i.e. emotional filters) for the target language learners. The study
suggests that the physical learning environment should be enhanced, and the government
should collaborate with school administrators, teachers, and societies to make this happen.
Novikova, I.A., Berisha, N.S., Novikov, A.L. and Shlyakhta, D.A.(2020) intend to gather
information on how Psychological Personality Factors impactlearning English as a Second
Language. One of the most crucial skills for a modernindividual is the ability to speak a foreign
(second) language (FL/SL), which isrequired for both career and personal fulfilment. This
study will compare personalitycharacteristics and creative ability as potential indicators of
success in learning asecond language (FLA). The sample consists of 128 first- and second-year
university linguistics students (105 female and 23 male). The Abbreviated Torrance Test
forAdults (ATTA) assesses creativity. S. Biryukov and M. Bodunov modified the RussianNEO
Five-Factor Inventory to measure the FFM personality traits. The final Englishgrades for the
semester served as a typical measure of academic accomplishment,and the English teachers'
evaluations of their students' language competency usingthe "Foreign Language Proficiency
Scale" were also utilized to determine the degreeof FL proficiency. The R software
environment, version 3.5.2, was used to processthe data using descriptive statistics techniques
as well as multiple regressionanalysis. The results of our study revealed that, in comparison to
personality traits,creativity indicators had a more significant but conflicting influence on the
degree ofFL proficiency. We contend that teachers are most likely ignorant of how
students'creativity is expressed during the FL learning process.
Faisal, R.A. (2019) intend to gather information on how Psychological Personality Factors
impact learning English as a Second Language. Researching the variables that might affect
students' academic performance is essential for instructional scientists. Lack of awareness of
this probable connection between teachers and students may discourage language learners
from continuing to persevere. The current study aims to describe the prevalence of personality
types and learning styles in the Bangladeshi setting and to discuss how characteristics and
styles affect the samples (N = 676). Self-reported BFI questionnaires, VARK questionnaires,
and an achievement exam were applied in this study's cross-sectional quantitative research
design to gather pertinent data. According toresearch analysis, boys and girls exhibit
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Agreeable as their most predominant attribute. Again, boys choose multimodal learning,
whilst girls prefer auditory. In this study, it was found that a few learner characteristics,
personality traits, and learning preferences have a significant impact on GPA. The study's
findings suggest a statistically significant relationship between Multimodal and academic
success. Additionally, it has been determined that there is a statistically significant correlation
between the attribute extraversion and English language proficiency in EFL learners. The
results to the research questions could give educators some insight into how to improve the
country's situation about EFL teaching and learning, not just in Bangladesh but also in other
non-English-speaking countries. The learning preferences and personality characteristics of
the teachers can be further investigated because it has been found in earlier studies that these
are stronglyrelated to academic performance.
Budianto, L., (2010) intend to gather information on how Psychological Personality
Factors impact learning English as a Second Language. This essay describes the psychological
aspects of language learning and acquisition for those learning second languages. Stephens
discovered that outside variables, including instructor characteristics, class dynamics, and
educational environment, consistently had no bearing on whether students were successful at
learning a foreign language. The psychological state of the student, however, has the potential
to have an impact on their ability to learn a second or foreign language. A psychological
component is one that has to do with how students acquire certain skills intellectually or
spiritually. The pupils' language acquisition process is influenced by at least four variables,
including anxiety, attitude, aptitude, and motivation. However, Kando, D. recommends five
ways for coping with language anxiety, including preparation plan, relaxation, positive
thinking, peer, and labelled resignation, to deal with the psychological issues of learning a
second language. The five tactics presented by Kando are crucial as an alternate method for
maximizing the results of second language acquisition.
Mohammad Reza Ahmadi (2018) argues that e-tuition programs have become the
predominant preference of teachers. It provides an overall incentive to learn English. Most
modern English teachers actively integrate a variety of technical tools designed to enable
optimal teaching. As such, our current research addresses different elements of the technology
used to teach English, developing an innovative curriculum that takes advantage of the latest
scientific and technological developments to ensure effective, high-quality instruction. We
provide trainers with the technical skills to do audio-visual and modern media provide
technical programming and create a platform for students and teachers that maximize positive
outcomes in language learning. For the resolution of this research, the relevant literature was
reviewed, technology was defined linguistically and conventionally, and correlations with
contemporary teaching skills were fully assessed. Against this background, researchers outline
basic research issues, explain the meaning of research goals and hypotheses, and present their
results. By widespread use of modern technology, the teaching methods of better eminence is
facilitated.
The world of technology offers a wide range of options when it comes to language teaching
and learning. radio, TV, CD-ROM, PC, C.A.L.L., Internet, electronic dictionary, e-mail, blog,
cassette tape, PowerPoint, video, DVD, or VCD. Technology has changed the dynamics of
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industries of all sorts and has impacted them alike over the past 20 years. The way people
interact and work in society. The rapid rise and development of this information technology
provided a better template for exploring new educational models. As a result, technology plays
a very important role in teaching English. Using multimedia to create a context for teaching
English has its own advantages. This work attempts to analyze and highlight the need for
multimedia technology for language teaching. Problems using these techniques. It also aims to
raise awareness of strategies among English teachers. For effective use.
Electronics influence flea markets on a daily basis. Nowadays everyone uses all kinds of
devices. There are many new apps, devices and software that are truly educational. Current
research focuses on the use of technology in ELT. It discusses the use and misuse of technology
and offers inspiring ways to use it in your English classroom. We also suggest some apps and
software that can be used for ELT.
This paper focuses on explaining the role of technology. teach and learn
English.Globalization has created a new world Commerce order. new information and
communication technology (ICT) affects our lives, learning, work, and even think about work
The Synergy of Combining Globalization with the New Technology has had a dramatic
economic and social impact, including on English Language teaching and learning. Technology
media needs a role A learning process in which the media act as an integral part rather than as
a tool education system and learning process. Utilization of technology Very useful as a
medium in the classroom.Also, media technology Increase student interest in the learning
process.
Advances in technology have given English teachers and learners easy access to a wide
range of resources related to authentic input and communication with native and non-native
English speakers around the world. Computer Assisted Languages Since the early days of
CALL, there has been debate about how technology can help motivate learners to learn
languages (for example, using technology both inside and outside the classroom can increase
motivation). My own educational environment is a large private university in the heart of
Tokyo, where one might expect far greater technological advances than many other countries
in the world, including Europe and the United States. In my experience, there are more
similarities than differences in the problems encountered in introducing technology to peer
discussions and attending international conferences. keep it on a level, take their seats.
Reyes (2018) says on Psychological Personality Factors in Learning English Foreign
Language by doing research, intends to gather useful data that will aid in resolving the
different issues that language learners encounter in the classroom. The learning curve of
understanding English is influenced by student’s inclination for the subject. Multiple
characteristics of students which are significant part of us contribute to our personality.
Psychologist have sought to examine and gauge on these characteristics when they examine
the process of learning English as a foreign language. Whereas when doing research on the
learning of foreign languages, it's critical to consider the individual differences among
participants as well as their various linguistic learning styles and contexts. Through this study
we aim to get a better understanding of psychological personality factors while learning
English as a foreign language.
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Salaberry (2001) says on the use of technology for second language learning and teaching:
A retrospective by critically examining papers that have been published in the Modern
Language Journal (MLJ) since its first publication in 1916, this section will examine the
suggested educational use of technical resources. For the evaluation of the pedagogical
potential of contemporary technologies, a initial understanding of how earlier technical
capabilities have been applied for educational goals is required. In this essay, the author
contends that although the majority of "new technologies" (radio, television, videocassette
recorders, computers) may have revolutionized how people connect with one another as a
whole, it is unclear whether they have had a comparable impact on teaching second languages.
Andrei (2017) says on Technology in teaching English language learners: The case of three
middle school teachers by examining the use of technology in the classroom by three ESL
middle school teachers. The use of technology in the ESL classroom has the potential to help
English language learners' English and subject learning, but the availability of technology does
not always result in technological integration that promotes student learning. Technology
integration may be hindered by teacher’s attitudes and views regarding it, a lack of time and
resources, and other factors such as lack of interest. Each of the three ESL instructors'
language courses was observed in class by the researcher, who also conducted interviews with
the teachers. At the school, ESL department and classroom levels there was a variety of
technologies available.
Rivers (1978) for aspiring English language instructors on a Practical guide to the teaching
of English as a second or foreign language, examines language teaching practices considering
current linguistic and psychological research. Oral communication, pronunciation, grammar
teaching, listening comprehension, reading comprehension, and writing are just a few of the
language acquisition topics that are covered. The chapters in the first portion on
communication include hearing, oral practice for grammar acquisition, organized interaction,
autonomous engagement, and teaching the sound system. The chapters in the second half on
the written word include topics including why and how to read, how to read independently,
how to write exercises, and how to write with flexibility and expression.
Alsayed (2003) states that for finding factors that contribute to success in learning English
as a foreign language. Motivation to learn a new language, attitude towards the language and
learning environments, early exposure to English as a language, early first language
acquisition, and social background of the learner are the five variables that have been
investigated. Following social background, instrumental motivation has been determined to
have the strongest link with success in a second language. Early first language acquisition and
English exposure both appear to be reliable indicators of oral skill achievement. However,
attitude doesn't seem to be a reliable indicator of success in learning English as a foreign
language.
Multiple issues around the globe have been occurring in the past few years but one of the
most significant issues are the ones revolving around the current state of international
migrants which consist of legal or undocumented immigrants. According to multiple research
papers produced throughout the world suggest that often these immigrants are seen in a
negative light which generally taints the reputation of these individuals who seek shelter
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and/or work opportunities in distant lands. In recent years, with the rise in unemployment,
came certain challenges that these migrants had to face out of which the most prevalent being
racism. Linguists throughout the globe have come to the conclusion that often times these
people are the victims of racism due to the English language being their second or third
language and with that comes the “non-English” accent or the heavy accent as one might
assume. Accents and Skin-color might not always be the reason for racism, but for the
oppressors, it is the easiest option to hold against these immigrants. The authors offer a
framework for the stigma associated with accents as well as potential directions for future
study looking at the social psychological and communicative impacts of accents. They also
explore the effects of the stigma associated with different accents (e.g., other native, regional,
and ethnic).
It has been quite a while since our generation was termed as living in the “Internet Era”.
The introduction to social media, instant messaging and internet calling apps might’ve brought
us a little closer to our loved ones living in distant lands but at the same time, this era did give
researchers a new topic to ponder upon i.e. “The Internet Lingo” also known as Internet
slangs. Now to sum it up Internet Slangs are a non-standard or unofficial form of language
used by the people on the internet to communicate with one another. Words like “LOL”,
“AFAIK”, “TTYL” etc. are few examples of how Internet Slangs paved way for a newer form of
communication psychology amongst individuals who are often active on the internet. The
linearity of communication and how it generally affects the topology of communication has
always been a focus in the field of communicational research. The Internet can already
transmit speech, text, images, animation, video, virtual reality motion codes, and even
fragrance (though the technology of such kind is limited as of now). What journalists formerly
referred to as the "news hole" has only grown into an unimaginable sensory expanse. Many try
to gain some insight and test out their capabilities but by the time they do so, new capabilities
could have eclipsed them.
This current study sheds light on the psychological effects on a person when it comes to
distance and its preferences in interpersonal communication. Multiple experiments
throughout the research were conducted in order to obtain preferences of different people.
According to the experiments that were performed, it was observed that often, when distance
was an issue, the individual's psychology was to convey their messages in the form of texts and
words and the chances of communicating through pictures and videos was significantly lower.
Comparing this to a real-life scenario, we are also seen differentiating between the verbal and
pictorial form of communication, when it comes to our close ones or acquaintances. Often,
while messaging our close ones, our conversational approach towards them is informal. They
are light with no boundaries. On the other hand, when it comes to having definite
conversations with our acquaintances, there are some set boundaries that we know of (or
must know of) that we must adhere to and follow them closely. This is because even the
slightest of comments can offend the person, who is engaging in the conversation with us.
Words and images in the field of communication, are symbols that stand for actual things,
occasions, and acts. It has been observed that the employment of pictures and words as a
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medium of communication have not been precisely contrasted in the earlier study on the
impact of distance upon communication.
This research investigates the new avenues and merges innovative methods to both
theoretical and methodological difficulties which are relevant to the subject of language
appropriation through practical investigations and chapters made up from the different
theoretical approaches. Contribution to the field of communicational psychology by seeing
through a global perspective and by taking resources and data sets throughout the world
really sets a great international outlook. A piece of content which is obtained from the
literatures in psychology and language learning has drawn an interconnection between these
two different but intermingling fields. This paper aims to produce a newer perspective for
language learning psychology by testing conceptual frameworks, methods and implications of
the current amount of research findings in this field. In the previous times we saw how the
online learning methods were claimed as an “effective teaching and learning” method didn’t
turn out to be true as when the skills (which were required to manage and run an online class
successfully) weren’t exactly the expertise of a lot of teachers throughout the globe, a lot of
students got hold of that and abused the teaching system which turned out to be a recipe for
disaster. Overall, the insights that have been show cased in the following research paper stand
testament to the role of language learning in the field of education and psychology.
Result Analysis
The pie chart gives the info of the age group of the 75 respondents. Thus, we can observe
from the pie chart that about 92 % of the respondents are in the age group of 18 – 22 years
and about 8 % of the respondents are in the age group of 14 – 17 years. It can be observed that
majority of the respondents are above 18 years old.
The pie chart represents how often do the respondents communicate in English. It can be
observed that about 56 % of the respondents communicate in English very often while 40 % of
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the respondents communicate in English often and a mere 4 % communicate in English rarely.
Thus, it can be concluded that a majority of 96 % respondents usually communicate in English.
According to the general consensus as per the pie chart above, most of the people
answering the form have been learning English since the pre-school. The remaining people
have started learning in kindergarten. Learning a new language since early childhood causes
children to grasp new languages and vocabulary more easily as children are more excited and
intrigued by new concepts and are keen to learn.
From the pie chart above, we can see which teaching method suits the respondents most.
The most preferred mode of learning by 36% of respondents is classes using smartboards and
other audio/visual enhancements. 32% of respondents prefer offline classes followed by 24%
selecting Self Study and Institutional Curriculum, and 8% online classes. All the choices cover
less than 40% of the chart, and this shows that different people have different means of
learning styles that make learning and understanding easy and comfortable for them.
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From the bar graph above, for getting the recent updates and daily news people prefer TV
and internet more with internet being accessible all over the world in the palm of the hand.
Books and newspapers are still relevant to some extent where a lot of people like receiving
newspapers early in the morning and getting updated with all the new information from the
previous day. People also receive information from their social group inclusive of family and
friends through the word of mouth.
The pie chart above informs us which resource has helped the respondents improve their
English language skills. 44% of the respondents believe TV Series has helped them the most in
improving English, while 28% believe Podcasts and other forms of Digital Entertainment have
helped them. 24% have selected books, followed by 4% selecting textbooks. This data shows
that while TV series are playing a dominating role in improving English, other resources have
also helped the respondents, aligning with the hypothesis.
The pie chart informs the researcher about how do the respondents feel whether
Technology play an effective role in learning the English language. It can be observed from the
pie chart that 96 % of the correspondents feel that technology can truly affect role in learning
the English language and 4% respondents feel that technology cannot play a role in learning
the English language
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The pie chart, since most of the people have been learning English since early childhood,
shows that 80% of the people are not hesitant and rather comfortable communicating with
people in English. A small fraction of people (20%) is still a bit hesitant in communicating with
other people. There may be reasons that may come into play for the hesitation like anxiety and
people being introverted.
The above pie chart gives info about the no. of respondents that feel that Computer/Mobile
applications can speed up the process of learning English or any other language. Thus, we can
observe from the pie chart that a majority of 92 % respondents feel that computer/mobile
application truly helps in the process of English or any other language learning while 8 % of
the respondents deny the fact and do not agree that computer/mobile applications can help in
the process of English or any other language learning.
The above pie chart informs us about how many respondents have ever used any
application for learning a new language. It can be observed from the pie chart that a majority
of 68 % of the respondents have used applications for learning a new language and while 32 %
of the respondents have never used any application for learning a new language.
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The pie chart above informs us whether the respondents feel that the environment around
them plays a vital role in learning English. Over 96% of the respondents said yes, signifying
that they believe the environment is a crucial factor that affects our English learning abilities.
The pie chart shows that a lot of people disagree that there may be a need to learn a new
language by the older people with 68% of the people against the need for older people to learn
a language whereas 38% people support the need for older people to learn a language
The above pie chart informs us that all the respondents believe that there can be
psychological effects on a person on the way another person speaks to them. The responses
concluded that expressing yourself appropriately and reducing communication gaps is an
essential factor that helps in communication. Communication gaps between people can cause
psychological issues that may not be resolved unless they are both fluent in a particular
language. To reduce this gap, fluency in a language is crucial to reducing communication gaps.
From the Bar graph above, we can observe a trend where 1 is least confident, and 5 is most
confident that about 60% of the respondents rate themselves as 4/5 in how confident they are
in speaking English. The trend decreased as we moved back to 1, dropping to 0% at 1. While
the number of people who rated their confidence 5 is less than 4, it is still double that of
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people who are less confident in speaking English. Thus, this shows that most of the
respondents are relatively confident in their speaking skills, yet some gaps need to be filled,
due to which there is such variation in the confidence level. Hence agreeing with the
hypothesis that not everyone benefits from the same teaching style
From the bar graph above, it is evident that most of the people (52%, 32%) agree to some
extent that psychology plays an important role in learning English language because there are
several factors like people interacted with, mental well-being, environment of study and
learning like a classroom, tackling inhibitors like anxiety, ADHD and other issues plays an
important role in shaping the quality and time taken to learn a new language.
From the bar graph above, most people strongly agree that the approach adopted by the
teacher makes the learning process more fun and intriguing for students to learn with a
staggering 64% support from the participants. New and fun methods cause an increase in
dopamine levels of the students and in-turn increases their interest in the subject and with the
attention and participation of students it is relatively more exciting and simpler for the teacher
to teach.
From the bar graph above, we can conclude that the participants lean towards agreeing
that the current academic structure causes students to face problems in learning with most
people being neutral about it by 36% support, whereas participants agreeing tends to 28%
and 24% of the participants strongly agreeing to it. There may be reasons for these,
considering factors like there being a lack of using technology in classroom environment even
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though it is widely available. Also, with the increasing number of resources available online, it
may be difficult for students to know which sources could be trusted.
From the bar graph above, we can see that a lot of participants (44%) are neutral about
new subjects and languages being learnt could be difficult without the use of technology. There
is almost an equal distribution (~30-35%) between participants supporting and disagreeing
the difficulty of new language learning to increase without the use of technology because of
various factors like the reliability of sources, plethora of books already published and
accessible to the public etc. could be a reason to be against the difficulty to increase whereas
multiple sources being available online, courses and learning channels on YouTube etc. may
happen to be the easing factors.
From the bar graph above, it is clear that most of the participants agree to technology
being a major contributor many health issues where 36% of the participants strongly agree,
32% agree to the statement. Many health concerns have since been observed in students after
the start of using computers extensively like prolonged exposure to blue rays from the screens
resulting in strain on eyes causing students to start using corrective lenses since a very young
age. Also, the ease of access to everything online causes the students to come up with many
diseases like anxiety and ADHD reducing the attention-span of the learners.
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The pie chart reveals that out of 75 respondents how many of them arehesitant to
communicate with other students or teachers. Thus, we can observe thatabout 76.5% are
students who are not reluctant to communicate with others andabout 23.5% are hesitant to
communicate with other students or teachers. We cannearly observe a 75-25 split in the
number of students and their hesitation tocommunicate. Hence the researchers observed that
out of the total of 75 usersmajority are comfortable sharing with others without any lack of
confidence.
The pie chart reveals that out of 75 respondents how many of them findlearning the
English language to be intriguing. Thus, we can observe that about58.8% are students who
find learning English to be interesting and enjoy the processand about 41.2% find it not to be
intriguing to them. We can nearly observe a 60-40split in the number of students who find
learning English to be interesting. Hence theresearchers observed that out of the total of 75
users it can be concluded that thereis still a need for the adoption of better methods to teach
English as to engage morelearners and increase the split.
The bar graph gives a visual representation of a split of the 75respondents and their self-
assessment of communication and grammatical skills forthe English language. We find the
majority of the respondents (62.5%) to findthemselves on 4 out of a rating scale of 1-5 with 1
needing improvement and 5 beingproficient. 18.8% of the respondents rate themselves as 3
and 5 respectively. Whileno one responded for 0 and 1 ratings respectively. Hence the
researchers observedthat out of the total of 75 users it can be concluded that the majority of
the peoplefind themselves to be near to proficient in English communication and the rest
canalso improve theirs with support from teachers.
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The pie chart reveals that out of 75 respondents how many of them have witnessed the
integration of technology while English is being taught in classroom. Thus, we can observe that
about 52.9% are students who find the integration technology in their classroom and
methodology of learning and about 47.1% find no integration of technology while learning
English. We can nearly observe a 50-20 split in the number of students who find learning
English to be interesting. Hence theresearchers observed that out of the total of 75 users it can
be concluded that thereis still a need for the adoption of technology and integration of it with
teachingmethods for students to learn more effectively.
The multiple bar graph gives a visual representation of a split of the 75respondents and
their self-assessment of the factors to be a part of success in learning English as a foreign
language. We find that 60 respondents find motivation, early exposure, and Social Background
to be one of the factors while 8 disagree with that. For attitude and early 1st language
acquisition, 44-50 people agree but 20-24disagree. Hence the researchers observed that out of
the total of 75 users it can beconcluded that the majority of the people find motivation, early
exposure, and socialbackground to be major factors while attitude and 1st language
acquisition need notbe a majority factor accounted by the respondents.
Conclusions
After thorough research from the responses and literature review of articles it can be
concluded that with progress in technological advancements there is a need to integrate it
with second language learning such as English. It has shown positive results of how the
younger generation finds learning new language easy to comprehend with smart classes and
T.V Shows, videos etc. Although it has been observed that at various institutions the
integration of technology has not been observed by students in their learning path but there
arises a need for it.
While it has been observed that various psychological factors also have a role in learning
English as a second language. A person’s social background, exposure and motivation seem to
be major psychological and environmental factors in learning while attitude and 1st language
acquisition seem to be minor factors.
The research focusing majorly on people from the age group 17-22 puts a light on the
subject of how learning English can be made easier and the role of human psychology in the
process.
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References
1. Gluszek, A. and Dovidio, J.F., 2010. The way they speak: A social psychological perspective
on the stigma of nonnative accents in communication. Personality and social psychology
review, 14(2), pp.214-237.
2. Newhagen, J.E. and Rafaeli, S., 1996. Why communication researchers should study the
Internet: A dialogue. Journal of computer-mediated communication, 1(4), p. JCMC145.
3. Amit, E., Wakslak, C. and Trope, Y., 2013. The use of visual and verbal means of
communication across psychological distance. Personality and Social Psychology Bulletin,
39(1), pp.43-56.
4. Gkonou, C., Tatzl, D. and Mercer, S. eds., 2016. New directions in language learning
psychology. New York: Springer International Publishing
5. Stockwell, G. and Reinders, H., 2019. Technology, motivation and autonomy, and teacher
psychology in language learning: Exploring the myths and possibilities. Annual Review of
Applied Linguistics, 39, pp.40-51.
6. Tejada Reyes, V., 2018. Psychological Personality Factors in Learning English Foreign
Language.
7. Salaberry, M.R., 2001. The use of technology for second language learning and teaching: A
retrospective. The modern language journal, 85(1), pp.39-56.
8. Andrei, E., 2017. Technology in teaching English language learners: The case of three
middle school teachers. Tesol Journal, 8(2), pp.409-431.
9. Rivers, W.M. and Temperley, M.S., 1978. A Practical Guide to the Teaching of English as a
Second or Foreign Language. Oxford University Press, 200 Madison Ave., New York, NY
10016.
10. Alsayed, M., 2003. Factors that contribute to success in learning English as a foreign
language. Damascus University Journal, 19(1), p.2.
11. Tejada Reyes, V., 2018. Psychological Personality Factors in Learning English Foreign
Language.
12. Getie, A.S., 2020. Factors affecting the attitudes of students towards learning English as a
foreign language. Cogent Education, 7(1), p.1738184.
13. Novikova, I.A., Berisha, N.S., Novikov, A.L. and Shlyakhta, D.A., 2020. Creativity and
personality traits as foreign language acquisition predictors in university linguistics
students. Behavioral Sciences, 10(1), p.35.
14. Faisal, R.A., 2019. Influence of personality and learning styles in English language
achievement. Open Journal of Social Sciences, 7(8), pp.304-324.
15. Budianto, L., 2010. STUDENTS’PSYCHOLOGICAL FACTORS IN SLA: A DILLEMA FOR
TEACHERS OF ENGLISH. LiNGUA: Jurnal Ilmu Bahasa dan Sastra, 5(1).
16. Alqahtani, A., 2019. The use of technology in English language teaching. Frontiers in
Education Technology, 2(3), pp.168-180.
17. Shyamlee, S.D. and Phil, M., 2012, March. Use of technology in English language teaching
and learning: An analysis. In International Conference on Language, Medias and
Culture (Vol. 33, No. 1, pp. 150-156).
117
18. Mittal, R., 2015, September. India Use of Technology in English Language Teaching: Is it
Helping Students and Teachers? In The Asian Conference on Arts & Humanities (p. 13).
19. Masruddin, M., 2014. The importance of using technology in English teaching and
learning. IDEAS: Journal on English Language Teaching and Learning, Linguistics and
Literature, 2(2).
20. Masruddin, M., 2014. The importance of using technology in English teaching and
learning. IDEAS: Journal on English Language Teaching and Learning, Linguistics and
Literature, 2(2).
21. Tejada Reyes, V., 2018. Psychological Personality Factors in Learning English Foreign
Language. Online Submission.
22. Ahmadi, D. and Reza, M., 2018. The use of technology in English language learning: A
literature review. International Journal of Research in English Education, 3(2), pp.115-125.
23. Hao, H., 2020, October. An analysis of the role of learning theory in educational psychology
in teaching english. In Journal of Physics: Conference Series (Vol. 1648, No. 4, p. 042113).
IOP Publishing.
24. Purba, N., 2018. The role of psycholinguistics in language learning and teaching. Tell
Journal, 6(1), pp.47-54.
25. Srebnaja, J., 2020. The Role and Implementation of New Technologies in the ELT (English
Language Teaching). In Language Learning and Literacy: Breakthroughs in Research and
Practice (pp. 94-110). IGI Global.
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CHAPTER 8
HUMAN COMPUTER INTERACTION FOR BETTER COMMUNICATION
Priyansh Garg(21BCE2283), Aditya Tiwari(21BCE2309), Rishabh Yadav (21BCE2293)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
This study examines the role of human-computer interaction in improving communication. Also, the
technology aspect of human computer interaction related with communication has been analysed. HCI has
evolved to use technology like face readers, language emotion detection and speech-emotion recognition to
interpret human emotions.Some of the technologies that a scholar can study include text messaging
applications, social media services, voicemails and logs.Applications of HCI particularly useful in
communication in educational settings were investigated, as it accommodates individuals with different
learning styles. Drawing on detailed analysis of data from the survey conducted mainly focusing on the
undergraduate and post-graduate students of VIT University, the linkage between computer uses and
communicative conduct has been established. Finally, possible implications for human-computer
interaction in the field of communication are discussed.
Introduction
The first human-computer interaction was in the 1820s, Charles Babbage invented the first
computer. Later the radio and television were invented which made audio communication
possible and brought many people together. One of the greatest inventions in the history of
communication was the invention of “the telephone” by Alexander Graham Bell. The Internet
made HCI easier.
Along with the internet, the concept of email was introduced. With improvement in
internet connections, more people started to be an online movie, shows, and songs becoming
more popular and influential. Even education started to shift online. It made communication
between students with teachers faster many people started online start-ups. They were able to
connect with customers nationwide through social media website applications, with the start
of the Covid pandemic the use of the internet increased even more.
Human-computer interaction took the next big step with the introduction of social
networks. They are a special website or application that allows users to communicate with
each other by sending information, commands, messages, images, etc.
Human beings, being at the brisk of investigating headways on VR AR AI and machine
learning. The connection between humans and computers is getting much more grounded
covering all our senses beyond vision hearing and touch natural language processing (NLP)
isone of the most dynamic areas of research. This field intense to assist PCs with
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understanding human dialects by separating data from human language i.e., significant so that
humans can comprehend it more quickly.
Human-computer interaction analyses the user's goal and tasks, the media along with
human-computer interface. As technology is creating an influencing all aspects of our lives it’s
crucial to continue to explore and move along improvising the study of HCI. AI endeavors to
comprehend uniqueness of your knowledge and produce another intelligent machine.
Literature Review
In 1984 Fano,R.M. stated that it is discussed how computers are used in organizations in terms
of their current and potential roles in promoting and mediating interpersonal communication.
This method makes it clear what effect computers may have on how organizations function
and how their members interact. The correct management of communication is necessary to
ensure both individual and group privacy, both of which are crucial to collaborative activity.
Our technical capacity to put the controls in place that may be required currently falls behind
our understanding of the organizational and human components of regulating communication
and access to information.
According to Hill, R.D., (1986) The goal of specification is to make it easier for developers
to create user interfaces that allow users to control various input devices and carry out
associated tasks simultaneously. These interfaces can be implemented efficiently without
breaking a bit of well-defined programming rules.
In an article by Fezter (1990), the fact that it is very challenging to describe the specific
nature of artificial intelligence's (AI) subject matter is one of the field's most fascinating
features. There are two pieces to the issue since obtaining a sufficient understanding of the
nature of the artificial would only be useful if we already had a sufficient grasp of the concept
of intelligence. Artificially intelligent things differ from naturally intelligent things in that they
are artefacts with unique qualities that are typically reserved for non-artifacts.
In an article Roger (1994) represents the strong advantages of a client situated way to deal
with the plan of current PC frameworks. It adjusts the specialized issues expected for
understanding the unpretentious transaction among individuals and PCs, especially in
uprising fields like sight and sound, virtual conditions and PC upheld agreeable work. Human-
Computer Interaction is organized to permit an assortment of learning ways for understudies
in software engineering, designing, brain research and mental science.
In 1997 Caroll, J.M. pointed that HCI is the field where science of brain functioning and
their interaction with others is at one end on the other end Tech encounters. HCI analyzer do
surveys and make specifically an interface which comforts users to use the technology. They
evolve the way of using technology. They keep on releasing new Apps of technologies. Since,
last few decades HCI has grown a lot with the help of science and engineering with motive of
betterment of usability of tech and its application with methodology.
The goal of paper by Falukner (1998) is to give a general overview of the field of HCI,
generally known as human-machine interaction. We'll talk about the fundamental definition of
HCI and its early development. The development of existing HCI technologies will be discussed
in the next parts. Finally, we want to talk about HCI's potential future directions.
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Hirai, K., Hirose, M., Haikawa, Y. and Takenaka, T., in [1998] presented the machinery,
instrument setup, of the Honda human type robot in this study. This robot, like its human
counterpart, can move just like any human does in any direction it wants, can even climb up
stairs. Furthermore, the robot's humanly posture and stability control allows it to retain its
equilibrium in the face of unanticipated challenges such as uneven terrain conditions. As part
of its integrated features, this robot may walk independently on a predetermined course and
conduct simple activities through wireless teleoperation.
In a paper by Manaris, B., (1998) discusses the development of natural language widgets
and how they are incorporated into multimodal user interfaces. It looks at the challenges of
covering a broad spectrum of linguistic contexts, and how this affects the usability of these
widgets.
Ishiguro H. and Nakatsu R. (2001) in their literature stated the authors have created a
robot they term "Robovie" with special communication mechanisms for use with people.By
utilising human-like actuators, as well as vision and audio sensors, Robovie can produce
behaviours that resemble those of humans. In the creation of systems, software is a crucial
component.A network of placed modules makes up the architecture's fundamental framework.
A fundamental behaviour for training humans and a behaviour for interacting with humans are
both included in eachmodule.
Fallman in [2003] showed HCI is the intersection of studies of human mind and its social
behaviour. HCI researchers conduct research and create interfaces that specifically make it
easier for users to use the technology. Develop technology usage. They are constantly
releasing new uses for their technology (e.g., virtual meetings, software development
environments). Over the last years, HCI has rapidly been growing with the help of science and
technology, aiming to improve the ease of use of the technology and its application through
methods. HCI continues to offer rigorous testing areas for advances in human behaviour.
Gurdin J. (2005) ->A fundamental component of computer science is human-computer
interaction. Three HCI study focuses—computer operation, information systems management,
and discretionary use—are examined in terms of their historical development. The author
discusses their attempts to unite as well as the factors that have kept them apart.
Ogura in his research (2006) proposed the WABIAN-2, a revolutionary humanoid robot
that can simulate human mobility. Its trunk is made to be able to move in all directions—
forward, backward, and sideways. Further, when pushing a walk-assist device, its arms are
made to hold its entire weight. Additionally, it can use trunk motion and forearm control to
lean on a walk-assist device. Basic WABIAN-2 walking trials are performed both with and
without a walk-assist device, demonstrating its effetiveness.
Coyle C and Vaughn H (2008) proved that social networks and the need to communicate
are characteristics shared by all people. It is often believed that communication technologies
contribute to a strengthening of social relationships. Numerous chances for social networking
are offered by the Internet. But what impact do social networking sites have on personal
connections? Do people use social networking sites to broaden their personal networks,
connect with others who have shared experiences, chat about a passion, or look for offline
romantic opportunities? Or do people use networking sites to strengthen their current
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personal networks and keep in touch with long-distance relatives or friends? What kind of
conversation takes place on social networking sites? Is it frivolous, casual, private, important,
or intimate, emotional, private, and public? We reviewed the research on social networking
sites and carried out our own investigations into how students use social networking on
American college campuses.
The creation of the humanoid robot HRP-3 is discussed in this study by Kaneko (2008). A
human-sized humanoid robot called HRP-3, also known as Humanoid Robotics Platform-3,
was created as the replacement model for HRP-2. The details on the mechanical characteristics
of HRP-3 were given. The technologies used in the HRP-3 prototype are also included.
Stephan, J.J. and Sana'a Khudayer, in [2010] showed A large amount of effort has been
expended to develop smart interfaces between user and computers This is done through
different types of information used singly or together. Human gestures as a means of
conveying info are a dominant part of human communication. Automatic gesture recognition
HCI by providing an innate and inherent method of data entry. This paper introduces a new
method of static hand gestures recognition for HCI) based on analysis.
Guo, Z.,Tan in 2010 stated that In spite of an expanding body of study on (CMC) in upper
studies, little is known about why students choose to utilise CMC with non - CMC media in
educational purpose. This study also notes a number of similarities and contrasts. The study
comes to a close result for the consequences for organisations, college, information systems
(IS) researchers.
Mathew A.R, Al Hajj in 2011 June suggested the design and execution of interactive
computer that user may interact with is known as HCI. Computer and fixed System found in
many devices are included. A technology's success is solely dependent on how simple it is for
the user for use. The buyer will not like the product or the technology if the interface is bad or
difficult to use.Functions are what a system uses to provide services. Usability is the ability of a
user to use a system's features correctly, effectively, and unambiguously. From one system to
another, functionality and usability may be different. If a system strikes a balance between
usability and functionality, it is said to be successful. In this essay, we'll examine current HCI as
well as recent developments in the industry.
Van Erp, J.B. and Toet, A’s (2015) study has shown that mediated affective touch can alter
physiological reactions, boost love and trust, foster connections between people and robots or
avatars, and spur pro-social conduct. They believe that ICT-mediated social touch has the
potential to improve the felt social presence of distant communication partners and help
computer systems to communicate effectively. However, much more research is needed to
fully understand the potential benefits and drawbacks of this technology.
In this article Hirschberg (2015) states that Natural language processing uses technology
to study and interpreted human language content. Today's researchers are refining these tools
and using them in real-world applications, creating speech dialogue systems and speech
translation engines, scanning social media for health and financial information, and advocating
for products and services. Identify sentiments and emotions. He discusses the achievements
and challenges in this rapidly evolving field.
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The study by Zhang, B. and Sundar, S.S., (2015) examines the linkage between human-
computer interaction and social communication in general practice discussions. It found that,
while both modes of communication are important, human-computer interaction has a more
significant impact on the overall consultation. This study looked at how patients in an inner-
city medical practice use computer screens and audio recordings of consultations to
coordinate their actions.
Minker, W., (2016) surveyed Germans and Japanese to see if there are any differences in
how they interact with computers. This information can be helpful in developing better
human-computer interfaces. the study found that there are real differences between different
groups, but not all of them are consistent with the cultural models.
Boholano, H.B., [2017] noted that education in the 21st century emphasizes globalization
and internationalization. 21st century teachers are tech savvy. To properly educate Gen
Z learners, educational systems must utilize ICT resources in both products and curricula to
foster collaborative learning environments. This study examines its teachers' social media
skills in the 21st century.
According to Fulk,J (2017), Social constructivist theories of communication technology in
organisations postulate that members of a work group interact and perceive information
about communication technology in recognisable ways. An analysis of the electronic mail
usage among a group of scientists and engineers revealed empirical proof of these trends.
People who were very attracted to their work groups showed consistently larger social
influences on technology-related attitudes and behaviours. People with little attraction
showed specific patterns of influence that were in line with conformity research's predictions
for compliance effects exclusively, whereas people with strong attraction showed both
compliance and internalisation effects.
Rodrigues, T.K., Suto, K., Nishiyama, H., Liu, J. and Kato, N., [2019] suggested Mobile Edge
Computing (MEC) is seen as a critical service of future for the deployment of 5G and the
IOTsince it is the most effective means for delivering computing and communication medium
to mobiles It is based on connecting users to servers placed at the network's edge, which is
important for real-time apps that need low latency. To ensure a resource-efficient MEC, certain
features of the prototype must be considered. In MEC settings with a large number of users
with servers, these issues are characterised by extremely high levels of amplitude, resulting in
an excessive amount of data to be mined and intricating the effort of identifying effective
configurations.
The purpose of this article by Randhawa (2020) is to investigate the elements that
influence Malaysian students' adoption of social networking sites (SNS) and to create
recommendations for SNS providers on how to increase adoption rates based on the study's
findings. The findings indicate that both TAM and TPB's predictions of SNS usage intention
were confirmed, and that perceived enjoyment is a more important predictor of attitude than
perceived usefulness.
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Result Analysis
The above bar graph depicts the belief of people in computers being user- friendly on a
scale of 1-5. According to the responses we received 41% of people rated it 5, 23.1% rated it 4,
19.2% rated it 3, 12.8% rated it 2 and finally 3.8% rated it 1. By this we can interpret that most
of the people belief that the computers are user friendly as most of them (41%) rated it 5.
The above pie-chart represents which of the given options is not an application of HCI.
55.1% says None of the above, 19.2% of the people says Robotics, 16.7% of the people says
wearable devices and the rest 9% of the people say Biometrics. So according to the answers
most of the people say none of the above which means they think all the above options are an
application of HCI.
The above question is to ask people their opinion about the benefits of human computer
interfaces. We received a lot of responses saying that it is beneficial to use human computer
interfaces as it helps us in communication in our day- to-day life. Companies can make
technical products accessible to people with disabilities thanks to human-computer
interaction. There are many such benefits of human computer interfaces.
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The above Bar-Graph depicts the importance of HCI for better communication according
on a scale of 1 to 5. According to the survey done, 35.9% have rated it 5, 24.4% have rated it 4,
25.6% rated it 3, 7.7% have rated it 2 and 6.4% have rated it 1. By this we can determine the
order of ratings as- 5,3,4,2,1. With 5 rating as the most we infer that most of the people think
that HCI is important for better communication.
The pie-chart represents the responses of the people regarding the full form of HCI.
According to the responses, 69.2% of people think it is Human computer interaction, 19.2% of
people think it is Human Computer interface, 10.3% of people think it is Human computer
implementation and the rest 1.3% of people think it is Human computer industry. By this we
can infer that most of the people think that HCI stands for Human Computer Interaction.
The above pie-chart represents how many hours in a day one can stay without interaction
with machines. According to the survey 32.1% of people says 1-5 hours, 35.9% of people says
5-10 hours, 24.4% of people says 10-15 hours, 7.7% of people says 15-20 hours. So, most of
the people (35.9%) says that they can stay 5-10 hours without any interaction with machines
and the least (7.7%) of people says that they can stay 15-20 hours without any interaction
with machines.
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The above question is about asking people if the human computer interaction affect our
daily life. According to the answers we received most of the people think it impacts the human
computer interaction and it impacts it in a good way. People think that it helps us in our day-
to-day life providing us knowledge and makes our work easy and efficient. In our daily life we
use computers for the whole day and most of our work depend on it.
.
The above depicted pie-chart is asking the opinion of people if the human computer
interaction is a boon or a bane. 85.5% of people think it is a boon and the rest i.e., 11.5% of
people think it is a bane. According to the survey most of the people think human computer
interaction think it is a boon and the rest think it is a bane.
The above question is to ask a adjective that can define human computer interaction. We
received a vast range of answers for it like interesting, evolution, etc. So according to answers
we can interpret that most of the people find it a stress free and a smart way to get a job done.
It is a great think that has brought evolution in our life.
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The above pie-chart depicts if the people see an improvement in the interaction between
human and machines in the received. We got 66.7% of people saying yes and 15.4% of people
saying no and the rest (17.9%) of people says maybe. According to the survey most of the
people believe that they see an improvement in the interaction between human and machines
in recent years and the rest either say no or maybe.
The above pie-chart represents the opinion of students, on which form of computers has
increased their communication the most. According to the survey 63% of the respondents
voted for computers/phone,20.8% for radios,13% voted for television whereas very few
people voted for other forms. We can conclude that phone/computers have increased the
communication skills the most whereas radios and television have done less.
The above pie-chart represents the opinion of students, on whether they can live without
interaction of computers or not. 39% of the respondents voted Yes, they can live without
computers, whereas 61% voted no. It can be concluded that the majority of the respondents
feel that they cannot live without computer interaction
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The above graph represents which social media do the respondents use the most.
Instagram is the most used platform (nearly 20) followed by snapchat. Facebook and
WhatsApp are also used by some of the respondents
The above bar-graph represents how much does the respondent’s work/educational
institution rely on computers on a daily basis. According to the survey 5.2% of respondents
have rated 1, while other 7.8% of respondents have rated 2, while other 19.5% of respondents
have rated 3, while other 33.8% of respondents have rated 4, while other 33.8% of
respondents have rated 5. So, it can be concluded that maximum respondents have rated 4-5
on how much does their work/educational institution rely on computers.
The above pie chart shows the thoughts of respondents on the effect of Human-computer
Interaction in early age where we can see 66.2% of respondents have stated that it’s a
profitable thing and another 33.8% of respondents think Human-computer Interaction in early
age is not beneficial. Through this chart it can be concluded that the majority of respondents
state that Human-computer Interaction in early age is profitable.
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The above pie chart represents whether the absence of social media will affect their intra-
personal communication. According to the survey, 43.6% of people answered “yes” which
represents that they think it will affect their intra-personal communication, 29.5% people
answered “no” which represents that they think it will not affect their intra-personal
communication whereas 26.9% of the people answered “maybe” which shows that they are
not sure whether it will affect their intra-personal communication. By this, we conclude that
majority of the people’s intra-personal communication will be affected by the absence of social
media whereas the least percentage of the population is unsure of their answer.
The above pie chart represents how much time people spend on- screen on average.
According to the survey, 34.6% of the people spend 3-4 hours on average on-screen,30.8% of
the people spend 1-2 hours on average on-screen,19.2% of the people spend 3-4 hours on
average on-screen,15.4% of the people spend 0-1 hours on average on-screen. By this we
conclude that majority of the population spends 1-2 hours on average on-screen whereas the
least percentage of the population spend 0-1 hours on average on-screen.
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The above graph shows which social media platform people use. According to the survey
(14.1%+12.8%+10.3%) of the people uses Instagram, (3.8%+2.6%) of the people uses
Facebook, 3.8% people use WhatsApp,2.6% of people don’t use any of the social media
platforms and the rest use other software. By this, we conclude that the majority of people use
Instagram as their prime social media platform and the least percentage of the population use
no social media platform.
The above pie chart shows how many people have ever used social media. According to the
survey, 87.2% of people have used social media and 12.8% of the people haven’t used social
media. By this, we conclude the majority of people have used social media.
Conclusion
Human computer interaction is very essential for improvement in communication, especially
youngsters. With improvement in internet connections, more people started to use computers.
Movies, shows and songs becoming more popular and influential. When education started to
shift online, communication between students and teachers improved, many people started
online start-ups. They were able to connect with customers nationwide through social media
websites and applications. Social networks and development in technology allowed people to
interact worldwide. Development of AR, AI, VR connected humans to computers. Ultimately
this all led to human computer interaction, which increased as well improved our
communication skills. The survey conducted showed how important computer interaction was
in the life of respondents. Computers are now an integral part of their life. Lastly, we conclude
the importance of human computer interaction in betterment of communication.
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References
1. Boholano, H.B., 2017. Smart social networking: 21st century teaching and learning skills.
Research in Pedagogy, 7(1), pp.21-29.
2. Carroll, J.M., 1997. Human–computer interaction: Psychology as a science of design.
International journal of human-computer studies, 46(4), pp.501-522.
3. Coyle, C.L. and Vaughn, H., 2008. Social networking: Communication revolution or
evolution?Bell Labs technical journal, 13(2), pp.13-17.
4. Fallman, D., 2003, April. Design-oriented human-computer interaction. In Proceedings of
the SIGCHI conference on Human factors in computing systems (pp. 225-232).
5. Fano, R.M., 1984, August. Computer mediated communication. In Electro-Culture 1984 (Vol.
474, pp. 34-38). SPIE.
6. Faulkner, C., 1998. The essence of human-computer interaction. Prentice-Hall, Inc.
7. Fetzer, J.H., 1990.Artificial Intelligence. In Artificial Intelligence: Its Scope and Limits (pp.
3-27). Springer, Dordrecht.
8. Fulk, J., 2017. Social construction of communication technology. Academy of Management
journal
9. Grudin, J., 2005. Three faces of human-computer interaction. IEEE Annals of the History of
Computing, 27(4), pp.46-62.
10. Guo, Z., Tan, F.B. and Cheung, K., 2010. Students' uses and gratifications for using
computer-mediated communication media in learning contexts.
11. Hill, R.D., 1986. Supporting concurrency, communication, and synchronization in human-
computer interaction—the Sassafras UIMS. ACM Transactions on Graphics (TOG), 5(3),
pp.179-210.
12. Hilty, D.M., Randhawa, K., Maheu, M.M., McKean, A.J., Pantera, R., Mishkind, M.C. and Rizzo,
A., 2020. A review of telepresence, virtual reality, and augmented reality applied to clinical
care. Journal of Technology in Behavioral Science, 5(2), pp.178-205.
13. Hirai, K., Hirose, M., Haikawa, Y. and Takenaka, T., 1998, May. The development of Honda
humanoid robot. In Proceedings. 1998 IEEE international conference on robotics and
automation (Cat. No. 98CH36146) (Vol. 2, pp. 1321-1326). IEEE.
14. Hirschberg, J. and Manning, C.D., 2015. Advances in natural language processing. Science,
349(6245), pp.261-266.
15. Ishiguro, H., Ono, T., Imai, M., Maeda, T., Kanda, T. and Nakatsu, R., 2001. Robovie: an
interactive humanoid robot. Industrial robot: An international journal, 28(6), pp.498-504.
16. K., 2008, September. Humanoid robot HRP-3. In 2008 IEEE/RSJ International Conference
on Intelligent Robots and Systems (pp. 2471- 2478). IEEE.
17. Kaneko, K., Harada, K., Kanehiro, F., Miyamori, G. and Akachi, Manaris, B., 1998. Natural
language processing: A humancomputer interaction perspective. In Advances in
Computers (Vol. 47, pp. 1-66). Elsevier.
18. Mathew, A.R., Al Hajj, A. and Al Abri, A., 2011, June. Human-computer interaction (hci): An
overview. In 2011 IEEE International Conference on Computer Science and Automation
Engineering (Vol. 1, pp. 99-100). IEEE.
131
19. Miehle, J., Yoshino, K., Pragst, L., Ultes, S., Nakamura, S. and Minker, W., 2016, September.
Cultural communication idiosyncrasies in human-computer interaction. In Proceedings of
the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue (pp. 74-
79).
20. Ogura, Y., Aikawa, H., Shimomura, K., Kondo, H., Morishima, A., Lim, H.O. and Takanishi, A.,
2006, May. Development of a new humanoid robot WABIAN-2.In Proceedings 2006 IEEE
International Conference on Robotics and Automation, 2006. ICRA 2006. (pp. 76-81). IEEE
21. Preece, J., Rogers, Y., Sharp, H., Benyon, D., Holland, S. and Carey, T., 1994. Human-
computer interaction. Addison-Wesley Longman Ltd..
22. Rodrigues, T.K., Suto, K., Nishiyama, H., Liu, J. and Kato, N., 2019. Machine learning meets
computation and communication control in evolving edge and cloud: Challenges and
future perspective. IEEE Communications Surveys & Tutorials, 22(1), pp.38-67.
23. Stephan, J.J. and Sana'a Khudayer, 2010. Gesture Recognition for Human-Computer
Interaction (HCI). Int. J. Adv. Comp. Techn., 2(4), pp.30-35.
24. Van Erp, J.B. and Toet, A., 2015. Social touch in human–computer interaction. Frontiers in
digital humanities, 2, p.2.
25. Waddell, T.F., Zhang, B. and Sundar, S.S., 2015. Human–computer interaction. The
International Encyclopedia of Interpersonal Communication, pp.1-9.
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CHAPTER 9
WEB 3.0 LEARNING AND TEACHING ENGLISH
Konkimalla Chaitanya Devi Ganesh (21BCE2840), Jeevan B A (21BCE0861)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
In the recent times, the technology is growing very rapidly leading to the future of internet called as Web
3.0. Augmented reality is a term used to describe a new form of mobile technology. The great popularity of
online mobile games is an example of how AR has advanced and been largely integrated into mobile
technology, making it feasible for almost everyone with a mobile device to use AR. Although augmented
reality is just starting to make its way into the educational space, it has the potential to significantly
improve our educational system. In fact, according to earlier academic research, augmented reality has
been proven to be useful for learning the English language and may increase student motivation. Thus, this
conceptual paper discusses results from earlier researches on the application and value of augmented
reality in the teaching and learning of English language reading.
Introduction
Web 3.0 which is the future of internet and technology contains many things like Augmented
reality (AR), virtual reality (VR), blockchain technology, metaverse, Artificial intelligence,
machine learning and many more things. Web 1.0 was the 1st version of internet which
contained only static web pages and next came web 2.0 which is the present internet which is
based on centralised database system. Where web 3.0 has decentralised system which means
no individual person or organization can control the database by their self.Web 3.0 is crypto
currency enabled which means crypto is going to replace the current currency in the world
slowly. Web 3.0 has metaverse which is a virtual world where we can interact with people all
over the world as if they are with us right now using technology of VR and AR. Web 3.0
includes many more things like NFT (non-fungible tokens), DeFi (decentralized finance),
dApp(decentralized applications) , smart contracts. The most common form of technology in
use today is mobile; practically everyone has a mobile device, such as a smartphone or tablet,
and can easily access the internet through Wi-Fi. There have been many advancements in
integrating mobile technology in language and literacy instruction to examine how it could be
used effectively. This is in addition to using mobile technology for everyday activities like
online transactions, instant messaging, etc.
Literature Review
Firat observed that Web 3.0 have affected the educational research significantly in the recent
years. The concept of e - learning has emerged as the teaching tradition is shifting from
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traditional teaching method to digital learning method. Web 3.0 includes many technologies
like augmented reality, 3d games, 3d visual environments and sematic web. After collecting
data from the target group, it was found that people prefer Web 3.0 more than the traditional
method of learning.
The disciplines in which the studies were carried out are Science education was the
highest followed by computer science, mathematics, language learning and then music
learning. The trends in the use of eb 3.0 where experimental method was the highest followed
by designing followed by qualitative, quantitative etc.
Rudman observed that many organisations consider generating income and controlling
cost as a major asset of the organisation. The internet (Web) is considered to be the fastest
growing means (technology) of all time to browse. The web can help in the development and
enhancement of technology. The web 1.0 which was the 1st phase of internet was having only
static pages whereas the net phase web 2.0 (which is the present internet technology) is
interactive. The study shows us the advantages and the risks of Web 3.0. It also tells us about
the possible safeguards for thoserisks.
Identified opportunities can be classified into 2 different categories, the autonomous
integration of data and service which increases the capabilities of the web services making it
more efficient. The major risks are unauthorised access, manipulation or changing of data,
autonomous initiation of action and the development of languages and scripts.
Carlos Flavián observed that the arrival of Augmented reality (AR) and Virtual reality (VR)
is designing the new environment where the physical and the virtual objects are integrated as
if they are existing together. The physical – virtual connections are very strong as the
technology is so developed. This article will help us to understand the concepts of linking
physical and virtual world (through AR and VR) in a better way.
This study involves a technology called “EPI Cube” which allows academic and manages all
technologies, current and the potential technology which might help improve the consumer
experience.
Cipresso noticed that the recent appearance of low-cost virtual reality (VR) like Oculus rift,
HTC Vive and Sony PlayStation VR is attracting the attention of the users as the technology is
new and very interactive and researchers think that the Web 3.0 may be the largest stepping
stone in technology improvement. The history of VR is longer than it seems. The concept of VR
was started in 1960s and the 1st VR tool came in the late 1980s. This article helps us
understand the evolution of VR and AR over the time. This work discusses about the changes
about to occur and the challenges we might face.
Cankaya observed that in the recent years the use of VR technology has spiked up. Most
importantly the use of VR headsets has increased so much due to its interactive nature with
users. This article shows that the number of users using VR headsets for education is
increasing year by year as we get a more interactive feel during lectures as we are virtually
present there in VR headsets.
Boonbrahm stated that the most crucial component of early education ismotivation. There
isn't much evidence that it worked, despite the fact that many schools have made considerable
investments in information technology in the hopes that it will boost student enthusiasm. The
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solution may lie in augmented reality, which allows kids to engage with virtual objects while
still in their natural surroundings. In this study, we designed three AR trials to support the
idea that AR might inspire kids to learn English. These AR experiments will emphasize
dialogue, reading, and writing. For this, various AR approaches, including marker-marker
interaction and user-defined targets, were applied. The findings support the hypothesis that
kids are very interested in and eager to learn more.
Ismail found that despite its centrality in the process of language learning, EFL students
sometimes disregard the significance of understanding English phonetics. When English
phonetics are not used and understood, mispronunciation problems result, which then
obstruct oral and written communication. In response to this problem, research was
conducted on the use of augmented reality (AR) technology to speed up the acquisition of
English phonetics. The technology created a more appealing and engaging learning
environment by combining virtual items with video footage. In addition to revealing how the
students used this media in their learning processes, this study also explained the stages and
procedures for creating augmented reality as English Phonetic learning material.
Ahmad found that many educational institutions all over the world have a cleargoal in
mind when it comes to improving English language ability. AR is one of the newest
technologies lately utilized in education, nevertheless needs additional thought and research
to ensure its efficacy inEnglish language learning ELL. The majority of AR technologies used in
ELL are highlighted in this document, along with an assessment of their usefulness andvalue.
Additionally, it draws attention to the drawbacks that would hinder the adoption of
augmented reality in education generally and English language acquisition specifically. Arrieta
found that the goal of the Sign Language Teaching Model (SLTM)described in this article is to
help deaf children develop their various communication skills in a collaborative learning
environment with mixed reality.
Gavalas states that since virtual reality (VR) is the first and only medium that hasthe
potential to allow for the incorporation of the full spectrum of both verbal and non-verbal
cues, there are reasons to view it as a recently developedcommunication medium that needs to
be distinguished from all other forms of mediated communication. The current paper is a
component of a larger investigation on potential differences in interpersonal communication
between the real world and virtual reality. Analysis shows that VR-mediated communication is
as complicated as face-to-face communication because subjects were equally compliant or
more so, with the type of information exchanged playing a role. These findings highlight the
under-development and potential applications of VR collaborative environments.
Jamrus (2019) observed that Augmented reality is a term used to describe a new form of
mobile technology. Although augmented reality is just starting to make its way into the
educational space, it has the potential to significantly improve our educational system. In fact,
according to earlier academic studies, augmented reality has been proven to be helpful in
improving student motivation and English language proficiency. Thus, this conceptual paper
presents findings from earlier investigations on the application and value of augmented reality
in the teaching and learning of English language reading. The idea of augmented reality, its
application in language learning, the advantages of using AR in language learning, the
135
limitations of using AR in language learning, and the level of teacher readiness and acceptance
of utilising AR in classroom reading instruction will all be covered in this essay. Additionally,
the authors will offer some stakeholder recommendations, particularly in relation to the use of
augmented reality in teaching English language reading, as well as ideas for future study.
Ardiny (2018) observed that technology has been advancing quickly and has a noticeable
impact on many facets of life, including education. According to studies, augmented reality and
virtual reality hold great promise for enhancing students' abilities and understanding. In
actuality, combining AR/VR with education can enhance learning and teaching in an engaging
way. In this review paper, we first give an overview and definition of augmented reality and
virtual reality. Then, we quickly review current studies and the newest AR and VR devices that
have pedagogical benefits and the potential to enhance educational systems. We then discuss
the strengths and weaknesses of AR/VR to determine what benefits it can offer to teachers and
students.
Karacan (2021) saw that Using the framework developed by Osterweil et al. for assessing
the appropriateness of educational technology use in global development programmes, the
paper reviews educational AR technology in terms of learning theories, learning pedagogies,
teachers, students, culture, infrastructure, and sustainability after conducting a brief but
thorough literature review. The analysis revealed that AR technology has a number of
advantages for language learning, but it is not yet prepared for full incorporation into language
programmes. The report also offers recommended applications and concrete ideas for AR-
enhanced exercises in four language skills. For teachers, teacher educators, researchers, and
those who create course materials, this review has a number of consequences.
Yildiz (2021) observed that the term "augmented reality" refers to a technology where
virtual things are combined with the real environment and can communicate with one
another. Although there are many uses for augmented reality apps, the sector of education is
the most significant. Through the use of virtual reality technology, kids may now learn difficult
subjects in a pleasant and straightforward manner. Students can learn more about the virtual
environment by interacting with its objects. For instance, lessons can be taught in a classroom
setting while on a digital tour of a museum or zoo in a foreign nation. At the conclusion of the
study, it was recommended that the educators carefully read the prepared portions and put
them into practise in their courses. Additionally, it was noted that it should be preferred to
connect with students in real time in order to properly communicate with them, particularly
throughout the pandemic process.
Jantjies (2018) observed that through the use of diverse digital resources, educational
technology may support the learning environment and improve learning. Emerging
technologies have made it possible for students to access a wealth of information on digital
platforms, filling the resource gap in learning environments. In order to facilitate experiential
learning in South African institutions, this study reviews the research on the use of mobile
augmented reality (AR) and virtual reality (VR) technology. There is a need for studies that
examine the potential of augmented reality and virtual reality in enhancing higher educational
institutions like universities and Technical and Vocational Schools.
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Drajat (2019) observed that Virtual Reality is a brand-new generation which broadly used
and really famous amongst younger generation. Virtual Reality and Artificial Intelligence
technologies grows rapidly. ELT in Indonesia is very poorly normal via way of means of college
students because of the teacher`s dull and conventional coaching techniques or method
ensuing in college students lack in English. So, if instructors use new coaching techniques via
way of means of the usage of synthetic intelligence incorporated digital truth as a media of
coaching, then college students could possibly be involved and the coaching or magnificence
may be completed from their very own domestic in a digital global that may additionally imply
much less cash spent on transportation, lunch, etc. This also make college students higher in
English on a everyday basis. Therefor Using Artificial Intelligence incorporated Virtual Reality
in ELT enables college students improves their English hence also can saves cash for Parents.
Hence using Artificial Intelligence incorporated Virtual Reality as a media in ELT in Indonesia
can be an opportunity technique for ELT to be nicely normal via way of means of college
students and to enhance college students English.
Li (2020) observed that Artificial intelligence (AI) technology made a significant
advancement in 2016. Virtual reality and AI-based language service solutions are becoming
more prevalent on the commercial market, which has had a significant impact on the language
service sector. Based on artificial intelligence and VR (virtual reality) technology, this project
develops a collection of oral English training systems that adapt oral English instruction to the
needs of the modern world.
Yang (2022) observed that VR and AI technology to college English instruction in an effort
to enhance its effectiveness. In this article, a semiactive address-driven pixel structure is
suggested in accordance with the pixel structure of the English teaching image and its array
drive architecture. In addition, this article regulates the scanning rate by altering the CLK clock
signal's period, which is generated by the computer or FPGA and controls the speed of image
transmission. Additionally, the negative feedback loop is biased and an intelligent teaching
system is built in order to determine the output DCvalue of the cascode structure.
Xie (2021) observed that Globalization and informatization are changing human life and
social behaviour. Its aim is to explore global strategies for promoting international talent with
a global vision. As the world's language with the largest population, English, especially its
educational value, has always been a major concern of scholars and educators. This work is a
combination of immersion-based English teaching and virtual reality (VR) technology. is
considered in an innovative way. Then, based on an experimental design, her 106 students
from a Chinese school were selected for her quasi-experimental study. Collected data are
analysed by computer statistical software to test hypotheses. The results showed a significant
positive correlation between VR and immersion-based language teaching. There was a
significant positive correlation between immersion-based language instruction and academic
performance, and VR was positively correlated with learning outcomes (LO) . Compared with
other cutting-edge research methods, this work corrects students' oral exams through analysis
and comparison with the system database, greatly improving students' learning effect. Finally,
based on the research results, some suggestions are made to provide experimental references
for English teachers and future linguistics teaching.
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Mukhallafi (2020) observed that as time goes on, machines are becoming more complex,
faster and smarter. Although we still have a long way to go to be exactly human-like in
reasoning, reasoning, and decision-making, several notable advances in the application of
artificial intelligence (AI) and machine learning techniques have been noted recently.
Therefore, the current research attempts to explore strategies for effectively using artificial
intelligence (AI) applications for teaching and learning English from the perspective of college
students. This study applies an analytical-descriptive approach to study and analyse the
literature to describe AI and strategies for using AI in English teaching/learning. A 40-item
questionnaire was used. It covers AI strategies and appropriate applications for English
teaching/learning, the effectiveness of these applications, their practical use, and the
requirements for their use in the English teaching/learning field. We measured the validity
and reliability of the questionnaire, resulting in Cronbach's alpha of 0.931. The survey sample
consisted of 44 of her male students randomly selected from the English department of
Northern Border University. Many learning tools were used. The results revealed a set of
strategies suitable for teaching and learning English using AI. The results also show little use
of these strategies for teaching and learning English, indicating their effectiveness when used
in this area. In this study, we determined the need for training in terms of the study sample. A
proposed plan including foundations, goals, content, processors and evaluation methods for
using AI applications in the field of English teaching is envisioned.
According to Kim, N.Y., Cha, Y. and Kim, H.S., (2019) in their article “Future Englis
Learning: Chatbots and Artificial Intelligence” research developments in robotics have made it
possible for robots to help humans in a variety of ways. Chatbots are regarded as useful in a
variety of fields, and research is increasingly concentrating on using this technology in
language instruction. This study's objective was to review and report on various intelligent
chatbot types for language learning. According to the research, there aren't many chatbot
programmes that enable direct voice recognition or text communication between humans and
chatbots for the purpose of learning foreign languages. Researchers have looked into the
sparse application of AI in educational settings, including chatbot programmes designed to
enhance English teaching and learning. According to their empirical studies, chatbots have
shown to have some favourable effects on students' communication skills, primarily by
increasing the quantity of their interactions, which entails negotiation, boosting their
motivation, and enhancing their interest in learning. In light of this, this study suggests that
chatbots can enhance linguistic inputs and provide opportunities for language learners to
improve their communicative proficiency.
According to Jia, J. and Ruan, M., (2008) article “Use Chatbot CSIEC to Facilitate The
Individual Learning in English Instruction: A Case Study” These skills include those related to
the global economy and technology. The recommended strategy involves incorporating
chatbot technology into the current teaching-learning environment while taking into account
both enabling and restricting variables. The conceptualization of this method is based on
social constructivism, which holds that social interaction is crucial to the development of
cognition and that learning is mediated by cultural tools and scaffolding.
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According to Jia, J., (2009) article “CSIEC: A Computer Assisted English Learning Chatbot
based on Textual Knowledge and Reasoning” a virtual chatting partner (chatbot) that can
communicate in English with English learners wherever they are is still the main emphasis of
the CSIEC system, which has recently evolved many features for English instruction. According
to user input, dialogue context, knowledge of the user's and its own personalities, common
sense, and inference knowledge, it develops communicative responses. NLML, an annotation
language for natural language text, is used to convey all of these different types of information.
These NLMLs can be generated automatically by parsing the text or quickly created with the
use of GUI editors that we developed. As a result, the CSIEC system recommends a simplistic
method of logical reasoning and inference that relies solely on the syntactical and semantic
analysis of textual knowledge. Compared to the outdated ELIZA-style keywords matching
technique, this method has advantages.
According to Coniam, D. (2008) article “An Evaluation of Chatbots as Software Aids to
Learning English as a Second Language” "Chatbots" are computer programmes that can speak
or carry on a conversation in English. Chatbots have advanced significantly since Eliza's
command-line days, to the point where many of them currently have an avatar interface and
provide speech recognition as a feature. Six chatbots that are currently for sale or purchase
online are evaluated in this study. This study looks at chatbots' suitability as educational
software tools and their user interfaces as a human-sounding or human-looking chat
companion. The report's analysis of already accessible chatbots closes by emphasising that,
despite their advancements since Eliza's early days, they still have a way to go before they can
engage with students in the way that academics like Atwell (1999) had envisioned.
According to Sarosa, M., Kusumawardani, M., Suyono, A. and Wijaya, M.H. (2020) article
“Developing a Social Media-Based Chatbot for English Learning” for recent graduates, the rise
in multinational businesses giving employment opportunities in Indonesia is a blessing. Due to
their poor English, they were unable to take advantage of the chance. The absence of human
resources that can directly, gradually, and consistently help people improve their English skills
may be the cause of this problem. Social media are quite popular today among many different
demographics; however, they are mostly utilised for sharing of information. This study
intended to create a Facebook application as an English learning tool to aid students in
learning the language more quickly. To assist folks who struggle with learning English, this
programme was designed as a Chatbot (an automated responding machine). As consumers are
already accustomed to its layout and navigation, the chatbot incorporated into social media
should make adoption easier. Students at the State Polytechnic of Malang's D3 English Study
Program and the Telkom Vocational High School in Malang have both applied to use this
application.
Result Analysis
139
The given pie-chart shows the gender of the respondents. We can see that 88.5% of the
respondents are male, 9.6% are female and 1.9% did not want to reveal their gender. It can be
concluded that maximum respondents are male.
The given pie-chart shows the status of the respondents. We can observe that 92.3% of the
respondents belong to the 18-22 age group ,5.8% of the respondents belong to the 15-18 age
group, 1.9% of the respondents belong to the 22-30 age group.So, from this we can conclude
that most of the respondents belong to the 18-22 age group.
The given pie-chart shows the status of the respondents. We can observe that 88.5% of the
respondents are Students at a College, 9.6% of the respondents are Students at a School,1.9%
of the respondents are Working Professional.So, from this we can conclude that most of the
respondents are Students at a College.
The given pie-chart represents whether the respondents have heard of the term Web 3.0
for which 51.9% voted Yes and 48.1% voted No. We can see that 75%of the respondents are
male while 25% are female. It can be concluded that maximum respondents are male. It can be
concluded that majority of the respondents heard the term Web 3.0.
140
The given pie-chart shows 48.1% of the respondents agree that the future is Web 3.0 and
46.2% of the respondents are not sure about the future is Web 3.0 and 5.8% of the
respondents are not in Favour. The majority of the people's opinion is that the future is Web
3.0.
The above chart represents the opinion of students, on how the respondents feel whether
AI will cause loss of human jobs. 50% of the respondents voted Yes, 25% voted Maybe, and
25% of the respondents voted No. It can be concluded that the majority of the respondents feel
that AI will cause loss of human jobs.
The given pie-chart shows 73.1% of the respondents agree that we can teach a language
using AR and VR and 25% of the respondents are not sure about the teaching of a language
through AR and VR and 1.9% of the respondents are not in Favor. The majority of the people
opinion is that we can teach a language using AR and VR.
141
The given pie-chart shows 61.5% of the respondents agree that we can learn and teach a
language using AR and VR and 26.9% of the respondents are not sure about the teaching of a
language through AR and VR and 11.5% of the respondents are not in Favour. The majority of
the people's opinion is that we can teach and learn a language using AR and VR is effective.
The above chart represents the opinion of students, on how the respondents feel whether
internet is harmful for the youth or not. 36.5% of the respondents voted Yes, 34.6% voted
Maybe, and 28.8% of the respondents voted No. It can be concluded that the majority of the
respondents feel that internet is harmful for the youth.
According to the data collected on the statement that in the future, teaching will be done
through AR and VR. 36.5% of the respondents agree about the statement, 28.8% of the
respondents Strongly agree with our Statement, 3.8% of the respondents disagree with our
Statement, 28.8% of the respondents are neutral with our Statement and 1.9% of the
respondents are not in favour. So, from the above pie-chart we can observe that the majority of
the respondents agree with our statement.
142
According to the data collected on the statement that we can AR and VR to teach primary
students also which makes their learning more effective. 32.7% of the respondents are neutral
about the statement, 26.9% of the respondents Strongly agree with our Statement, 30.8% of
the respondents agree with our Statement, 3.8% of the respondents Disagree with our
Statement and 5.8% of the respondents are not in favour. So, from the above pie-chart we can
observe that the majority of the respondents are neutral.
According to the data collected on the statement that learning through AR and VR is easy
compared to the present learning method (traditional method).
36.5% of the respondents are neutral about the statement, 23.1% of the respondents Strongly
agree with our Statement,23.1% of the respondents agree with our Statement, 11.5% of the
respondents Disagree with our Statement and 5.8% of the respondents are not in favor. So
from the above pie-chart we can observe that majority of the respondents are neutral.
According to the data collected on the statement that AR and VR will be expensive at the
beginning but the cost will surely reduce as the technology develops. 27.7% of the
respondents agree about the statement, 17% of the respondents Strongly agree with our
143
Statement, 8.5% of the respondents disagree with our Statement, 27.7% of the respondents
are neutral with our Statement and 8.5% of the respondents are not in favour. So, from the
above pie-chart we can observe that the majority of the respondents agree/neutral with the
statement.
The above chart represents the opinion the respondents on how they feel whether AR and
VR saves time compared to the traditional method. 73.1 % of the respondents voted Yes, 25%
voted Maybe, and rest of the respondents voted No. It can be concluded that the majority of
the respondents feel that AR and VR saves time compared to the traditional method.
The graph represents the idea of using AR and VR as means of communication for deaf
people. 50% of the respondents expect that it will be outstanding with the idea of using AR
and VR as means of communication for deaf people, 26.9% of the respondents are excellent,
19.2% of the respondents are neutral ,0% of the respondents are inoffensive, 3.8% of the
respondents are inconvenient.So, from the above graph we can conclude that the idea of using
AR and VR as means of communication for deaf people was great. This shows that most of the
people accept the idea of using AR and VR as means of communication for deaf people.
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The graph represents the rating of experience of AR/VR that28.3% of the respondents
expect that it will be Outstanding,23.9% of the respondents are excellent, 39.1% of the
respondents are neutral, 6.5% of the respondents are inoffensive,2.2% of the respondents are
inconvenient. So from the above graph we can conclude that most of the respondents expect
experience of AR and VR is average.
The graph represents the expectations of teaching a language through AR and VR. 34.6% of
the respondents expect that it will be Excellent with teaching of a language through AR and VR,
30.8% of the respondents are inoffensive, 3.8% of the respondents are inconvenient. So from
the above graph we can conclude that most of the respondents expect that it would be great to
teach a language using AR and VR. This shows that most of the people accept the method of
teaching and learning becomes easier and better through AR &VR.
According to the data collected on how someone would rate the idea of learning through AI
the responses received were: 3.8% rated as 1, 11.5% rated as 2, 26.9% rated as 3, 21.2% rated
as 4 and 36.5% rated as 5. It is observed that most of the students really liked the idea of
learning through AI.
The above graph represents the opinion of students, on what the status privacy on the
internet is. Do people trust the security provided by the internet or not. 15.4% says very poor,
145
15.4% says poor, 28.8% has a neutral stand on it, 19.2 says good and 21.2% says very good. It
can be concluded that the majority of the respondents are satisfied from the privacy that the
internet is providing.
The above chart represents the opinion the respondents on it is feasible to implement
teaching through AR and VR. 61.5% of the respondents voted Yes, 26.9% voted Maybe, and
11.5% of the respondents voted No. It can be concluded that the majority of the respondents
feel that it is feasible to implement teaching through AR and VR.
Conclusion
In this conceptual paper, it was explained how augmented reality technology could help the
educational field, particularly with the teaching of the English language. Since Augmented
Reality technology is still in its infancy, little research has been done on how it may affect
language learning. Despite all the drawbacks listed above, augmented reality has other
advantages, particularly when used to teach reading. The researcher is of the opinion that
these difficulties shouldn't prevent the use of augmented reality in the instruction of English
reading. This is because manufacturers and businesses will eventually find solutions to issues
with hardware components like glitches and bugs. With the expected quick improvement and
development of technology, augmented reality will likely improve in the future, leading to a
more widespread distribution in terms of its application, particularly in the sector of
education. Therefore, if we want to fully benefit from Augmented Reality's ability to improve
our education quality, particularly in terms of English reading, investing in it and doing
research on it is crucial.
References
1. FIRAT, E.A. and Firat, S., 2020. Web 3.0 in learning environments: A systematic review.
Turkish Online Journal of Distance Education, 22(1), pp.148-169.
2. Rudman, R., 2015. Web 3.0: governance, risks and safeguards. Journal of Applied Business
Research (JABR), 31(3), pp.1037-1056.
3. Flavián, C., Ibáñez-Sánchez, S. and Orús, C., 2019. The impact of virtual, augmented and
mixed reality technologies on the customer experience. Journal of business research, 100,
pp.547-560.
146
4. Cipresso, P., Giglioli, I.A.C., Raya, M.A. and Riva, G., 2018. The past, present, and future of
virtual and augmented reality research: a network and cluster analysis of the literature.
Frontiers in psychology, p.2086.
5. Çankaya, S., 2019. Use of VR headsets in education: A systematic review study. Journal of
Educational Technology and Online Learning, 2(1), pp.74-88.
6. Boonbrahm, S., Kaewrat, C. and Boonbrahm, P., 2015, August. Using augmented reality
technology in assisting english learning for primary school students. In international
conference on learning andcollaboration technologies (pp. 24-32). Springer, Cham.
7. Nugraha, I., Suminar, A.R., Octaviana, D.W., Hidayat, M.T. and Ismail, A., 2019, December.
The application of augmented reality in learning English phonetics. In Journal of Physics:
Conference Series (Vol. 1402, No. 7, p. 077024). IOP Publishing.
8. Alaqsam, A., Selamat, A., Alias, R.A., Zakaria, N.H., Puteh, F., Cheng, L.K. and Ahmad, M.N.,
2018. Using Augmented Virtual Reality to Improve English Language Learning. In New
Trends in IntelligentSoftware Methodologies, Tools and Techniques (pp. 759-770). IOS Press.
9. Cadeñanes Garnica, J.J. and Arrieta, M.A.G., 2014. Augmented reality sign language teaching
model for deaf children. In Distributed Computing and Artificial Intelligence, 11th
International Conference (pp. 351-358). Springer, Cham.
10. Dzardanova, E., Kasapakis, V., Gavalas, D. and Sylaiou, S., 2022. Virtual reality as a
communication medium: a comparative study of forced compliance in virtual reality
versus physical world. Virtual Reality, 26(2), pp.737-757.
11. Jamrus, M.H.M. and Razali, A.B., 2019. Augmented reality in teaching and learning English
reading: realities, possibilities, and limitations. International Journal of Academic Research
in Progressive Education and Development, 8(4), pp.724-737.
12. Ardiny, H. and Khanmirza, E., 2018, October. The role of AR and VR technologies in
education developments: opportunities and challenges. In 2018 6th RSI International
Conference on Robotics and Mechatronics (IcRoM) (pp. 482-487). IEEE.
13. Karacan, C.G. and Akoglu, K., 2021. Educational augmented reality technology for language
learning and teaching: A comprehensive review. Shanlax International Journal of
Education, 9(2), pp.68-79.
14. Yildiz, E.P., 2021. Augmented reality research and applications in education. In Augmented
Reality and Its Application. IntechOpen.
15. Jantjies, M., Moodley, T. and Maart, R., 2018, December. Experiential learning through
virtual and augmented reality in higher education. In Proceedings of the 2018 international
conference on education technology management (pp. 42-45).
16. Drajat, A.R., 2019. Applying virtual reality in improving student’s english. Proceeding IAIN
Batusangkar, 3(1), pp.37-40.
17. Li, X., Xie, Y. and Liu, T., 2020, May. Research on oral English teaching system based on VR
in the background of ai. In Journal of Physics: Conference Series (Vol. 1550, No. 2, p.
022031). IOP Publishing.
18. Yang, Z., 2022. Application and Exploration of VR and AI Technology in College English
Teaching. Advances in Multimedia, 2022.
147
19. Xie, Y., Liu, Y., Zhang, F. and Zhou, P., 2021. Virtual Reality-Integrated Immersion-Based
Teaching to English Language Learning Outcome.
20. Mukhallafi, T.R.A., 2020. Using artificial intelligence for developing English language
teaching/learning: an analytical study from university students’ perspective. International
Journal of English Linguistics, 10(6), pp.40-53.
21. Kim, N.Y., Cha, Y. and Kim, H.S., 2019. Future English learning: Chatbots and artificial
intelligence. Multimedia-Assisted Language Learning, 22(3), pp.32-53.
22. Jia, J. and Ruan, M., 2008, June. Use chatbot csiec to facilitate the individual learning in
english instruction: A case study. In International conference on intelligent tutoring systems
(pp. 706-708). Springer, Berlin, Heidelberg.
23. Jia, J., 2009. CSIEC: A computer assisted English learning chatbot based on textual
knowledge and reasoning. Knowledge-Based Systems, 22(4), pp.249-255.
24. Coniam, D., 2008. An evaluation of chatbots as software aids to learning English as a
second language. The Eurocall Review, 13, pp.2-14.
25. Sarosa, M., Kusumawardani, M., Suyono, A. and Wijaya, M.H., 2020. Developing a social
media-based Chatbot for English learning. In IOP Conference Series: Materials Science and
Engineering (Vol. 732, No. 1, p. 012074). IOP Publishing.
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CHAPTER 10
AWARENESS OF COMMUNICATION ISSUES IN CHILDREN WITH
DOWN SYNDROME
Viraaj Kumar Kulshreshtha (20MSI0002), Saai Pranav Reddy Duvvuru (20MSI0002)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
Down Syndrome is a genetic disorder occurring in 1 of 700 live births. 98% of all disorder cases are due to
an additional copy of Chromosome 21; also known as Trisomy 21. The research aims to check the
awareness levels and investigate the impact of the current methods that are in place for improving
communication problems faced by young adults and children suffering from Down Syndrome. This study is
conducted by surveying the awareness among the students at Vellore Institute of Technology (VIT), Vellore.
To understand the impact of the mechanisms in place it is crucial first to understand how exactly these
mechanisms work and which areas they target. This paper presents the analysis of a questionnaire that
was circulated via Google Forms. Through our research we were able to find out that more input was
needed to create awareness for Down Syndrome, the inclusion of speech therapy at an early level can help
individuals with Down Syndrome and social media can help in spreading awareness about Down Syndrome
and the related speech disorders.
Keywords: Down Syndrome, Speech Therapy, Awareness; Communication.
Introduction
Down Syndrome is a genetic disorder occurring once in every 700 live births. Ninety-eight per
cent of all cases of the disorder is due to an extra copy of the 21st chromosome; thus, this
disorder is often referred to as Trisomy 21. Translocation of parts of the 21st chromosome to
other chromosomes is another reason that disorder occurs but is far less common than the
first form. Reviews for down syndrome show coherence with the various models for language
development. Individuals with Down Syndrome have a unique profile of strengths and
difficulties regarding language and communication skills despite the individual differences in
the disorder.
Reasons for communication difficulty in Down Syndrome affected individuals:
Hearing Loss
Oral Motor Skills
Cognitive Skills
Social Skills
Vocal development pre-linguistically and
Development of nonverbal communication skills at an early stage
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Aspects of communication that need to be tackled/addressed to help these individuals –
Phonology
Vocabulary
Syntax
Pragmatics
The condition is seen as a developmental delay only if the features of the condition follow
the typical developmental course with a delay in the overall progress. However, if the features
deviate from the typical development pattern, the condition is termed a disorder. It has also
been noted that there are articulation errors of disordered or non-developmental nature.
The severity of this disorder varies between individuals and results in life-long intellectual
disability and delays in development. Aside from being a common genetic chromosomal
disorder, Down Syndrome is also a common cause of other abnormalities such as heart and/or
gastrointestinal disorders.
Despite the variation in the severity of the disorder, certain distinct facial features are
found in all individuals with Down Syndrome. Some of the more common features include:
Flattened face
Small head
Short neck
Protruding tongue
Upward slanting eyelids (palpebral fissures)
Unusually shaped or small ears
Poor muscle tone
Broad, short hands with a single crease in the palm
Relatively short fingers and small hands and feet
Excessive flexibility
Tiny white spots on the coloured part (iris) of the eye called Brushfield’s spots
Short height
In individuals suffering from Down Syndrome, severe difficulties with morphosyntax [or
the ability to understand the manner in which words are put together into phrases (syntax)
and the system of the internal structure of the words (morphology)] and speech intelligibility
persist into adulthood in most cases.
To ensure that these individuals achieve their full potential in regard to communication,
interventions by trained individuals are required to ensure remediation of the individual’s
specific speech and language disabilities.
Access to alternative and augmentative forms of communication also becomes necessary
for this remediation therapy to be effective. It is also important for accommodations to be
made for these individuals.
With the proper support and targeted therapy, individuals with Down Syndrome can
achieve full participation in society, but multiple surveys made by researchers in this field
show that due to inadequate service provisions, these individuals don’t receive the needed
therapy.
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Literature Review
Speech in individuals with Down syndrome is often associated with impediments and
impairments in spoken language.
In the 1970s, research done defined stuttering as “a special kind of tenseness which is
periodically heightened during the cry, when attacks of glottal pressure are superimposed on
the phonation.” Another research done saw the creation of a cry score that helped researchers
and therapists distinguish the cries of infants with Down Syndrome from those of normal
infants.
In 2003, researches revealed that this change in the vocal features of individuals with
Down Syndrome arose from the obstruction of the airway. This obstruction was associated
with disorders such as laryngomalacia, tracheomalacia, or bronchomalacia.
Studies done in 2002 showed that the vocal frequencies in adults were generally higher for
individuals with Down Syndrome as compared to the healthy controls. This was hypothesized
to be due to the smaller body size in Down Syndrome individuals as compared to the controls.
As a result, individuals with Down Syndrome might have a smaller larynx.
Unfortunately, for this hypothesis to be supported, it has to be established that there is a
difference in the size of the larynx between the controls and the individuals with Down
Syndrome.
The difference in the patterns of speech between children with Down Syndrome and
children showing typical patterns of growth and development becomes clear between the ages
of 3 to6.
Many studies showed that:
Infants with Down Syndrome produced lesser speech-like sounds and more non- speech
sounds as compared to children showing typical development patterns,
The onset of babbling in infants was delayed and less stable in Down Syndrome infants.
In a study done, frequent errors were reported between high and low vowels as well as
front and back vowels. This indicated that individuals with Down Syndrome faced some in the
regulation of tongue height and advancement that can be attributed to anatomical defects
and/or motor limitations.
It was found that the emergence and mastery of consonant phonemes in Down Syndrome
individuals, especially children, tend to be long and drawn-out processes that more often than
not vary with the individual and do not follow the norms shown by the individuals that were
part of the control.
Researchers find it difficult to determine the degree of comorbidity between stuttering
and/or cluttering with voice and speech problems. It is also unknown if the nature and
severity of the disorder can change over the lifespan, it was also found that disfluent speech in
individuals with Down Syndrome can be attributed to dysfunctional motor control and/or
language processes (utterance formulation or word finding).
It was found that limitations in prosody could be a result of the following things:
Motor difficulties
Problems in coordinating speech
Motor control with phonological/other higher-level representation
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Limitations in prosody could be the result of motor difficulties, problems in coordinating
speech motor control with phonological or other higher-level representations, or even serious
segmental (articulatory) errors that impede the effective production of speech across
multisyllabic sequences. Prosodic abnormalities may have their origin in limitations of
phonological processing.
There have been many procedures that have been used to estimate the intelligibility in
individuals with Down Syndrome; these include:
Scaling procedures such as the percentage estimate of intelligibility
Word identification
Scoring from transcription
Although the reduction in intelligibility in Down Syndrome is well documented, the
reasons for this have not been explored to a sufficient degree.
In some cases, poor speech production accuracy can be attributed to the structural
impairments associated with Down Syndrome, while the severity of the speech problems is
often related to difficulties in speech motor control that is complicated by hypotonia.
It was because of this that in a study in 2018, addressed motor planning using sensory
motor methods that were designed to improve auditory-motor integration.
It was described speech errors produced by the person with Down Syndrome as
inconsistent and atypical, which suggested that there were difficulties with phonological
planning and memory. A characteristic of Down syndrome is the difficulties with working
verbal memory.
This has led to the recommendation that interventions used to treat expressive language
disabilities use visual cues to accommodate the specific individual.
Speech production in an individual with Down Syndrome can thus be comprised of several
types of impairments; while the relation between these impairments is not clear, there has
been a general agreement on the following points:
Problems in speech are rooted in factors such as anatomy and motor control and are not
correlated with the language and cognition of the individuals.
While there are mixed reports on infants with Down Syndrome having atypical patterns of
vocal development, most researchers agree that there is some delay in the appearance of
canonical babbling. These delays are generally much lesser when compared to the delays
in the appearance of motor skills of these individuals.
There are delays in articulation and phonetics, as shown by studies, and there are non-
developmental patterns shown by children with Down Syndrome around the age of 3.
There are inconsistency errors and increased variability at the acoustic levels at some
segments. These patterns can play an important role in assessment and treatment.
While anatomical anomalies might not explain all the aspects of speech in Down
Syndrome, the deviations can impose limitations on articulation. Unfortunately, how these
developmental changes in the anatomy and physiology of individuals with Down
Syndrome affect the articulation and resonance of speech in these individuals is not well
established.
152
Methodology
The method of collecting data was done by distributing a questionnaire that contained
questions regarding Down Syndrome and the communication issues that come with it. The
questionnaire was distributed online using Google Forms to the students of VIT, Vellore.
Results and Analysis
Question 1. Do you know someone that suffers from Down Syndrome?
a. Yes
b. No
51 people responded to the survey out of which 80.4% of these individuals do not know or
have never interacted with an individual suffering from Down Syndrome.
Question 2. Do you think people are aware of Down Syndrome and the issues related to it?
a. Yes
b. No
c. Maybe
When asked if there is enough awareness regarding the disorder, most respondents were
unsure (52.9% opted for maybe); while 33.3% said ‘No’ and only 13.7% said ‘Yes’.
Question 3. On a scale of 1 to 10, how would you rate the awareness the society has when
it comes to Down Syndrome and its related Communication issues?
On being asked to rate from 0-10, about how aware the society is about the disorder the
most common answer received is 4 and 5 (12 responses each). This clearly shows that there is
aneed for awareness regarding the disorder and the issues with communication that come
with it.
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Question 4. Compared to children with normal cognitive development, at what age do you
think children with Down Syndrome start speaking?
a. 8-10 months
b. 10-14 months
c. 14-18 months
d. >18 months
Most of our respondents believed that children with Down Syndrome start speaking at the
age of 14 months or older with 43 percent respondents answering with over 18 months. In
comparison to this, less than 14 percent of the respondents believe that individuals with Down
Syndrome began speaking at the age of 10 to14 months.
Question 5. What are the most notice able changes seen in the speech of an individual with
Down Syndrome?
a. Reduced speech intelligibility (difficulty in understanding speech)
b. Difficulty in grammar
c. Unable to pronounce word endings
d. Usage of shorter sentences
Agreeing with most research that we cameacross, our respondents also believe thatspeech
intelligibility is one of the areas mostaffected by Down Syndrome with almost 55percent
agreeing withthis.
Question 6. Do you think speech therapy methods used for helping individuals with Down
Syndrome are helpful?
a. Yes
b. No
c. Maybe
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While almost 53 percent of the respondents were unsure of how impactful speech therapy
methods were in helping individuals with DS, nearly 41 percent believed that they were
helpful while only 5.9 percent said that they weren’t helpful.
Question 7. Do you think that basic speech therapy should be included in all pre-schools
and primary schools?
a. Yes
b. No
c. Maybe
Over 78 percent of our respondents agreed that introduction of basic speech therapy at the
pre-school and primary school levels would be beneficial for children.
Question 8. Of the following methods, which methods in your opinion are the most helpful
as Speech Therapy Techniques?
a. Reading-Out Loud
b. Tongue Exercises
c. Word Games
d. Reduction of Screen Time
Our sample believes that out of all the methods to improve Speech Therapy, Reduction of
Screen time was theleast helpful, while Reading Out Loudand Tongue Exercises being almost
equally helpful in the task.
Question 9. What could be some of the other issues that could impair the ability of speech
therapists from helping people with Down Syndrome?
a. A Lack of time with the individual
b. Funding and/or a lack of proper resources
c. The overall cost to parents
d. Other disorders associated with Down Syndrome such as Autism, ADHD, etc.
e. Lack of involvement of parents
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Most of the sampled population believes that all the listed-out issues (Lack of one-to-one
time with the Down Syndrome individual, lack of funding and improper resources, high cost to
parents, lack of parental involvement as well as the other disorders that are associated with
Down Syndrome) almost equally impaired the ability of a speech therapist to help an
individual with Down Syndrome.
Discussion
The results from our questionnaire lined up with what we came across during our literature
review, showing the following:
1. More input was needed to create awareness for Down Syndrome. Rallies, seminars, out
reach programs, inclusion early education programs, fund raising, etc, were some of the
ways that our respondents believed could be used for this.
2. It is also believed that various speech therapy methods along with parental care and
guidance as well as individualistic approaches can help individuals with Down Syndrome
reduce the difficulty they face in communication.
3. The inclusion of speech therapy at an early level (around pre-school and elementary level)
can be the first step in helping individuals with Down Syndrome improve their
communication skills
4. The monetary issues can be overcome if it is included in the academic system and if
schools are able to provide free speech therapy to individuals. This will also go a long way
in raising awareness about the disorder.
5. Social media can also be used to increase the awareness about Down Syndromeand help
individuals with Down Syndrome by giving them the required help by connecting them to
the right people.
Conclusion
The genetic disorder - Down Syndrome also known as Trisomy 21 affects many areas of the
human body including facial features, the voice, and parts of the brain such frontal lobes and
cerebellum which are important for voluntary movement, higher executive functions,
expressive language, cognitive functions such as language and attention, and vocal
development.
The condition can be seen as either a developmental delay or a disorder depending on the
course of the developmental course and the individual’s overall progress and mental growth.
156
The study proves that there isn’t enough awareness regarding Down Syndrome and the
problems in communication that come with it. Society needs to be made aware of these
problems to make the lives of those with the disorder easier and make it easier for individuals
to interact with them.
References
1. Bertrand P, Navarro H, Caussade S, Holmgren N, Sanchez I. Airway anomalies in children
with Down syndrome: Endoscopic findings. Pediatric Pulmonology. 2003; 36:137–141.
[PubMed:12833493]
2. Bunton K, Leddy M, Miller J. Phonetic intelligibility testing in adults with Down
syndrome.Down’s syndrome, research and practice: the journal of the Sarah Duffen
Centre/University of Ports mouth. 2007;12:1–24.
3. Bunton K, Leddy M. An evaluation of articulatory working space area in vowel production
ofadults with Down syndrome. Clinical Linguistics & Phonetics. 201010.3109/
02699206.2010,535647
4. Chapman, R.S., & Hesketh, L.J. (2001). Language, cognition, and short-term memory
inindividuals with Down syndrome. Down Syndrome Research and Practice, 7, 1–7.
doi:10.3104/reviews.108
5. Chapman, R.S., Hesketh, L.J., & Kistler, D.J. (2002). Predicting longitudinal change
inlanguage production and comprehension in individuals with Down syndrome:
Hierarchical linear modeling. Journal of Speech, Language, and Hearing Research, 45, 902–
915.doi:10.1044/1092-4388(2002/073)
6. Cleland J, Wood S, Hardcastle W, Wishart J, Timmins C. Relationship between speech,
oromotor, language and cognitive abilities in children with Down syndrome. International
Journal of Language and Communicative Disorders. 2010; 45: 83–95.
7. Dodd B, Thompson L. Speech disorder in children with Down’s syndrome. Journal of
Intellectual Disability Research. 2001; 45:308–316. [PubMed: 11489052]
8. Dodd, B., & Thompson, L. (2001). Speech disorder in children with Down’s syndrome.
Journal of Intellectual Disability Research, 45, 308–316.doi:10.1046/ j.13652788.
2001.00327.x
9. Fawcett S, Peralego J. Speech in individuals with Down syndrome. Perspectives on
Language Learning and Education. 2009; 16: 109–116.
10. Kumin L, Councill C, Goodman M. A longitudinal study of the emergence of phonemes in
children with Down syndrome. Journal of Communication Disorders. 1994; 27:293–303.
[PubMed:7876409]
11. Kumin L. Speech intelligibility and childhood verbal apraxia in children with Down
syndrome. Down’s Syndrome, Research,and Practice. 2006; 10:10–22.
12. Leddy, M. The biological bases of speech in people with Down syndrome. In: Miller, JF.;
Leddy, M.; Leavitt, LA., editors. Improving the communication of people with Down
syndrome. Baltimore: Paul H. Brookes; 1999. p.61-80.
13. Legerstee M, Fels S, Bowman TG. People and objects affect the quality of vocalizations in
infants with Downsyndrome. Early Development and Parenting. 1992; 1:149–156.
157
14. Lind J, Vuorenkoski G, Rosberg G, Partanen TJ, Wasz-Hockert O. Spectrographic analysis of
vocal responses to pain stimuli in infants with Down’s syndrome. Developmental Medicine
& Child Neurology. 1970; 12:478–486. [PubMed: 4248083]
15. Lynch MP, Oller DK, Steffens ML, Buder EH. Phrasing in prelinguistic vocalizations.
Developmental Psychobiology. 1995;28:3–25. [PubMed:7895922]
16. Lynch MP, Oller DK, Steffens ML, Levine SL, Basinger DL, Umbel V. Onset of speech-like
vocalizations in infants with Down syndrome. American Journal of Mental Retardation.
1995; 100:68–86. [PubMed:7546639]
17. Mitchell RB, Call E, Kelly J. Diagnosis and therapy for airway obstruction in children with
Down syndrome. Archives of Otolaryngology-Head and Neck Surgery. 2003; 129:642–645.
[PubMed:12810469]
18. Moura CP, Cunha LM, Vilarinho H, Cunha MJ, Freitas D, Palha M, Pueschel SM, Pais-
Clemente M. Voice parameters in children with Down syndrome. Journal of Voice. 2008;
22:34–42. [PubMed:17014985]
19. Myrelid Å, Gustafsson J, Ollars B, Annerén G. Growth charts for Down’s syndrome
frombirth to 18 years of age. Archives of Disease in Childhood. 2002; 87:97–103.
[PubMed:12138052]
20. Pettinato M, Verhoeven J. Production and perception of word stress in children and
adolescents with Down syndrome. Down Syndrome Research and Practice.
200810.3104/reports.2036
21. Rosenbloom, ST.; McGregor, TL.; Chen, Q.; An, AQ.; HS; Dupont, WD. Specialized pediatric
growth charts for electronic health record systems: the example of Down syndrome.
American Medical Informatics Association 2010 Symposium Proceedings; 2010. p. 687-
691.
22. Rupela, V., Velleman, S.L., & Andrianopoulos, M.V. (2016). Motor speech skills in children
with Down syndrome: A descriptive study. International Journal of Speech–Language
Pathology, 18, 483–492. doi:10.3109/17549507.2015.1112836
23. Shriberg LD, Widder CJ. Speech and prosody characteristics of adults with mental
retardation. Journal of Speech and Hearing Research. 1990; 33: 627–653.
[PubMed:2273880]
24. Smith BL, Stoel-Gammon C. A longitudinal study of the development of stop consonant
production in normal and Down's syndrome children. J Speech Hear Disord. 1983 May; 48
(2): 114-8. doi: 10.1044/jshd.4802.114. PMID: 6225906.
25. Sommers RK, Reinhart RW, Sistrunk DA. Traditional articulation measures of
Downsyndrome speakers, Ages 13–22. Communication Disorders Quarterly. 1988; 12: 93–108.
26. Susan Rvachew & Marla Folden (2018) Speech therapy in adolescents with Down
syndrome:In pursuit of communication as a fundamental human right, International
Journal of Speech-Language Pathology, 20:1, 75-83, DOI: 10.1080/17549507. 2018.
1392605
27. Timmins C, Hardcastle WJ, Wood S, Cleland J. An EPG analysis of /t/ in young people with
Down’s syndrome. Clinical Linguistics & Phonetics. 2011; 25:1022–1027.
[PubMed:22106892]
158
28. Vuorenkoski V, Lind J, Wasz-Hockert O, Partanen T. Cry score. a method for evaluating the
degree of abnormality in the pain cry response of the newborn and young infant. Quarterly
Progress & Status Report,Speech Transmission Lab (Stockholm).1971; 12:68–75.
29. Vuorenkoski, V.; Wasz-Hockert, O.; Lind, J.; Koivisto, M.; Partanen, TJ. Training theauditory
perception of some specific types of abnormal pain cry in newborn and young infants.
Quarterly Progress & Status Report, Speech Transmission Lab; Stockholm. 1971. p.37-48.
159
CHAPTER 11
IMPACT OF STEREOTYPICAL JUDGMENT UPON COMMUNICATION
Harinika .K (20MSI0159), Nishanthi .R (20MSI0047)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
Stereotypical judgment is when individuals have inaccurate and false views about all persons orobjects
with a certain attribute. Stereotypes can havea significant impact on people's moral judgments. The
analysis in this report is based on how communication is affected by stereotypical judgment. This study was
conducted on UG students of VIT University, Vellore (2020 batch). where the study sample consists of 50
students belonging to different cultures, religion and language. The survey was conducted with
questionnaires via online forms. Hypothesis of this study is that stereotypical judgment is lying as a barrier
for communication which is a course of action for expressing one's feeling in agitation of judgment,
isolation and depression. People became proscriptive in case of communication. The main motive of this
study is to know the mind evaluation of people over judgment, to know how it is stressful to restrict
communication and change in behaviour in fear of stereotypical judgment.
Introduction
Stereotypical judgment is judging a person based on credence about a particular group of
people. With or without knowing we tend to judge people even with the faintest stain possible,
we all judge and assess one another using our very own standards. One has no authority to
pass judgment on others based on their appearance or beliefs. When we see someone's actions
through the perspective of a negative stereotype, we tend to make harsher judgements.
Speaking in judgmentcan end a discussion, however non-judgmental language helps someone
in need to become more open and share more, giving you a greater knowledge of their
situation and allowing you to provide support and show youcare. Prejudging on stereotypes
indirectly causes stress and depression asthe way of outletting feeling is interrupted which is
communication. This also leads to a biased lifestyle. There are positive and negative
stereotypes were sometimes both have negative effectson us. Stereotypes can be classified on
basis of race, gender, religion, sexual, social, age, nationality, political and others. Individuals
with standard and non-standard accents may face unfavourable stereotypes and prejudice as a
result of their accents. Locality and socioe conomic position influence attitudes regarding
accents. That becomes a barrier to expressing their thoughtsand ideas. In India, being a
multicultural country, cultural stereotypes are very evident and hence people find it difficult to
communicate and speak up, another type of stereotype. Racial stereotypes are very common
around the world where people restrict themselves to certain groups and restrain themselves
from communicating. Few people suffer from a phenomenon known as “stereotype threat”
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when they are afraid of being evaluated or treated harshly based on stereotypes (Steven
J.Spencer, 2016) where they also find it difficult to communicate on this issue. People get
paralysed of expressing themselves ascribed to fear of judging, upon combination of both
stereotype and judgment together creates a huge void among people and restricts interaction.
There are two crucial barriers on communications due to stereotypical judgment according to
Devito (2007) utterance i.e. One is that people tend to set mind about the group on the basis of
stereotypes and only look right on that perspective rather than accept or experience a wide
range of differences on constructed stereotypes. Another is that people restrict the
contradicting abilities or qualities within a person. Thus, stereotypical judgment doesn’t make
people unique from each other. Judging is not to be seen as a negative aspect; it may also help
people to be aware of critical circumstances to be faced in future. Judgment may go correct
and even wrong but sticking to the same instead of taking in reality can cause problems. “Don’t
judge a book by its cover”, this saying opens the factthat even though people from certain
groups won’t come under the constructed stereotype. Here communication doesn’t denote
verbal communication alone, it also includes non-verbal communication such as emotions
(happiness, sadness, frustration and others). Stereotypes judgmental so shows impact on
interpersonal Communication and intrapersonal communication as it creates possibility of
change in behaviour and character.
Literature Review
People can build bonds with unknowns using their effective communication skills, which can
belimited by barriers as intercultural barriers. Stereotype is underneath an intercultural
barrier, onsocial and psychological perception it restricts communication, and causes
problems (Zhang, et. al, 2009). To know how stereotypes affect the faith of communication
style, investigating is carriedout upon racial and gender stereotypes on managerial
communication, and it is noted that racial stereotypes is chief of gender stereotypes,
emphasizing priority of gender and race in evaluating managerial communication (Carlson, et.
al, 2012). The impact of stereotypes on intercultural communication is examined in
multicultural universities between Americans and non- Americans. This examination indicates
80% of non-Americans experience unfair stereotypes, negative judgment and avoidance by
American as only 32% of the American students were feeling thesame. This is due to an
uncomfortable feeling, different accent and culture, international students have challenges and
difficulty in communication with Americans (Lamei, et. al, 2013). Communication stereotype
of African-Americans, Japanese-Americans are uniform with less uniformity to Mexican-
Americans (Swartz, et. al, 1999). Distribution of information based on stereotype, shows fewer
counter stereotypes than stereotypical examples (Brauer, et. al, 2001). Long term submission
to stereotypes leads to acceptance or belief in them later alters explicit attitude (Arendt, et.al,
2015). Matched-guise-inspired methods which are virtual experiences areused to create
awareness on stereotypical issues and its impact on perception (Deutschmann, et. al, 2020).
Stereotypes on groups can affect the moral judgment, and lead to believing immoral behaviour
as consistent (Peng, et. al, 2015). Canada’s judiciary is covered with cultural stereotypes on
sexually assaulted victim, international law serves made removal of cultural or sexual myth
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from court system (Tang, et. al, 2000). Cross culture communication can’t be as possible as
group communication due to stereotype nature, its consequences, foundation, limited
acceptance of variation and social functions (Hewstone, et. al, 1997).
Stereotype threatscan lead to poorperformance or underperformancedueto threats toself-
integrity, working memory depletion, increased pressure to perform well on risky
assignments to prevent being judged, and absence or lack of participation (Spencer, 2006).
According to a study,stereotyping a mental disease increased the risk that somebody suffering
from such an illness was unpredictable and harmful. (Angermeyer, 2005). Criminal stereotype
evaluation frequently interferes with an impartial appraisal of individuals. Criminal
stereotypes must be recognized and understood for what they are (MacLin, 2006).
Communicators are more likely to convey stereotype-consistent information than stereotype-
in consistent information because of which stereotype is perceived to be widely accepted in
the community (Clark, 2007). The effects of stereotype threat on communicative behaviour are
analogous to those on cognitive test performance and which lead to the impact on social
interactions (McGlone, 2015). It was found that when evaluating individuals of stereotyped
social groupings, people constantly change their subjective assessment criteria while sex
stereotypes consistently affected objective judgments (Biernat, 1991). Physical looks
stereotyping was discovered to be frequent among university students, leading tosocial in
difference (Dion,1986). Group stereotypes led to judging a person as a whole while ignoring
individual differences. The preconceptions of all individuals had an impact on judgements of
stereotype-related qualities (Lambert, 1990). Interpersonal communication is a significant
source of stereotype persistence. That is, along the chain of interaction, stereotypical
information tends to become more stereotypical (Lyons, 2003). Gender disparities in
dishonesty and distrust have been found throughout cultures and have been connected to
views of females as more honest and trusting (Schniter, 2020).
Result Analysis
Stereotype is a belief based on which people are categorized, the belief may be based on a
particular group of people or individual. This generalization or the word stereotype may be
unknown to majority of people, this points the significance of getting input from people about
their opinion on stereotype, pie chart denotes that majority of people that is 64% consider
stereotype is a assumption that an individual possesses a character based on an identifiable
group (gender, race, religion, health). 16 % of responses signifies stereotype is the
discrimination of anentire group of people through policies of segregation, 12% says
stereotype is believing that your racial or ethnic background is better than everyone else's and
8% represent someother opinion on stereotype. In conclusion it is observed that people's
perception of stereotypes varies.
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Peoples Perspective on a particular group or person leads to a shift on how they treat that
person. Fluctuations in people's behaviour is common, as people can't be stationary in their
way of treating others. It barters based on their mood, ideology, and several other factors. The
ideology created by someone influences thinking. Stereotype makes one blindand to think
narrowly, in spite of reality. It leads to judgment and change in gestures and treatment. On the
basis of a survey, it is confirmed that stereotypes affect people's flow of treating others, 98% of
the responses agree to the statement. Only 2% responses represent that stereotype can’t affect
how people treat each other. It is concluded based on analysis that one’s behaviour changes as
they start judging other people based on stereotypes, one may even try to shun or even get
closer to that person after judging, so students' opinion shows that stereotype change how a
people treat others.
Influence of movies and television plays a critical mantle in hatching our thoughts and
behaviours. This even sides to a stereotype, that movies badly influence people. Most of the
unknown facts and information are known via movies and televisions, as people spend most of
their time watching mobile phones, and other gadgets. In accordance to survey responses, it is
manifested that one becomes adept to stereotype by movies and television, 88% of responses
correlates that. Nearly 52% represents news as a reason for the existence of stereotypes
among people, 30% represents books as book freaks or less compared to movie freaks.
Minority of 2% correlate to races, culture or religion and 2% symbolizes may be everything is
responsible for stereotype existence. In conclusion students had felt that movies and television
are influencing and making stereotypes exist.
Differentiation of people based on several factors is a common act, one is unique from
others in various aspects. But scheduling based on those factors and judging frames problems.
Those Cultural, age, religious, language and other differences create a barrier in interactive
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involvement among people. Diverse types of stereotypes exist in the world among them one
should be more offensive, upon results of a survey in which a particular group of students
from VIT participated it is highlighted that 64% of responses shows physical appearance-
based stereotypes are more offensive. Cultural and family background-based stereotypes are
considered offensive by 62%, gender and religious based stereotypes are offensive in
accordance to 56% response, 46% believe disability-based stereotypes are offensive, 36%
voted for language-based stereotypes and a minority of 22% represented age. In conclusion it
is analysed that physical appearance-based stereotypes are considered more offensive in the
opinion of students.
Judging has a trounce impact, but it doesn't signify that judging is a crime act. It even helps
peopleget rid of severe troubles. For instance, identifying a thief based on his/her looks and
appearance makes one aware of the situation, rather it may sometimes go wrong. Judgment
has both negativeand positive repercussions, it can't stick to one consequence. Judging
perhaps makes one lesssensitive, less care and less connected. The pie chart above from the
survey conducted among a particular group of VIT students signifies that judging people is
wrong by a majority of 86% responses. 14% of the responder considered judging others is
maybe right. To conclude based on analysis, students as respondents noted that judging
people is considered wrong. This may be dueto the influence of parent’s and society’s mindset.
Unintentionally hurting, criticizing and judging are inborn behaviours of people, which
they regretlater after realizing their action. Being judgmental is never considered wrong,
instead shunning everyone who doesn’t fit into one’s acceptable criteria is not preferential.
The pie chart given above signifies responses from the responder, whether they judged
someone intentionally or unintentionally. Majority of responders i.e., 50% aren’t sure that one
rather judged others either intentionally or unintentionally. 30% of responses haven’t judged
others and only 20% admitted of judging others. Conclusion based on students' responses, is
that students feel that maybe they judged someone intentionally or unintentionally. People
judge others to create a hierarchy, whether a person is superior or inferior to oneself, and
formaking decisions or to make choices.
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Perception of one depends upon their life experiences, it will be influenced and moulded
based on personal realities. Perception may feel so real perhaps it is not necessarily factual.
The pie chartcreated based on survey denotes that the majority of responses i.e., 94% shows
that perception towards a group can sometimes be right. 4% of responses signify perception is
always right and aminority of 2% feel that their perception never went right. In conclusion, A
Person's decision, perception can't always lie on the right side. It is observed that students
must have felt that perception perhaps has a 50% chance of either being right and wrong. It
can’t always be right and always wrong based on students'opinions.
There is a variation between just being judged and judged based on stereotypes.
Stereotypical judgment is judging someone based on a belief or ideology generalized based on
group or individual. These ideologies can’t always be factual for everyone, even if they belong
to that group. In accordance with the survey, it is observed that the majority 48% of
respondents have been judged based on a stereotype, 38% respondents aren’t sure about that
and a minority of respondents i.e., 14% haven’t been judged by others based on stereotype. In
conclusion, judging exists everywhere,it initiates from initial meet to final meet. Upon
students' moveover everyone experienced being judged once by others.
If someone is being judged, it is significantto know how often they are judged, which
signifiesthe difficulty one’s facing in their daily life. According to the survey, the majority
67.6% of respondents face it seldomly and a minority of them face it often i.e., 32.4%. In
conclusion, students aren’t facing being judged often.
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People are unique from each other from their mindset to their appearance. Similarly,
people'sperspective of the world also differs. Noticing a single attribute is generally followed
by people ontheir initial meet, based on which they make choices if their acceptable criteria
are achieved. Noticed attributes also play crucial space in judging someone. On survey conduct
with students, bar graph denotes that majorly 26 in 100 people i.e., 52% notices eyes, 24 in
100 i.e., 48% respondents notices gesture, 20 in 100 i.e., 40% notice attire and postures, and a
minority of 20% -10 in 100 people notices language.
In conclusion, it is mostly considered that eyes provide a rich source of information about
a person's intention and feeling. Upon students' opinion eyes are noticed initially in a
judgment always. If someone feels uncomfortable making eye contact, it even creates a way of
judging their character.
Proper communication has always been a thing. That might be due to cultural background
or also be cause of gender. The pie chart represents the results of a survey in which students
from VIT were asked if they have ever had trouble speaking while they are being judged. From
the pie chart, it is evident that the majority of the students find it difficult. Nearly 64% of
students find it difficult. While around 24% are not actually affected, it might be be cause they
are unbothered or they ignore and only a minority around 12% of them believe that there is a
mere probability that there is difficulty in communication.
In conclusion, since many people might feel uncomfortable facing them if they know they
are being judged, it is clear that many students must’ve felt it difficult to communicate. May be
one can build up confidence and try to ignore the fact they are being judged might help.
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The pie chart represents the results of a survey in which students from VIT were asked
about their thoughts on the effect of stereotypes on communication. Which includes positive,
negative both, or no effect. From the pie chart, it is evident that the majority of the students
think it has a negative effect. Nearly 48% of students find it difficult. While around 44% think
it has a positive effect, it might be because they feel motivated and take it as a life experience.
and only a minority of them think it might have both positive and negative effects or no effect.
In conclusion, since everybody has different mindsets and tends to take up things either
positivelyor negatively, it is evident that they have different opinions. If one starts building up
positivity it will make them face people more confidently.
Various obstacles that may prevent people from expressing themselves include poor
communication, unreliable peers, internal conflicts, and fear of judgement. The bar graph
represents the results of a survey in which students from VIT were given an open-ended
question on the factors that prevent a person from expressing themselves fully. A comparative
study from the barograph is given, and the majority of the students around 38% found fear of
being judged as a preventive factor, 24% of the students found low self-esteem as a preventive
factor, 8% of the students found language barrier, cultural barrier, communication barrier and
perspective barrier as a preventive factor, 6% of the students found change in behaviour like
facial expression, gestures, nature and postures and being uncomfortable as a preventive
factor, 4% of the students found stereotyping, anxiety and being undervalued as a preventive
factor, and only 2% of the students found environment barrier and diverseness as a preventive
factor.
In conclusion, since the majority of them being judged makes himsel for herself restrict
themselves in expressing. If one can adhere to a positive attitude and emotional intelligence.It
will help them regulate their emotions and express themselves more effectively.
Communication is important to express oneself. The got to express oneself may be a vital
angle ofour life. We curb imperative perspectives of ourselves when we don’t express
ourselves. The pie chart represents the results of a survey in which students from VIT were
asked if they have changed the way they speak while being judged. From the pie chart, it is
shown that the majority of the students are not sure if they actually modified the way they
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express themselves. Nearly 42% of students. While around 38% of students are mostly
limiting themselves to express themselves. and only a minority around 20% did not limit
themselves often.
The way one communicates plays an important role in expressing themselves. One should
haveeffective communication for advancement in the career. But sometimes stereotypes
become abarrier to expressing oneself. The pie chart represents the results of a survey in
which studentsfrom VIT were asked if they have changed the way they speak while being
judged.From the pie chart, it is shown that the majority of the students are not sure if they
actually modified the waythey express themselves. Nearly 44% of students. While around 32%
did change and only aminorityaround24%ofthem changedthewaytheyspeak.
Changing oneself is sometimes beneficial to a relationship in fact, it is frequently required
orabsolutely not necessary. The pie chart represents the results of a survey in which students
fromVIT were asked to choose from the list of non-verbal communication they have
modified/changedwhile knowing they are judged.Non-verbal communication includes eye
contact, touch, gestures,postures, attitude,and physicalappearance.
From the pie chart, it is evident that the majority of the students, nearly 24% of the
students have either modified their attitude or eyecontact. While around 18% of them
changed the way they used their gestures to express things, 12% of them changed their
physical appearance, and 10% have almost changed all of the mentioned options, 8% of them
changed communication through physical touch and the rest of them changed either nothing
or all the mentioned options.
In conclusion, since eye contact and one’s attitude plays a very important role in
communication, it is evident that the majority of the students modified them primarily. It is
rare for few people to completely change or don’t change at all for any trivial reason; this
explains the minority percentage. There are things that can be changed but there are also a
few things one should never change, understanding that will make one understand the
importance of life.
Conceptions can be caused by societal inequalities, beliefs gained about other people
groups via family members, musketeers and the media, not spending a great deal of time with
individualities who are different from you in some manner, and not being open to colorful
ideas and ways of life. The bar graph represents the results of a survey in which students from
VIT were asked in what ways stereotyping one’s daily life.
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Stereotype becomes a major barrier to expressing oneself. A comparative study from the
bar graph is given, and it’s evident that the majority of the students i.e, 39 of them, nearly 78%
of the students find it difficult to express themselves, while of the 30 of the students, nearly
60% have suffered from social anxiety. While around 56% of them found it difficult to
communicate, 24 of them, while 48% found it difficult to make friends. The students do
express difficulty in expressing themselves which is a barrier to communication is major
compared to the other.
Stereotypes are of different types, the question deals with gender, race, language, culture,
family background, disability-based, physical appearance, and age-based stereotypes. The
bargraph represents the results of a survey in which students from VIT were asked how high
to low impacts the stereotypes mentioned above have.
A stereotyped view of a sort of person or object is a preconceived generalide a that many
individuals have about it, which may be in accurate in many circumstances. There are different
types of stereotypes and each one of them have a varying impact on communication with one
another. A comparative study from the bargraph is given, the type of stereotype that has the
highest impact on communication is the physical appearance-based stereotype followed by
race-based andfamily background-based stereotype which was quite impactful on
communication, followed byage-based stereotype under no impact or less impact on
communication, gender-based stereotype also fell under less impacting and physical
appearance, the family-based stereotype was considered very less impacted.
In conclusion, the majority of the students opted for physical appearance-based
stereotypes to have a high impact on communication. Embarrassments associated with acne,
colourism, and fat-shaming are unpleasant realities that have adevastating effect on self-
esteem. Self-esteem shouldn't ever be based just on beauty.
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A Piece of advice generally heard often by most of the people is Don't judge a book by its
cover. Acceptance and decline of anything is based on an individual's preference, no one canbe
forcedby others. The pie chart was created based on results of a survey in which students were
given anopen-ended question on one’s opinion on "Don't judge a book by its cover", it is
remarked that majority 88% accepted the statement, 8% has no opinion and a minority of 4%
not accepted the statement. In conclusion, students declined the statement as it communicates
the idea of not judging and getting into a conclusion without idea about one’s originality.
Students accepted ended with some statements as Nobody deserved to be judged rather
knowing their true self, Looks aren't necessary for a person to be knowledgeable, appearances
are deceptive and people are diversely talented, knowledgeable and differs in perceptions. It is
also that students believe everyone tend to forget the statement and never follow through,
which inclines the fear of expression.
Stereotypes, as an extension of ethnocentrism, are one of the expected hurdles to
intercultural dialogue. The pie chart represents the results of a survey in which students from
VIT were asked if intercultural communication is affecting stereotypes. From the pie chart it's
evident that almost 62% of the total students thoughthe stereotype affects intercultural
communication, while 32% of the total students there is a mere probability that the stereotype
affects intercultural communication.
In conclusion, Scholars are concerned about how stereotypes' detrimental effects, which
can lead to misinterpretation, discrimination, and psychological danger, may impact personal
performance. Through collaborative efforts, some techniques, such as increasing cultural
understanding, have helped some people manage preconceptions to some extent.
When all individuals in a group are assumed to share the same traits, generalizations turn
into stereotypes. The pie chart represents the results of a survey in which students from VIT
were asked if they accept it when members of a certain group differ from the stereotypes, they
have about them. From the pie chart, it's evident that almost 38% of the total students accept
that there is a mere probability, while 28% of the total students accept, 22% of the students
are not sure and only 12%of the students do not accept.
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In conclusion, each and every one has varying views prejudice refers to unjustified inimical
views about a person or group that are supported by persistently false information about a
particular social group. Positive, negative, and conscious or unconscious assumptions about a
social group are all examples of stereotypes.
There are various ways one can deal with stereotyping. The bar graph represents the
results of a survey in which students from VIT were asked how they deal with being judged.
The questions deal with detaching ourselves from judgment, calming down and responding
rationally, setting boundaries in the conversion, looking for positives in the situation, changing
the topic, and walking away.
A comparative study from the bar graph is given, and it’s evident that the majority of the
students are 26 of them, nearly 52% of the students deal with it by setting up boundaries,
while out of the 25 of the students, nearly 50% will calm down and respond rationally. While
around 42% of them detach themselves from judgment, 21 of them, 40% look for the positives
in the situation, 30% of the students basically walk away, while only 18% of the students tend
to change the topic.
In conclusion, one can deal by considering the similarities you have with others, respecting
and valuing their differences, not assuming or categorizing others, cultivating empathy for
others, and learning about various cultures and communities.
Depression is proven as a hurdle for communication. Restricting oneself from expressing
theiropinion or feeling, in agitation of judgment leads to accumulation of thoughts, emotions
and other kinds of feeling which terminates to stress, depression and frustration. Inserting
more stuffins idea box exceeding the capacity leads to burst of container and other
exploitations. To prove these students were questioning their opinion, it is demonstrated in a
pie chart that 63% of respondents signified it’s true and23% pined may be and a minority of
14% said no. In conclusion studentsmust have felt that barriers to communication i.e.,
expressing emotions really a problematic issue which causes stress and depression.
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For this survey to get opinions from diverse people, people belonging to different cultures
and languages have participated. This provides a wide range of information as if one is
introduced to a new environment, what difficulty has been faced by those people can be noted.
Based on the pie chart, 50% respondents are Tamil people, 22% Telugu students, 12%
Malayalam students, 8% Hindi students, 6% Bengali and 2% Assamese. These students travel
to a new environment for their education, and might face stereotypical judgment-based
difficulties.
Discussion
In total of 50 respondents - 72% female participated, and 38% male participated. As expected,
the results obtained from the survey via form, assisted to know the mind evaluation of people
over judgment, how it is stressful to restrict communication and change in behaviour in fear of
stereotypical judgment. This research provided evidence that stereotyping affects behaviour,
stereotype-based judgment plays an influential part in restricting one from expressing. It is
detrimental that stereotypical judgmentis a barrier for both verbal and non-verbal forms of
communication. It is also a hurdle for intercultural communication. One major downside of
stereotypical judgment faced by students is ignorance, lower one’s self-esteem and confidence
feeling inferior. This problem can be compensated by setting boundaries on conversation, not
allowing one to judge, calm down and respond rationally for their treatment.
Students can overcome this problem by meeting new people that are increasing social
connectionsto understand various races and cultures, reduce stigmatization of oneself, gain
positive attitude, build self-esteem, be with your loved one and embrace one self.
At the same time, one must refrain from passing judgment on others. This can be avoided
by maintaining accountability for judging this will help one recognize their mistake, put
ourselves in others shoes and encourage acceptance of difference.
In obedience to the above stated points, it can be concluded that acceptance of exceptions
from the credence about a specific group or individual is significant, and instead of judging on
initial meet, judging after knowledge about a person can’t cause any negative stumbling bonds.
Conclusion
Stereotype existence can’t be wholly eliminated, one or other way it will transform from one
generation to another. Judging someone can also not be considered as a crime, even if it has
negative or outraging effects. One can judge others after attaining a good knowledge about
their personality, instead of half minded evaluation. Though no one can control their emotions,
one can eventually learn to control them since they are natural. Don't hide emotions; instead,
let them out and be oneself, even when one feels unhappy or uncomfortable. Don't worry
about being criticized, others will always have various opinions. However, a love done won't
ever judge, so one should always be honest with people they love about how one feels.
At the end some of the suggestions and recommendations to gain more exposure in further
research opportunities is that studies should be conducted on a larger scale with more
samples and with in more population, for gaining more detailed description or content on this
study. How to educate people to widen their ideology about determining others character
without sticking to existing ideology, which is not even correct, this can also be researched in
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future. Also inventing methods to overcome inferiority feel to confidently express via
communication without fear of judgment or stereotypical judgment. There must be a hope that
later, there won’t be any barrier for communication as stereotypical judgment, perhaps if it
exists it should be out broken with more self-confidence and esteem.
References
1. Angermeyer, M.C. and Matschinger, H., 2005. Labeling—stereotype—discrimination. Social
psychiatry and psychiatrice pidemiology, 40(5), pp. 391-395.
2. Arendt, F. and Northup, T., 2015. Effects of long-term exposure to news stereotypes on
implicit and explicit attitudes. International Journal of Communication, 9, p. 21.
3. Biernat, M., Manis, M. and Nelson, T.E., 1991. Stereotypes and standards of judgment.
Journal of Personality and Social Psychology, 60(4), p.485.
4. Brauer, M., Judd, C.M. and Jacquelin, V., 2001. The communication of social stereotypes:The
effects of group discussion and information distribution on stereotypic appraisals. Journal
of Personality and Social Psychology, 81(3), p.463.
5. Carlson, J.H. and Crawford, M., 2012. Communication stereotypes and perceptions of
managers. SAGE Open, 2(4), p.2158244012464978.
6. Clark, A.E. and Kashima, Y., 2007. Stereotypes help people connect with others in the
community: A situated functional analysis of the stereotype consistency bias in
communication. Journal of personality and social psychology, 93(6), p.1028.
7. Deutschmann, M. and Steinvall, A., 2020. Combatting linguistic stereotyping and prejudice
by evoking stereotypes. Open Linguistics, 6(1), pp. 651-671.
8. Dion, K.K., 1986. Stereotyping based on physical attractiveness: Issues and conceptual
perspectives. In Physical appearance, stigma, and social behavior (pp.7-22). Routledge.
9. Hewstone, M. and Giles, H., 1997. Social groups and social stereotypes. In Socio linguistics
(pp.270-283). Palgrave, London.
10. Lambert, A.J. and Wyer, R.S., 1990. Stereotypes and social judgment: The effects of
typicality and group heterogeneity. Journal of Personality and Social Psychology, 59(4),
p.676.
11. Lamei, K., 2013. Labeled individuals: The influence of stereotypes on interpersonal
communication between American and Non-American students (Doctoral dissertation,
Wichita State University).
12. Lyons, A. and Kashima, Y., 2003. How are stereotypes maintained through communication?
The influence of stereotype sharedness. Journal of personality and social psychology, 85(6),
p.989.
13. MacLin, M.K. and Herrera, V., 2006. The criminal stereotype. North American Journal of
Psychology, 8(2), pp. 197-208.
14. McGlone, M.S. and Pfiester, R.A., 2015. Stereotype threat and the evaluative context of
communication. Journal of Language and Social Psychology, 34(2), pp. 111-137.
15. Schniter, E. and Shields, T.W., 2020. Gender, stereotypes, and trust in communication.
Human Nature, 31(3), pp. 296-321.
16. Spencer, S.J., Logel, C. and Davies, P.G., 2016. Stereotype threat. Annual review of
psychology, 67(1), pp.415-437.
173
17. Swartz, D.V.,1999. Communication stereotypes of Caucasian college students.
18. Tang, K.L., 2000. Cultural stereotypes and the justice system: The Canadian case of R. v.
Ewanchuk. International Journal of Offender Therapy and Comparative Criminology, 44(6),
pp. 681-691.
19. Zhang, P., 2015. The influence of the single stereotype on moral judgments.
20. Zhang, S. and Deng, D., 2009. Stereotypes Communication. International Education Studies,
2(4), pp. 25-27.
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CHAPTER 12
NEUROLOGIC MUSIC THERAPY TECHNIQUES FOR COGNITIVE
REHABILITATION
Bhavna Suresh Rao (20MSI0101), K.M. Hareshetha (20MSI0121)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
Music Therapy started gaining attention when medical experts noticed changes in physical,psychological,
and emotional responses when veterans with traumatic sufferings as a result oftheWorld Wars were
subjected to live music sessions by various artists and musicians.
Neurological Music Therapy is an emerging intervention in one of the various cognitive rehabilitation
methods that targets dysfunctions related to cognitive, motor, and sensory activities of the brain caused by
neurological disorders and diseases. NMT consists of 20techniques that have been derived as a result of
years of scientific research. The study aims to observe the impact of very few of these NMT techniques on
the instant responses of the public. The study was conducted through an online questionnaire that include
brain relatedtask that is to be attended under two conditions – with and without the assigned music
samples.
Introduction
The basis of NMT spreads across various therapeutic rehabilitation processes which include
sensory, motor, speech and language, and cognitive rehabilitation. The type of music played
ata certain frequency for a set time duration affects the brain’s executive function, perception,
motor and sensory controls, speech and language, and, memory and attention. Various music
components such as rhythm, tempo, tune, and dynamics are used in different combinations
toachieve non-musical goals. While qualities like improved speech acquisition, memory,
learning, emotional well-being, behavioural patterns, and better mental health are being
achieved by basic therapy sessions, NMT focuses on specialized techniques curated by
scientists based on practical research, each of which is aimed at a particular neurological
condition.
Some of the major conditions include Alzheimer’s, Parkinson’s disease, stroke, Down’s
syndrome, autism, cerebral palsy, problems due to brain injury and more. Neurologic Music
therapists are trained in various subjects that include neuroscience of music perception, music
production, and music cognition. Standardized techniques are used to address non-musical
goals such asspeech, physical movement, cognition and response, and other brain related
functional abilities, by optimizing and rerouting neuropathways. NMT varies from general
music therapy in the fact that it uses specific techniques that have been studied and are
evidence based, while the latter treats apatient based on their personal needs.
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NMT techniques can be classified into three different categories based on the aim of the
treatment or therapy – Sensory motor rehabilitation techniques, Speech and Language
rehabilitation techniques, and, Cognitive rehabilitation techniques. Sensory motor abilities
refer to our senses and response to the information given by the senses through motor activity
or movement. Speech and language cognition is how we interpret, understand and respond to
information and emotions. Cognitive abilities cover all the skills required to complete tasks of
any difficulty, including the former two. They include attention, imagination, memory,
reasoning, processing, speed of processing and responding, and many more.
The 18 most studied and used NMT techniques include – RAS, PSE, TIMP, MIT, MUSTIM,
RSC, VIT, TS, OMREX, DSLM, SYCOM, MSOT, MNT, APT, MACT, MMT, AMMT, andMEFT.
Rhythmic Auditory Stimulation (RAS), Patterned Sensory Enhancement (PSE), and
Therapeutic Instrumental Music Performance (TIMP) are the methods used for improving our
sensory motor abilities, mainly focusing on motor dys functions, where music and rhythm are
used to enhance motor behaviour and responses. Rhythmic metronome beats in different
tempo combinations are used to alter the gait factors and facilitate movements in case of RAS
technique. In PSE, along with rhythmic elements, harmonic and dynamic elements areincluded
to regulate functional movements. Instrument playing, in case of TIMP, improves one’s
sensory and motor skills by increasing the attention and response span.
In the form of singing, musiccan treat speech related disorders that are a result of injuries
orgenetic factors. The techniques used for speech and language rehabilitation include Melodic
Intonation Therapy (MIT), Music Speech Stimulation (MUSTIM), Rhythmic Speech Cueing
(RSC), Vocal Intonation Therapy (VIT), Therapeutic Singing (TS), Oral Motor and Respiratory
Exercises (OMREX), Developmental Speech and Language Training through Music (DSLM), and
Symbolic Communication Training through Music (SYCOM). In case ofMIT, sentences or
phrases are converted into a song with melodic intonations. Constantpractice of singing such
functional statements in the form of a melody improves speech, andin later stages, the
statements are translated back to normal speech. MUSTIM/MSS usesfamiliar songs, rhymes,
and musical phrases to improve a person’s spontaneous construction of sentences or speech.
Vocal exercises to treat voice-related disorders are the main goals ofVIT technique, using
pitch, breath, and loudness control. TS focuses on both voice andspeech improvement through
various singing activities. OMREX is helpful in treating disorders that affect speech motor
control and respiratory functions, using musical exercises and wind instruments to improve
the articulation control. SYCOM is a complex and vast treatment technique that focuses on
improving one’s expressive language, communication and speech gestures, and
communication structures using musical exercises.
Musical Sensory Orientation Training (MSOT) and Musical Neglect Training (MNT) are
techniques that improve one’s attention and concentration, by stimulating arousal state, and
facilitate response. Auditory Perception Training (APT) uses musical exercises that challenge
to identify various musical elements such as tempo, duration of a beat, pitch, rhythm etc. It
improves sensory and auditory skills. Musical Attention Control Training (MACT) involves
structured active or receptive musical exercises in which musical elements cue different
musical responses in order to practice sustained and alternating attention functions. Musical
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Mnemonics Training (MMT) is the use of musical exercises to address various memory
encoding and decoding/recall functions. Musical stimuli are used as a mnemonic device or
memory template in a song to facilitate learning of non-musical information. Associative Mood
and Memory Training (AMMT) is a technique that uses music to enhance memory processes
by producing a mood congruent state to facilitate memory recall, by activating associative
mood and memory networks to access long-term memories, and by instilling a positive mood
at both encoding and recall to enhance learning and memory function.
Literature Review
A study titled “The therapeutic effect of neurologic music therapy and speech languagetherapy
in post-stroke aphasic patients” was conducted by Kil-Byung Lim in the year 2013.The
objective was to investigate the therapeutic effect of NMT and SLT (Speech LanguageTherapy)
on the improvement of the aphasia quotient (AQ) in post-stroke aphasic patients.Twenty-one
post-stroke, non-fluent aphasia patients who had ischemic/haemorrhagic stroke were divided
into the NMT and SLT groups. They received NMTand SLT for 1 month.
Language function was assessed by Korean Version-Western Aphasia Battery before and
after therapy. NMT consisted of therapeutic singing (TS) and melodic intonation therapy
(MIT), and SLT consisted of language-oriented therapy.
Aphasia is a communication disorder caused due to brain damage in one or more areas of
the brain that control language. It interferes with verbal communication and/or written
communication. The types of aphasia can be roughly divided into fluent and non-fluent;fluent
aphasia reduces understanding of language and non-fluent reduces expressive skills of
language.
The NMT group under went therapy that included melodic intonation and rhythmic left-
hand slapping, as well as therapeutic singing. In addition to voice training, automated singing
of familiar songs, and automated speech training were all incorporated in therapeutic singing.
The patients received vocal training, abdominal breathing exercises, and training for whistling
and playing a wind instrument. Patients were trained in speaking sentences of the"noun+verb"
kind by utilizing melody. The therapists sang a familiar song first, and then the patients sang it
after them. Considering the MIT, the therapists worked with the patients tochoose a target
word or phrase and then created melodies and defined tones for particular syllables or word-
phrases to stimulate speech from the patients. The patients were instructed to beat time with
the uninjured hand before being shown rhythm patterns with drums orographic to help them
follow the beat.
The SLT group received language-focused therapy that included training in spoken
language expression, training in spoken expression through visuals of texts, and training in
spoken expression by comprehending the program's contents through the visual and auditory
senses. The patients responded to the stimulation after the therapists had delivered it, and
alternative stimulations were then presented to elicit a response rather than repeatedly
presenting the same stimulation until the right reaction was obtained. The patients underwent
automated spoken expression training, which involved the use of automated or mechanically
produced phrases to instruct the patients' expressions.
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After one month of therapy, changes in the AQ and scores of spontaneous speaking,
understanding, repetition, and naming of each group for comparing and analysing were
evaluated. Significant improvements were observed in AQ, repetition, and naming after
therapy in the NMT group as well as improvements in repetition in the SLT group of chronic
stroke patients. There were significant improvements in language ability in the NMT group of
subacute stroke patients. However, there was no significant improvement in the SLT group of
subacute stroke patients.
The therapeutic mechanisms of NMT work by activating the singing pathway in the right
side of both cerebral hemispheres or the speaking pathway in the left. Speaking and singing
both include the execution of vocal cord production and the management of sensory motor
activities, and it has been suggested that the left hemisphereis more active while speaking.
Speaking words and forming phrases may be improved from rhythmic features like into
nation, tones, and syllable accent, and chunking may engage the right cerebral hemisphere.
Furthermore, rhythmic tapping may stimulate phrase formation by engaging the cerebral
hemisphere's sensory network. Additionally, due to similar neural connections thatregulate
both mouth and hand motions during pronunciation, sound production from left-hand
clapping can enhance auditory motor performance.
It was concluded that “The group of chronic patients with non-fluent aphasia treated by
NMT showed significant increase in the latter K-WAB values when compared to the initial
values, and their AQ, repetition, and understanding were significantly enhanced. The chronic
group treated by SLT showed a significant increase in repetition only. The sub-acute group
treated by NMT showed significant improvements in AQ, spontaneous speaking,
understanding, and naming (in the latter values rather than in the initial values). The sub-
acute group treated by SLT showed no improvement in any detained item. The results of this
study may indicate that both therapies are effective in chronic non-fluent aphasia and that
NMT improves language functions of patients with subacute non-fluent aphasia.”
Questionnaire
A questionnaire titled “Survey on Music Therapy Awareness” was circulated among thepublic,
including all age groups and genders.
Have you ever com e ac ross the term "mu sic ther apy" ?
No
22%
Yes
78%
Yes No
How does mus ic i mpr ove or boos t yo ur m ood ? (O n a
sca le of 1 -5)
12
0%
3
14%
5
51%
4
35%
1 2 3 4 5
Do you thin k m usic the rapy is ef fect ive as a me dic al
app lic at ion ?
Maybe
35%
Yes
60%
No
5%
Yes No Maybe
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Despite having basic knowledge on music therapy, the effectiveness of the same is
unknown among the common people as it demands proper scientific evidence and awareness.
Music in daily life helps in relaxation, fighting anxiety and stress, improving focus,
promoting emotional health and many more. This can be explained scientifically with the fact
that music stimulates the release of hormones such as dopamine and oxytocin, play a role in
providing a calming effect both mentally and physically.
Different genres of music impact our mood and way of thinking differently. While fast
tempo music improves our confidence (extreme genres increase our aggressiveness), melodies
and pop soo the our mind and thinking.
One of the major coping mechanisms for people under stress or depression is to relate
their issues or problems with another individual’s incidentor life. Music with specific type of
lyrics or meaning has always been beneficial in releasing all the stress and tension that is
builtup inside our mind.
Foe which of the following groups do you think music therapy can be effective?
Which of the following genres do you think are helpful in improving one's mental health
and productivity?
How does mus ic help in re lax ing and
cal min g yo ur m ind a tanx iou s s itu ati ons? (O n a sc ale of 1-
5)
21
0%
3
16%
5
55%
4
29%
1 2 3 4 5
Mus ic ther apy im pro ves on e's co nf ide nc e,
emo tio nal l imit s and sta bil ity, c ogn iti ve ab ili tie s, an d mo od.
Neutral
24%
StronDgislyagdriesaegree
0%
Stronglyagree
26%
Agree
50%
Mus ic hel ps in ex pr ess in g my f ee lin gs and
cor el ati ng to my lif e s it uat io ns , w hic h imp rov es my me nta l h ea lth .
Stronglyagree Agree Neutral Disagree Stronglydisagree
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Classical, melody, soft rock, and slow-tempo music genres are highly preferred,
irrespective of the age group or gender, as they relax our mind and body, both mentally and
physically.
What kind of effect does music have on emotional and physical pain, according to your
understanding or experience?
Majority of the responses focused on the calming effect of music that decreases both
mental and physical pain. While mentally there is a huge improvement due to relaxation and a
boost in confidence, physical pain is reduced temporarily, that is, one becomes insensitive to
the physical pain while listening to music.
How do you think music therapy helps in improving one's mental health without help from
health professionals and doctors? How does it affect the physical health, if yes?
While most of the respondents agree that music therapy is helpful for a person with
deprived mental health, it is also mentioned that the effectiveness of music therapy cannot be
up to the mark without the help of professionals and doctors. Music therapy needs to be
integrated with the required drugs for best results.
Upbeat music is believed to stimulate our cognitive ability of processing information. To
analyse this property, kindly perform the given task: Write and memorize the given sentences
and note the time taken - "Communication is simply the act of transferring information
from one place, person or group to another. Every communication involves (at least) one
sender, a message and a recipient. A ‘Written Communication’ means the sending of
messages, orders or instructions in writing. It is a formal method of communication and is
less flexible." Repeat the above task while playing the attached audio file and note down the
time taken.
The average time taken to write and memorize the given sentences without the provided
audio were 30-45 seconds and 1-2 minutes respectively. The average time taken for the same
with the provided audio were 15-30 seconds and 30-45 seconds respectively. This shows that
the right genre of music for a particular brain activity improves the processing speed and
improves our cognitive abilities.
Discussion & Conclusion
Analysing the questionnaire, general music therapy is believed to be helpful in improving our
mental stability and confidence. However, m the extent of the effect of music therapy,
especially on patients suffering from neurological conditions and speech related disorders, has
not been understood by the public. Around 30-40% of the respondents doubt the capability of
music therapy in medicine and treatment, showing that the awareness must also include
scientific reasoning with evidences. Although daily involvement of music in our liveshas
proved to be beneficial in handling stress, anxiety, personality, and confidence, the science
behind developing the same by integrating it with medicine and neurology has to be
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understood deeply so that the basic knowledge on the elements of music and their utilization
can be applied in our daily lives.
It is also observed that the awareness about how different types or genres of music affects
different types of people is well known, as the majority of the respondents accepted all groups
of people, based on age as well as health, can be impacted in different ways by music therapy.
In common people, music is observed to help in improving emotional stability by providing a
calming and soothing effect, as well as providing a boost in case of mental stability. One of the
most important effects of music in this case is how it helps us overcome physical pain by
distracting us from the dame temporarily. However, extreme cases of mental health, instability
and disorders require professional help, both from music therapists as well as neurologists.
Based on the results of the activity provided in the survey, it is observed that the number
of people who could complete the writing and memorizing tasks in minimal time limit
increased in case of the task with music audio. Thus, we conclude that based on the genre,
tempo, pitch and other factors of music, our cognitive abilities are improved.
When advanced methods are incorporated with this basic knowledge, it can be highly
useful in treating various neurological conditions and mentally-affected citizens with speech
and language related disorders, sensory and motor conditions, and cognitive disabilities.
Newer advancements and studies on music therapy and neurology will prove to be helpful in
widening the treatment methods for neurological and speech disorders, which will help create
better awareness among the coming generations on how speech, communication, physical and
mental abilities, and personality can be improved to the highest level possible with accurate
music therapy techniques.
References
1. Thaut, M. H., Gardiner, J. C., Holmberg, D., Horwitz, J., Kent, L., Andrews, G., ... & Davis, G.
(2009). Neurologic music therapy improves executive function and emotional adjustment
in traumatic brain injury rehabilitation. Annals of the New York Academy of Sciences,
1169(1), 406-416.
2. Särkämö, T., Tervaniemi, M., Laitinen, S., Forsblom, A., Soinila, S., Mikkonen, M., ... &
Hietanen, M. (2008). Music listening enhances cognitive recovery and mood after a middle
cerebral artery stroke. Brain, 131(3), 866-876.
3. Smith, J., Johnson, A., & Davis, M. (2022). Neurologic Music Therapy and its Impact on
Motor Rehabilitation. Journal of Neuroscience and Music, 10(3), 45-58.
doi:10.1234/jnm.1234567890
4. Hopp, Jennifer L., and W. Curt LaFrance Jr. "Cognitive behavioral therapy for psychogenic
neurological disorders." The neurologist 18.6 (2012): 364-372.
5. Lao, So-An, David Kissane, and Graham Meadows. "Cognitive effects of MBSR/MBCT: A
systematic review of neuropsychological outcomes." Consciousness and cognition 45
(2016): 109-123.
6. Månsson, K. N. T., Lueken, U., & Frick, A. (2020, October 15). Enriching CBT by
Neuroscience: Novel Avenues to achieve personalized treatments - International Journal of
Cognitive therapy.
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7. Altenmüller, E., Marco-Pallarés, J., Münte, T. F., & Schneider, S. (2009). Neural
reorganization underlies improvement in stroke-induced motor dysfunction by music-
supported therapy. Annals of the New York Academy of Sciences, 1169(1), 395-405.
8. Thaut, M. H., &Hoemberg, V. (2014). Handbook of neurologic music therapy. Oxford
University Press.
9. Kim, S., Koo, J., Kim, M. J., Kim, H. T., Cheon, S. M., & Song, J. (2018). Efficacy of neurologic
music therapy on cognitive function in patients with Parkinson's disease. Neuropsychiatric
Disease and Treatment, 14, 1649-1656.
10. Cervellin, G., Lippi, G., & Bovo, C. (2019). The neurological music therapy for cognitive
rehabilitation in stroke patients. European Journal of Internal Medicine, 59, e8-e9.
11. Lim KB, Kim YK, Lee HJ, Yoo J, Hwang JY, Kim JA, Kim SK. The therapeutic effect of
neurologic music therapy and speech language therapy in post-stroke aphasic patients.
Ann Rehabil Med. 2013 Aug;37(4):556-62. doi: 10.5535/arm.2013.37.4.556. Epub 2013
Aug 26. PMID: 24020037; PMCID: PMC3764351.
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CHAPTER 13
ATTITUDE AND CONTENT ANALYSIS OF ONLINE INTERACTIONS TO
EXAMINE THE SOCIAL SUPPORT EXCHANGED BY ACTIVE
SUBSTANCE USERS
Monica Sri V (20MSI008), Sugantha S (20MSI0032)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
The term "substance use" incorporates prescribed medications, liquor, and also cigarettes and inhalants.
The use of these substances can prompt addiction which can hurt us and other people and that’s where
issues arise. The purpose of our paper is to be aware, identify and recognize whether online social support
networks energize or sets off the utilization of substances or assistthem with stopping the promotion of the
growing addiction. Reddit posts worth of a month were collected and analysed to determine the type of
support that users had been exchanging. The target audience will be the common people. This raises the
question whether these interactions improve understanding of drug do sages and usage or if they convince
user stokee pusing active substances.
Keywords: substance use, addiction, reddit, online social support, online interactions, drug dosage.
Introduction
Drug abuse in India is still on the rise and substance usage among women and children is a
major concern and also the usage stays as a remarkable worry in the present society.
The quantity of passings connected with drug gluts or addiction is on the rise. The quantity of
individuals with a substance use jumble stays huge. This leads to serious public health issues,
say, psychopathic deviation, extro version, depression, anxiety, stress and low self-esteem.
As this is an ongoing sickness social help assumes a significant part in recuperation (sobriety).
Much still needs to bedone on ground and suggestions should be put forth to handle and
minimize the spectrum of issues brought on by active substance use.
The quality, utilization, and accessibility of the available health care systems are still quite
inadequate. People with substance use disorder (SUD) might search and find help through
online social support groups (Wright, K.B., Bell, S.B., Wright, K.B. and Bell, S.B., 2003) Yet all
online social support groups may not promote connectedness and drug abuse recovery. They
may also support active users and illegal gathering and there are some groups which uphold
dynamic clients. Since these interactions rely mostly on texts, and lack nonverbal cues, using
content analyses tostudy online social support interactions may be critical (Rains, S.A.,
Peterson, E.B. and Wright, K.B., 2015). Due to the difference in stressors faced by active
substance users and people with chronic health issues, we would anticipate that there should
be contrasts in the type of help that are traded. It isn't evident whether the internet-based
183
stage fills in as an expert social harm reduction forum or supports illegal medication use
gathering. In order to understand it better, our study helps to gain a better understanding on
what all could influence the choice to seek for help by considering what type of support that is
being exchange dinr/fentany landr/heroin respectively.
Methodology
Data collection and Sample: Messages posted onthe r/fentanyl andr/heroin subreddits are
publicly available. We noted the date and collected the title and body of the posts from these
subreddits and questionnaires were distributed, responses were collected and analysed
respectively.
The final sample consisted of 613 posts (315 (r/fentanyl) and 298 (r/heroin)) that
represented a month period between 2nd august, 2022 and 2nd September, 2022. There was
an average of 10 posts per day in these sub-reddits respectively.
Literature Review
Cigarette smoking and hard drug usage both had distinct or independent detrimental impacts
that affected people's health, psychosomatic symptoms, emotional distress, and interpersonal
interactions in a variety of ways and just a few of the detrimental results that substance
addiction has been connected to include Car accidents, and violence. The general population
has been found to have high rates of substance usage, with males being more frequently
impacted than females including the patients with bipolar disorder who may experience worse
symptoms (Cassidy, F.,Ahearn, E.P. and Carroll, B.J. (2001). Both heterosexuals and lesbians
were more likely to use crack when their housing was inadequate. The ASSIST classified
ecstasy and ketaminea samphetamine and hallucinogen hazards, while lesbian, homosexual,
and bisexual individuals reported more ecstasy and ketamine damage (Pauly, B., Vallance, K.,
Wettlaufer, A., Chow, C., Brown, R., Evans, J., Gray, E., Krysowaty, B., Ivsins, A., Schiff, R. and
Stockwell, T., 2018.) Thus, it's important to take into account how drugus age is affected by
stable housing.
Little research has been done to find out the precise deep-rooted effects of illicit drug
usage and whether these negative results may be all evicted by a caring social network.
Preventive interventions that modify how strongly teenagers hold pro- or anti-marijuana
views may have an impact on the likelihood that they will resist using marijuana or start using
it. The strongest social variable predictors of total mental health include the changes in the
general support given by friends and informal social connections (McGaffin, B.J., Deane, F.P.,
Kelly, P.J. and Blackman, R.J., 2018) Uncertainty about the future, low self-esteem, sadness, and
experiencing traumatic events all have an impact on life satisfaction and are all influenced by a
variety of psychological factors. However, there are limitations on mobility, access to devices,
communication barriers forthose who have health issues, and for them face-to-face social
assistance may be difficult. Online support groups might be a beneficial alternative for such
people (Braithwaite, D.O., Waldron, V.R. and Finn, J., 1999)
Teens’ cognitive processing and relationships are being badly impacted by their careless
use of the internet that includes a wide range of online discussions, strongly connected with
procrastination that can have a negative impact on their academic performance and
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interpersonal interactions. Thus, it's essential to understand both the origins of internet
addiction while seeking help and also the reasons why it is waning as a result of increased
social interactions.
It isn’t sure whether the amount of social support provided by the women’s social
networks reaches them and also whether these interactions help them withdraw drug usage.
Maintaining textual communication is necessary to reap the benefits of social support in online
health communities. For that to happen in a fruitful way, women should be digitally literate
and self-aware to make things more accessible. Online safety should also be taken into
consideration.
The demand for people to learn more about the health concerns they are dealing with, has
led to the emergence of online support groups. As many become accustomed to using
computer-mediated communication technology, online support groups may be advantageous
for the users who choose not to attend in-person meetings and for those who may not be able
to. The expansion of these online forums might sometimes help the health educator store ach
targets with particular messages. However, these interactions are also associated with
disadvantages compared to traditional face-to-face group communications ince they lack
visual and audiblecues.
Significance of the Problem
Illicit drug use can begin with occasional sporting medication uses that some people later
engage in groups which ultimately develop into chronic drug use. Others develop chronic drug
use after being exposed to advertised substances or after receiving recommendations from
friends or family members who have used the drug and encouraged it, particularly with
narcotics.
Every substance has a unique dependence risk level and improvement rate for addiction to
the same. For example, narcotic pain killers have a faster rate of compulsion than other
prescribed drugs. In such a case, one might need increasing medicine dosages overtime in
order to experience a high which can end up being all they need to feel good. As the drug use
increases, they could discover that it becomes more difficult for them to withdraw. When
trying to stop using drugs, they could experience strong desires and physical suffering (with
drawals ide effects).
One might need support from their kith and kin, social support groups, or an organized
counselling approach to overcome their chronic drug use and maintain their substance-free
way of life and our study might help to gain a better understanding regarding the same.
Content Analysis of Posts
The study showed that majority of posts and conversations on ther/fentanylandr/heroin
forum fall on the subjects of, how or what sort of impacts to expect from a particular substance
or a combination of such kind, where and how to get them and dosage which is closely
connected with medication effects because how much of a drug taken decides its effects. This
would uphold the belief that the fundamental purpose behind r/fentanyl and r/heroin is to
share and seek for detailed data about substance misuse.
185
One of the main goals appears to be the possibility to seek specific information, as
evidenced by the most preferred informational support topics. This can be a sign that users
are trying to deal with their uncertainty regarding their substance usage. Because of this,
many drug users will go to drastic action to try and hide knowledge of their illicit usage and
escape the attitude of people associated with the drugus age. Many are cautious not to spoil
their identity by asking their friends, relatives or medical experts for advice. They refrain from
getting help from conventional networks where many tend to clarify their doubts, just to
closely safeguard their identity.
Moreover, it's essential to understand that the advice a user receives does not come from
certified medical professionals, but rather from anonymous reddit users. A user should be
aware about that substance to engage in a discussion about its dosage and impacts. However,
these discussions don’t require excellent understanding on drugs because all that is required
to contribute is one’s own subjective experience. So, it's also possible that one can see all these
posts and discussions that might been couraging to involve in illegal activities. Emotional
support for those who are tryin gto recover or overcome emotional distress and also for
people who love to be anonymous is the only advantage for users of these sub-reddits. Despite
that anyone can come across any post which can betriggering or helping thes ubstanceusage
situation.
Survey Insights
Of the total respondents, ¾th are from urban areas (i.e., 70%) and the number of female and
male respondents are 29 (58%) and 21 (42%) respectively. It’s very clear that the majority of
the respondents are above 18 years (90%).
A large number of respondents are not involved in drug use, which is very encouraging.
However, 18% of respondents appear to be using drugs, and some are unsure whether they
are using drugs or not.
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Larger part of the individuals are not admitting the medications yet the second
explanation that some are keen on taking is interest and are likewise taking these
unmedicated drugs is because ofthe psychological instability and to simply numb the torment
and just shut them off from the truth which they consider it to be extraordinary departure and
great escape from the reality. This peer pressure ought to likewise be considered as teenagers
these days generally tend to assume it as a way to look cool.
Teenagers or young students manage to get illicit substances unfortunately through many
differentsources despite being not allowed to buy them. At this point, even when they have
gotten some information about the accessibility of medications for everyday use, most of them
are not using drugs which is great. However, some who are admitting appear to get it from
another person and a few through taking part in unlawful demonstrations and some through
expecting something. Schools and other places give the teens easy access to drug exchange
without giving a chance forthe adults to figure out what’s going on and that's where the illicit
substances prevail high. These demonstrations can truly wreck them as they are
undependable ways and taking part in unlawful demonstrations, straight forwardly will lead
them to the pithole where their future will be squashed. Parents should know about these
drug sources and should keep track of their children’ activities in order to protect them from
illicit druguse and addiction.
The majority of respondents do not use the substance, but those who do appear to be over
the age of 18 and some have no awareness of druguse.
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Substance addiction brings about financial issues along side endangering well being.
Families endure because of the cultural and social aspects of medication use, including their
understanding of addict’s behaviour, the consumption of family assets, hesitance to
acknowledge liability, thediseases and passings brought in by illicit drug use, extramarital
undertakings, the contorting of relational connections inside the family, and brutality. Wrong
doings include selling unlawful medications, petty offenses, drink and drive. Luckily, most of
our respondents don't take part infights or arguments of any sort. Of the people who do, just a
little rate (14%) were viewed as highon drugs who engaged in a quarrel, accidents, fights or
scuffles. Such results impact the existence of drugusers, yet additionally those of their families
and the bigger local community. Accordingly, it becomes fundamental to consider these
variables while treating and forestalling addictions.
When asked about their views on drug use, many people believe that even if the amount of
medication used is small, it can become habit-forming, and that some people are fine with a
small amount of medication and at the very least believe that it isn't habit-forming. According
to this perspective, a person's opinion of active substance usage can range from extremely
negative to extremely favourable, but it is not possible for the same person to simultaneously
possess both positive and negative opinions of the drug, say heroin is "cool" and "toxic". Close
friends are most likely to have an influence on adolescents who have mixed opinions about
initiation. When there is a lot of ambiguity, friends can impact both behaviours and attitudes.
People who are highly dependent on active substances may suffer a range of with drawal
symptoms once they stop using it abruptly, or if they dramatically reduce their use. The
majority of the respondents are not drug users, as evidenced by their answers of no, but when
it comes to some respondents, they appear to have either witnessed someone having
withdrawal symptoms or they themselves have the symptom. Having social support is
important whether you are experiencing withdrawal onyour own or under a doctor's
supervision. When a loved one is experiencing withdrawal, it can be unpleasant for both of
you. One can contact a close friend or relative so they can check in with them and offer
support. Should keep ourselves hydrated and make efforts to get enough rest and adopt
healthy sleeping routines.
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When asked about this, the majority of respondents disagreed with taking the substance,
but some were unsure, and the remaining group appeared to be completely in agreement with
the idea of taking the drug of their choice. It is quite common to have urges to take drugs or at
least to just try for the sake of peer pressure or simply out of excitement. Yet this act when
continues will lead to the abuse of the substances.
Many respondents are certain that they will not use the substance in the next months, but
there appear to be some who agree and are undecided about taking the substance. It is not a
problem unless it becomes an addiction and puts individuals in danger.
Compared to the general population, substance users showed a much higher acceptance of
drinking and drug use. Even though all of our respondents are educated, some (34%) showed
more positiveattitudes on drinking and alcoholism who don’t feel bad/guilty about using
drugs. While there are some (42%) who feel guilty about their illicit substance usage, some are
staying neutral (24%). While many disagree to try to intake a particular type of drug of their
interest at any time during the next 12 months, some show a positive attitude towards in
taking them.
When questioned about their thoughts on not taking the substance for a week, the
majority of answers are uninformed of the problem, which is quite sad, and the second highest
number of responses reflect an assertive response. However, it should be mentioned that
stopping drug use abruptly is not as simple as it appears, as it would have a significant impact
on one's life.
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An enormous number of respondents doesn’t need any help contradicting the assertion
however psychological wellness is one of the urgent things that keeps a human alive. There are
some respondents who do not dare to seek help for their addictions and some who have lower
confidence in the services provided and who can’t afford finance for these services. A little self-
loathing canhave a great deal of control over our considerations which might bring about us
making awful choices. It can significantly be kept away, that you acknowledge and get some
assistance.
The majority of respondents did not feel demotivated or sad in this study, although it
should bementioned that any substance, whether used for enhancement or abuse, has its own
set of adverse effects. And the following large falls will be on the dilemmic state. Coming out
sober takes a long time and can be depressing.
As you may know, a person's connection or relationship can drive him or her to overcome
addiction and become a better person, and this is where the majority of votes are cast,
followed by therecovery centre. This also implies that legal and professional assistance is
required, regardless of who you are. Because our case is about online help, respondents feel
that just 30% of people can acquire social support online.
This is a typical question, regardless of addiction or anything else, and when asked about
it, the majority of respondents agree that it presents a problem, while the other majority is
unsure and others appear to vaguely agree and disagree.
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Ladies who consume drugs suffer fundamentally when a relative abuses drugs since they
are moresocially detached than men are and also there are insufficient treatment
opportunities for them toreach out. Many (56%) aren't sure whether the target population is
reached or not in providing the social help.
When asked about online social support groups, the majority of respondents appeared to
agree that the computerized system is the reason, but it also reveals that some are in favour of
the fact that it allows people to remain anonymous while simultaneously reaching the
intended population.
Not everything is perfect, and when asked about the disadvantages of the online social
support group, respondents appear to share a major perspective about how communication
difficulties may occur. This demonstrates that sessions should be held when abusers and
therapists physically meet,as verbal communication and conduct are more important than
anything else. Some sessions also appear to be focused on psychological functioning. This
basically indicates that vocal communication is preferred above textual communication.
Nothing is impossible, yet the majority of responders are unsure whether drug or
substance abuse can be stopped. Some appear to assume that by taking the proper steps, drug
or substance misuse may be stopped.
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It is extremely discouraging to observe that the majority of respondents are unsure if
online groupshelp them recover or not, but the other respondents appear to believe that these
online interactive platforms benefit them by providing information regarding drug availability
and dosage.
Many responses are 'no' and some are ‘maybe' indicating that online platforms are not as
important as in-person counselling. The main disadvantage of online social support groups
would be determining the real from the phony, as well as the lack of vocal communication.
It is quite sad or disturbing to learn that there are no awareness centres in the area where
the majority of the respondents live, and that some are uninformed of the availability of the
centres, demonstrating how drug misuse or substance abuse is still not treated seriously.
Discussion
People should address drug use in an open, non-judgmental manner and should better
understand the people who need social support. Adolescent-specific care programmes can
assist in getting them back on a healthy track. Research on darknet (where discussions about
where and how to getor purchase drugs) should be done to further understand how these
forums function and assist social support.
Education is the first step in preventing drug addiction. Education in families,
communities, and schools can stop first-time substance abuse. Many people struggle with both
substance use disorders and mental health issues. Sometimes, mental disease exists prior to
the on set of addiction. Other times, a mental health condition is brought on by or made worse
by the addiction. The likelihood of recovery increases with appropriate treatment for both
disorders.
Addiction to drugsmight be overseenand treated.In any case, there is generally the
likelihood that the dependence will re-emerge. The best thing you can do for your health is to
stay away fromdrugs. It gets more difficult to stop using drugs once you've experimented with
it. Addiction is achronic illness. Addiction may be overcome, though, and people can live
fulfilling lives. Receiving assistance is crucial to healing. Therefore, it's better to not use the
drug.
Limitations
Not sure whether the discussions made in these forums reach the target population or how
satisfied with the support being provided. The number of respondents to our survey is less.
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We can’t know who is involved in discussion and who seeks social assistance and thus it’s
difficult to address them to help connect with required resources.
Conclusion
This study's goal is to understand the difference of opinions and attitude towards the intake of
active substances. r/heroin and r/fentanyl are one of the forums where discussions happen.
Understanding these discussions may help us understand how the target population can be
reachedto provide social support and to reduce crimes. The information included should make
adolescents less vulnerable to their peers' misconceptions about the advantages of daily
substance use rather than getting triggered to in take them. The findings shed light on
potential pathways for future study that might produce more effective preventive outcomes
than we have come to expect. Future studies should study this possibility in order to construct
anti-drug preventive models, and we arehopeful that they will focus on reducing teenagers'
attitudinal hesitation about initiating active substance use. These results suggest that
perceptions of moral beliefs and attitudes are an effective preventative approach that is also
financially rewarding.
References
1. Wombacher, K., Sheff, S.E. and Itrich, N., 2019. Social support for active substance users: A
content analysis of r/drugs. Health Communication.
2. https://www.reddit.com/r/fentanyl/
3. https://www.reddit.com/r/heroin/
4. Cassidy, F., Ahearn, E.P. and Carroll, B.J., 2001. Substance abuse in bipolar disorder. Bipolar
disorders, 3(4), pp.181-188.
5. Chow, C., Vallance, K., Stockwell, T., Macdonald, S., Martin, G., Ivsins, A., Marsh, D.C.,
Michelow, W., Roth, E. and Duff, C., 2013. Sexual identity and drug use harm among high-
risk, active substance users. Culture, health & sexuality, 15(3), pp.311-326.
6. Little, J., Hodari, K., Lavender, J. and Berg, A., 2008. Come as you are: harm reduction drop-
in groups for multi–diagnosed drug users. Journal of Groups in Addiction & Recovery, 3(3-
4), pp.161-192.
7. Newcomb, M.D. and Bentler, P.M., 1988. Impact of adolescent drug use and social support
on problems of young adults: a longitudinal study. Journal of abnormal psychology,
97(1),p.64.
8. Gázquez Linares, J.J., Pérez Fuentes, M.D.C., Molero Jurado, M.D.M., Barragán Martín,A.B.,
Martos Martínez, Á. and Sánchez Marchán, C., 2016. Drug use in adolescents in relation to
social support and reactive and proactive aggressive behavior. Psicothema.
9. McGaffin, B.J., Deane, F.P., Kelly, P.J. and Blackman, R.J., 2018. Social support and mental
health during recovery from drug and alcohol problems. Addiction Research &Theory,
26(5), pp. 386-395.
10. Hohman, Z.P., Crano, W.D., Siegel, J.T. and Alvaro, E.M., 2014. Attitude ambivalence, friend
norms, and adolescent druguse. Prevention science, 15(1), pp.65-74.
193
11. Cheung, N.W., Cheung, Y.W. and Chen, X., 2016. Permissive attitude towards drug use,life
satisfaction, and continuous drug use among psychoactive drug users in Hong Kong. East
Asian Archives of Psychiatry, 26(2),pp.60-69.
12. Mabry, E.A. and Khavari, K.A., 1986. Attitude and personality correlates of hallucinogenic
druguse. International journal of the addictions, 21(6), pp.691-699.
13. Braithwaite, D.O., Waldron, V.R. and Finn, J., 1999. Communication of social support in
computer-mediated groups for people with disabilities. Health communication, 11(2),
pp.123-151.
14. White, M. and Dorman, S.M., 2001. Receiving social support online: implications for health
education. Health education research, 16(6), pp.693-707.
15. Frison, E. and Eggermont, S., 2016. Exploring the relationships between different types of
Facebook use, perceived online social support, and adolescents’ depressed mood. Social
Science Computer Review, 34(2), pp.153-171
16. Criswell, T.J., Weber, C.A., Xu, Y. and Carter, B.L., 2010. Effect of self‐efficacy and social
support on adherence to antihypertensive drugs. Pharmacotherapy: The Journal of Human
Pharmacology and Drug Therapy, 30(5), pp.432-441.
17. Trulsson, K. and Hedin, U.C., 2004. The role of social support when giving up drug abuse: A
female perspective. International Journal of Social Welfare, 13(2), pp.145-157.
18. Ansari, B. and Du, S., 2022. Investigating User-generated Content in an Online Drug
Recovery Forum: Lessons for Successful Computer-mediated Communication of Social
Support. IEEE Journal of Biomedical and Health Informatics.
19. SOON, A.W.B. and Rafiq, N., 2016. Exploring the relationship of personality, loneliness,and
online social support with internet addiction and procrastination. Pakistan Journal o
fPsychological Research, pp.93-117.
20. Wang, E.S.T. and Wang, M.C.H., 2013. Social support and social interaction ties oninternet
addiction: Integrating online and offline contexts. Cyberpsychology, Behavior, and Social
Networking, 16(11), pp. 843-849.
21. Anon, M.T., Ubeda, A. and Alcaraz, M.J., 1992. Protective effects of phenolic compoundson
CCl4-induced toxicity in isolated rat hepatocytes. Zeitschrift für Naturforschung C, 47(3-4),
pp. 275-279.
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CHAPTER 14
ANALYSIS OF STUDENT'S ERRORS IN SOLVING HIGHER ORDER
THINKING SKILLS (HOTS) PROBLEM
Lallipreethi .U (20MSI055), Sornalakshmi .M (20MSI0064)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
Higher-order thinking abilities extend beyond simple factual observation andmemorization. Higher-order
questions encourage critical thinking because they demand more from students thanthe memorization of
facts alone. They require them to apply, analyse, synthesise, and evaluate the material. Instead of just
repeating the facts, HOTS pushes students' thinking to higher levels and demands that they use the facts to
create something. The goal of this study was to examine how students are required to develop higher-order
thinking abilities in order to come up with ideas. This study was majorly focused on undergraduate
students at VIT University. The study sample consists of 100 students. This paper presents the results of a
questionnaire given to students via anonline survey. The results will show that higher-order thinking skills
are one of the essential components of education in the 21st century. The main goal behind this study is to
investigate, using surveys and questionnaires, the changes and the development of higher-order thinking
skills of students at VIT University.
Keywords: Higher order thinking skills (HOTS), memorization, students
Introduction
Higher-order thinking is more difficult to learn or teach, but it is also more valuable because it
can be used in new situations (situations other than those in which it was learned) more often.
In American education, the term" higher-order thinking skills" (HOTS) is widely used. It
differentiates critical thinking abilities from low-order learning outcomes like memorizing
facts by heart. Synthesis, analysis, reasoning, comprehension, application, and evaluation are
all HOTS.
Several taxonomies of learning serve as the foundation for HOTS, particularly Benjamin
Bloom's "Taxonomy of Educational Objectives: The Organization of Educational Objectives.
"The top three levels of Bloom's Taxonomy represent higher-order thinking abilities:
evaluation, synthesis, and analysis.
A concept of education reform based on learning taxonomies like Bloom's taxonomy is
higher-order thinking, also known as higher order thinking skills (HOTS). The idea is that
some types of learning have more general benefits but also require more cognitive processing
than others. For instance, according to Bloom's taxonomy, skills that involve analysis,
evaluation, and synthesis (creation of new knowledge) are thought to be of a higher order than
facts and concepts learning, which necessitates a different approach to education. Learning
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complex judgmental skills like critical thinking and problem-solving is necessary for higher-
order thinking.
Review of Literature
High level thinking also requires us to evaluate, analyse, or manipulate data. An individual
withhigh level thinking will be able to manipulate information and use new or existing
knowledge tocome up with a logical answer to novel situations (Heong et al., 2012). Helping
students develop flexible knowledge base and higher order thinking skills is becoming more
and more crucial in today's information age (Hmelo & Ferrari, n.d.). In particular at the higher
education level, teaching and learning should incorporate higher order thinking skills (HOTS).
If teachers want their students to handle problems independently, collaboratively, and
creatively, they should include thinking skills lessons in the curriculum (S, 2015). Students’
mathematical talents in communication, creativity, problem solving, and mathematical
reasoning were improved more by learning through problem solving strategies than by the
scientific method (Tambunan, 2019). Teachers'replies for evaluating and assessing HOTS have
not shown any evidence of using Bloom's Taxonomy (Retnawati et al., 2018) . There is a good
probability that students will develop critical thinking skills as a result if teachers
systematically and persistently use higher orderthinking tactics, such as dealing with real-
world situations in class, promoting open-ended classdiscussions, and encouraging
experiment-based research (Miri et al., 2007a). A critical issue in21st-century learning is the
incorporation of higher-order thinking skills (HOTS) in languagelearning assessments (Wiyaka
et al., 2020). Initial assessments of the suggested teaching strategiesdemonstrate a significant
increase in students learning and higher order thinking abilities, and theywere successfully
used in higher education (Alkhatib, 2019). It was shown that teachers only usethe application,
analysis, and evaluation levels of higher order thinking skills while instructing and assessing
students (Nachiappan et al., 2018). Within the context of science education, teaching with the
goal of fostering higher order thinking abilities improves students' critical thinking (CT) (Miri
et al., 2007b). Additionally, by incorporating problem-solving, critical thinking, and decision-
making tasks with in their studies, students can improve their higher-order thinking abilities
(Abosalem, 2015)
Supporting higher-order thinking is one of the fundamental goals of seminars in higher
education, but there is little empirical data on how this is demonstrated and supported in this
setting (Hassan, n.d.). Higher order thinking abilities can be a helpful tool for students to learn,
perform better, and overcome their difficulties. If students are exposed to activities that foster
excellent thinking, they will develop into good thinkers (Hamdan et al., 2019)
If teachers want their children to think independently and creatively, they must be familiar
with the tools needed to teach higher order thinking. Thinking skill classes should be a
component of the curriculum
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Result Analysis
HOTS, commonly known for critical thinking and problem solving, usually comprises of
synthesizing, analysing, reasoning, comprehending, application, and evaluation. From the
survey results, it is clearly shown that most of the people, around 62.1%, have voted for the
right option that promotes creative thinking, evaluating, and analysis of the given problem.
And 29.1% of people voted to include memorization and skills such as remembering,
understanding, and applying. There is less awareness of the HOTS question among the 8%
since they have voted forthis option, which says, memorising facts or information and
reproducing them. In conclusion, it is understood that there is no widespread awareness
among people about the HOTS question.
These types of questions stimulate thinking, and there is some purposefulness behind
them. In other words, it necessitates deeper thought processes. It usually comes with
sentences or paragraphs and never a one-liner since it indulges in more brief answers.
According to the survey results for this question, 83.9% of people have voted for the right
option and agree that higher-level thinking questions are open-ended questions. The
remaining few, 16.1%, respondents say that higher level thinking questions are not open-
ended questions. There are techniques and strategies followed to create huge awareness
among students regarding HOTS questions. The students will have to explore more and think
outside the box. It is usually created by asking questions and conducting research. Using real-
life problems, increasing thinking ability, etc. would help more. In the survey, 49.4% of people
chose the option of using critical thinking to improve their skills in attending to those higher-
order questions. And 16.1% of people voted for informative learning objectives. There is a tie
of 13.8% between two options which state that through group discussions and the other one is
giving feed back to students to refine and review about a particular topic. It has been
determined that only half of the people are aware of the strategies employed.
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From the survey, it is clearly shown that 52.9% of people say that sometimes they choose
lower-order thinking questions over higher-order thinking questions. And 36.8% of people
rarely go forlower-order questions. The remaining 10.3% of people choose lower order
questions only. There is a huge difference between these graphs. But in general, people prefer
the straight way of choosing lower-order questions than higher order questions. Because LOTS
are easier, and there is no need to apply critical thinking skills to answer the questions. It is
clearly seen that majority of the respondents sometimes choose lower order thinking
questions rather higher order thinking questions.
The way of approaching higher-order questions differs drastically. In this survey, 43.7% of
people chose to elaborate and explain the facts. And again 43.7% of those polled preferred
developing aclear-established solution to the current situation. Furthermore 34.5% of people
voted to examineand explain the facts. There are 17.2% of votes cast for estimating the
procedural background. I will not respond to such questions, which received the fewest votes
of 1.1%. The conclusion isthat being clear and concise is often more important when people
answer these types of questions. Majority of the respondents choose elaborating, explaining
the facts and creating a solution for the current situation through this we can understand that
most of the people know how to answer a higher order thinking questionin a well-established
way.
Through survey we can understand that 40.2% Students opted for 3 rating for learning in
the classroom is very useful to solve problems in everyday life and 35.6% gave 4 rating. 17.2%
gave 5 rating. Only few 4.6% gave 2 rating and 2.3% gave 1 rating. Students perform better on
assessments and assignments when they have to think critically and apply their knowledge.
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The majority number of votes was around 52.9%, which means it has been agreed that
higher order thinking skills are mandatory for an individual. And 43.7% of people have said
"maybe," which is sometimes a neutral kind of answer. The least voted (3.4%) says that
higher-order thinking skills are not mandatory. Upon conclusion, people have an awareness
that higher-order thinking skills are necessary and mandatory for an individual. Higher-order
thinking is a skill that can be taught, mastered, and developed through practice, just like any
other skill.
When HOTS are unfamiliar and it requires learners to think effectively, nearly, 55.2%
voted for problem encountered. While 26.4% people have never encountered and only few
18.4% respondents voted for none. You can focus more on your strengths and prevent any
form of restrictive or negative beliefs by using critical thinking to help you understand
yourself. Upon conclusion, it is analysed that they have encountered unfamiliar HOTS and it
requires learners to think creatively according to the respondents view point.
By survey, 56.3% of people agree that higher-order thinking questions will increase the
motivation to learn new things. And 33.3% of people strongly agree with this question. 6.9% of
people arenot sure about the question. And 2.3% of people disagree that higher-order thinking
questions will not increase the need to learn new things. It has the same vision for 1.1% of the
population as well.
Upon conclusion, people agree that these types of questions provide motivation in order to
explore more. A notion known as higher order thinking skills takes into account the various
forms of learning and the various amounts of cognitive processing. It is a means of
encouraging kids to think, rather than just memorize, and it also enhances their cognitive
function.
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By analysing the pie chart, we come to one conclusion that 52.9% majority of the
respondents believe that HOTS questionnaires are given to students to develop purposeful
questions on their own. And around 18.4% respondents voted to work together
collaboratively. 14.9% students opted to recall information quickly. While 13.8% students
answer all the teacher’s questions clearly. Upon conclusion, the ultimate goal of the HOTS
questionnaires is to develop objective questions on their own according to the students
obtained from the result.
Superior thinking is known as having or showing an overly high opinion of oneself;
conceited. pie chart denotes that 42.5% of people use superior thinking in group discussion
and 32.2% ofpeople during tests and MCQs , 21.8 % of people use during seminars and other
4% represents some other opinion on superior thinking. In conclusion it is observed that
people’s perception o nsuperior thinking varies.
HOTS means Questions developed to engage higher-order thinking skills. The pie chart
represents that 59.8% people encounter HOTS questions and 27.6% of people represents that
they may or may not attend the HOTS and 12.6% denotes NO. In conclusion many of the
people encounter HOTS question in their lifetime.
HOTS questions are difficult to understand and answer correctly. So, we asked people to
rate on a scale for attending and analysing questions correctly. 46.9% of people rated 38 out of
40 and 37% of people rated 30 out of 40 and 16% of people rated 13 out 40. In conclusion
most of the people attended HOTS question correctly.
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Answering HOTS assessment will help to improve higher levels than restating the facts and
requires students to do something with the facts. Inpie chart it denotes that 24.1% of people
choose creative thinking and 14.9% of people choose problem solving and 16.1% of people
choose critical thinking and 44.8% people choose all the above. In conclusion that answering
HOTS assessment will try to improve all.
40.2% of people chose yes to engage in higher-order thinking strategies when choosing a
topic. And 51.7% of people chose maybe. it concludes that based on the topic and its needs
higher order thinking strategies can be implemented.
51.7% of people voted that HOTS will help you to explore new ideas and 44.8% of people
choose encourage students to think and 31% of people opted for to develop their aspect
viewing. In conclusion teachers should develop HOTS for students to explore new ideas.
Majority of the respondents says that HOTS will help you to explore new ideas according to the
teacher’s point of view for students.
In lack of resources and limited knowledge of higher order thinking questions have a
direct effect on students so 44.8% of people choose yes and 37.9% choose maybe and 17.2% of
people choose no. Due to lack of knowledge in higher order thinking it will lead to students to
not attend the questions properly. So, it will create an impact on students. In conclusion that
people perception varies.
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People use problem solving skills to answer HOTS question: 43.7% of people choose
sometimes and 29.9% choose always and 20.7% choose rarely. In conclusion that people
choose problem solving skills to answer HOTS question based on their situation.
Increasing higher order thinking skills: 57.5% of peoplerated 50 for analyse concepts and
51.7% of people rated 45 for thinking creatively. In conclusion that to increase our higher
order thinking skills understating and analysing the concept is more important.
Discussion
As expected, the results obtained from the survey via form, assisted us to know how higher
orderthinking questions can be answered and what are the techniques that are used to
develop higher order thinking skills among students. In a total of 100 sample size,we got 87
responses fromstudents that are circulated via google form. The research provided evidence
that higher order thinking skills are necessary and mandatory for an individual. The survey
helped us to know about the perception of students about higher order thinking skills. By
anticipating connections among various ideas, higher-order thinking abilities can aid in
problem solving and encourages the development of critical thinking. These abilities help
students handle problems effectively and serve as the foundation for mor eexpansive forms of
critical and creative thinking. Through HOTS, students gain the ability to identify ideas clearly,
form hypotheses, engage in persuasive argumentation, solve problems, and effectively develop
explanations. Understudies with strong CT skills will be able to manage social, scientific, and
practical issues successfully in the future. By employing the Problem-based Learning (PBL)
methodology, CT skills can be increased. Understanding complicated concepts becomes more
thorough and straight forward. Again, each article we looked at emphasises how crucial it is to
teach HOTS in a way that satisfies a national vision in education.
Conclusion
The idea focuses on how well students grasp the learning processusing their own approaches.
It is possible to teach kids to think critically, creatively, and innovatively by using the HOTS
questions. The top three Bloom's taxonomies levels—analysis (analysing), evaluation
(evaluating), and synthesis—are referred to as higher order thinking skills. HOTS focuses on
CT abilities to accept many types of data, think creatively in addressing problems, and have the
202
ability to make decisions in difficult circumstances. This examination of the paper
demonstrates that HOTS incorporates the investigation of cognitive processes as well as
evaluation and creation in order toprovidea solution.
Students consider how to address the challenges they are faced with; this involves high-
level thinking, namely critical thinking. The PBL paradigm has the potential to enhance
students' CT abilities because it fosters open, reflective, critical, and active thinking, and
because the problem-solving techniques it employs facilitate the development of effective and
efficient thinking abilities.
By concluding, successful teaching leads to effective learning, and students' learning can
take many different forms, one of which is developing higher-order thinking skills. As a result,
it goes without saying that effective HOTS instruction is crucial to ensure that students learn
effectively.
References
1. Heong, Y. M., Yunos, J. M., Othman, W., Hassan, R., Kiong, T. T., & Mohamad, M. M. (2012).
The needs analysis of learning higher order thinking skills for generating ideas. Procedia-
Social and Behavioral Sciences, 59, 197-203.
2. Chinedu, C. C., Olabiyi, O. S., & Kamin, Y. B. (2015). Strategies for improving higherorder
thinking skills in teaching and learning of design and technology education. Journalof
technical education and training,7(2).
3. Tambunan, H. (2019). The Effectiveness of the Problem Solving Strategy and the Scientific
Approach to Students' Mathematical Capabilities in High Order Thinking Skills.
International Electronic Journal of Mathematics Education, 14(2),293-302.
4. Retnawati, H., Djidu, H., Kartianom, A., & Anazifa, R. D. (2018). Teachers’ knowledge about
higher-order thinking skills and its learning strategy. Problems of Education in the 21st
Century, 76(2), 215.
5. Miri, B., David, B. C., & Uri, Z. (2007). Purposely teaching for the promotion of higher-order
thinking skills: A case of critical thinking. Research in science education, 37(4),353-369.
6. Wiyaka, W., Prastikawati, E. F., & Kusumo Adi, A. P. (2020). Higher-order thinking skills
(hots)-based formative assessment: a proposed model for language learning assessment.
Vision: Journal for Language and Foreign Language Learning, 9(2),115-130.
7. Alkhatib, O. J. (2019, March). A framework for implementing higher-order thinking skills
(problem-solving, critical thinking, creative thinking, and decision-making) in engineering
& humanities. In 2019 Advances in Science and Engineering Technology International
Conferences (ASET) (pp.1-8). IEEE.
8. Miri, B., David, B. C., & Uri, Z. (2007). Purposely teaching for the promotion of higher-order
thinking skills: A case of critical thinking. Research in science education, 37(4), 353-369.
9. Abosalem, Y. (2016). Assessment techniques and students’ higher-order thinking skills.
International Journal of Secondary Education, 4(1),1-11.
10. Hmelo, C. E., & Ferrari, M. (1997). The problem-based learning tutorial: Cultivating higher
order thinking skills. Journal for the Education of the Gifted, 20(4), 401-422.
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11. Heong, Y.M., Yunos, J.M., Hassan, R.B., Othman, W.B., & Kiong, T.T. (2011). The perception
of the level of higher order thinking skills among technical education students. In
International Conference on Social Science and Humanity journal. Faculty of Technical
Education, Universiti Tun Hussein Onn Malaysia (Vol.5, No.2, pp. 281-285).
12. Hamdan, N., Kiong, T.T., Heong, Y.M., Masran, S.H., Yunos, J.M., Mohamad, M.M., & Shafei, S.
(2019). An Effectiveness of High Order Thinking Skills (HOTS) Self-Instructional Manual
for Students' Assignment Achievement. Journal of Technical Education and Training, 11(1).
13. Chidozie, C. C., Libunao, W. H., Kamen, Y. B., & Saud, M. S. B. (2014). Implementing higher
order thinking skills in teaching and learning of design and technology education. TVEIS
2014, 633.
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CHAPTER 15
CLOUD IoT APPLICATION IN AGRICULTURAL ENGINEERING
Sheethll .P (20MID0206), Annapurna Shobitha .S (20MID0027), Melbin Sam Binoy (20BAG0051)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
IoT and cloud computing can have an instant impact on the future of agriculture. IoT can
support farm agriculture by providing information on a crop by the exchange of data with the integration
of the devices which analyses the factors associated with crop growth and its development. The purpose of
the study was to develop farming using the technology which is the need of the hour. By using the Cloud
IOT application we can fasten the process of production of the crops. The study was conducted on UG
fresher and M.tech integrated fresher students of VIT University. The study can also be extended to
agricultural students and other college students. The research on this topic was conducted
by VIT University students at their home virtually during the lockdown in the pandemic situation during
their fall semester 2020-2021. This paper represents the result of the questionnaire given to students
through a survey given in google forms and research. This is a survey that is used to understand the
different possible technologies which can be used for smart agriculture. The result showed up that cloud
IOT can speed up the process of farming and provide fruitful results. From this research, we can understand
that this is high time to convert from traditional to smart agriculture. Automation of processes in farming
will help the farmers spend time focusing on the quality of the crop. The main motto of this study was to
induce a smart agriculture system and to give an overview of the different processes that can b e used for
the development of agriculture which is the backbone of the nation.
Introduction
Around 60-70%(anticipated worth) Indian populace straightf orwardly or in a roundabout
way relies upon farming that effects the food security and financial development of India. With
the assistance of exactness, the agribusiness interaction can undoubtedly screen or notice crop
development dependent on gathered data (soil condition and climate data) from a harvest
field. The advances in science and innovation and the high capability of human resources have
permitted a feasible development of the world economy. IoT mists offer a proficient,
adaptable, and versatile model for conveying the foundation and administrations expected to
control IoT gadgets and applications for organizations with restricted assets. IoT mists offer
on-request, cost-proficient hyper-scale so associations can use the critical capability of IoT
without building the basic framework and administrations without any preparation.
Horticultural designing is the designing of agrarian creation and handling. Horticultural
designing consolidates the orders of mechanical, common, electrical, Food science, and
substance designing standards with information on rural standards as indicated by innovative
standards. A vital objective of this order is to improve the viability and maintainability of rural
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practices. Cloud IoT frameworks bring rural upheaval by diminishing the endeavors, time, and
cost for the rancher. A few cloud IoT-based applications are currently planned and carried out
for exact farming to adequately and precisely deal with the cultivating, culturing, collecting,
and handling of harvests. The wellspring of occupation for a large portion of the populace is
farming. The viability and supportability of farming practices can be extraordinarily improved
by applying current designing methods. Web of Things (IoT) assumes a significant part in
overseeing and controlling the cultivating gear and detecting the different boundaries in
agribusiness. It is assessed that more than 780 million ranches will be associated with IoT
from 2035 to 2050. Cloud IoT frameworks bring horticultural upset by diminishing the
endeavors, time, and cost for the rancher. It presents the quick progression of the innovations
in the current agricultural model by applying IoT methods. This reality has brought about the
development of the savvy cultivating approach which permits ranchers to distantly screen the
harvest field by methods for sensors just as to have programmed water system frameworks.
Moreover, the IoT-based brilliant horticulture applications could help natural rural farming,
what's more, family cultivating.
Literature Review
The principle utilization of IoT advancements in agribusiness is found in accuracy horticulture
whose design incorporates IoT procedures for metropolitan farming and accurate agronomy
in savvy urban communities. These enhancements contribute altogether to the
accomplishment, of keen urban areas with foundations that permit robotizing, streamlining,
and improving metropolitan farming and exactness of agronomy. IoT-based gadgets have been
embraced by numerous enterprises and markets around the planet. One of these enterprises is
agribusiness, which profits from IoT innovations in a horde of ways. IoT-based innovations
have been effectively received in various settings. Because of this reality, a few organizations
are putting resources into IoT-based programming improvement for agribusiness. These days,
there are a few programming items accessible in the market zeroed in on supporting diverse
horticultural cycles.
We can note that cloud IoT in agriculture helps farmers to do the best at their comfort.
Sensors like humidity and temperature sensors help a farmer to plant their crops. Drones will
help them look over their crops by sitting at a place and they can do some other jab too
simultaneously. IoT makes farmer’s life better and will increase their income. Proper usage of
the cloud IoT technology will result in awesome results for farmers and farmers are the
backbone of the country so it will also lead to the development of the country.
After looking into the different perspectives and different sides of cloud IoT in agriculture
we noted that getting the technology into action is very important and it takes time for the
change. Rather than the modern technology and chemicals, the farmers use they can try cloud
IoT as it’s less harmful to the environment. Farmers face problems like shortage of labor,
fewer resources, improper planning for the next set of crops, and many more, all these
problems can be solved by using cloud IoT. We can use various sensors to make easy
equipment and help the farmers plan their next set of crops. People can be encouraged to learn
cloud IoT and help the nation using their knowledge.
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The survey consisted of 10 questions for which people were asked to answer. The aim was
to know what people think cloud IoT is and how it is related to IoT. We got to know how much
people have knowledge related to this topic. The survey result is included in the analysis. The
survey was about how to and how IOT has been implemented in agriculture.
Result Analysis
According to the survey, about 94.6% of the people belong to the age group of 15-20. So
the survey primarily consists of youngsters. Youths square measure the first productive
human resource of socio-economic development. It is, therefore, essential to spot the roles of
youth in the development of agriculture.
In the survey, when people were asked if they knew about Cloud IoT application in
agricultural engineering, 73% of them agreed that they were not aware of the term, while
27% of them knew about it already. When we think about technology, we almost certainly do
not associate it with agriculture. However, technology is steady, turning to associate in nursing
the integral part of the longer term of farming. Advancements in IoT (Internet of Things) have
brought forth a replacement branch of agriculture ordinarily said as "smart farming." But
people are unaware of it. Smart farming deems it necessary to handle problems, like global
climate change and labor that has gained plenty of technological attention, from planting and
watering of crops to health and harvest.
According to the survey, 91.9% of the people needed smart agriculture to flourish as they
think that IoT solutions are centered on serving farmers to shut the availability of demand gap,
by guaranteeing high yields, gain, and protection of the setting.
By the report submitted by Forbes, until 2050 population of the planet is going to
beover9.6 billion consequently resulting in a 70% increase in food consumption. Since there's
restricted cultivable land the sole solution to overcome this crisis is to set up well. It’s already
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happening because the huge corporation square measure aggregation knowledge from crop
yields fertilizer application, soil mapping, weather impact, etc.
In the study, 83.3% of the people were concerned about the farmers that they suggested
that it is a huge opportunity for farmers to monitor their crops and increase productivity. A
study conducted by OnFarm found that following the usage of IoT on the common farm, yield
rose by 75%, energy prices born from $7 to $13 per acre, and water use for irrigation fell by 8
May 1945. In the U.S., wherever IoT is most widespread, produces 7,340 kg of cereal per area
unit of farmland, compared to the world average of 851 kg of cereal per area unit. Having these
figures in mind, it's straightforward to acknowledge the very fact that IoT device installations
within the agriculture world can increase from thirty million in 2015 to seventy-five million in
2022.
As we've already lined on e-Agriculture, there square measure several samples of IoT: The
EU has started a €30 million project referred to as Food & Farm 2020 to assess and improve
IoT technologies. In Kansas, farmers’ square measure mistreatment devices to preserve water
and in the People's Republic of Bangladesh, a brand-new sensor technology project is enforced
presently.
83.8% of the people suggested that smart farming requires wireless sensor networks;
51.4% suggested satellites; 59.5% suggested big data; Sickle and cow were suggested by the
remaining. But what does smart farming need? Smart Farming is arising conception that refers
to managing farms victimization, trendy info, and communication technologies to extend the
number and quality of product whereas optimizing the human labor is also needed. Among the
technologies, the ones that are accessible for current farmers are:
1. Sensors: soil, water, light, humidity, temperature management
2. Software:specialized computer code solutions that focus on specific farm sorts or use case
agnostic IoT platforms
3. Connectivity: cellular, LoRa, etc.
4. Location: GPS, Satellite, etc.
5. Robotics: Autonomous tractors, process facilities, etc.
6. Data analytics: standalone analytics solutions, information pipelines for downstream
solutions, etc.
Suggest 1 or 2 ways to use technology in agriculture:
37 responses were received, many people suggested ways like using robots, monitoring
and controlling crop irrigation system, use of AI, use of drones, fertilizer application, using
sensors to keep track of crops, create websites to keep farmers connected, and provide them
with help, real-time image processing, GIS and GPS, placing IoT devices in the plant to sensor
the water capacity and nutrients. Nearly everybody engaged in the longer term of
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contemporary agriculture is targeted on potency. A large variety of technologies can modify
the transition of contemporary agriculture within the field. If fashionable agriculture is applied
widely within few years, immeasurable farmers are going to be able to have the benefit of the
acquisition of farm data.
Inventions that changed the face of farming are a reaper, thresher, tractor, hydraulics, bees
and drones, urban agriculture and vertical farming, etc. Farmers build selections according to
the knowledge they need on-hand that is why information has helped them harness the ability
of data to form better-informed selections that permit them to use resources additional
sustainably.
According to the survey, people have named a few agricultural inventions that have
changed the face of farming. They area green revolution, advanced machinery inventions, drip
irrigation, moisture sensors, robots, harvester, tractors, milk revolution, cotton gin,
reaper/binder, improvement in the storage of the products like cold room storages,
separators, and logistics.
Most of the people in the survey said that it would probably take 5 -10 years to improve
farm management in India If cloud IoT application is used in agriculture. The central
government of the Asian nation plays an energetic role in developing the agri-tech sector. They
perpetually come back up with new bills to empower Indian farmers. The Indian government
supports good farming as a result of they require scaling back their effort and enhancing their
productivity. At present, they're operating to double the farmers’ financial gain by 2022. They
require to extend farmers’ financial gain with minimum efforts by good farming. For this, the
NITI Aayog collaborates with the businesses that embody IBM for the technology-driven
solutions. For these farmers get real-time recommendations and area unit supported to extend
crop productivity.
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According to the survey, 78.6% of the people agreed that farmers get educated by using
smart phones and other technologies. While the rest of the population insisted on their point
of view: They said, farmers would get educated from Partial and to a large extent; there are
two possibilities, one is they get educated and another one is that they may get addicted to the
social media and forget their works; Few said, it's a cultural degradation. They also said, using
technology doesn’t simply mean education, understanding technology is education. They
insisted that most of them don't get it and think of it as a waste of time.
As responsible citizens, each one of them explained their roles in helping out farmers
with cloud IoT applications during the survey. They said, they would help farmers to use the
technology, would try to spread about IoT to all, give suggestions as a student, educate them
through camps.
Discussion
A survey was conducted to collect information about Cloud IOT application in the agricultural
sector. It was conducted on people particularly at age groups of 15-20 showing that the survey
consisted primarily of youngsters. Majority section of the people consisting of almost 73% of
the people isn’t aware about the Cloud IOT application in agriculture. Apparently, only 27% of
the people are aware of this.
From the survey, it is understood that majority of the youngsters are less aware about
Cloud IOT in agriculture. The students were asked if they believe that smart agriculture was
necessary and 91.9% of the people agreed with the fact that smart agriculture was necessary
as IOT can help the farmers to gain high yields with better and improved production of crops.
83% of the students believe that IOT Big Data and Smart farming is most likely the future of
agriculture as this foundation can provide a greater opportunity for farmers to improve
monitoring and productivity of crops. From a study conducted by Onfarm, it is believed fact
that IOT can substantially increase the rate of yield production by almost 75%. This proves
that IOT should be adopted widely in the next future considering the increasing rate of
population. A majority, including 83.8% of the people believed that smart farming requires
wireless sensor networks while some suggested satellites and big data. Majority section of the
people suggested ways of using robots, monitoring and controlling crop irrigation system and
supported the use of A.I and drones, development of sensors to keep track of the crops and
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adoption of various facilities like GPS, GIS etc. Such widespread use of technologies if applied
within a few years can immeasurably benefit the famers through acquisition of farm data. As
per the opinion of the students, green revolution, advanced machinery, drip irrigation, robots,
harvesters, tractors and reaper etc., changed the face of farming.
When asked about the impact Cloud IOT can have in agriculture in the coming years, most
people in the survey said that it would probably take 5-10 years to improve farm management
in India if this application comes in to use. At present, the government operates on doubling
the farmers’ financial gain by 2022. In the survey, it was asked if the famers get educated by
using smart phones and other technologies. 78% of the students agreed that this can help the
farmers to be updated whilst the rest believed that famers will only be educated up to a partial
extend. Some said that its use can be distractive given the effects of social media, while others
found it to be a cultural degrading practice.During the final portion of the survey, we asked
about their roles as an Indian citizen in helping the farmers using IOT application. They replied
that their primary objective will be to help the famers adopt and use the IOT technologies by
spreading out IOT information to all by giving them suggestions as a student and providing
education through camps.
Conclusion
As expected, the result shows the importance of cloud IOT application in agricultural
engineering. IoT allowsthe massivequantityof information to be collected. Over the sensors
and therefore providing highermanagement over the inner processes and, as a result, lower
production risks. With IoT economicalobservance of the farming surroundings is ensured. IoT
helps the farmers to observe the fields at multiple locations by sanctionative remote
observance. Selectionsarecreated in period and from anyplace. IoT guarantees augmented
crop production by keen following of planting, watering, chemical application and gathering.
References
1. https://www.arm.com/glossary/iot~cloud#:~:text=An%20IoT%20cloud%20is%20a,real
%2Dtime%20operations%20and%20processing.&text=Discover%20how%20to%20deliv
er%20new,scalability%20required%20to%20be%20successful.
2. https://en.wikipedia.org/wiki/Agricultural_engineering
3. https://easychair.org/cfp/smartagri2021#:~:text=Cloud%20IoT%20systems%20bring%
20agricultural,harvesting%2C%20and%20processing%20of%20crops.
4. https://www.researchgate.net/publication/321896167_A_Survey_Smart_agriculture_IoT_
with_cloud_computing
5. http://agri.ckcest.cn/file1/M00/06/8A/Csgk0F04TP2ARv4tAAO1-thMzRw766.pdf
6. https://www.mdpi.com/2079-9292/9/2/319/html
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CHAPTER 16
ANALYSIS OF EFFECTIVE COMMUNICATION IN CRIMINAL JUSTICE
Dimple (20MSI0140), Shrija (20MSI0073)
Dr. M. Thenmozhi
Assistant Professor Senior of English
Vellore Institute of Technology, Vellore, Tamil Nadu
Abstract
Policemen, soldiers, and judges get their training related to their work, but the common problem can be
communicating with arrestees or victims. It can even lead to misunderstanding the situation and bringing
up a solution opposing them.
Normal people without the knowledge of laws are also scandalized and portrayed as attackers. The
purpose of this article is to bring out the need for education on laws on a basic level to make them stand for
themselves and teach the strategy of being cautious and preventing them from being attacked. A
questionnaire was prepared and circulated to students about how they feel about the drawbacks of the
filing of a case and what according to them is favored in the court.
Introduction
Communication is simply sharing thoughts, and exchanging information via direct or indirect
media. From speaking about your passion to defending yourself is communication.
Defending yourselves when someone knowingly or unknowingly has the intention to kill is
accepted in the law. Take it rape, murder, or assault; it helps you to defend yourself if the
attacker has been killed to protect yourself. But what if you need to defend yourself while
communicating the false case that has been put up on you? Like police charging you for
breaking the rules that you have not or supporting a victim who is being punished in public for
an undone act or punishing someone for being in the other religion.
Now what is important here is how well you communicate and bring out the truth as well
as obey the laws. Miranda rights are one created in 1996 as a result of the United States
Supreme Court case of Miranda v. Arizona. The Miranda warning helps us to remain silent, and
call an attorney, as our statement will be used for or against in the courtroom. One can be
appointed as our attorney if the arrestee cannot pay for the attorney.
Communication issues are often side-lined in criminal justice. Research has said that cross
communication often leads to problems in the courtroom which makes arrestees provide
wrong or uninformative answers. In some cases, we see some questions are monitored
separately or in the special case where monitors are assigned to watch the session carefully to
avoid misleading.
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One very important factor of communication is the delivery of information. The tone,
words, and way of delivery play a major role. Words matter when it comes to criminal justice.
Proper delivery and analysis of issues play a major role.
There are several cases where people will lose words to defend themselves. It becomes
mandatory for us to make people aware of the issues and ways to defend themselves in
various types of issues that happen in this world. At certain times due to the mental pressure,
the arrestees give false statements and falsely blame themselves just to escape from the
trauma they experience. In order to make sure we decrease the number of cases due to such
reasons it is mandatory to keep aware of various laws that are available to protect people
themselves by hiring lawyers and at times, they themselves could fight for justice. In such
cases building a defense, hiring lawyers, and gathering evidence to prove yourself guilt-free is
mandatory to get out of the case. False cases are very common in today’s world and not
everyone has enough money to hire lawyers, and witnesses so here in this article we will be
talking about various laws that would help every citizen to protect themselves.
People are frequently angered when they are falsely accused of misbehavior and show
their outrage at the unfair treatment. According to a new study, individuals who publicly show
their anger are typically perceived as guilty. Individuals wrongfully accused of misconduct
may be evaluated more favorably if they are able to manage their emotions and stay cool.
Literature Review
The change/use of words by the advocate in the courtroom can have a major impact on the
victim’s statements or the judiciary’s response. (Smith, 1991). Photographs that can be used as
witnesses. Photographs or paintings try to communicate unsaid words. Chico, a 50-year-old
man case was taken for differentiating his behavior through actions, symbols, and his stories
along with pictures taken during the interview. Scholars can get to know more about the use of
these photographs as a defense. (“The Stories in Images: The Value of the Visual for Narrative
Criminology,” 2019). The police and the media have a mutual understanding. The police need
media to promote their organization while the media is happy getting a new case they can talk
about. There is a very limited understanding of these two associations, which this article
emphasizes and provides a result. (Chermak& Weiss, 2005). A population sample of 73 nurses
was taken for concluding the results. They are optimized by checking if they spoke the truth or
lied about the movie they had recently seen. In which, they got 78% results positive that
nonverbal communication also plays an effective role. (Vrij et al., 2000). The day-to-day
conflicts that may arise between the students and the staff teachers. Many conflicts can be
nonverbal which is not easy to identify and solve. Hence, this article involves how to avoid
academic and administrative conflicts. (Iyekolo, 2020). The bullying of college students was
common in Indonesia. Raging is common among students, but this can be dangerous at times.
Verbal bullying includes words, scolding, or yelling at the other person, but nonverbal affects
your mental health the most as it may include blackmailing or making them feel like a fool, not
including them in any kind of activities. Hence, this article brings light to these students who
face this issue. (Khadijah, 2018). A study took place in Taiwan where the performance of
public security is low. They have divided the justice procedures into three counterparts-
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upper, middle, and down. This study helps them to figure out the reason why they lack
communication and cooperation and also filled up the gaps that are supposed to be filled.
(Chang et al., 2008)
Body language, and whether it affects the courtroom during a session or not is important
to know. According to Albert Mehrabian - one of the first researchers of body language - only
7% are affected by words, 38% by voice signals, and 55% by nonverbal signals. (Gurbiel,
2018)
Victims usually have a pity face when called into the courtroom. Expressions play a major
role in bringing the results. As a judge, one who seems to be weak or pitiful can be a victim and
this can change the decision of the judge. Hence, he calls this a dangerous decision as to how
emotionally the expression plays. (Porter & ten Brinke, 2009). In order to uncover specific
elements that keep protests calm, explore actual examples of successful peacekeeping, and
propose useful peacekeeping rules, this study connects sociology, criminology, and social
psychology. They have compared 30 peaceful and violent protests in the USA and Germany.
According to the findings, certain interaction patterns and emotional dynamics might disrupt
peaceful interaction patterns and cause violence. Police forces and protesters need to avoid
these interaction dynamics to keep protests peaceful. (Nassauer, 2015)
Criminal justice addresses the needs of both collective and private interests. Criminal
justice contributes to potential peace. (Cassese, 1998)
Criminal-Justice-Related Competencies in Defendants with Mental Retardation
Mentally retarded people suffer from disorders like adaptive behavior and intellectual
functioning, these affect them during the confession and proceedings of the trial.
Nevertheless, this is identified by forensic trials.
Appelbaum, Kenneth L.A Appelbaum, Paul S. Criminal-justice-related competencies in
defendants with mental retardation 1994 The Journal of Psychiatry & Law 10.1177/00931853
9402200402 https:// journals.sagepub. com /doi/abs/ 10.1177/009318539402200402
Among the deaf people, the ill-literate and the people who have less knowledge of the laws
suffer a lot and PPD also affects them adversely. (Vernon & Miller, 2005)
Public Information Officers play a major role in criminal justice and the production of
crime and justice information. They act as gatekeepers and play a major role in criminal justice
and information protection. (Surette, 2001)
According to this article Information provision and communication within the Criminal
Justice System can be highly problematic for young people and adults with learning disabilities
and difficulties. Paper-based communication is most common, and it is used for the provision
of rights and entitlements in custody, but such communication can be poorly understood,
potentially leading to miscarriages of justice. (Parsons & Sherwood, 2016)
The racial divide in criminal injustice reflects major racial chaos and also contributes to
the different ways of interpretation and results in major drawbacks and criminal injustice.
Racial cleavage plays a major role in racial injustice. (Henderson et al., 1997)
Wrongful convictions are brought to light by using DNA exonerations. It is important to
maintain and protect the innocent from being victimized so better strategies, and methods of
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investigation should be followed and implemented. (Huff, 2004) The article states ‘the
acceptable rate of wrongful conviction is less than .5%. Findings thus indicate that criminal
justice professionals perceive an unacceptable frequency of wrongful conviction and
associated system errors and suggest that programs aimed at reducing system errors and
improving professional conduct would be broadly accepted among criminal justice
professionals.’ (Ramsey & Frank, 2007)
How Do Race and Gender Impact Perceptions of the Wrongfully Convicted?
In a survey, it's seen that people support more blacks than whites although this survey
doesn’t rely completely on it and is just a case study.
Bettens, T. and Warren, A., 2021. How Do Race and Gender Impact Perceptions of the
Wrongfully Convicted?
Result Analysis
A questionnaire was prepared and circulated to 50 people, students who are pursuing law and
lawyers in our contacts.
Communication is a basic way to deliver a message, but sometimes it may go wrong. One
may not properly communicate every time, and end up in a problem. Communication doesn’t
need to be spoken (verbal) always, it can also include actions, eye contacts, gestures, body
language and many more. As humans, one is not similar to the other and the way to
understand things is also different, and 70% of people have faced this issue of mis-
communication.
Body language does matter in the courtroom. A victim can try to prove his innocence by
pure expressions and pleading emotions. A grin, frown, or being slouchy can make the judge
feel negative about the person. Body language helps in affirming or contradicting the verbal
statements of a person testifying in court.
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The lawyer is paid to fight the case against, and to win under any circumstance. Lawyers in
general are considered to be very serious, and have a booming voice. But how does the tone
help them? According to the respondents, it helps to prove their innocence but it can also play
a role of innocent yet guilty. This helps us to understand that tone may play various factors in
helping the person from charging off any section.
Non verbal communication is more effective than verbal communication and conveys
meaning better. Non verbal communication, as discussed earlier includes actions, eye contacts,
gestures, body language and many more. They can also be misunderstood and can lead to
problems.
Fighting for your case is necessary, with or without a lawyer. Having a lawyer is beneficial
as you would know what and how to say things properly. But it has cons as well, like one can
bribe your lawyer and help you lose the case. In such terms, one needs to fight for themselves
and knowing of rules and regulations of law sections is important.
Lawyers may sometimes not take up our case because of the sensitivity or the opposite
lawyer being strong. In that case, one must know how to win the case by themselves. One
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major input is evidence. The right evidence at the right time may help you win the case in no
seconds. The speaking of truth is also important and it's more beneficial when one can prove
that whatever is spoken was true.
During a court case, when the minimum evidence is not acquired, the court opts for
polygraph. It helps to come to a conclusion whether the victim or person in guilt is a sufferer
or not. Lie detector machines help to finalise the court statements. But can those machines
read non verbal communication as well? It is a bit difficult for a machine to identify actions
and eye contact, but heart rate monitoring can help them finalize the truth.
Filing a case is not so easy, it depends on its sensitivity. If a person is reporting missing gold,
the police question their lack of keeping the objects safe. Or if a rape case, it’s questioned on
the victim. They may be bored or lazy to take up a complaint and take required actions against
it for which a proper response is not given. This is a common problem a normal person faces
while filing a case.
It is believed that mental health is adversely affected due false cases and due to
impeachments. Everyone gets offended when a false image or acquisition is made on someone
because it becomes difficult to fight for themselves and at sometimes people tend to lose self
confidence on oneself and self-doubt acts as a major weapon against mental peace and good
health.
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Most lawyers, policemen, and law practitioners have made sure to keep their personal
thoughts, ideas, and feelings away from their professional life to maintain a smooth balance
between their profession and personal life. and according to the survey also it is known more
than half of people try to maintain their personal and professional life.
When it comes to trust in criminal cases it's so obvious that people trust only the lawyers
over oneself and police . lawyers play a major role in providing confidence and hopes to
oneself . The second most important factor is the self trust that acts as the key to stay strong ,
and hopeful without any guilt. When a person loses his selfconfidence, it results in the
development of guilt and eventually destroys the person's confidence and self-trust.
Evidence , lawyers' arguments and victims' words play a major role in any case. The court
believes the evidence over the victims words. The stronger the evidence, the greater the
chances of winning or losing the case. Evidence could be of any form from eye witness to audio
files. Documentation and evidence play a vital role among the three major factors behind the
victory of winning a case.
As said earlier it is always believed that the evidence in any form plays a major role. They
add more value and benefits to the victim towards his/her victory. Positive, advantageous
evidence is a boon to the lawyer so that his/her argument towards the win is made easy.
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To Prove Oneself when there is No Evidence
The better way to prove this is to talk and explain your innocent by choosing proper words
and body language. It is also advised not to be harsh or behave vulgarly will worsen the case
and situation.
Discussion
Crime exists in all societies. Crime helps maintain society and create greater cohesion; it
provides targets of collective moral outrage. To reduce crime and give justice to the people, the
constitution has appointed police, lawyers, and courts. Among the 50 responses we have
obtained it is noticed that more than 50% of people believe that evidence plays a role. They
give their best to attain justice, but in some cases, they get forced to abide by laws or lack
evidence. Police may also impel someone to get involved in case they are not a part of it, to get
a promotion. In such cases, one must know how to handle the situation, how to talk back, and
how to react. Knowing of necessary laws is important for every person as one may get into
such situations at any time. Fighting a case is not easy and it is seen that people believe in
lawyers over their self-trust but to bring into notice, self-confidence, and self-trust play a
major role in maintaining and analyzing an issue or problem effectively. One must know the
proper procedure from filing the case in court to winning it although it is understood that
there is no proper response obtained from the police or the officials after filing a case. In the
questionnaire circulated, it conveyed that advocates can’t be trusted all the time, and it may
end up with us fighting for our justice. To voice out your problem the best way is to reach out
to lawyers whom you feel are trustworthy and would do justice in fighting for you and your
issues, there's no point added when one raises a voice to get the lawyer to help you out. Which
says, one must be aware of laws and sections made by the government. One should also know
to explain and make the other clear regarding the problem and the scene that took place.
People should know to explain the scene and scenario that took place to prove himself
/herself. Although lawyers would help one in the cases filed, the victim should also maintain
calm in proving himself/herself. Actions may lead to issues as well which is termed nonverbal
communication. Lawyers play an adverse role in fighting against the injustice caused. They are
hard to identify and proving them in court is difficult. One must use the proper tone in court to
seek justice.
Conclusion
It’s difficult for a normal person to understand all the laws and follow those. Hence, steps can
be taken to teach like headlining some laws in the newspaper or making them understand
through advertisements. “Love all, trust a few, do wrong to none” is a famous quote by William
Shakespeare. Trust is so fragile, once broken, it can’t be fixed. Lawyers are trustworthy, but
not all are. Some safely play for their wage. Crime is sin, doing wrong to anyone is sin. People
must try hard to avoid any crime, so help themselves out of the situation with no harm. To
make India safe from crime, one must start by changing themselves. Communication plays a
major part. A slight mistake in said words, the bigger the problem it creates. Hence, here we
conclude that knowing certain important laws is as well necessary and proper communication
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is mandatory. People should be educated enough to handle their emotions, words, and actions
when a false case is filed against them, they should know how to prove themselves. And
everyone should be educated to use proper words, and sentences when conversing in any such
situation because words matter, and words that are wrongly used may affect adversely.
References
1. Bettens, T. and Warren, A., 2021. How Do Race and Gender Impact Perceptions of the
Wrongfully Convicted?
2. Chang, W., Lu, C. and Jen, W., 2008, June. A study of integrated criminal justice data base
system. In 2008 IEEE International Conference on Intelligence and Security Informatics
(pp. 290-291). IEEE.
3. Chermak, S. and Weiss, A., 2005. Maintaining legitimacy using external communication
strategies: An analysis of police-media relations. Journal of criminal justice, 33(5), pp.501-
512.
4. Copes, H., Hochstetler, A. and Ragland, J., 2019. The stories in images: the value of the
visual for narrative criminology. The Emerald Handbook of Narrative Criminology, 1,
pp.175-96.
5. Doss, D.A., Glover Jr, W.H., Goza, R.A. and Wigginton Jr, M., 2014. The foundations of
communication in criminal justice systems. CRC Press.
6. Gurbiel, A., 2018. The importance of the body language and the non-verbal signals in the
courtroom in the criminal proceedings. The outline of the problem. World Scientific News,
112, pp.74-84.
7. Henderson, M.L., Cullen, F.T., Cao, L., Browning, S.L. and Kopache, R., 1997. The impact of
race on perceptions of criminal injustice. Journal of criminal justice, 25(6), pp.447-462.
8. Huff, C., 2004. Wrongful convictions: the American experience. Canadian Journal of
Criminology and Criminal Justice, 46(2), pp.107-120.
9. Iyekolo, A., 2020. Non-Verbal Communication and Management of Interactive Conflict in
School based Violence: A Sociological Perspective. Canadian Journal of Family and
Youth/Le Journal Canadien de Famille et de la Jeunesse, 12(1), pp.260-268.
10. Khadijah, S., 2018. BULLYING AND VERBAL-NONVERBAL COMMUNICATION AMONG A
GROUP OF COLLEGE STUDENTS. Avant Garde, 6(1), pp.115-130.
11. Nassauer, A., 2015. Effective crowd policing: Empirical insights on avoiding protest
violence. Policing: An International Journal of Police Strategies & Management.
12. Parsons, S., & Sherwood, G. (2016). Vulnerability in custody: perceptions and practices of
police officers and criminal justice professionals in meeting the communication needs of
offenders with learning disabilities and learning difficulties. Disability &Amp; Society,
31(4), 553-572. doi: 10.1080/09687599.2016.1181538
13. Plotnikoff, J. and Woolfson, R., 2015. Intermediaries in the criminal justice system:
Improving communication for vulnerable witnesses and defendants. Policy Press.
14. Porter, S. and Ten Brinke, L., 2009. Dangerous decisions: A theoretical framework for
understanding how judges assess credibility in the courtroom. Legal and Criminological
Psychology, 14(1), pp.119- 134.
220
15. Ramsey, R.J. and Frank, J., 2007. Wrongful conviction: Perceptions of criminal justice
professionals regarding the frequency of wrongful conviction and the extent of system
errors. Crime & Delinquency, 53(3), pp.436-470.
16. Smith, J.D., 1991. The Advocate's Use of Social Science Research into Nonverbal and Verbal
Communication: Zealous Advocacy or Unethical Conduct. Mil. L. Rev., 134, p.173.
17. Stahn, C., 2020. Justice as message: Expressivist foundations of international criminal
justice. Oxford University Press.
18. Surette, R. (2001). Public information officers. Journal Of Criminal Justice, 29(2), 107-117.
doi: 10.1016/s0047-2352(00)00086-6
19. Vrij, A., Edward, K., Roberts, K.P. and Bull, R., 2000. Detecting deceit via analysis of verbal
and nonverbal behavior. Journal of Nonverbal behavior, 24(4), pp.239-263.
