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Color code tool made of cardboard to be used by students.
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Effective assessment is an important way for improving the learning process. There are existing guidelines for assessing the learning process, but they lack holistic digital knowledge society considerations. In this paper the authors propose a method for real-time evaluation of students’ learning process and, consequently, for quality evaluation of...
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With the development of underwater image processing, more and more underwater image restoration algorithms have been proposed. To date, most underwater image degradation perception methods are ineffective in multi-color environments. In this paper, we proposed a referenceless image degradation perception method based on the underwater imaging model...
Citations
... Whitehill et al. (2014) classified student engagement estimation methods into three categories, namely: manual, semi-automatic and automatic methods. Manual methods include paper-based or computer-based self-reports (Haddad 2014), survey-based methods like National Survey of Student Engagement (NSSE) (Kuh, G.D. 2003), Student Engagement Instrument (SEI) (Appleton et al., 2006), observational checklist, and rating scale (Odiri Amatari, 2015; Dzelzkaleja & Kapenieks, 2016) methods. These methods remain laborious, tedious, interruptive, and vulnerable to biases. ...
Students' disengagement problem has become critical in the modern scenario due to various distractions and lack of student-teacher interactions. This problem is exacerbated with large offline classrooms, where it becomes challenging for teachers to monitor students' engagement and maintain the right-level of interactions. Traditional ways of monitoring students' engagement rely on self-reporting or using physical devices, which have limitations for offline classroom use. Student's academic affective states (e.g., moods and emotions) analysis has potential for creating intelligent classrooms, which can autonomously monitor and analyse students' engagement and behaviours in real-time. In recent literature, a few computer vision based methods have been proposed, but they either work only in the e-learning domain or have limitations in real-time processing and scalability for large offline classes. This paper presents a real-time system for student group engagement monitoring by analysing their facial expressions and recognizing academic affective states: ‘boredom,’ ‘confuse,’ ‘focus,’ ‘frustrated,’ ‘yawning,’ and ‘sleepy,’ which are pertinent in the learning environment. The methodology includes certain pre-processing steps like face detection, a convolutional neural network (CNN) based facial expression recognition model, and post-processing steps like frame-wise group engagement estimation. For training the CNN model, we created a dataset of the aforementioned facial expressions from classroom lecture videos and added related samples from three publicly available datasets, BAUM-1, DAiSEE, and YawDD, to generalize the model predictions. The trained model has achieved train and test accuracy of 78.70% and 76.90%, respectively. The proposed methodology gave promising results when compared with self-reported engagement levels by students.
... Useful solution was found in the real time color codes learning process assessment approach, implemented by Riga Technical University [22,23,24]. It suggests an enrichment of LMS with learning objects (LO) acquisition (understanding) level tool which indicates ( Fig. 1): ...
Taking into account that each new day an amount of daily processed data grows exponentially, it is obvious that knowledge society needs flexible, effective and high performing tools to retrieve, learn and apply necessary information. Learning management systems become more and more intelligent and adaptive. Learning analytics instruments give course developers a possibility to assess and analyze learners' activities and behavior patterns within e-learning environment, allowing to propose them personalized self-paced learning path and types of learning objects. This paper discusses challenges in development of adaptive learning management system and outlines its prospective models and properties.
... Image coding and decoding are denoted as an important fields of image processing [5,6,7,8]. Most of the published works at this filed are concentrated the accurate results and real time processing [9,10]. ...
Image coding becomes an interested issue for its extensive use in wide range of applications. This work deals with the Fast approaches of hardware implementation for Forward Discrete Cosine Transform (FDCT) and the Inverse Discrete Cosine Transform (IDCT). These approaches are normally used for image coding and decoding applications. The implemented approaches are built using hardware design with specific control parameters to speed up the processing. The implemented approach based on one dimensional Discrete Cosine Transform (1D-DCT) and fast transposing through high access memory that offer real time operation. The control system of flow of pixels is built to have two principal processing of rows and columns and the flow of coefficients comes from high speed access memory. The implementation of the system is done to achieve high speed and accurate results. The differences between the original image and the recovered image for all tested sizes are very small and it is about 10⁻¹⁶.
... A new approach, presented in the authors previous paper (Dzelzkaleja, 2016) for continuously evaluating learning process in real time was presented. In this paper the method is further analysed with the data gained form the first experimental observations. ...
Colour is one of the codes that has proved successful in helping students retrieve knowledge, become aware of their strengths and weaknesses and provide them with an opportunity to improve their knowledge, skills and confidence effectively. Using descriptive statistics and hypothesis testing, this paper presents a comparative analysis of the performance of an experimental group of students who received colour-coded feedback and a control group of students who received non-coded feedback. The analysis is aimed at determining the contribution of colour-coded feedback to successful error identification and correction and the development of metacognitive activity. The results of this study point to more successful error correction in self-revisions and improved performance in translation, revision and reflection tasks among the students who received colour-coded feedback. This project is suggestive of enhanced metacognition, particularly for the specificities of scientific and technical translation.
