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International Journal of Academic Research in Business and Social Sciences
Vol. 10, No. 5, May, 2020, E-ISSN: 2222-6990 © 2020 HRMARS
642
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Online Distance Learning Readiness During Covid-19
Outbreak Among Undergraduate Students
Siti Nurshahidah Sah Allam, Mohd Sufiean Hassan, Rosilawati Sultan
Mohideen, Aini Faezah Ramlan, Rusydi Mohd Kamal
To Link this Article: http://dx.doi.org/10.6007/IJARBSS/v10-i5/7236 DOI:10.6007/IJARBSS/v10-i5/7236
Received: 20 March 2020, Revised: 21 April 2020, Accepted: 02 May 2020
Published Online: 28 May 2020
In-Text Citation: (Allam et al., 2020)
To Cite this Article: Allam, S. N. S., Hassan, M. S., Mohideen, R. S., Ramlan, A. F., & Kamal, R. M. (2020). Online
Distance Learning Readiness During Covid-19 Outbreak Among Undergraduate Students. International
Journal of Academic Research in Business and Social Sciences, 10(5), 642–657.
Copyright: © 2020 The Author(s)
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Vol. 10, No. 5, 2020, Pg. 642 - 657
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JOURNAL HOMEPAGE
International Journal of Academic Research in Business and Social Sciences
Vol. 10, No. 5, May, 2020, E-ISSN: 2222-6990 © 2020 HRMARS
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Online Distance Learning Readiness During Covid-19
Outbreak Among Undergraduate Students
Siti Nurshahidah Sah Allam
Universiti Teknologi MARA (UiTM), Melaka Branch, Malaysia
Mohd Sufiean Hassan
Kolej Universiti Islam Melaka (KUIM), Malaysia
Rosilawati Sultan Mohideen, Aini Faezah Ramlan, Rusydi Mohd
Kamal
Universiti Teknologi MARA (UiTM), Melaka Branch, Malaysia
Abstract
In Malaysia, the COVID-19 outbreak reported day-by-day positive carrier statistic increasing that
force government action to impose movement control order (MCO); Malaysian stay at home to stop
the virus from spreading fast. The MCO affects the Faculty of Communication and Media Studies
undergraduate students who are just starting a new semester in the week fourth to stay at home
while learning activities continue using Online Distance Learning (ODL) mode. The implications of
online learning are the concern of university as a teaching method that is expected to improve
students’ academic performance by enhancing computer/Internet literacy competency (CIL), self-
directed learning (SDL), and motivation for learning (MOL) level. Does during the COVID-19 outbreak
that spark anxiety and panic are suits for ODL activities? A survey conducted (n= 631) among
undergraduate students to measure the level of ODL readiness. By using descriptive statistical
analysis, this study found that CIL among undergraduate students is at a high level, while SDL and
MOL reported at a low level. This study suggests the ARP initiative taken by the lecturer. The ARP
refers to attention, recognition, and pressure less. The ODL seems new norms that should not hinder
potential interactive learning for best academic performance and to drive excellent achievement.
This study highly contributes a new idea to the lecturer, faculty management, the university and HEI
as the best practice of ODL in the future.
Keywords: Online Distance Learning, Academic Performance, Computer/Internet Literacy
Competency (CIL), Self-directed Learning (SDL) and Motivation for Learning (MOL).
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Introduction
Coronavirus disease (COVID-19) is an infectious disease triggered by a new virus outbreak from
Wuhan, China. The COVID-19 has been spreading rapidly across the global, overreaching health
services and intensified with the shelter confinement. Global disease outbreak such as Middle East
respiratory syndrome coronavirus (MERS-CoV) from Saudi Arabia, Influenza A (H1N1) from Spain,
Henipavirus (Nipah) from China and Severe acute respiratory syndrome (SARS) increase death rate
statistic, basically, affect Malaysia sphere but not forcing government action to quarantine
movement.
COVID-19 outbreak in Malaysia early 2020 reported day-by-day positive carrier statistic
increasing that force government action to impose movement control order (MCO); Malaysian stay
at home to stop the virus from spreading fast. The MCO affects Communication and Media Studies
undergraduate students who are just starting a new semester in the week fourth to stay at home but
learning activities continue using Online Distance Learning (ODL) method.
Little and not exaggerate to mention, no study conducted on ODL due to disease outbreak that
creates spark panic and fear; force current semester students complete their study and new teaching
method that rarely apply during ‘peace situation’. Most of ODL study directed due to the fact that
the nature of the study programme or syllabus mode in ODL; structured, well-planned class activity
and monitored for quality academic purposes. Besides, many researchers found that ODL brought
advantages in teaching and learning activities compared to conventional; face-to-face method.
However, the future researcher needs to consider ODL method chosen by the university due to
disease outbreak and findings surprisingly and urged standard operation (SOP) for ODL conducted.
Faculty of Communication and Media Studies (FKPM), University Teknologi MARA, Melaka,
Malaysia have three undergraduate academic programs and most of the syllabus went through
blended learning (online learning) but not mandatory just optional. By using i-learn (online learning
platform initiate by the university), Google Classroom, Skype and Facebook Live majority of students
enjoy the learning activities conducted by lecturer due to the fact that students can study from
anywhere, flexibility to choose learning session, saving time and money (mobility from residential
college to a classroom) but they still have social interaction with the lecturer for assessment and
lecture consultation. Totally different mode for ODL where the student started their learning
activities from home with no physical social interaction with lecturer and groupmate to perform
course assessment and expected destruction occur can affect academic performance. These are the
challenges expected occur in applying distance education during a disease outbreak.
The conceptual definition of distance education stated that the teaching method in which
students completed their study from anywhere but not always be physically come to the lecture
session. In other words, a student learns, study, and completed in their registered courses through
online learning without having to attend any physical class such as lecture hall, computer lab, library
or any physical classes. According to (Kenny, 2010), the most of distance education today fully utilize
the Internet network and easy access for the vast majority of students either through laptop or
mobile phone (Hussin et al., 2017) whether in their own homes.
The term online distance learning is also used interchangeably with terms like e-learning (Keis
et al., 2017), blended learning (Deschacht & Goeman, 2015), online learning (Wallace, 2010) and
virtual learning with the main idea stated that learning activities in an informal form, utilize any
Internet tools and little or no physical social interaction with lecturer (Kuo et al., 2014). Besides, these
teaching methodology approaches are used to deliver course content through teleconferencing (Bhat
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645
et al., 2018), online chatting or forum , interactive video, recorded video and audio. By using online
teaching materials delivery, students are expected to have a stable Internet network connection,
workable hardware and high online learning readiness level. The most important factors need to
consider for ODL methods are the student must possess computer/Internet literacy (Hernández-
sellés & Muñoz-carril, 2019), self-directed learning (Garrison, 1987) and high level motivation of
learning (El-Seoud, 2016) to complete their study.
The purpose of this study to measure the level of computer/internet literacy, self-directed
learning and motivation of learning among undergraduate students in order to provide view student
online learning readiness to the faculty management and the lecturers for teaching planning.
Literature Review
Online Distance learning (ODL) known as online distance education (D Randy Garrison, 1987), e-
learning (Keis et al., 2017), blended learning (Deschacht & Goeman, 2015), interactive learning and
virtual learning is a form of education in which the key practice include physical separation of
lecturers and students and the use of various online applications innovate to facilitate interactive
communication between lecturers and students. Students and institutions embrace distance learning
with a good reason.
Universities benefit by adding students without having to construct classrooms and housing,
and students reap the advantages of being able to work where and when they choose (Doculan,
2016). Basically, ODL practice flexible learning activities to enhance access to education for the
society, flexible learning for disable or unhealthy people and rarely grab researchers attention is to
examine the conduct of ODL during pandemic disease where the approach is not same to ODL
program enrol by students (Kenny, 2010).
The early year of 2020, Malaysian shocked with the attack of coronavirus known as COVID-19
and seriousness level force to government action to apply for movement control order. This order is
based on Prevention and Control of Infectious Diseases Act 1988 and the Police Act 1967 where most
of the Malaysian subject to home quarantine for 14 days. Sudden command by government spark
fear and panic situation that directly affect the education system. All education centre such as school,
college and university ordered to stop the operation immediately. As for the higher learning
education system, they are allowed to go back home, all teaching and learning activities hold until
next order given by the government.
As a result, fear and panic infected among teachers and lecturers how to complete the syllabus
and the most relevant method are ODL. Being and educators, they are facing multiple issues in
conducting ODL such as little exposure to set up the platform (zoom meeting, Google Hangout Meet,
Telegram, Google Classroom etc), concerning student participation (Foon & Sum, 2014), limited
assessment method to measure course learning outcomes (Zhu et al., 2018) and less experience to
develop e-content . Besides, educators are concerned about device and Internet access among
students to join ODL sessions, technical issues facing by students to join ODL activities such as do not
have email to sign up a new account, can student explore how to use tools in the platform, do they
know how to search the assessment uploaded, basically, trigger another panic among educators.
Besides educators, student’s anxiety to join the ODL activities must take into consideration.
Before planning ODL activities, educators need to analyse about Internet access connection and
ability to use computer that develop anxiety (Tuncay, 2010), especially students in a sub-rural and
rural area, does student be able to complete the task listed in ODL activities independently without
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physical discussion with friends and lecturers (Ajmal & Ahmad, 2019), student's motivation to
complete study while facing interruption and difficulties at home. Potential factors mentioned
suggested significantly affect students online learning readiness level (Hung et al., 2010) and
academic performance (Saadé et al., 2017).
Prediction of this study supported by the previous research that highlighted the shortcomings
of ODL experience among undergraduate students. Most of the study conducted to examine online
learning mode as the nature of the study programme rather than during pandemic disease that sparks
panic, anxiety and fear feeling among students. According to Newman (2008), drawbacks of the
online learning experience by respondents who generally choose among undergraduate students
reported that Internet speed connection caused frustrations.
The ODL activities listed by the lecturer can’t be performed by students and it’s trigger anxiety
that leads fear to achieve the best result for the course enrolled. Besides Internet speed connection,
basic computer skills that need student’s ability to participate in ODL must have at least a satisfactory
level to use a computer, software, applications and online learning tools (Suprabha et al., 2017). The
competency of using computer and access to Internet connection skill align with student online
learning readiness dimension (Hung et al., 2010).
Furthermore, lack of self-discipline that refers to self-directed learning influence readiness level
due to environmental interruption such as working commitment and massive home environment.
Besides, friend interruption during ODL session by inviting the student to join online conversation
such as chatting, online shopping and gossiping influence readiness level and self-discipline. The
student who lacks self-discipline and lower level of motivation can fall in the attrition group of student
that affect their academic performance and achievement.
Another grey area of ODL, feeling of isolation with no physical social interaction to their lecturer
and classmate that influence level of readiness. Lack of physical social interaction stimuli level of
anxiety, low self-confident to perform ODL task and increase procrastination chances. All factors
highlighted in this study align with Student Online Learning Readiness (SOLR) Model that consists of
social competencies with the instructor, communication competencies, social competencies with
classmates, and technical competencies. However, this study chooses common term used by the
previous researcher to measure student online learning readiness level that predicted applicable to
online distance learning such as computer and internet literacy, self-dependent learning and
motivation of learning dimension (Hung et al., 2010).
Computer and Internet Literacy enhance Student Online Distance Learning Readiness
As ODL becomes useful to learning institutions, especially during a pandemic disease outbreak,
an observation of online learning readiness is vital for the successful implementation of ODL as a
platform for learning. Success in ODL can be achieved by understanding student online learning
readiness environments such as competency of using a computer and to reach Internet access
(Thammathirat & Tuntirojanawong, 2013). An assessment of computer and Internet literacy (known
as CIL in this study) is required for successful implementation of an ODL among students.
In ODL, personal computers/laptops are used as educational supports hardware and computer
literacy level is to ensure students able to work independently for completing ODL activities
(Suprabha et al., 2017). The CIL level measure includes the use of computers for searching reading
materials through Internet browser for ODL activities, students can upload and download documents
from the Internet and possess the ability to use application or software for ODL. From this study, the
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researcher suggests that the lecturer needs to gather CIL data before conducting ODL activities so
that learning session can be reached and participate by students.
Many researchers who study on student online learning readiness reported that CIL dimension
significantly influences readiness level among students (Hung et al., 2010). According to Gordon
(2013), many students are ready to adopt online learning technology but it must complement with a
high competency CIL. Even though most of the students accept ODL as an innovative learning
platform but lack of basic computer skills restricted them to use the e-learning platform effectively
(Kuo et al., 2014). Besides, a rigorous study on student online learning attitude reported that higher
CIL level was correlated with a higher online learning attitude. Eager to explore computer tools and
possess the ability to use Internet applications can reduce the symptom of technology stress among
students, especially in joining ODL activities (Yang et al., 2018).
It is a different atmosphere in joining the ODL as nature of the academic program mode
compared to ‘force’ to join online learning due to pandemic outbreak, no good plan, highly urge for
self-dependent learning, the student has to develop self-motivation learning for academic
achievement and equiped themselves with computer/Internet literacy. Much online learning
platform such as Google meet, Zoom meeting and Cisco Webex demand the student computer
literacy on engaging camera and microphone device to the computer for successful online
conversation. Apart from that, the student must competent to participate in online conversation by
clicking invited link, waiting for admin approval to join the meeting, ethically aware in joining online
conversation mute the microphone to avoid noise unless students intent to participate, using the
chat box to response any requirement asked by administration such as fill up a google form for
attendance, survey and the students must know how to get lecture notes or video to conduct self-
directed learning.
Self-Directed Learning enhance Student Online Distance Learning Readiness
Measuring online learning education, self-directed learning (SDL) is a vital dimension and has been
noted for decades. Enormous study reveals that SDL enhances the need for learning responsibilities
to be independent learner, enjoyable than face-to-face traditional learning, and embedded with a
sense of personal autonomy (D Randy Garrison, 1987). In reviewing the literature on SDL, researchers
highlighted that a student who has self-directed learning element are possessed high self-disciplined,
self-independent study and high self-confident to complete a task in ODL (Zainuddin, 2019).
The idea expands from the knowledge explore by the most cited researcher in SDL, Garrison
(1997) who stated that self-directed consist of self-management, self-monitoring and motivation as
interacting dimensions towards the comprehensive model of adult education. However, many
studies on student online learning readiness separate motivation dimension as another item to be
explored that known as a motivation of learning (Hung et al., 2010). This item will discover in the next
section of this research.
The notion of SDL in ODL study, the researcher must consider measuring self-independent
learning, self-management and self-monitoring level among undergraduate students (Thammathirat
& Tuntirojanawong, 2013). However, this study expands the SDL dimension by measuring self-goal
item. Successful students not only be able to manage the learning activities but must know what and
how to reach the learning goal for their performance and achievement.
The idea to expand the SDL dimension by including self-goal as unit analysis; this study
concern student ability to set up self-goal for achievement driven by self-performance (Annuar &
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Shaari, 2014). Most of the students set up a high expectation for their academic achievement but
how this goal sync with their commitment and performance, especially in ODL mode during the
pandemic outbreak.
Expected from this study on SDL students may have difficulty to present high performance on
ODL activities during a pandemic outbreak because the mode of study seems strange to them and to
work independently, completing the list of assessments with little or no contact with the lecturer
(face-to-face classroom), facing difficulty to manage their stress feeling lead to low academic
achievement that affects their final result of the study (Barak et al., 2016).
Motivation of Learning enhance Student Online Distance Learning Readiness
Motivation has been defined as the ‘engine’ of learning by Paris & Turner (1994) and supported by
Howe (1998) mentioned the fuel of human learning is motivation. By engaging mental activities with
physical that produce learning outcomes demand of time, money and commitment. This
manufacturing of learning to take place there needs to be some kind of motivation to make the
process work (Casaló et al., 2010).
Joining ODL activities during pandemic outbreak helps to make learning feasible to ensure
teaching and learning continue for the knowledge transfer (Park & Yun, 2017). But what makes
students join the ODL activities in the first place? To gain practical understandings into the causes of
joining ODL during the pandemic outbreak, this study not only have to examine a type of learning
activities but researcher also goes a step further and discover what makes learners ‘attend’ the ODL
session.
According to Howe (1998) in principles of abilities and human learning on the role of
motivation he claimed that for the student to attend in the learning session, there wishes to be an
incentive or motivation raised. Motives and incentives for people attend to learning session 1) to
complete the task for all registered courses (Chen, 2017), 2) the student needs to be strongly
motivated for higher academic achievement (Samir A. El-Seoud, 2016), 3) by establishing good study
habits the student make themselves into the productive learner.
However, integrating technology in the learning process does not positively significant to
enhance student’s learning motivation level. Online instruction and e-learning activities resulted
demand high Internet connection speed (Cooper, 2006), time consuming, effort and commitment to
take place. Besides, ODL during pandemic outbreak urge the lecturers to turn the classroom into an
online environment. The question is what specifically is required of the lecturers to develop students
learning motivation in ODL mode?
The lecturers need to understand their students’ motivations while the students must adapt
from conventional courses (face-to-face learning) into online classes to complete them (El-Seoud,
2016), they tend to fail for many reasons. This study believed that the success or failure of ODL is
related to student motivation and propose suggestion to the lecturers what to do to stimulate
student motivation. To stimulate students, the lecturers should keep in mind that motivation must
be natured in students. By explaining to their students how the online environment may be used and
encourage interaction and collaboration among their students suggested by previous study to
strengthening learning motivation.
Beside, build study groups so that students will no longer be studying in isolation and help
students to make friends by meeting fellow students in the online environment claimed to develop
learning motivation (Kenny, 2010). Furthermore, online social interaction with their students by
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monitoring the online presence and construct their learning materials reported to enhance students
learning motivation (Doculan, 2016).
Research Methodology
The respondents of this study were 631 student from Faculty of Communication and media studies
(FKPM), Universiti Teknologi MARA, Melaka Branch, Malaysia comprising three program of studies.
Student selection was based on random sampling. This study use questionnaires as a means of
collecting data. Based on the number of respondents (n = 631) with complete data in this study, the
sample size is large enough as population of FKPM student is 809. Pilot test was conducted before
proceeding to the final data collection to make sure that the reliability and validity of the instrument.
Cronbach Alpha's reliability coefficient for all three variables, above 0.70, shows a good internal
consistency (Hair et al., 2010).
Table 1 Respondent Demographic Distribution
No
Category
Frequency
Percentage %
1.
Programme
a) MC110
b) MC111
c) MC242
358
155
118
56.7
24.6
18.7
2.
Semester
a) Semester 1
b) Semester 2
c) Semester 3
d) Semester 4
e) Semester 5
f) Semester 6
13
238
34
286
41
19
2.1
37.7
5.4
45.3
6.5
3.0
3.
Computer/laptop use:
Yes
No
571
60
90.5
9.5
4.
Smartphone use:
Yes
No
617
14
97.8
2.2
5.
Computer/laptop internet access:
Yes
No
423
208
67.0
22.0
6.
Smartphone use internet access:
Yes
No
593
38
94.0
6.0
7.
Internet Data speed
a) GPRS
b) EDGE
c) 3G
d) 4G
e) 5G
5
28
244
344
10
.8
4.4
38.7
54.5
1.6
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The adapted instrument was reviewed by a specialist and subsequently a pilot test was conducted
to determine the validity of the question. The purpose of this study is to identify the indicator of the
research reliable and valid.
Research Instrument
The questionnaire consists of two parts used as the instrument of this study. Part A consists of general
information on demographic variables such as program, semester, computer use, smartphone use,
and internet use. Part B contains an e-learning readiness scale adapted from Alem et al., (2016) and
Hung et al. (2010). The scale to measure online learning is a well-established scale that has proven its
reliability because it is widely used in past studies. After run pre-test and pilot test, reliability
Cronbach’s Alpha for all three e-learning readiness scales - the constructs of computer internet
literacy, self-dependent learning and motivation of learning are between 0.963 - 0.965. This scale
contains 16 items and is measured using a 5-level interval scale of 1 = strongly disagree to 5 = strongly
agree. This measurement scale measures computer internet literacy, Self-dependent learning and
Motivation of learning.
Table 2: Validity and Reliability
Code
Items
Cronbach's
Alpha
CIL1
I feel confident using computer
.964
CIL2
I feel confident in using the Internet (Google, Yahoo) to find or gather
information for online learning
.964
CIL3
I feel confident to search, download and upload document by using
Internet.
.964
CIL4
I feel confident to use any applications or software for online learning
.963
SDL1
I carry out my own study plan.
.963
SDL2
I seek assistance when facing learning problems.
.963
SDL3
I manage time well.
.963
SDL4
I set up my learning goals
.963
SDL5
I have higher expectations for my learning performance
.963
MOL1
I am able to complete my work even when there are destructions in my
home (television, children etc)
.964
MOL2
I am able to complete my work even when there are online destructions
(friends sending email, online chatting and shopping etc)
.964
MOL3
Even in the face of technical difficulties I am certain I can learn the material
presented in online learning
.963
MOL4
I have motivation to learn for best academic achievement and performance
.965
PUL1
Using the online learning improves my performances in my studies
.964
PUL2
Using online learning will increase productivity
.963
PUL3
Using online learning enhances my effectiveness in my studies
.963
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Data Analysis
The respondents of this study were 631 student from Faculty of Mass Communication and media
studies (FKPM), Universiti Teknologi MARA, Melaka Branch, Malaysia comprising three program of
studies; 1) Diploma in Communication and Media (MC110), 2) Diploma in New Media and
Contentpreneurship (MC111) and 3) Bach. of Mass Comm. (Hons) Public Relations (MC242). Student
selection was based on random sampling. This study use questionnaires as a means of collecting data.
Based on the number of respondents (n = 631) with complete data in this study, the sample size is
large enough as population of FKPM student is 809. Pilot test was conducted before proceeding to
the final data collection to make sure that the reliability and validity of the instrument. Cronbach
Alpha's reliability coefficient for all four variables, above 0.70, shows a good internal consistency (Hair
et al., 2014).
Findings
Table 3 shows how the five-point likert scale is divided into mean-level scales. The five-point likert
scale ranged from 1 (strongly disagree) to 5 (strongly agree). To calculate the mean difference to
obtain the mean divided into three categories namely low, medium and high mean, 5 is subtracted
by 1 and divided by 3. Therefore, the interval for each min is between 1.33. The low mean levels are
1.00 to 2.33, the moderate mean levels are between 2.34 and 3.67 while the high mean levels are
3.68 to 5.00 as shown in table 3 below.
Table 3 Mean score range
Mean Scale
Level
1.00 to 2.33
Low
2.34 to 3.67
Moderate
3.68 to 5.00
High
Table 4 shows that the level of students’ computer internet literacy by program. It is found
that the mean for each program is slightly different between 2.05 to 2.40. Only MC242 program is
at moderate level. While MC111 and MC110 have a low computer internet literacy. Furthermore,
the descriptive analysis also found that the percentage of program respondents who scored high
was very small with the highest is MC242 (48.3%) followed by MC111 (38.7%) and MC110 (29.1%).
Based on the classification of the mean score range, table 4 showed that the overall mean value of
the level of Computer Internet Literacy undergraduate students is 2.16 (SD = 0.71), which is at the
level of low Computer internet Literacy.
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Table 4: The level of Computer Internet Literacy toward Perceive Usefulness of Online Learning
(n=631)
Program / level
MC110
(n = 358)
%
MC111
(n = 155)
%
MC242
(n = 118)
%
Low
23.7
14.2
8.5
Moderate
47.2
47.1
43.2
High
29.1
38.7
48.3
Mean
2.05
2.25
2.40
MC110 = Diploma in Communication and Media, MC111 = Diploma in New Media and
Contentpreneurship, MC242 = Bach. of Mass Comm. (Hons) Public Relations
Mean=2.16; SD=0.71
From the Table 5, the level of students’ Self-Dependent Learning in Perceive Usefulness of Online
Learning is low (Mean = 1.89) with a range mean by program from 1.81 (MC110) to 2.07 (MC242).
When examined in terms of the percentage of distribution at high level, MC242 program is the
higher (27%) follow by MC111 (18.7%) and MC110 (12.8%).
Table 5 : The level of Self-Dependent Learning toward Perceive Usefulness of Online Learning
(n=631)
Program / level
MC110
(n = 358)
%
MC111
(n = 155)
%
MC242
(n = 118)
%
Low
31.8
25.8
20.4
Moderate
55.3
55.5
52.5
High
12.8
18.7
27.1
Mean
1.81
1.94
2.07
MC110 = Diploma in Communication and Media, MC111 = Diploma in New Media and
Contentpreneurship, MC242 = Bach. of Mass Comm. (Hons) Public Relations
Mean=1.89; SD=0.66
From the Table 6, this study found that the level of motivation of learning among program is also at
low level (1.77) with a range mean by program from 1.75 (MC111) to 1.95 (MC242). It mean that all
respondent did not have motivation of learning during Covid-19. In addition those with high level of
motivation of learning show that all programs have a low percentage of 13.5% (MC111) to 22.1%
(MC242).
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Table 6 : The level of Motivation of Learning toward Perceive Usefulness of Online Learning
(n=631)
Program / level
MC110
(n = 358)
%
MC111
(n = 155)
%
MC242
(n = 118)
%
Low
41.9
38.1
27.1
Moderate
43.8
48.4
50.8
High
14.2
13.5
22.1
Mean
1.72
1.75
1.95
MC110 = Diploma in Communication and Media, MC111 = Diploma in New Media and
Contentpreneurship, MC242 = Bach. of Mass Comm. (Hons) Public Relations
Mean=1.77; SD=0.69
Discussion
This study conducted to measure Faculty of Communication and Media Studies (FKPM)
undergraduate students’ online distance learning readiness and the survey conducted pre-online
distance learning (ODL_ session purposely to get some view for lesson planning by the lecturers. In
order to measure students’ online learning readiness, the researchers outline possible factors from
previous study such as computer/internet literacy, self-dependent learning and motivation of
learning (Hung et al., 2010). From the data, we found that FKPM undergraduate students are possess
high computer/Internet Literacy (CIL). Not surprisingly, the students are able to use computer,
searching materials through Internet and use any applications or software for ODL such as Google
Classroom, Google Meet, Zoom meeting and uFuture (university system develop for online learning
platform).
This association may relate to nature of the program which demand students must have
computer in order to complete course assessment tasks and facilities available in campus along the
study (Li & Lee, 2016). From Table 4 this study reported that MC242 (bachelor program) possess high
CIL skills than other diploma program (MC111 and MC110) and this is due to maturity of the students
and educational background (Navani & Ansari, 2017) that expose them be able to work with software
and hardware even during ODL. Even though many study claimed that ODL was exposed students
with technology anxiety, especially computer anxiety and this study revealed that by having greater
experience working with computer can increase self-efficacy (Keis et al., 2017), enhance CIL skills and
directly reduced computer anxiety among students especially during ODL (Tuncay, 2010). The MC111
retain among the higher CIL skills than MC110 because nature of the study plan (Diploma in New
Media and Contentpreneurship) exposed the students working greater level with technology such as
applications, software and hardware than MC110 (Diploma in Communication and Media).
Another factors affect student online distance learning readiness level is self-directed learning
(SDL). The essence of SDL to measure student online distance learning readiness is to test level of
internal monitoring, external monitoring and motivational monitoring among undergraduate
students. Students are expected to have high motivation of learning to forecast personal
performance and plan personal responsibility by managing cognitive performance to achieve learning
outcomes (D R Garrison, 1997). As undergraduate students in Public University, they are expecting to
have greater SDL due to previous academic achievement. High SDL level students must be able to
International Journal of Academic Research in Business and Social Sciences
Vol. 10, No. 5, May, 2020, E-ISSN: 2222-6990 © 2020 HRMARS
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carry out their own study plan, managing time very well and having high expectation for learning
performance (Yu & Richardson, 2015). Therefore, this study take into account SDL level among
undergraduate students in FKPM in order to analyse students online distance learning readiness
(Hung et al., 2010). Surprisingly, learners who have high academic performance from previous
achievement and this study found all three programs reported low level of SDL. This findings reported
that students are not be able to manage the internal monitoring (cognitive factors), external
monitoring (environment factors) and motivational monitoring among undergraduate students.
Study by Adams et al., (2018) who study on e-learning readiness among students in Higher Education
Institution propose that to get high level of SDL and greater readiness, students must have high
technology usage, better technology availability and facility.
As discuss in Table 4, respondent do not face any constraint of using the technology for ODL
and reported CIL in high level for the three programs. What factors seems affect SDL level? Low level
of SDL justified with number of factors; 1) nature mode of study (Park & Yun, 2017), 2) low face-to-
face social interaction with support group (El-Seoud, 2016) and 3) low self-directed learning to
perform course assessment task (Yilmaz, 2017). All undergraduate program in FKPM running in UiTM
Melaka offered in full time based and naturally, course content delivered 10% blended learning and
90% face-to-face with direct interaction with the lecturer. While, ODL mode totally strange to
undergraduate students who never facing 100% online learning with minimum interaction to the
lecturer. This factor may lead to low level of SDL even high level for CIL. In addition, ODL mode allow
the lecturer and students interaction through virtual platform and very minimum contact because of
Internet connection and most of the lecturer manage to have Google meet session in less than 1 hour
as suggested by the university management due to Internet access among student.
Besides CIL and SDL, another factors that affect student online distance learning level is
motivation of learning (MOL). In order to measure level of MOL, the researcher eager to know what
motivate the students to join ODL activities and any potential destruction may affect their focus to
maintain high motivated learner. Many online learning study reported that MOL is a crucial factor for
the students to maintain focus to achieve high academic performance due to many issues such as
family, environment and technical destruction, especially during MCO. Compared to online learning
course as the nature, ODL learning during MCO affect emotional and mental stability.
Learning environment is not conducive due to all family members stay at home and limited
space to do revision and perform course assessment task these are the factors predicted affect MOL
level among undergraduate students. Besides, technical destruction such as computer failed to run
smoothly, limited Internet data and single device being used by many family members to perform
work task are the issues raised that affect MOL level. Another potential factor that affect MOL level
is lack of interaction with the lecturer to perform course assessment task. Lack of understanding to
do the assessment and the lecturer keep forcing for progress submission positively affect MOL level
among undergraduate students. Online learning open new method of interactive learning and also
expose the students with potential issues with low level of MOL that affect online learning readiness.
There many suggestion by previous researcher on how to increase or sustain readiness level
and this study conclude all ideas as ARP. The ARP strategies refers to attention, recognition and
pressure less. The attention through frequently interaction spent by lecturer toward students was
expected to increase the readiness level. By having social interaction through virtual platform, the
lecturer deliver briefing about course assessment frequently, QnA session from students being
answered effectively and any motivational say for the students to sustain their focus and strike for
International Journal of Academic Research in Business and Social Sciences
Vol. 10, No. 5, May, 2020, E-ISSN: 2222-6990 © 2020 HRMARS
655
excellence. As for recognition, any good behaviour such as full attendance of participation, best
students’ performance for the lesson or assessment (El-Seoud, 2016) being rewarded. This initiative
taken by the lecturer directly spark their interest to sustain student best achievement and
performance. Next, strategy is pressure less. Do not put strict fix time for attendance, participation
and submission for led to a higher level of involvement to the courses and a willingness to actually
join the ODL session until the end.
Conclusion
Surprisingly, findings reported from this study was evolved teaching and learning activities made to
ensure student online distance learning readiness at premium level. This study found that CIL among
undergraduate students are at high level, while SDL and MOL reported at low level. This study suggest
the ARP initiative taken by the lecturer. The A.R.P refers to attention, recognition and pressure less.
The objective of ODL is not only to complete the semester but to strike the excellence academic
performance and finally, contribute towards university academic quality. The ODL seems new norms
that should not hinder potential interactive learning for best academic performance to drive excellent
achievement. Future researcher may examine the effectiveness of ARP initiative to enhance student’s
self-directed learning and motivation for ODL. It is important to have learner analytic data for the
lecturer and management setup best ODL implementation. Besides, the study contributes to the
present body of knowledge on ODL practice and student readiness. The main contribution of this
article also provides directions for the lecturer, faculty management and to the university to apply
best practice of ODL in future. Suggestion for future study to explore the effectiveness of ARP
initiative for ODL implementation effectiveness towards undergraduate students. This is valuable
finding that contribute towards students, lecturers, faculty management, university and HEI.
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