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Knowledge Management & E-Learning, Vol.16, No.1. Mar 2024
Undergraduate students’ learning experiences and
strategies in online learning during the pandemic: An
Indonesian perspective
Harry Budi Santoso
Universitas Indonesia, Depok, Indonesia
Oenardi Lawanto
Utah State University, Logan, Utah, USA
Setiasih
Srisiuni Sugoto
Ni Putu Adelia Kesumaningsari
Universitas Surabaya, Surabaya, Indonesia
Ariana Yunita
Universitas Pertamina, Jakarta, Indonesia
Knowledge Management & E-Learning: An International Journal (KM&EL)
ISSN 2073-7904
Recommended citation:
Santoso, H. B., Lawanto, O., Setiasih, Sugoto, S., Kesumaningsari, N. P.
A., & Yunita, A. (2024). Undergraduate students’ learning experiences
and strategies in online learning during the pandemic: An Indonesian
perspective. Knowledge Management & E-Learning, 16(1), 110–133.
https://doi.org/10.34105/j.kmel.2024.16.005
Knowledge Management & E-Learning, 16(1), 110–133
Undergraduate students’ learning experiences and
strategies in online learning during the pandemic: An
Indonesian perspective
Harry Budi Santoso*
Faculty of Computer Science
Universitas Indonesia, Depok, Indonesia
E-mail: harrybs@cs.ui.ac.id
Oenardi Lawanto
Department of Engineering Education
Utah State University, Logan, Utah, USA
E-mail: olawanto@usu.edu
Setiasih
Faculty of Psychology
Universitas Surabaya, Surabaya, Indonesia
E-mail: setiasih@staff.ubaya.ac.id
Srisiuni Sugoto
Faculty of Psychology
Universitas Surabaya, Surabaya, Indonesia
E-mail: srisiuni@staff.ubaya.ac.id
Ni Putu Adelia Kesumaningsari
Faculty of Psychology
Universitas Surabaya, Surabaya, Indonesia
E-mail: kesumaningsari@staff.ubaya.ac.id
Ariana Yunita
Department of Computer Science
Universitas Pertamina, Jakarta, Indonesia
E-mail: ariana.yunita@universitaspertamina.ac.id
*Corresponding author
Abstract: Transitions in learning implementation have occurred at various levels
of education during the COVID-19 pandemic. Learning that previously took
place in conventional, face-to-face formats has been adjusted to fully online
·
Knowledge Management & E-Learning, 16(1), 110–133 111
learning. Not all educational institutions are equally prepared for a pandemic,
necessitating the study of student learning experiences and the strategies they
employ in online classes during the pandemic. This study focuses on the positive
and negative contributions of Virtual Learning Environment (VLE) features in
student learning experiences and strategies during the pandemic. This study used
a survey method consisting of closed- and open-ended questions. Data analysis
using descriptive statistics and qualitative data analysis was employed to obtain
several themes. Approximately 1,400 students from 23 higher education
institutions across several provinces in Indonesia participated in this research.
The results show both positive and negative contributions of VLE features.
Among the VLE features that positively contribute to learning during the
pandemic are video materials and downloadable documents. More than half of
the respondents claimed there were no negative features of the VLE. Findings
also revealed the most frequently reported negative aspect is poor internet
performance. In addition, seven themes related to student learning strategies
emerged including: considering the availability of infrastructure, monitoring the
class schedule and calendar (or announcements), collaborating with peers,
participating in the university’s learning management system, applying
notetaking strategies and other specific strategies, searching for additional
learning resources, and no specific strategy applied while learning during the
pandemic.
Keywords: Learning experience; Online learning; Regulation strategies; Virtual
learning environment; Pandemic
Biographical notes: Harry Budi Santoso, Ph.D. is a professor at the Faculty of
Computer Science, Universitas Indonesia (UI). He received his B.Sc. and M.Sc.
in Computer Science from UI, and his PhD in Engineering Education from the
Department of Engineering Education at Utah State University, USA. He is the
Head of Digital Library and Distance Learning Laboratory at UI. His research
interests include adaptive & personalized systems, self-regulated learning, HCI,
user experience, and online learning.
Oenardi Lawanto received the B.S.E.E. degree from Iowa State University, the
M.S.E.E. degree from the University of Dayton, and the Ph.D. degree from the
University of Illinois at Urbana–Champaign. He taught and held several
administrative positions at one large private university in Indonesia. He is a
Professor with the Department of Engineering Education, Utah State University,
USA. He has developed and delivered numerous international workshops on
student-centered learning and online learning-related topics during his service.
His research interests include cognition (and metacognition), self-regulated
learning, problem-solving, and online learning.
Setiasih is a lecturer and researcher at Faculty of Psychology Universitas
Surabaya. S holds a doctoral degree. Some of courses she taught include
Psychological Application of Assessment, Construction of Instruments, Survey
Research Methods, and Adolescent & Adult Development.
Srisiuni Sugoto is a lecturer and researcher at Faculty of Psychology Universitas
Surabaya. SS holds a doctoral degree. Some of courses she taught include
Psychological Application of Assessment, Child and Adolescent Assessment,
Psychological Assessment of Adult, and Educational Psychology.
Ni Putu Adelia Kesumaningsari is a lecturer and researcher at Faculty of
Psychology Universitas Surabaya. NPAK holds a master’s degree. Some of
112 H. B. Santoso et al. (2024)
courses she taught include Psychological Application of Assessment, Survey
Research Methods, Adolescent dan Adult Development, and Exceptional
Learners.
Ariana Yunita is a lecturer and researcher at Department of Computer Science,
Universitas Pertamina, Jakarta, Indonesia. She received her Bachelor of
Informatics Engineering in Institut Teknologi Sepuluh Nopember, her Master’s
degree in Information Technology from James Cook University and doctoral
degree from Faculty of Computer Science, Universitas Indonesia. Her research
interests include learning analytics, machine learning, big data analytics, and
Information Technology for education.
1. Introduction
Since the outbreak of COVID-19 in 2020, the ongoing pandemic has necessitated changes
in teaching and learning practices in higher education institutions, from traditional face-to-
face interactions to internet-based online learning. At the peak of the pandemic in March
2020, one and a half-billion students engaged in remote learning around the world
(UNESCO, n.d.). This change in conditions disrupted the learning process, as students had
to adjust and adapt to study successfully in a new learning environment. These changes
require adjustments in class administration, which has primarily taken place face-to-face
in the classroom. Although some educational institutions have previously used information
and communication technology to support the learning process, others are not yet familiar
with online learning modes, including both full online and blended learning.
Indeed, distance education and online learning are not novelties in Indonesia.
Indonesia has an open university which was established in 1984, called Universitas
Terbuka (UT). It has extensive experience in organizing distance education. Additionally,
at the national level, Indonesia has an Indonesian Online Learning System, abbreviated as
SPADA in Bahasa. It includes Online Lectures and Open Lectures held by various
universities. Blended learning has also been implemented by higher education institutions,
according to their needs and capacities. Beyond individual institutions, the Association of
Computer and Informatics Higher Education (Aptikom) has a Massive Open Online Course
(MOOC), MOOC Aptikom.
In pandemic conditions, educational institutions at various levels need time to
adjust, especially regarding the preparation of infrastructure, Virtual Learning
Environments (VLE), and teaching staff trained in online pedagogy. Lecturers have limited
time to prepare for online classes; however, they can use the available time to improve their
competence in teaching in an online learning environment.
In general, pedagogy refers to theory and practice related to teaching activities and
is also called the “art of teaching”. Teaching itself is related to knowledge clusters, types
of teaching material, technological media, learning environments, and the personal
characteristics and objectives of students. Online learning environments require a different
teaching approach than classroom teaching (Bates, 2015; Humphrey & Wiles, 2021; Leyer
et al., 2023), and online pedagogy informs the implementation of online learning.
The design of online classroom administration is closely related to the choice of
technology (Bates, 2015). This design considers the usability of a learning management
·
Knowledge Management & E-Learning, 16(1), 110–133 113
system (LMS) product, communication tools, and internet access. A variety of LMS and
communication tools are now available, even if an institution does not use a particular
application in its academic community. A number of questions related to technology must
be considered in planning online classes. To what extent has technology supported the
instructional design developed? To what extent is the accuracy and convenience of the
technology chosen to support student learning and assessment activities? How can the
challenge of high bandwidth be addressed if access is individual and outside the campus
environment? Indeed, challenges related to bandwidth encourage us to consider the details
of interaction strategies with students through online discussion forums in the LMS.
The implementation of unplanned online learning raises questions regarding VLE
features’ contribution to student learning experiences. The extent to which students adapt
to unplanned, fully online learning also needs to be studied. Previous studies have
investigated factors related to students’ experiences in online learning, including the
implementation of online learning in different contexts during the pandemic. These factors
include emotion (AlDahdouh, 2020; Jiang & Koo, 2020); course design, instructional
strategies, and online instruction (Rios et al., 2018); technology (Urazbaev & Kholmatov,
2019); feelings towards the experience, particularly negative ones (Kaufmann & Vallade,
2020; Munir et al., 2021); demography (Abdous, 2019; Rizvi et al., 2019); prior online
learning experience (Wang et al., 2020); culture (Bhagat & Chang, 2018); IT and computer
skills (Al-Taweel et al., 2020); and media diversity (Lange & Costley, 2019). Studies
related to online learning experiences during the pandemic are extensive, mostly
investigating students’ perceptions and challenges in studying online during this period.
Researchers from many countries have attempted to elucidate the phenomenon of
emergency remote learning, such as in Jordan (Al-Salman & Haider, 2021), Malaysia
(Selvanathan et al., 2020), and Indonesia (Rahiem, 2020).
However, studies of VLE features’ contribution to undergraduate students’ learning
experiences and strategies, especially during the pandemic, remain limited. Thus, it is
necessary to explore the level of student ability in using virtual learning environments and
their perspectives on their learning experiences and strategies.
Two research questions guide the current study:
RQ1: What are the positive and negative contributions of virtual learning environment
features to student learning experiences?
RQ2: What strategies do students employ to handle unplanned, fully online learning
during the pandemic?
The paper is organized into the following sections: Introduction, Literature Review,
Method, Findings and Discussion, and Conclusion.
2. Literature review
This section outlines literature relevant to the study of virtual learning environments, online
learning experiences and strategies, and fully online learning during the pandemic.
Literature was searched using the Scopus database. At the first iteration, we found 690
related papers; then, after applying inclusion and exclusion criteria using Kitchenham’s
method for Systematic Literature Review (Kitchenham et al., 2009), the final number of
papers to be reviewed totalled 17 journal papers and 1 conference paper. The papers’
publication years spanned from 2018 to 2021 (the search was conducted on 22 April 2021).
114 H. B. Santoso et al. (2024)
2.1. Virtual learning environment: Its features and learning facilitation
For each clinical case, the patient information including texts, charts, and images is
organized into different categories and subcategories. Learners may access initial
information and perform clinical actions such as ordering a specific lab test to achieve
additional information to explore and solve the problem. Most clinical cases are
progressive and patient information is achieved in a time sequence, instead of one snapshot.
Learning paradigms have shifted from teacher-centred learning to student-centered
learning (Rayens & Ellis, 2018), and the rapid development of Information and
Communication Technology (ICT) has impacted the form of both learning and teaching.
Many technologies have changed dramatically over the last two decades, but VLE has
remained stable, supporting online learning services throughout universities (Newman et
al., 2018). In general, VLEs are defined as web-based applications that implement Web 2.0
and enable learners to interact with teachers and peers, access learning materials, and use
cutting-edge technology to enhance their learning (Farrelly et al., 2020). Educational
institutions frequently develop their own form of VLE or use available open source-based
VLEs such as Moodle, a Learning Management System (LMS) platform.
One of the most prominent concepts in online learning theory that penetrates virtual
learning environments is student-centered learning (Bates, 2015), in which students are
able to learn at their own pace. Applying this concept, students become the major players
in the learning process rather than teachers, and, ideally, students are metacognitively
involved in their learning process (Wong et al., 2019). Additionally, pedagogies are
becoming more dynamic as they evolve in response to the innovative teaching and learning
modes made possible by ICT. To implement effective online pedagogy, the teacher must
integrate technology, select relevant VLE features to accommodate student needs and
preferences and optimize online teaching strategies.
While VLEs provide features, such as quizzes, assignments, virtual laboratories,
feedback forums, online discussions, and more, to enhance the learning process, not all
features are universally relevant to students. A study at Middlesex University reported
several VLE features were favored in students’ preferences (Hamutoglu et al., 2020). This
study was conducted before the COVID-19 pandemic, confirming that student preferences
for VLE features and the selection of VLE features by instructors are key concerns even in
normal learning situations. Moreover, courses made available online in response to a crisis
or disaster are significantly different from well-planned online learning experiences.
2.2. Online learning experiences and strategies
Although online learning would seem advantageous for students, since they are able to
learn at their own pace and on their own time, providing students with positive and
satisfying online learning experiences continues to be a challenge. Our review showed that
studies addressing student online learning experiences both before and during the pandemic
are extensive. Before the pandemic, the literature primarily confirmed that conducting
online learning using a specific VLE positively impacts student learning experiences, such
as augmented reality to enhance learning (Czerkawski & Berti, 2021), a simulation of
virtual patients for pharmacy students (Lim et al., 2020), and a 360o video for craft skill
learning (Hallberg et al., 2020). They acquired feedback on the learning experience created
in well-planned online learning from the learners. Before the COVID-19 outbreak, many
studies aimed to compile students’ perceptions of to shift from face-to-face to online
·
Knowledge Management & E-Learning, 16(1), 110–133 115
learning, such as in dental education in Saudi Arabia (Linjawi & Alfadda, 2018) and in
Lithuania (Valantinaitė & Sederevičiūtė-Pačiauskienė, 2020).
Meanwhile, during the pandemic, almost all studies focused on gathering student
perspectives on unplanned online learning. With varying numbers of participants, from
either a single institution or several, most of these studies were conducted online using
such tools as Google Forms, online interviews, and SurveyMonkey. The resulting literature
showed the existence of different points of view regarding the shift away from traditional,
face-to-face education, with some in favor of online learning during the pandemic and
others not. Two out of 17 papers state that students were frequently not in favor of the shift
away from traditional, face-to-face education (Humphrey & Wiles, 2021; Selçuk et al.,
2021), while other literature gave a more optimistic perspective. Several challenges that
arise in unplanned online learning are the internet connection (Prieto et al., 2021; Rasiah
et al., 2020), homework load (Rahiem, 2020), technological adaptability (Al-Taweel et al.,
2020; Prieto et al., 2021; Rahiem, 2021), and financial issues (Rahiem, 2021). On the other
hand, the reasons why students are in favor of online learning are its flexibility (Jaradat &
Ajlouni, 2021; Prieto et al., 2021; Rahiem, 2021) and the opportunity it affords for self-
development and self-care, since they do not have to travel.
Several studies claim to be representative of a specific country, such as Jordan (Al-
Salman & Haider, 2021) and Indonesia (Rahiem, 2020, 2021). Meanwhile, several others
aimed to compile student perceptions of specific subjects and specific backgrounds (e.g.,
academic background) of students during the COVID-19 outbreak, such as student
assessments of a mathematics course (Almarashdi & Jarrah, 2021) and feedback from
biology students (Humphrey & Wiles, 2021), medical students (Ibrahim et al., 2020),
theology students (Selçuk et al., 2021), and public affairs students (Ni et al., 2021). In
addition, existing literature recommends several improvements for unplanned online
learning, such as effective instructional design (Al-Salman & Haider, 2021; Ni et al., 2021;
Selvanathan et al., 2020) and increased social presence (Ibrahim et al., 2020; Ni et al., 2021;
Rahiem, 2020).
The factors impacting the online learning experience are course design, including
the type of learning resources used, the interaction between instructor and students, and
learning activities, each of which may lead to positive or negative learning experiences for
students (Caskurlu et al., 2021). Factors introduced by the students’ personalities may also
impact the learning experience (Cohen & Baruth, 2017).
According to our review, most of the studies were related to the term “learning
strategy” or “self-regulated learning strategy.” One study categorized learning strategies
into four groups: cognitive strategy, metacognitive strategy, resource management strategy,
and affective strategy (Ariffin et al., 2021). However, the definition of learning strategy is
commonly agreed to refer generally to particular learners’ patterns while learning
(Schwendimann et al., 2018). Although the use of particular learning strategies was shown
to have no significant relationship with student performance (Stark, 2019), an
understanding of students’ learning strategies may still be useful to educators.
2.3. Completely online learning during the pandemic
Due to the emergency caused by the pandemic, educational institutions have been forced
to shift learning formats from face-to-face to online teaching. This unplanned situation
creates a dilemma for teachers. On one hand, during the pandemic, teachers are expected
116 H. B. Santoso et al. (2024)
to guide, assist, and offer feedback to students remotely and conduct all teaching online,
using innovative strategies (Davis et al., 2018) and synchronized or asynchronized learning.
On the other hand, the use of many types of technology may seem overwhelming
(Hamutoglu et al., 2020), especially in the pandemic situation in which many students
return to their hometowns and not all have internet access. In this situation, a digital divide
(Talandron-Felipe, 2020) exists in Indonesia that may contribute to device accessibility
(Puspitasari & Ishii, 2016). Consequently, students with limited internet access prefer text-
based instruction to video-based instruction (Istenič, 2021).
3. Method
3.1. Research design
The research employed a survey research design. An online questionnaire was created
consisting of both closed- and open-ended questions.
3.2. Participants and context of the study
A total of 1,485 students participated in this study, including both male students (811
students) and female students (631 students). 43 students did not disclose their gender. The
students were from 23 higher education institutions that participated in the study of
unplanned online learning during this pandemic. The institutions whose students
participated are in various provinces throughout Indonesia and represent the regions of
Western (19 institutions), Central (3 institutions), and Eastern Indonesia (1 institution). The
three universities with the most participants were: two universities from the Western part
of Indonesia (207 participants from University A and 347 participants from University B)
and one university from the Central part of Indonesia (115 participants from University C).
In addition to the distribution of regions, the universities in which the respondents’ study
can be divided according to their status: state universities and private universities.
The research participants came from different levels of study. More than 50% of
the participants were freshmen (460 participants) and sophomore students (452
participants), while the remainder were junior (295 participants) and senior students (278
participants) (see Table 1).
Table 1
Participants’ level of study (academic status)
Level of study
N
%
1
Freshman and have taken under 30 credits
460
31.0
2
Sophomore and have taken 30-59 credits
452
30.4
3
Junior and have taken 60-89 credits
295
19.9
4
Senior and have taken more than 89 credits
278
18.7
Total
1,485
100
Most of the participants had a GPA greater or equal to 3.00 (84.3%). Meanwhile,
participants who had a GPA smaller than 3.00 were 15.7%. Detailed information regarding
participants’ GPAs can be seen in the following Table 2.
·
Knowledge Management & E-Learning, 16(1), 110–133 117
Table 2
Distribution of participants based on GPA
GPA
N
%
1
3.50 or more
588
39.6
2
3.00 – 3.49
664
44.7
3
2.50 – 2.99
180
12.1
4
2.00 – 2.49
40
2.7
Total
1,485
100
Of the total participants, 664 students had taken online classes before even (spring)
semester of 2020 (see Table 3).
Table 3
Participants’ experience in online class
Question
Response
F
%
Respondents’ experience of taking online classes before even
semester 2020
Yes
664
44.7
No
821
55.3
Total
1,485
100
3.3. Survey instrument
Participants’ perceptions related to their learning experiences and strategies were collected
using an online questionnaire. The questionnaire consists of demographic information
questions and closed- and open-ended questions related to learning experiences and
strategies while engaged in fully online learning during the pandemic.
The survey consists of nine questions (eight multiple choice and one open-ended)
and requires no more than 15 minutes for completion. The questions are categorized into
students’ demographic profiles, perceptions regarding the online learning environment
used in their classes and learning strategies while taking online lessons. Details of the
survey items can be found in the Appendix I.
3.4. Data collection procedures
Data were collected in the online questionnaires involving undergraduate students from
July 2020 to September 2020. The students participated in the study voluntarily. They were
asked to reflect upon their participation in their online classes before filling out the
questionnaire. They were free to leave the study or to not fill out the questionnaire. No
reward was given to the students.
3.5. Data analysis
Data collected were analyzed using descriptive statistics and thematic analysis. To observe
the learning strategies implemented by students while taking online classes during the
pandemic, researchers conducted an analysis of the frequency of keywords that appeared,
as well as a thematic analysis of answers given by participants. Using a free web-based text
mining tool, www.voyant-tools.org, researchers obtained a number of relevant keywords.
118 H. B. Santoso et al. (2024)
Thematic analysis was applied to analyze the qualitative data and reveal the themes for
open-ended questions. There are five steps for data analysis, which are in accordance with
Peel’s (2020) recommendations: 1) getting familiar with the data; 2) coding the extract
from data; 3) creating code categories from the codes; 4) constructing themes from the
coded extracts that have been classified; and 5) Contextualize and represent the results.
The coding analysis was conducted by two raters.
4. Findings and discussion
This section elaborates on the findings that address two research questions.
4.1. Findings and discussion for RQ1
RQ1: What are the positive and negative contributions of virtual learning environment
features to student learning experiences?
In implementing online learning, each higher education institution uses a different
online learning environment with variations in their features. Respondents stated that most
of the features used were exams, as seen in Table 4, including midterm and final semester
exams (1,337 respondents); downloadable documents or files (1,270 respondents);
electronic homework collection (1,266 respondents); video material (1,224 respondents);
and quizzes, including formative quizzes/exercises (1,143 respondents). It is also
interesting to note that 1,347 respondents stated that virtual laboratories were not available
in the learning environment they used. In addition, as many as 1,091 respondents stated
that no assistance was provided online by teaching assistants.
Table 4
Features of the VLE available for the respondents
Features of the VLE
N
%
1
Exams (midterm exam and final exam)
1,337
90.0
2
Downloadable documents or files
1,270
85.5
3
Electronic homework collection
1,266
85.3
4
Video material
1,224
82.4
5
Quizzes, including formative/practice quizzes
1,143
77.0
6
Online group discussions
984
66.3
7
Online tutoring sessions
761
51.2
8
Synchronous chat facility
757
51.0
9
Projects (tasks that are larger than homework)
702
47.3
10
Assistance provided by assistant lecturers
394
26.5
11
Virtual labs
121
8.1
12
Others
20
1.3
In online learning, it is crucial to identify the features that support the student
learning process. Below, Table 5 shows the features of the online learning environment
that respondents thought contributed positively to their learning activities. A total of 1,144
respondents stated that video material contributed positively to their learning activities.
The existence of downloadable documents also contributed positively, according to 1,029
students (69.3%).
·
Knowledge Management & E-Learning, 16(1), 110–133 119
Nearly half of the respondents (49.4%) stated that online group discussions also
made a positive contribution to their learning activities. These results align with previous
studies of the relationship between online collaborative learning and learning performance.
Previous studies also found that several teaching and learning strategies can enhance the
learning experience: team-based learning in online learning (Hernández et al., 2021), social
presence (Akcaoglu & Lee, 2018; Andel et al., 2020; Weidlich & Bastiaens, 2019),
effective instructional strategies (Rios et al., 2018), active learning (Lamon et al., 2020),
collaborative learning (Vahed & Rodriguez, 2020), and learning design (Bearman et al.,
2020).
Other features that have an average percentage of contribution, between 20-48%
were quizzes, exams, internet network performance, and synchronous chat facility.
Meanwhile, less contributed to students’ learning experiences were virtual labs. Virtual
labs might have the least impact on students’ learning experiences because it is rare to be
implemented by the instructor in online learning. Only specific courses need virtual labs to
feature in online learning.
Table 5
Positive contributions of VLE features to students’ learning experiences
Features of the VLE
N
%
1
Video material
1,144
77.0
2
Downloadable documents or files
1,029
69.3
3
Electronic homework collection
773
52.1
4
Online group discussion
734
49.4
5
Online tutoring sessions
699
47.1
6
Quizzes, including formative/practice quizzes
690
46.5
7
Exams (midterm exam and final exam)
679
45.7
8
Internet network performance
646
43.5
9
Synchronous chat facility
505
34.0
10
Assistance provided by assistant lecturers
294
19.8
11
Projects (tasks that are larger than homework)
280
18.9
12
Virtual labs
110
7.4
13
I feel that none of these features have a positive contribution to my learning activities
58
3.9
14
Others
15
1.0
The findings of this study indicate that not all features in the online learning
environment contribute positively to student learning activities. Table 6, below, shows
features of the online learning environment that respondents believed contributed
negatively to their learning activities. Some of these features include projects or tasks that
are larger than homework (33.9% of respondents), virtual laboratories (15% of
respondents), and internet network performance (39.7% of respondents). Meanwhile,
29.8% of respondents stated they felt that none of these features had a negative contribution
to learning activities. Several previous studies mentioned internet providers as a primary
challenge in unplanned online learning (Prieto et al., 2021; Rahiem, 2021; Rasiah et al.,
2020).
The responses from the respondents were almost consistent. Several features that
have highly positive contributions to their learning experience were also features that have
less negative contributions to their learning experience. Video materials and downloadable
120 H. B. Santoso et al. (2024)
documents were in the first and second rank in Table 5. In line with that, these features
were in the 12th and 13th rank in Table 6.
Table 6
Negative contributions of VLE features to students’ learning experiences
Features of the VLE
N
%
1
Internet network performance
589
39.7
2
Projects (tasks that are larger than homework)
504
33.9
3
I feel that none of these features have a negative contribution to my learning activities
443
29.8
4
Virtual labs
223
15.0
5
Exams (midterm exam and final exam)
194
13.1
6
Quizzes, including formative/practice quizzes
175
11.8
7
Online group discussions
164
11.0
8
Electronic homework collection
141
9.5
9
Online tutoring sessions
134
9.0
10
Assistance provided by assistant lecturers
129
8.7
11
Synchronous chat facility
106
7.1
12
Video material
71
4.8
13
Downloadable documents or files
41
2.8
14
Others
29
2.0
Nearly half of respondents, 686 or 46.2% of respondents, stated that online learning
features have an influence or effect on their learning activities (see Table 7). Other features
that do not highly influence students’ learning experiences, with a percentage between 10-
20%, were synchronous chat facility, virtual lab, online group discussions, assistance
provided by assistant lecturers and projects. Meanwhile, the internet network performance
was in the bottom rank, which means that the internet performance highly influences
student’s learning experience.
Table 7
VLE features that do not influence students’ learning experiences
Features of the VLE
N
%
1
I feel that all of them have an influence or effect on students’ learning activities
686
46.2
2
Synchronous chat facility
227
15.3
3
Virtual lab
211
14.2
4
Online group discussions
180
12.1
5
Assistance provided by assistant lecturers
171
11.5
6
Projects (tasks that are larger than homework)
156
10.5
7
Electronic homework collection
140
9.4
8
Quizzes, including formative/practice quizzes
138
9.3
9
Downloadable documents or files
130
8.8
10
Online tutoring sessions
128
8.6
11
Exams (midterm exam and final exam)
127
8.6
12
Video material
117
7.9
13
Internet network performance
107
7.2
14
Others
8
0.5
·
Knowledge Management & E-Learning, 16(1), 110–133 121
4.2. Findings and discussion for RQ2
RQ2: What strategies do students employ to handle unplanned, fully online learning
during the pandemic?
To observe the learning strategies implemented by students while taking online
classes during the pandemic, researchers conducted an analysis of the frequency of
keywords that appeared as well as a thematic analysis of answers given by participants.
Based on the results of the analysis, the researchers obtained a number of relevant
keywords, shown below in Table 8.
Table 8
Most frequent words in the corpus
Words
N
Assignment
373
Checking
362
Schedule
289
Well-organized
188
Course
185
Calendar
167
Online
164
Class
160
Creating
159
Announcement
128
Lesson
127
Information
115
Group
114
Time
114
Looking at
110
Learning material
105
Checking
97
Learning
94
Friend
89
Lecturer
87
Deadline
73
Following
73
Course
72
Taking notes
70
Alarm
61
Findings also revealed the effective strategies respondents employed during their
online learning. From the data gathered, the researchers divided each participant’s
comments into different categories. Each category represents a theme found in the
qualitative data. The researchers identified seven themes: (1) considering the availability
of the infrastructure; (2) time scheduling and monitoring the calendar (or announcements);
(3) collaborating with peers; (4) monitoring and participating in the university’s learning
management system; (5) applying notetaking strategies and other specific strategies; (6)
additional learning resources; and (7) no specific strategy applied while learning during the
pandemic.
122 H. B. Santoso et al. (2024)
4.2.1. Theme 1: Considering the availability of infrastructure
A number of 41 statements from students show that some students considered the
availability of infrastructure or facilities to support their learning during the pandemic. This
finding is in line with previous studies which show that poor internet connection is a
challenge for online learners (Prieto et al., 2021; Rasiah et al., 2020). Moreover, the issue
of the digital divide (Puspitasari & Ishii, 2016; Talandron-Felipe, 2020), especially in
Indonesia, is a challenge that policymakers should address. These are the examples of
students’ statements:
“Prepare the internet device properly...”
“Usually, I check the facilities provided by the campus for online classes and write
it down in my cellphone notes.”
“Set an alarm every hour when a class is about to start and ensure a stable
connection.”
“Make sure the city has enough internet and install an alarm, so I am not late if
there are classes.”
4.2.2. Theme 2: Monitoring the class schedule and calendar (or announcements)
A number of 810 statements from students indicate that some students were concerned
about the schedules of their learning activities and the calendar of announcements while
learning in completely online classes during the pandemic. This finding is very much in
accordance with previous studies in Jordan (Jaradat & Ajlouni, 2021) and Malaysia (Rasiah
et al., 2020). Despite the high flexibility of time and place afforded by studying online,
53% of respondents in Jordan faced the challenge of lacking time management skills
(Jaradat & Ajlouni, 2021), and students in Malaysia reported the same issue (Rasiah et al.,
2020). Therefore, learning strategies related to scheduling are considered important (Aeon
& Aguinis, 2017) for online learners. These are examples of students’ statements:
“Regularly check class groups to find out academic information because sometimes
a lot of information provided on the website or mobile app is not in sync properly.”
“Regularly I like to check whether there are assignments given by the lecturer and
also always check the deadlines for submission.”
“I always record important dates such as quiz and exam dates.”
“I am able to manage time and adequate rest.”
4.2.3. Theme 3: Collaborating with peers
A number of 63 statements show that some students chose to learn collaboratively.
Collaborative learning is an effective active learning strategy. Studying online during the
pandemic may cause negative feelings in students (Kaufmann & Vallade, 2020; Munir et
al., 2021) since lecturers and peers are not physically present. By learning collaboratively
with peers, students cooperate and ask their friends if they encounter difficulties in learning.
These are examples of students’ statements:
·
Knowledge Management & E-Learning, 16(1), 110–133 123
“Not ashamed to ask questions and ask for opinions when experiencing problems in
the learning process, especially with friends who are in the same group on the
project.”
“Discuss with friends to discuss problems in class.”
“Cooperating with friends to remind each other of the class material, deadlines,
etc.”
“Ask a friend if I don’t understand.”
4.2.4. Theme 4: Monitoring and participating in the university’s learning
management system
A number of 119 statements from students indicate that some students regularly monitored
updates in the university’s LMS. This theme suggests that LMS promotes student-centered
learning (Hasibuan & Santoso, 2005) and plays a number of roles in enhancing learning,
such as facilitating students’ self-regulated learning (Wong et al., 2019) and increasing
student engagement through VLE features such as quizzes and synchronous and
asynchronous discussions. However, the usability and user experience of LMS should be
considered to maximize its benefits. These are examples of students’ statements:
“Because the online system has to catch up to the demands of this pandemic, it is
much more accessible than it has ever been. I am rarely late on an assignment
anymore. I can learn things at my own pace, and the test calendar provided by my
campus is very good.”
“Regularly checking the online web course that has been determined by the campus.”
“Checking the learning platform and class group, then adjusting the time and
assignments/classes according to priority.”
“Every day I see on Microsoft Teams if maybe there are friends who are asking
questions or have other info.”
“I always check the e-learning website from my university every morning, then set
an alarm for every course hour.”
4.2.5. Theme 5: Applying notetaking strategies and other specific strategies
A number of 273 statements from students reveal that they applied notetaking strategies
and other specific strategies while learning in completely online classes during the
pandemic. Studies found that notetaking strategies contribute positively to students’
learning performance or academic achievement (Salame & Thompson, 2020). These are
examples of students’ statements:
“I set goals every day.”
“Recording material in the form of presentation or video files.”
“Doing assignments properly and always attending online lectures.”
“My strategy is to study hard and have discipline.”
“Joining each class to understand the material. Regularly checking the material.”
124 H. B. Santoso et al. (2024)
4.2.6. Theme 6: Searching for additional learning resources
A number of 30 statements from students show that some students were willing to ‘go the
extra mile’ to search for additional learning resources. Students with the initiative to learn
more can be characterized as self-directed or self-regulated learners, one of the
characteristics of which is possessing metacognitive skills. One study states that
metacognitive strategy is an invaluable skill in learning online, which may present a
challenge for instructors attempting to support students’ self-regulated learning skills while
teaching online (Wong et al., 2019). These are examples of students’ statements:
“Looking for other learning resources.”
“Looking for a video as clarification.”
“Studying the material through YouTube or other media so that it can be
understood.”
“Often open the laptop, study alone on YouTube.”
“Looking for learning materials on the internet when not understanding any lessons,
watching the video uploaded by the lecturer.”
4.2.7. Theme 7: No specific strategy applied while learning during the pandemic
A number of 60 statements from students show that some students did not apply specific
learning strategies to completely online learning during the pandemic. Although some
students stated that they did not have a specific strategy, this statement represented a small
proportion of all respondents. The statement may have come from students who were
familiar with online classes. They may have been taking online classes for several
semesters before the pandemic. These are examples of students’ statements:
“There is no strategy.”
“Nothing. I just follow what is, learning online as usual.”
“So far, I don’t have any strategy. I tend to look at the possibility of when
assignments are given and collected because every Saturday and Sunday, I have to
go back to the village.”
From the student preferences and perceptions of VLE features and the thematic
analysis of students’ learning strategies, several implications and recommendations for
stakeholders emerge. The recommendations are provided below.
5. Conclusion
This study examined the use of VLE features and students’ learning strategies during the
COVID-19 outbreak. It can be concluded that among the VLE features that positively
contribute to learning during the pandemic are video materials and downloadable
documents/files. More than half of the respondents claimed that there were no negative
features of the VLE. However, the most frequently reported negative aspect is poor internet
performance, with roughly 40% of respondents experiencing this problem. Furthermore,
seven themes of students’ learning strategies were found in this study: considering the
availability of infrastructure, time scheduling and monitoring the calendar (or
·
Knowledge Management & E-Learning, 16(1), 110–133 125
announcements), collaborating with peers, monitoring, and participating in the university’s
learning management system, applying notetaking strategies and other specific strategies,
additional learning resources, and no specific strategy applied while learning during the
pandemic. To conclude, the research findings provide insight to any stakeholders in
education, including students, lecturers, and institutions, on how to improve their strategies
for online learning implementation, particularly during the pandemic.
6. Recommendations
The current research findings suggest several recommendations for relevant stakeholders.
Firstly, the research findings are useful for lecturers or instructors to accommodate learners’
experiences and strategies and reconsider their teaching strategies. Choosing appropriate
learning resources and offering alternatives to students with internet performance problems
is one of the recommendations. Another is improving course design (such as course
materials and learning activities) by thoroughly adapting to the pandemic situation. For
course materials, lecturers might provide more videos, and for learning activities, lecturers
might implement collaborative learning, which would be beneficial to students who are in
favor of collaborating with peers. Furthermore, lecturers should identify the most effective
instructional design in order to optimize the learning process during the pandemic.
Secondly, institutions might deliver relevant policies and regulations to support
learners, especially concerning infrastructure. Reliable infrastructure should be prepared
for online learning. Additionally, training related to online pedagogy could be offered to
support lecturers who teach online. The usability and user experience of the current VLEs
in institutions also deserve consideration. Since video is the most popular item among
online students, institutions might employ specialists in video editing to accompany
lecturers.
Thirdly, students may use these research findings to improve their learning
strategies. Students who are reluctant to read additional learning materials might alter their
approach or begin to practice notetaking.
Author Statement
The authors declare that there is no conflict of interest.
Acknowledgements
This research was supported by Direktorat Riset dan Pengembangan (Risbang) Universitas
Indonesia through Hibah Publikasi Terindeks Internasional (PUTI) Q1 2022 (Number:
NKB-393/UN2.RST/HKP.05.00/2022).
ORCID
Harry Budi Santoso https://orcid.org/0000-0003-0459-0493
Oenardi Lawanto https://orcid.org/0000-0002-9554-1226
126 H. B. Santoso et al. (2024)
Setiasih https://orcid.org/0000-0002-3906-9078
Ni Putu Adelia Kesumaningsari https://orcid.org/0000-0003-3378-9995
Ariana Yunita https://orcid.org/0000-0001-7883-5065
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Appendix I
Survey Instrument (English Translation)
Q0. Write down the last five digits of your Student Identification Number?
Q1. Your current academic status:
▪ First Year (Freshman) – Has taken under 30 credits
▪ Second Year (Sophomore) – Has taken 30-59 Credits
▪ Third Year (Junior) – Have taken 60-89 Credits
▪ Fourth Year (Senior) – Have taken more than 89 credits
Q2. What is your current cumulative GPA?
▪ 3.50 or more
▪ 3.00 – 3.49
▪ 2.50 – 2.99
▪ 2.00 – 2.49
▪ Under 2.00
Q3. What is your gender type?
▪ Men
▪ Woman
▪ Prefers not to mention
Q4. Have you ever taken online classes before this Even semester 2020?
▪ Yes
▪ No
Q5. What features in the online learning environment are available for you to use in your online
classes? Please select all that are appropriate.
▪ Video material
▪ Synchronous chat facility
▪ Electronic collection of homework
▪ Projects (tasks that are bigger than homework)
▪ Virtual lab
▪ Quizzes, including formative/practice quizzes
▪ Exams (mid and final)
▪ Online tutoring sessions
▪ Online group discussion
▪ Downloadable documents or files
▪ Assistance provided by a lecturer assistant
▪ Others: _______________________
Q6. Which of the following features of the online learning environment do you think contributes
POSITIVELY to your learning activities? Please select all that are appropriate.
▪ Video material
▪ Synchronous chat facility
▪ Electronic collection of homework
▪ Projects (tasks that are bigger than homework)
132 H. B. Santoso et al. (2024)
▪ Virtual lab
▪ Quizzes, including formative/practice quizzes
▪ Exams (UTS and UAS)
▪ Online tutoring sessions
▪ Online group discussion
▪ Downloadable documents or files
▪ Assistance provided by a lecturer assistant
▪ Internet network performance
▪ Others: _______________________
▪ I don’t think any of these features contribute POSITIVELY to my learning activities
Q7. Which of the following features of the online learning environment do you think is contributing
NEGATIVELY to your learning activities? Please select all that are appropriate.
▪ Video material
▪ Synchronous chat facility
▪ Electronic collection of homework
▪ Projects (tasks that are bigger than homework)
▪ Virtual lab
▪ Quizzes, including formative/practice quizzes
▪ Exams (UTS and UAS)
▪ Online tutoring sessions
▪ Online group discussion
▪ Downloadable documents or files
▪ Assistance provided by a lecturer assistant
▪ Internet network performance
▪ Others: _______________________
▪ I don’t think any of these features contribute NEGATIVELY to my learning activities
Q8. Which of the following features of the online learning environment do you think is contributing
UNEFFECTIVELY to your learning activities? Please select all the options that you think are
appropriate.
▪ Video material
▪ Synchronous chat facility
▪ Electronic collection of homework
▪ Projects (tasks that are bigger than homework)
▪ Virtual lab
▪ Quizzes, including formative/practice quizzes
▪ Exams (UTS and UAS)
▪ Online tutoring sessions
▪ Online group discussion
▪ Downloadable documents or files
▪ Assistance provided by a lecturer assistant
▪ Internet network performance
▪ Others: _______________________
▪ I feel all of them have INFLUENCE / EFFECT on my learning activities
Q9a. How do you feel about your ability to succeed in an online learning environment? Please select
all that apply.
▪ Motivated
▪ Not sure
▪ Safe
▪ Fear
·
Knowledge Management & E-Learning, 16(1), 110–133 133
▪ Confident
▪ Isolated or feeling alone
▪ Anxious
▪ Depression
▪ Comfortable
▪ Depressed
▪ Independent
▪ Have the power/control to do something
▪ Feeling supported
▪ Others (please specify): _______________________
Q9b. Why do you feel you have the feelings shown above.
Q10. How do you describe how you feel during online learning?
▪ I grow MORE POSITIVE about my ability to succeed
▪ I grew up MORE NEGATIVELY about my ability to succeed
▪ My feelings have NOT changed
Q11. What are you doing to adapt to your new online learning environment in this class?
Q12. What effective strategies did you use during online learning in this class (e.g. regularly checking
calendars/course announcements, etc.)?
