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ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXIV October 2025
Exploring Online Group Work Interaction Using the Social Cognitive
Theory
*1
Azrin Raimi bin Ahmad,
2
Nur Adibah binti Zamri,
3
Shairah Hana binti Sulaiman,
4
Salwa binti
Othman,
5
Azrin Waheedy bin Ahmad,
6
Noor Hanim Rahmat
1,2,3,4,6
Akademi Pengajian Bahasa, Universiti Teknologi MARA, Shah Alam, Malaysia
5
Kuliyyah of Medicine, International Islamic Universiti Malaysia
*Corresponding Author
DOI: https://dx.doi.org/10.47772/IJRISS.2025.924ILEIID0037
Received: 23 September 2025; Accepted: 30 September 2025; Published: 30 October 2025
ABSTRACT
This research explores the students’ perceptions of online group work applying Bandura’s Social Cognitive
Theory as a framework, focusing on the inter-relationship between personal factors, behavioural factors, and
environmental factors. Respondents participating in this study were 250 undergraduates from two Malaysian
universities, responding to a 23-item Likert scale survey adapted from Aderibigbe (2021), with good reliability
(α = .891). Results depict that students reported high cognitive presence in terms of disseminating and using
new information, strong social presence in collaborative chances, and high teaching presence in instructional
clarity and resources. From the correlation analyses, it is revealed that all three factors showed moderate
positive relationships, indicating mutual inter-dependencies that influence online group work dynamics. The
findings on the importance of trust, clarity, and active engagement resonate with past studies in collaborative
learning. The study also provides insights on how group work can be enhanced by adapting cognitive, social
and teaching presence.
Keywords: Online group work, Social Cognitive Theory, cognitive presence, social presence, teaching
presence, collaborative learning.
INTRODUCTION
Nowadays, the world has witnessed an increasing leap from traditional physical classroom learning to online
and blended learning. This has made online group work a central feature of modern education. Therefore, in
order to complete tasks, solve problems and share knowledge, students need to collaborate virtually. While
online group work offers access and flexibility, it still has drawbacks. Sometimes online group work can lead
to miscommunication, uneven participation and difficulties in establishing social connections (Systematic
Review, 2023). Therefore, it is important to comprehend how students perceive and engage in online group
work in order to increase their efficacy.
Online group work actually refers to collaborative tasks conducted by students using internet-based platforms.
There are a few examples of online platforms such as video conferencing, discussion forums, and shared
documents. According to Hrastinski (2019), technology alone is insufficient for online collaboration, students
need to be active while interacting with their group members, build trust and be a role model among group
members. Meanwhile, blended learning is no longer viewed as a mix of online and in-person methods, but as
an integration of pedagogical thoughtfulness and purposeful design in order to enhance flexibility, engagement
and learning outcomes (Bozkurt, 2022).
Over the past two decades, even though extensive research on online learning has been conducted, the
relevance of studying group work in online learning remains high. This happened after the COVID-19
pandemic in 2020,
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when many institutions shifted to online or hybrid learning as a norm (Bond et al., 2021). Furthermore, a few
challenges have emerged due to online group work, such as digital fatigue, unequal digital literacy and the
importance of creating online group environments that can make individuals feel safe to express themselves
without fear of judgment, ridicule or punishment (Robinson & Held, 2024)
This study aims to explore how students perceive personal factors, behavioural factors and the environmental
factors in online group work. Furthermore, this study also aims to determine whether a relationship exists
between these three factors. Therefore, by examining students’ perceptions across these three factors, it is
hoped that the findings can contribute to a deeper understanding of the mechanisms that facilitate or hinder
effective collaboration in online learning environments.
Statement of Problem
In recent years, online learning has become a significant mode of education delivery, with group work as one
of the essential components of collaborative learning strategies. According to Robinson and Held (2024),
digital platforms can help students facilitate learning through flexible group interactions. However, these
researchers also highlighted that students often face issues such as a lack of motivation, digital fatigue, and
unequal participation. Another study also revealed that students find it difficult to build trust and understand
when working through online platforms (Van der Toorn, Van der Wijst, & Damen, 2015).
Therefore, these issues raise several questions on how students perceive their role in online group work
(personal factors), how students behave during online group work (behavioural factors), and how the online
environment itself (medium, tools, and group structure) influences collaboration. Hence, there are lots of
studies that focus on these factors separately, however, only a few studies have looked at how all factors work
together using Bandura’s Social Cognitive Theory (SCT).
A recent study conducted by Bach and Thiel (2024) mentioned that more research is needed to explore how
students’ personal factors and environmental factors work together in order to ensure students actively
participate in online groups. This study also found that relationships between group members, such as trust and
respect, and thinking-based activities like decision-making have helped improve group results. However, the
researchers also stated that more thorough studies focusing on how personal factors, behavioural factors and
environmental factors are connected or influence each other in online group work need to be conducted. This
aligns with the current study, which aims to investigate three factors, which are personal factors, behavioural
factors and environmental factors as interrelated components influencing online group work interaction. It is
hoped that by addressing this gap, this study will not only explain how students experience online group work,
but it will also help educators in designing collaborative tasks.
Objective of the Study and Research Questions
This study is conducted to investigate online group work. Specifically, this study is done to answer the
following questions;
How do learners perceive personal factors in online group work?
How do learners perceive behavioural factors in online group work?
How do learners perceive the environmental factors in online group work?
Is there a relationship between all factors in online group work?
Theoretical Framework: Social Cognitive Theory
This study is grounded in Bandura’s Social Cognitive Theory in which one of the key aspects is the emphasis
on the role of self-efficacy which is the belief in one’s ability to be successful in specific situations or in
accomplishing tasks. Bandura (1997) determined self-efficacy as an essential factor in how people approach
goals, tasks and challenges (Schunk & DiBenedetto, 2020). A greater motivation and persistence could be the
result of having higher self-efficacy, whereas lower self-efficacy can lead to avoidance and a lack of effort.
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Special Issue | Volume IX Issue XXIV October 2025
In relation to the concept of self-efficacy is another key aspect of the Social Cognitive Theory which is the
concept of observational learning. This concept suggests that learners improve or learn from one another
through observation, imitation and modelling. In such cases, effective models will bring trust, admiration and
respect towards the other learners or observers and this may result in the learners visualising attaining for
themselves (Mimiaga et al., 2009). They further added that learners are more motivated in practicing
behaviours that are perceived as having positive consequences or ones that are associated with a sense of self-
efficacy such as self-perceived competence. This shows that group work may contribute to positive outcomes
especially when effective models are present as indirect motivators for the other learners. Learners will tend to
develop confidence and replicate behaviours when involved in group forums, peer evaluations and
collaborative projects which have direct impacts on their academic achievement.
Types of Presence in Online Group Work
Group work is a common arrangement that is carried out in learning institutions. According to Rahmat (2020),
group work, regardless of it being physical or online, promotes collaborative communication as well as
encourages critical thinking skills. In order for group work to function well, the members of the group have to
interact effectively. This is even more so when online group work is conducted as learners are physically
distanced from one another which could lead them to be disengaged. Garrison et. al (2000) came up with the
Community of Inquiry (CoI) framework where it emphasised the importance of three interdependent elements
in making online learning experiences effective namely social presence, cognitive presence, and teaching
presence.
According to Garrison et al. (2000), social presence is the ability of learners to make themselves perceived
socially and emotionally in a community. This promotes learners to be able to communicate purposefully in an
environment while at the same time able to develop relationships by projecting their respective personalities.
The ability to do this will ensure effective collaboration between the learners as good rapport and open
communication have been established.
Cognitive presence is related to the ability of learners in constructing meaning through reflection and
discussion. Where group work is concerned, cognitive presence occurs when the learners solve problems,
discuss topics critically and co- construct knowledge among themselves. According to Garrison et al. (2000),
cognitive presence involves four phases which are (1) a triggering event, where an issue is recognised for
further inquiry; (2) exploration, where a learner explores the issue; (3) integration, where learners concept
meaning from ideas formed in the previous phase and (4) resolution, where learners can apply the newly-learnt
skills and knowledge into a real-world application.
The facilitation and direction of the cognitive and social processes is called teaching presence where learners
are guided in achieving learning outcomes. According to Anderson et al. (2001), teaching presence involves
instructional design and organisation (focuses on planning and structuring the course), facilitating discourse
(guiding interactions among learners) and direct instruction (offering subject matter expertise and explaining
errors). They also emphasised that when it comes to online group work, teaching presence can also be shared
among the learners and is not solely dependent on the instructor.
Past Studies
A lot of studies were conducted to examine various facets of online group work, with a particular focus on
understanding the dynamics of interaction, presence, and their impact on learning outcomes (Barberà et al.,
2011; Anyau et al., 2023). Researchers have examined how different types of presence that relate to social,
cognitive, and teaching contribute to the effectiveness of collaborative online learning environments (Donelan
& Kear, 2023; Thomas & Thorpe, 2018; Watson et al., 2023; Singh et al., 2022). Strong social presence,
characterised by open communication and perceived connection among participants, has been found to
significantly enhance learner engagement and satisfaction in online group activities (Bentley et al., 2015). This
is particularly critical in asynchronous contexts, where a robust teaching presence has been linked to higher
engagement, satisfaction, and overall learning effectiveness (Watson et al., 2023).
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In light of this, Wang et al. (2025) investigated cognitive and social presence in asynchronous online learning
through their Generative Co-Learners (GCL) system, which simulated peer learners using multimodal
communication, shared notes, and real-time feedback. Twelve university students, all with basic Python skills
but no prior knowledge of data structures and algorithms, participated in the study. Using pre- and post-
quizzes, Likert scale surveys, usage logs, and interviews, the researchers found that GCL significantly
enhanced perceived cognitive and social presence compared to a non-interactive baseline. Although short-term
learning gains did not differ significantly, the study illustrates how AI-mediated peer modelling can foster
collaboration, self-efficacy, and social reinforcement in line with Social Cognitive Theory (SCT).
In a related study, Borup et al. (2025) examined ways to strengthen social presence in AI-augmented
asynchronous learning. They proposed a hybrid model combining AI-generated text with instructor- and
student-created asynchronous videos. Drawing from prior empirical work, reflection, and design heuristics,
they found that pairing AI with human-generated video content humanises online interactions, strengthens
perceived connections, and clarifies the boundaries between human and AI contributions. This aligns with
SCT’s emphasis on purposeful environmental design and social reinforcement.
Similarly, Anyau et al. (2023) explored students’ perceptions of cognitive, social, and teaching presence in
online group work. Surveying 200 undergraduates at a Malaysian public university, they measured these
presences using a validated instrument adapted from Aderibigbe (2021). Results revealed strong
interrelationships among all three presences, indicating that higher levels of each dimension positively
influence the quality of group work. The findings underscore the interconnected nature of the CoI framework
and support SCT’s proposition that environmental structure, social engagement, and cognitive integration
mutually shape collaborative learning outcomes.
Adding another perspective, Presley et al. (2023) compared cognitive and social presence across synchronous
and asynchronous online instruction. Their survey of 233 university students found that synchronous
environments promote stronger real-time social connections, while asynchronous formats benefit from
structured prompts that sustain cognitive engagement. This highlights the importance of aligning
environmental design with the learning modality to optimise both social and cognitive presence.
In addition, earlier research done by Kear et al. (2014) examined whether simple design features could reduce
the impersonality often associated with asynchronous, text-based communication. In an experimental study
involving 124 distance-learning students from The Open University (UK), they compared online forums with
and without enhanced profile features such as personal photos. Findings showed that personal profiles
encouraged more personal exchanges and fostered a stronger sense of community, offering a low-tech but
effective strategy for enhancing social presence.
Other than that, Shea and Bidjerano (2010) expanded the CoI framework by introducing “learning presence,”
defined as learners’ self-efficacy and self-regulation. Using data from 3,165 online and hybrid learners across
42 institutions, they applied structural equation modelling and found that teaching and social presence
significantly predicted cognitive presence, with self-efficacy and effort regulation mediating the relationship.
This reinforces SCT’s principle of reciprocal determinism and highlights the central role of personal agency in
shaping online group work outcomes.
Collectively, these studies demonstrate that personal factors, behavioural factors, and environmental factors
work in concert to shape effective online group work. Across the literature, social, cognitive, and teaching
presence emerge as mutually reinforcing elements, while student agency and self-regulation consistently drive
positive outcomes. Effective learning design should therefore integrate environmental structure, technological
affordances, and the cultivation of learner self-efficacy and engagement. As online education evolves—
especially with the rise of AI-enhanced platforms—the key challenge lies in balancing innovation with the
human dimensions of learning.
For the present study, this means that integrating AI tools into online collaborative writing should not be
limited to technical enhancement; it must actively foster all three presences and empower learners to take
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ownership of their contributions. By doing so, AI can function not only as a support tool but also as a catalyst
for deeper engagement, stronger peer connections, and more meaningful writing outcomes within the digital
academic environment.
Conceptual Framework
Figure 1 below exhibits the study’s conceptual framework. This study combines the Social Cognitive Theory
(Bandura, 2012) and Aderibigbe’s (2021) categories of presence to understand interactions in online group
work. This study explores the relationship of different types of presence in online group work. One of the
challenges of online learning is that learners' attention is divided between the learning task and other non-
learning tasks (Rahmat, et.al., 2021). It may seem that students are more independent in an online learning
environment, the teaching presence needs to be sufficient to provide an initial push into independent learning
with ample learning prompts and materials. This study is anchored from the Bandura’s (2012) Social Cognitive
Theory which claims that in learning, there is a dynamic interaction between personal factors, behavioural
factors and the environmental factors. Personal factors refer to the learners’ beliefs and thoughts of a situation.
This is in accordance with the concept of cognitive presence where it refers to the learners’ thought processes.
Next, Bandura (2012) posits that behaviour refers to the learners’ social world and how the social world
influences their learning. This is similar to social presence by Aderibigbe (2021) where it refers to the learners’
feelings of being connected to the online social community. Finally, the environment is a crucial factor for
learning. A conducive learning environment allows learners to learn through observation and modelling. The
concept of learning environment is similar to teaching presence by Aderibigbe (2021) as the instructor is
responsible to provide a learning environment for learners; be it face-to-face or traditional classroom. The
learning environment is a “place” where learners can learn by observing, imitating, and modelling good
learning behaviour from the instructor and from their peers.
Figure 1. Conceptual framework integrating Social Cognitive Theory and Community of Inquiry model,
forming the basis for RQ1–RQ3.
METHODOLOGY
This quantitative study is conducted to examine students’ perceptions of online group work. A convenient
sample of 250 participants responded to the survey. The instrument used is a 5 Likert scale survey. Table 1
below shows the categories used for the Likert scale; 1 is for Never, 2 is for Rarely, 3 is for Sometimes, 4 is for
Very Often and 5 is for Always.
Table 1 Likert Scale Use
1
Never
2
Rarely
3
Sometimes
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4
Very Often
5
Always
Table 2 Distribution of Items in the Survey
SECTION
SOCIAL COGNITIVE THEORY
(Bandura, 2012)
ELEMENTS
(Aderibigbe, 2021)
NO. OF
ITEMS
CRONBAC
H ALPHA
B
PERSONAL FACTORS
COGNITIVE
PRESENCE
7
.769
C
BEHAVIOURAL FACTORS
SOCIAL PRESENCE
8
.789
D
ENVIRONMENTAL FACTORS
TEACHING
PRESENCE
8
.908
TOTAL ITEMS
23
.891
Table 2 shows the distribution of items in the survey. The instrument is anchored from Social Cognitive Theory
by Bandura (2012) and replicated from Aderibigbe (2021) to reveal the variables in table 3 below. Section B
has 7 items on Personal factors. Section C has 8 items on Behavioural factors and section D has 8 items on
Environmental factors.
Table 2 also shows the survey’s reliability results. The analysis indicates a Cronbach alpha of .769 for
Personal factors, .789 for Behavioural factors and .908 for Environmental factors. The total Cronbach alpha for
all 23 items is .891 and this signals a good reliability of the instrument chosen (Jackson, 2015). Further SPSS
analysis is conducted to present findings to fulfil the research questions for this study
RESULTS AND DISCUSSION
Demographic Analysis
Table 3 - Percentage for Demographic Analysis
Question
Demographic Profile
Categories
Percentage (%)
1
Gender
Male
26%
Female
74%
2
Semester
1-3
62%
4-6
27%
7 and above
11%
3
University
Local public university
94%
Local international university
6%
4
Online Learning Experience
Less than one year
35%
One year and above
65%
5
Duration of online learning
per week
2-4 hours per week
42%
5-8 hours per week
40%
More than 8 hours per week
18%
6
Class type
Mostly lectures
56%
more activities than lectures
11%
More lectures than activities
29%
Mostly activities
4%
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The table shows the demographic profile. The data shows that the greater part (74%) of the respondents were
female and the remaining (26%) samples were male. The data also showed that most of the respondents (62%)
were in their semester 1 to 3, followed by 27% from semester 4 to 6 and the remaining 11% were from
semester 7 and above. The largest proportion of the sample were from a local public university with 94%
respondents and the rest were from a local international university with only 6% respondents. From the data,
we can see that 65% of the respondents had been engaged in online learning for one year or more, while the
35% stated that they had not even a year of online learning experience. In terms of the duration of online
learning spent per week, 42% responded that they spent 2 to 4 hours, while 40% spent 5 to 8 hours, and 18%
of the respondents stated that they engaged in online learning more than 8 hours weekly. Finally, for class type,
most respondents were involved in sessions that were mostly lectures (56%), followed by 29% who had more
lectures than activities, 11% who experienced more activities than lectures, and only 4% whose classes were
mostly activity-based.
Findings for Personal Factors
This section presents data to answer research question 1- How do learners perceive personal factors in online
group work? In the context of this study, this is measured by cognitive presence.
Figure 2. Mean scores for personal factors (cognitive presence) addressing RQ1, showing information
exchange and application of ideas rated highest and confusion about ideas rated lowest.
for personal factors. Three items share the same mean of 4.1. The first is item 4 (mean=4.1, SD=0.8) which
states that group work facilitates exchange of information. Next, item 5 (mean=4.1, SD=8) reports that the
team members are able to share new information. Item 7 (mean=4.1, SD=0.8) states that the team members
used new ideas from the discussions. The lowest mean is item 2(mean=3.1, SD=0.9) which reports that team
members are confused with the ideas discussed within the online group.
Findings for Behaviour Factors
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This section presents data to answer research question 2- How do learners perceive behavioural factors in
online
group work? In the context of this study, this is measured by social presence.
Figure 3. Mean scores for behavioural factors (social presence) addressing RQ2, showing opportunities to
collaborate rated highest and emotional awareness rated lowest.
Figure 3 shows the mean for behavioural factors. Item SPQ8 shares the highest mean, which is 4 (SD=0.8),
which states that online group work offers an opportunity for students to collaborate on a task with their team
mates. Items SPQ6 and SPQ7 share the same mean of 3.8. Item SPQ6 reports that students were not hesitant to
express their opinion when online (mean=3.8, SD=0.9). Meanwhile, item SPQ7 shows that online group work
allows students to communicate clearly with their team members (mean=3.8, SD=0.9). The lowest mean is
item SPQ2, which is 2.9 (SD=1.1). This item reveals that students can sense the team’s unhappiness when
conducting an online group work.
Findings for Environmental Factors
This section presents data to answer research question 3- How do learners perceive the environmental factors
in online group work? In the context of this study, it is measured by teaching presence.
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Figure 4. Mean scores for environmental factors (teaching presence) addressing RQ3, showing task templates
and relevant examples rated highest and task instructions rated lowest.
The findings indicate that in general, learners perceived the online group work environment positively, as
reflected in consistently high mean scores for teaching presence. All items scored above 4.0, suggesting strong
agreement that the teacher’s practices supported their learning. The highest-rated aspects were the use of
templates for tasks (M = 4.3, SD = 0.7) and the use of relevant examples to aid topic understanding (M = 4.3,
SD = 0.7), highlighting the value of clear, structured guidance and concrete illustrations. Similarly, learners
reported benefiting from the teacher’s demonstrations (M = 4.2, SD = 0.7) and the clarity of task instructions
(M = 4.2, SD = 0.7). Even the slightly lower mean for topic explanation clarity (M = 4.1, SD = 0.8) still
indicates a high level of satisfaction. Overall, the results suggest that well-prepared materials, explicit
demonstrations, and structured resources significantly enhance the perceived quality of the online learning
environment.
Findings for Relationship between all factors in online group work
This section presents data to answer research question 4-Is there a relationship between all factors in online
group work? To determine if there is a significant association in the mean scores between all factors in online
group work, data is analysed using SPSS for correlations. Results are presented separately in table 4, 5 and 6
below.
Table 4 Correlation between Environment Factor and Personal Factor
ENVIRONMENTAL
PERSONAL
ENVIRONMENTAL
Pearson (Correlation
1
.407**
Sig (2-tailed)
.000
N
250
250
PERSONAL
Pearson (Correlation
.407**
1
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Sig (2-tailed)
.000
N
250
250
**Correlation is significant at the 0.01 level (2-tailed)
Table 4 shows there is an association between environmental factors and personal factors. Correlation analysis
shows that there is a moderately significant association between environmental factors and personal factors
(r=.407**) and (p=.000). According to Jackson (2015), coefficient is significant at the .05 level and positive
correlation is measured on a 0.1 to 1.0 scale. Weak positive correlation would be in the range of 0.1 to 0.3,
moderate positive correlation from 0.3 to 0.5, and strong positive correlation from 0.5 to 1.0. This means that
there is also a moderate positive relationship between environmental factors and personal factors.
Table 5 Correlation between Personal Factor and Behavioural Factor
PERSONAL
BEHAVIOURAL
PERSONAL
Pearson (Correlation
1
.482**
Sig (2-tailed)
.000
N
250
250
BEHAVIOURAL
Pearson (Correlation
.482**
1
Sig (2-tailed)
.000
N
250
250
**Correlation is significant at the 0.01 level (2-tailed)
Table 5 shows there is an association between personal factors and behavioural factors. Correlation analysis
shows that there is a moderate significant association between personal factors and behavioural factors
(r=.482**) and (p=.000). According to Jackson (2015), coefficient is significant at the .05 level and positive
correlation is measured on a 0.1 to 1.0 scale. Weak positive correlation would be in the range of 0.1 to 0.3,
moderate positive correlation from 0.3 to 0.5, and strong positive correlation from 0.5 to 1.0. This means that
there is also a moderate positive relationship between personal factors and behavioural factors.
Table 6 Correlation between Behavioural Factor and Environmental Factor
BEHAVIOURAL
ENVIRONMENTAL
BEHAVIOURAL
Pearson (Correlation
1
.468**
Sig (2-tailed)
.000
N
250
250
ENVIRONMENTAL
Pearson (Correlation
.468**
1
Sig (2-tailed)
.000
N
250
250
**Correlation is significant at the 0.01 level (2-tailed)
Table 6 shows there is an association between behavioural factors and environmental factors. Correlation
analysis shows that there is a moderate significant association between behavioural factors and environmental
factors (r=.468**) and (p=.000). According to Jackson (2015), coefficient is significant at the .05 level and
positive correlation is measured on a 0.1 to 1.0 scale. Weak positive correlation would be in the range of 0.1 to
0.3, moderate positive correlation from 0.3 to 0.5, and strong positive correlation from 0.5 to 1.0. This means
that there is also a moderate positive relationship between behavioural factors and environmental factors.
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CONCLUSION
Summary of Findings and Discussions
Four research questions on how learners perceive personal factors, behavioural factors and environmental
factors in online group work were addressed in this study. It also examines whether relationships exist among
these factors. Students are shown to highly value the exchange and application of new knowledge, while
confusion about discussed ideas scored lowest for personal factors (cognitive presence). This observation is
consistent with Hrastinski (2019), who remarked that active engagement and information exchange are
important for effective collaboration.
Meanwhile, for the behavioural factors (social presence), the students scored opportunities to collaborate the
highest and this is aligned with Bach and Thiel’s (2024) findings that collaborated projects promote
participation. However, the students scored perception of team unhappiness the lowest ratings indicating that
emotional condition is less visible or less openly exhibited in online settings. This echoes Van der Toorn et al.’s
(2015) findings on reduced interpersonal signals in online communication.
Finally, the environmental factors (teaching presence) that receive high scores from the students to clear
instructions, relevant materials and illustrative examples, aligns with Aderibigbe (2021) and Robinson & Held
(2024), who highlight structured guidance for maintaining group productivity. Correlation analyses affirmed
moderate positive relationships between all factor pairs, reflecting the relationship between cognitive, social,
and teaching presence and this data supports Bandura’s (2012) hypothesis of reciprocal determinism between
personal factors, behavioural factors and environmental facets in learning.
While the present findings highlight the importance of personal, behavioural, and environmental factors in
shaping online group work, their application may vary across cultural and educational contexts. For example,
in more collectivist educational cultures, students may place greater value on group harmony and shared
responsibility, whereas in individualist settings, learners may prioritise autonomy and individual contributions.
Similarly, institutional policies, assessment practices, and classroom norms influence how students engage in
online collaboration, suggesting that the dynamics observed in Malaysian universities may manifest differently
in other higher education systems.
Another important consideration is the role of technological barriers. Although this study focused on
pedagogical and social dynamics, effective online group work is often constrained by uneven access to stable
internet, appropriate devices, and sufficient digital literacy. Students with limited connectivity may struggle to
participate synchronously, leading to uneven contributions and reduced collaboration. Future research should
therefore account for infrastructural differences and examine how technology access intersects with personal,
behavioural, and environmental factors to influence group outcomes.
Implications and Suggestions for Future Research
The study validates the relevance of Bandura’s Social Cognitive Theory in online collaborative contexts,
showing that personal factors, behavioural factors and environmental factors do not operate independently but
mutually strengthen each other. The framework is enhanced with the integration of Aderibigbe’s (2021)
cognitive, social, and teaching presence factors within it, thus, provides strong conceptual insights for
understanding group work dynamics in online learning. This relationship suggests that treatment to boost one
factor may implicitly boost others.
Pedagogical Implications
The findings of this study suggest several important implications for teaching and learning. Firstly, instructors
should conduct more online group work or collaborative activities as these motivate knowledge sharing among
learners. This aligns with the findings of this study which found that learners shared and used new information
from the discussions. This shows that such activities encourage engagement which promotes social presence as
well as cognitive presence. At the same time, having more online group work and collaborations allows for
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Special Issue | Volume IX Issue XXIV October 2025
teaching presence among the learners as the role can be shared among the learners and they will not be
dependent on the instructor. On another note, instructors should take into consideration the amount of content
covered and the group size when conducting online group work to ensure learners are able to participate
productively in the activities. Doing this too will help in enhancing the social and cognitive presence of the
learners.
Suggestions for Future Research
Although this study provides valuable insights into learners’ perceptions towards online group work, future
research could further explore other issues on a similar topic. Future research could include a larger sample
size across different institutions so that the generalisability of the results could be enhanced. In addition,
comparative studies could also be carried out to examine the learners’ academic performance when conducting
physical group work versus online group work. This is important to see which mode of learning benefits
learners the most.
ACKNOWLEDGEMENTS
First and foremost, our utmost gratitude is dedicated to God the Almighty, whose blessings, strength, and
guidance have made this research possible. We also extend our heartfelt appreciation to Dr. Hanim binti
Rahmat and the Academy of Language Studies for their unwavering support, insightful guidance, and
invaluable contributions to the success of this study.
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