Student motivation is crucial for engagement and success in online learning. This quantitative study is based

learning. Social Cognitive Theory emphasizes the interaction between personal factors, behaviour, and

with online motivation. The study refines the MLOQ framework and suggests future research on cultural,

gender, and emotional factors to sustain long-term online learning motivation.

With the swift shift to digital learning, understanding factors that support student engagement is

increasingly important. Motivation strongly influences participation, persistence, and performance in online

learning (Artino, 2008; Keller, 2008). It fuels learning behaviors, sustains attention, and shapes positive

attitudes, making learning more meaningful (Bedi, 2023).

Guided by Social Cognitive Theory (SCT), this study investigates how value, expectancy, and social support

Fragmented social interactions weaken motivation, while unclear relevance of tasks to careers or society

reduces commitment (Al-Thani & Ahmad, 2020). Disconnections between curriculum and authentic

practices further contribute to disengagement (Devkota et al., 2017).

Liu et al. (2024) found that intrinsic motivation, emotional engagement, and psychological capital strongly

predict performance in blended learning, while extrinsic motivation has a negative direct but positive

mediated effect. Other studies highlight the roles of teacher feedback (Guo & Zhou, 2021), wellbeing and

relationships (Sudarnoto et al., 2025), and consistent platform use (Clark et al., 2025). In Malaysia,

expectancy, task value, and social support are key motivators (Siok et al., 2023; Santos et al., 2025).

However, existing studies show inconsistent findings and seldom address students’ perceptions of

motivational constructs in practice. Limited research explores how university learners experience self-

Objective of the Study and Research Questions

This study is done to explore motivation to learn online. Specifically, this study is done to answer the

following questions;

Similarly, in the context of online learning today, the environment of learning has been changed to online

mode. The online mode sets the background for learning. The learner “enters” the online learning with hope

and motivation to succeed on learning. Whatever takes place within the online classroom affects the learner

(personal factors). This can take the form of modelling of behaviour from the learner through online

interactions.

Figure 1- Social Cognitive Theory (Source:Bandura, 2012)

Motivation, a crucial element in education, significantly influences a student's desire and commitment to

learning within a specific environment (Mazlan et al., 2021). Motivation in online learning is multifaceted,

encompassing both intrinsic and extrinsic factors that significantly impact student engagement and

academic outcomes (Liu et al., 2024).

concepts such as self-efficacy, observational learning, and self-regulation. Learners with high self-efficacy

are more likely to persist through challenges, especially when they receive support from mastery

experiences, role models, feedback, and a responsive learning environment (Fuente et al., 2022; Siok et al.,

2023).

Deci and Ryan’s (1985) Self-Determination Theory pinpoints autonomy, competence, and relatedness as

core psychological needs that drive motivation. Online learners are more engaged when they feel in control

of their learning (autonomy), observe themselves as capable (competence), and experience a sense of

belonging (relatedness) (Fowler, 2018; Jiang & Xie, 2022; Siok et al., 2023). These needs foster both

intrinsic motivation-driven by curiosity or personal development - and extrinsic motivation, which depends

on how well external goals are internalized by the learner.

factors, including control of learning beliefs, task value, instructor support, social engagement, and both

intrinsic and extrinsic goal orientation. Students who believe they can control their learning, find value in

course content, and receive support from instructors are more likely to remain engaged. However, the lack

of face-to-face interaction in online environments may reduce social motivation unless intentional actions

are taken to enhance peer and instructor interaction (Liu et al., 2023).

found that value, expectancy, and social support influence motivation, with curiosity, self-efficacy, and peer

expectations, organizational issues, and poor course design.

factors. Guided by SCT, this study highlights how personal, behavioral, and environmental factors shape

online learning motivation.

Conceptual Framework of the Study

Figure 2 below presents the conceptual framework of the study. This study is supported by the SCT by

Bandura (2012) and is supported by Fowler’s (2018) motivation for online learning. The SCT presents a

general representation of factors that facilitates learning, personal factors, behaviour and environment. Since

the context of this study is online learning, the environment is set as online mode. Online learning has

encouraged learners to be flexible in their quest for attaining knowledge (Rahmat & Thasrabiab, 2024). To

investigate the relationship between all motivational factors in online learning.

Figure 2- Conceptual Framework of the Study Relationship of Motivational Components for Online

Learning

Table 2 shows the distribution of items in the survey. This study is replicated from Fowler’s (2018)

constructs on motivation to learn online. Section B has 16 items on value; section C has 13 items on

thus, revealing a good reliability of the instrument chosen/used. Further analysis using SPSS is done to

This section presents data to answer research question 1- How do value components influence students’

motivation to learn online? In the context of this study, this refers to (i) intrinsic goal orientation, (ii)

mean of 4.3 (SD = 0.8) and suggests that learners were motivated to perform well in their classes to

demonstrate their abilities to family, friends, employer, or others. Items 2 and 3 share the same mean score

reflects learners’ perception of the transferability of knowledge from this course to other courses.

Figure 6 presents the mean scores for self-efficacy. The highest mean score, 4.1 (SD=0.7) was recorded for

item 6, which shows that learners expect to do well. The second highest mean score, 3.9 (SD=0.8), is shared

by items 3 and 8. Item 3 suggests that learners are confident in their ability to learn the basic concepts being

taught, while item 8 reflects that, despite the difficulty of the classes, the teachers, and skills, learners

believe they can do well. Item 2, which has the lowest mean score of 3.4 (SD = 0.8), suggests that learners