The Influence of Instructor Support in Online Classes

Authors

Teo Ai Min

Akademi Pengajian Bahasa, Universiti Teknologi MARA, Shah Alam, Malaysia (Malaysia)

Lee Sek Yui

Akademi Pengajian Bahasa, Universiti Teknologi MARA, Shah Alam, Malaysia (Malaysia)

Wan Mohamad Iskandar Bin Haji Harun

Akademi Pengajian Bahasa, Universiti Teknologi MARA, Shah Alam, Malaysia (Malaysia)

Lee Chai Chuen

Akademi Pengajian Bahasa, Universiti Teknologi MARA, Cawangan Kedah, Malaysia (Malaysia)

Hong Wei San

Akademi Pengajian Bahasa, Universiti Teknologi MARA, Shah Alam, Malaysia (Malaysia)

Noor Hanim Rahmat

Akademi Pengajian Bahasa, Universiti Teknologi MARA, Shah Alam, Malaysia (Malaysia)

Li Rui

Faculty of Chinese Studies, University Tunku Abdul Rahman, Malaysia (Malaysia)

Article Information

DOI: 10.47772/IJRISS.2026.102100161

Subject Category: Education

Volume/Issue: 10/21 | Page No: 1941-1962

Publication Timeline

Submitted: 2026-09-02

Accepted: 2026-09-07

Published: 2026-10-03

Abstract

In recent years, the widespread adoption of virtual learning environments has fundamentally transformed teaching and learning practices in higher education. However, many students continue to struggle with a lack of motivation, engagement and a profound sense of isolation in virtual classrooms. This quantitative survey study investigated the relationship between instructor support and university students’ motivation to learn online, specifically examining the dimensions of expectancy, value and social support. Data were collected using a four-section questionnaire adapted from Fowler (2018) and distributed to a convenience sample of 182 undergraduate respondents in Malaysia. The findings revealed that while students highly valued the task content, they were heavily driven by grade-oriented extrinsic goals, and their academic self-efficacy dropped significantly when facing complex online materials. Independent samples t-test results showed a significant difference in online learning motivation across gender, with male students scoring higher than females (p = .034), but no significant difference across academic clusters (p = .057). Crucially, Pearson correlation analyses demonstrated strong, positive and statistically significant relationships between instructor support and all motivational variables: expectancy (r = .529), value (r = .574) and social support (r = .510, all p < .001). In terms of teaching, these results show that online classes need to move away from heavy exam-centric structures. Instead, instructors should focus on breaking down complex content into smaller steps and using real-world, practical assessments. To fill the remaining gaps in the literature, future studies should consider using mixed-methods approaches and looking closer at how a teacher's presence works in highly interactive, specialized digital environments.

Keywords

Online learning, instructor support, student motivation, task value

Downloads

References

1. Ahmad, N., Alias, F.A., Hamat, M., & Mohamed, S.A. (2024) Reliability Analysis: Application of Cronbach’s Alpha in Research Instruments. SIG: e-L earning@CS, 114-119. https://appspenang.uitm.edu.my/sigcs/ [Google Scholar] [Crossref]

2. Daphne Koller (2012). The online revolution: Education for everyone. Coursera and Online Learning Studies. Retrieved from Coursera Official Website [Google Scholar] [Crossref]

3. Fowler,S. (2018) The Motivation to learn Online Questionnaire. Doctor of Philosophy Dissertation. Graduate Faculty, The University of Georgia. Retrieved from https://getd.libs.uga.edu/pdfs/fowler_kevin_s_201805_phd.pdf [Google Scholar] [Crossref]

4. Garrison, D. R., Anderson, T., & Archer, W. (1999). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2–3), 87–105. https://doi.org/10.1016/S1096-7516(00)00016-6 [Google Scholar] [Crossref]

5. He, L. (2024) The Application of SPSS Correlation Analysis in the Study if Precision Teaching of English in Universities. Applied Mathematics and Nonlinear Science, 9(1), 1-13. http://dx.doi.org/10.2478/amns-2024-1371 [Google Scholar] [Crossref]

6. Jennifer C. Richardson, Maeda, Y., Lv, J., & Caskurlu, S. (2017). Social presence in relation to students’ satisfaction and learning in the online environment: A meta-analysis. Computers in Human Behavior, 71, 402–417. [Google Scholar] [Crossref]

7. Jennifer C. Martin, & Bolliger, D. U. (2018). Engagement matters: Student perceptions on the importance of engagement strategies in the online learning environment. Online Learning Journal, 22(1), 205–222. [Google Scholar] [Crossref]

8. John T. E. Richardson (2005). Students’ approaches to learning and teachers’ approaches to teaching in higher education. Educational Psychology, 25(6), 673–680. [Google Scholar] [Crossref]

9. Kangwa, D., Xiulan, W., Msambwa Msafiri, M., & Fute, A. (2024). Enhanced learning engagement through teaching presence in online distance education. Distance Education. Advance online publication. [Google Scholar] [Crossref]

10. Karen Swan (2001). Virtual interaction: Design factors affecting student satisfaction and perceived learning in asynchronous online courses. Distance Education, 22(2), 306–331. [Google Scholar] [Crossref]

11. Kathryn E. Linder, & Hayes, C. M. (2018). High-Impact Practices in Online Education: Research and Best Practices. Sterling, VA: Stylus Publishing. [Google Scholar] [Crossref]

12. Li, W., & Wang, W. (2024). The impact of teaching presence on students’ online learning experience: Evidence from 334 Chinese universities during the pandemic. Frontiers in Psychology, 15. https://doi.org/10.3389/fpsyg.2024.1327426 [Google Scholar] [Crossref]

13. Michael G. Moore (2013). Handbook of Distance Education (3rd ed.). New York: Routledge. [Google Scholar] [Crossref]

14. Park, C., & Kim, D.-G. (2020). Perception of instructor presence and its effects on learning experience in online classes. Journal of Information Technology Education: Research, 19, 475–488. https://doi.org/10.28945/4611 [Google Scholar] [Crossref]

15. Rahmat, N.H. (2025). A Comparison of Online Engagement for Undergraduates. International Journal of Research and Innovation in Social Sciences (IJRISS), 1X(VI), 3260-3270. https://dx.doi.org/10.47772/IJRISS.2025.906000240 [Google Scholar] [Crossref]

16. Rena M. Palloff, & Pratt, K. (2007). Building Online Learning Communities: Effective Strategies for the Virtual Classroom (2nd ed.). San Francisco: Jossey-Bass. [Google Scholar] [Crossref]

17. Shen, Q., Gao, B., Lu, J., Ge, Q., Yan, X., & Chen, B. (2024). Overcoming the “screen dilemma”: The psychological mechanisms of social presence promoting college students’ online learning engagement. Education and Information Technologies, 29(16), 21095–21114. https://doi.org/10.1007/s10639-024-12706-y [Google Scholar] [Crossref]

18. Terry Anderson (2008). The Theory and Practice of Online Learning (2nd ed.). Edmonton: Athabasca University Press. [Google Scholar] [Crossref]

19. UNESCO (2021). Reimagining Our Futures Together: A New Social Contract for Education. Paris: UNESCO Publishing. [Google Scholar] [Crossref]

20. Vetter, T.R. (2017) Descriptive Statistics: Reporting the Answers to the 5 Basic Questions of Who, What, Why, When , Where, and a Sixth, so What? Anesth Analg, 12595), 1797-1802. https://doi.org/10.1213/ane.0000000000002471 [Google Scholar] [Crossref]

21. Ziegenfuss, J. Y., Casey A. E., Jennifer M. D., Meghan M. J., Thomas E. K, and Marna, C.. (202) Impact of Demographic Survey Questions on Response Rate and Measurement: A Randomized Experiment. Survey Practice 14 (1), https://doi.org/10.29115/SP-2021-0010. [Google Scholar] [Crossref]

Metrics

Views & Downloads

Similar Articles