E-learning Satisfaction during COVID-19 Pandemic Lockdown: Analyzing Key Mediators

Document Type : Original Research


1 Research Center for Software Technology and Management (SOFTAM), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia

2 School of Accounting & Business Management, FTMS Global Malaysia, Cyberjaya, Malaysia

3 Faculty of Social Sciences & Humanities, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia


An ample of studies have recently been conducted to explore and analyze the predictors of students’ e-learning satisfaction (ELS) during the COVID 19 pandemic lockdown. However, research is scarce on investigating mediating roles of key aspects, such as students’ learning stress (SLS) and students’ willingness to learn (SWL). This research intends to investigate mediating effect of SLS and SWL in relationships among selected IT characteristics factors and ELS during lockdown enforced to curb the COVID 19 pandemic. Selected factors of IT characteristics are IT complexity, IT pace change and IT presenteeism. The data was collected through online questionnaire survey on 470 students in Malaysia selected by employing the convenience sampling during the Movement Control Order period when universities and colleges shifted to online learning platforms. The data was then subjected purification, assessment of normality and reliability. Thereafter, confirmatory factor analysis and validity assessment were conducted. Finally, hypotheses were tested by formulating structural equation model using IBM SPSS AMOS 24.0.  The mediation effects were tested by developing parallel mediation structural model. The findings show that SLS fully mediates relationship between IT pace change and ELS. Students’ willingness to study fully mediates relationships between IT presenteeism and IT pace change with ELS.


Main Subjects

Abidah, A., Hidaayatullaah, H. N., Simamora, R. M., Fehabutar, D., & Mutakinati, L. (2020). The Impact of Covid-19 to Indonesian Education and Its Relation to the Philosophy of “Merdeka Belajar.” Studies in Philosophy of Science and Education, 1(1), 38–49.
Ali, M., Alam, N., & Rizvi, S. A. R. (2020). Coronavirus (COVID-19)—An epidemic or pandemic for financial markets. Journal of Behavioral and Experimental Finance, 27.
Almaiah, M. A., & Alyoussef, I. Y. (2019). Analysis of the effect of course design, course content support, course assessment and instructor characteristics on the actual use of E-learning system. IEEE Access, 7, 171907–171922.
Almaiah, M. A., Al-Khasawneh, A., & Althunibat, A. (2020). Exploring the critical challenges and factors influencing the E-learning system usage during COVID-19 pandemic. Education and Information Technologies, 25, 5261-5280.
Ames, C. (1984). Achievement attributions and self-instructions under competitive and individualistic goal structures. Journal of Educational Psychology, 76(3), 478.
Anderman, E. M., & Maehr, M. L. (1994). Motivation and schooling in the middle grades. Review of educational Research. Review of Educational Research, 64(2), 287–309.
Anderson, D., Imdieke, S., & Standerford, N. S. (2011). Feedback please: Studying self in the online classroom. Online Submission, 4(1), 3–15.
Awang, Z. (2015). SEM made simple: A gentle approach to learning Structural Equation Modeling. MPWS Rich Publication.
Bartik, A. W., Bertrand, M., Cullen, Z. (2020). The impact of COVID-19 on small business outcomes and expectations. Proceedings of the National Academy of Sciences, 117(30), 17656-17666.
Benson, A. (2002). Using online learning to meet workforce demand: A case study of stakeholder influence. Quarterly Review of Distance Education, 3(4), 443−452.
Carliner, S. (2004). An overview of online learning (2nd ed.). Human Resource Development Press.
Chi, X., Becker, B., Yu, Q.,  et al. (2020). Prevalence and psychosocial correlates of mental health outcomes among chinese college students during the coronavirus disease (COVID-19) pandemic. Frontiers in Psychiatry, 11(1), 803–816.
Conrad, D. (2002). Deep in the hearts of learners: Insights into the nature of online community. Journal of Distance Education, 17(1), 1–9.
Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5–22.
Donni, R., Dastane, O., Haba, H. F., & Selvaraj, K. (2018). Consumer perception factors for fashion M-Commerce and its impact on loyalty among working adults. Business and Economic Research, 8(2), 168. https://doi.org/10.5296/ber.v8i2.13044
Elliot, A. J., & Church, M. A. (1997). A hierarchical model of approach and avoidance achievement motivation. Journal of Personality and Social Psychology, 72(1), 218.
Ferneini, E. M. (2020). The financial impact of COVID-19 on our practice. Ournal of Oral and Maxillofacial Surgery, 78(7), 1047.
Gonzalez, T., de la Rubia, M. A., Hincz, K. P. et al. (2020). Influence of COVID-19 confinement in students performance in higher education. PLOS One, 15(10), 239490.
Gorges, J., & Kandler, C. (2012). Adults’ learning motivation: Expectancy of success, value, and the role of affective memories. Learning and Individual Differences, 22(5), 610-617.
Haba, H. F., & Dastane, O. (2019). Massive open online courses (MOOCs)–understanding online learners’ preferences and experiences. Journal of Learning, Teaching and Educational Research, 18(8), 227–242.
Hair, J.F., Ringle, C.M., Sarstedt, M. . (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Plan, 46(1), 1–12.
Harackiewicz, J. M., Durik, A. M., Barron, K. E.,  et al. (2008). The role of achievement goals in the development of interest: Reciprocal relations between achievement goals, interest, and performance. Journal of Educational Psychology, 100(1), 105.
Hashim, N. A., Mukhtar, M., & Safie, N. (2019). Factors affecting teachers’ motivation to adopt cloud-based E-learning system in Iraqi deaf institutions: A pilot Study. In 2019 International Conference on Electrical Engineering and Informatics (ICEEI), 272–277.
Helmke, A., & Weinert, F. E. (1997). (n.d.). Bedingungsfaktoren schulischer leistungen. Max-Planck-Inst. für Psychologische Forschung.
Hsu, H. H. (2012). (2012). The acceptance of Moodle: An empirical study based on UTAUT. Creative Education, 3(1), 44.
Islam, S. D. U., Bodrud-Doza, M., Khan, R. M.,  et al. (2020). Exploring COVID-19 stress and its factors in Bangladesh: a perception-based study. Heliyon, 6(7), 43–99.
Kapasia, N., Paul, P., Roy, A.,  et al. (2020). Impact of lockdown on learning status of undergraduate and postgraduate students during COVID-19 pandemic in West Bengal, India. Children and Youth Services Review, 116(1), 105194.
Kayali, M., Safie, N., & Mukhtar, M. (2019). The effect of individual factors mediated by trust and moderated by IT knowledge on students’ adoption of cloud based e-learning. Int. J. Innov. Technol. Explor. Eng, 9(2).
Kinshuk, D., & Yang, A. (2003). Web-based asynchronous synchronous environment for online learning. United States Distance Education Association Journal, 17(2), 5–17.
Knowles, M. S., Holton, E., & Swanson, R. (2005). The adult learner: the definitive classic in adult education and human resource development (6th ed.). Elsevier.
Krapp, A. (2000). Interest and human development during adolescence: An educational-psychological approach. In J. Heckhausen (Ed.), Motivational psychology of human development: Developing motivation and motivating development (pp. 109–129). Elsevier Science. https://doi.org/https://doi.org/10.1016/S0166-4115(00)80008-4
Malhotra, M. K., & Grover, V. (1998). An assessment of survey research in POM: from constructs to theory. Journal of Operations Management, 16(4), 407–425.
Manzoor, A. (n.d.). Online teaching and challenges of COVID-19 for inclusion of persons with disabilities in higher education. 2020. https://dailytimes.com.pk/595888/online-teaching-and-challenges-of-covid-19-for-inclusion-of-pwds-in-higher-education/.
Martin, F., Ahlgrim-Delzell, L., & Budhrani, K. (2017). Systematic review of two decades (1995 to 2014) of research on synchronous online learning. Journal of Distance Education, 31(1), 3-19.
Martins, L. L., & Kellermanns, F. W. (2004). A model of business school students’ acceptance of a web-based course management system. Academy of Management Learning & Education, 3(1), 7–26.
Organisation, W. H. (n.d.). No Title. https://www.who.int/news-room/detail/27-04-2020-who-timeline-covid-19
Pajarianto, H., Kadir, A., Galugu, N.,  et al. (2020). Study from home in the middle of the COVID-19 pandemic: Analysis of aeligiosity, teacher, and parents support against academic stress. Journal of Talent Development and Excellence, 12(2), 1791-1807.
Palmer, L. (2013). The relationship between stress, fatigue, and cognitive functioning. College Student Journal, 47(2), 312–325.
Piccoli, G., Ahmad, R. & Ives, B. (2001). Web-based virtual learning environments: A research framework and a preliminary assessment of effectiveness in basic IT skills training. MIS Quarterly, 25(2), 401-426.
Reeve, J., Deci, E. L., & Ryan, R. M. (2004). Self-determination theory: A dialectical framework for understanding socio-cultural influences on student motivation. Big Theories Revisited, 4(1), 31–60.
Rehman, U., Shahnawaz, M. G., Khan, N. H.,  et al. (2020). Depression, anxiety and stress among Indians in times of Covid-19 lockdown. Community Mental Health Journal, 4(1), 1–7.
Roy, S., Raju, A., & Mandal, S. (2017). An empirical investigation on E-retailer agility, customer satisfaction, commitment and loyalty. Business: Theory and Practice, 18, 97–108. https://doi.org/10.3846/btp.2017.011
Safie, N., & Morshidi, A. (2007). An evaluation of cultural roles and usability attributes in learning management system. Multimedia Communication, 5(1), 55–72.
Safie NMS, & Morshidi A. H., Dastane, O. (2020). Success factors affecting e-learning satisfaction during COVID-19 pandemic lockdown. Int. J. Adv. Trends Comput. Sci. Eng, 9(5).
Sahu, P. (2020). Closure of universities due to coronavirus disease 2019 (COVID-19): impact on education and mental health of students and academic staff. Cureus, 12(4).
Sakib, N., Bhuiyan, A.K.M.I., Hossain, S. et al. (2020). Psychometric validation of the Bangla Fear of COVID-19 Scale: Confirmatory factor analysis and Rasch analysis. International Journal of Mental Health and Addiction, 4(3), 1–12.
Samadarshi, S. C. A., Sharma, S., & Bhatta, J. (2020). An online survey of factors associated with self-perceived stress during the initial stage of the COVID-19 outbreak in Nepal. The Ethiopian Journal of Health Development, 34(2).
Sandars, J., Correia, R., Dankbaar, M.,  et al. (2020). Twelve tips for rapidly migrating to online learning during the COVID-19 pandemic. MedEdPublish, 9(1).
Satar, N. S. M., Dastane, O., & Ma’arif, M. Y. (2019). Customer value proposition for E-Commerce: A case study approach. International Journal of Advanced Computer Science and Applications, 10(2). https://doi.org/10.14569/ijacsa.2019.0100259
Scagnoli NI, Choo J, T. J. (2019). Students’ insights on the use of video lectures in online classes. Br J Educ Technol, 50(1), 399–414.
Schunk, D. H., & Zimmerman, B. J. (2012). Motivation and self-regulated learning: Theory, research, and applications. Routledge. Lawrence Erlbaum Associates.
Scott, D., Durnell, C., Gauvin, S.,  et al. (1997). Internet based collaborative learning: an empirical evaluation. Third Australian World Wide Web Conference.
Seetharaman, P. (2020). Business models shifts: Impact of Covid-19. International Journal of Information Management, 55(1), 102173.
Shahzad, A., Hassan, R., Aremu, A. Y.,  et al. (2020). Effects of COVID-19 in E-learning on higher education institution students: the group comparison between male and female. Quality & Quantity, 4(2), 1–22.
Simpson, O. (2000). Supporting students in open and distance learning. Kogan Page.
Son, C., Hegde, S., Smith, A.,  et al. (2020). Effects of COVID-19 on college students’ mental health in the United States: Interview survey study. Journal of Medical Internet Research, 22(9), 21279.
Strielkowski, W. (2020). COVID-19 pandemic and the digital revolution in academia and higher education. https://doi.org/doi:10.20944/preprints202004.0290.v1
UNESCO. (2020). Education: From disruption to recovery. https://en.unesco.org/covid19/educationresponse/
Wan, Y. S. (2020). Education during COVID-19. Brief Ideas, 19(2), 3–9.
Wang, Y., Di, Y., Ye, J., & Wei, W. (2021). Study on the public psychological states and its related factors during the outbreak of coronavirus disease 2019 (COVID-19) in some regions of China. Psychology, Health & Medicine, 26(1), 13–22.
WHO Timeline - COVID-19, April 2020, https://www.who.int/news-room/detail/27-04-2020-who-timeline-covid-19. World Health Organisation
Wu, J. H., Tennyson, R. D., Hsia, T. L., & Liao, Y. W. (2008). Analysis of e-learning innovation and core capability using a hypercube model. Computers in Human Behavior, 24(1), 1851–1866.
Yang, Z., & Liu, Q. (2007). Research and development of web-based virtual on-line classroom. Computers & Education, 48, 171–184.