%0 Journal Article
%@ 10447318
%A Poon, W.C.
%A Kunchamboo, V.
%A Koay, K.Y.
%D 2022
%F scholars:17518
%I Taylor and Francis Ltd.
%J International Journal of Human-Computer Interaction
%K E-learning; Education computing; Learning systems, Computer self-efficacy; E - learning; Effective learning; Interaction modeling; Learning effectiveness; Learning satisfactions; Managerial implications; Steep learning curve; Structural equation models; Student expectations, COVID-19
%R 10.1080/10447318.2022.2119659
%T E-Learning Engagement and Effectiveness during the COVID-19 Pandemic: The Interaction Model
%U https://khub.utp.edu.my/scholars/17518/
%X COVID-19 has disrupted the education environment. But, little is known on how e-learning engagement impacts learning effectiveness and satisfaction with the interaction of computer self-efficacy in the study from home context. We examine how students� expectations to adopt e-learning contribute to e-engagement that influences e-learning effectiveness and satisfaction and explore the moderating role of computer self-efficacy between e-learning engagement and effectiveness using structural equation modelling. Results from the 212 usable data reveal that e-learning expectations to adopt e-learning contribute positively to e-learning engagement, which is fundamental for effective learning that leads to learning satisfaction. Computer self-efficacy appears to have a significant positive effect on e-learning effectiveness, but no evidence on e-learning engagement. Computer self-efficacy moderates the relationship between e-learning engagement and perceived e-learning effectiveness in the study from home context during the pandemic. The findings have important managerial implications for administrators in the universities. Students are adjusting and facing a steep learning curve as they work through the mechanics of e-learning in the new normal COVID-19 environment. They learn to interact with peers and lecturers via electronic means, digest and absorb complicated content and concepts through unfamiliar e-learning platforms in home spaces. Limitations and future research are discussed. © 2022 Taylor & Francis Group, LLC.
%Z cited By 3