E-learning engagement and effectiveness during the COVID-19 pandemic: the interaction model

Poon, WC, Kunchamboo, V ORCID: https://orcid.org/0000-0002-1698-8928 and Koay, KY, 2022. E-learning engagement and effectiveness during the COVID-19 pandemic: the interaction model. International Journal of Human–Computer Interaction. ISSN 1044-7318

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Abstract

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.

Item Type:	Journal article
Publication Title:	International Journal of Human–Computer Interaction
Creators:	Poon, W.C., Kunchamboo, V. and Koay, K.Y.
Publisher:	Informa UK Limited
Date:	13 September 2022
ISSN:	1044-7318
Identifiers:	Number Type 10.1080/10447318.2022.2119659 DOI 1597606 Other
Rights:	Copyright © 2022 Informa UK Limited. This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Human-Computer Interaction on 13 September 2022, available at: http://www.tandfonline....0/10447318.2022.2119659
Divisions:	Schools > Nottingham Business School
Record created by:	Linda Sullivan
Date Added:	26 Sep 2022 11:13
Last Modified:	13 Sep 2023 03:00
URI:	https://irep.ntu.ac.uk/id/eprint/47117

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