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

Poon, W.C., Kunchamboo, V. ORCID: 0000-0002-1698-8928 and Koay, K.Y., 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:
NumberType
10.1080/10447318.2022.2119659DOI
1597606Other
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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