ABSTRACT
The main objective of this study was to examine the factors of individual characteristics (e.g., self-regulation in terms of metacognition and motivation) and learning environmental expectancy (e.g., performance expectancy, effort expectancy, and social influence) that influence students’ behavioural intention to continue online courses. The questionnaire data collected from 312 college students were analyzed using the structural equation modelling approach to examine the relationship between self-regulation and the Unified Theory of Acceptance and Use of Technology model. The experimental results revealed that self-regulation in terms of metacognition and motivation directly related to performance expectancy, effort expectancy and social influence. In addition, performance expectancy, effort expectancy and motivation significantly and directly influenced students’ intention to use online courses. However, this study found that metacognition and social influence did not positively directly relate to behavioural intention. The discussion of the present findings and practical implications for possible future research have also been analyzed and concluded.
Acknowledgments
The authors would like to thank Prof. Chin-Chung Tsai for providing valuable suggestions in revising the paper.
Disclosure statement
No potential conflict of interest was reported by the authors.
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Notes on contributors
Pei-Ying Chen
Pei-Ying Chen is currently an Associate Professor at the Department of Tourism and Travel Management, Chungyu University of Film and Arts, Taiwan. She is also a PhD student at the Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan. Her research interests include flipped learning and collaborative mobile learning.
Gwo-Jen Hwang
Gwo-Jen Hwang is currently a Chair professor at the Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan. His research interests include mobile and ubiquitous learning, digital game-based learning, web-based learning and artificial intelligence in education.