Résumés
Abstract
In response to the COVID-19 pandemic, many educational institutions switched to online learning to maintain learning activities. With the global pandemic, the educational environment was forced to shift from traditional face-to-face teaching or blended learning to a fully online learning model. In February 2020, China took the lead in announcing the implementation of online learning, encouraging most teachers to use it. Exploring the potential of online learning to replace traditional face-to-face teaching is a topic deserving consideration. This study explored the factors that influenced teachers’ intention to switch to online learning during the pandemic, using a push-pull-mooring model. The study analyzed 283 valid responses gathered through an online questionnaire and found that push effects, pull effects, and habits significantly impact teachers’ intention to switch from offline to online teaching. The findings provide additional insights into the future of higher education after the pandemic.
Keywords:
- COVID-19,
- migration behavior,
- online learning,
- push-pull mooring model
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Biographical notes
Chien-Liang Lin is currently an Assistant Professor at the Department of Information Management at Ming Chuan University, Taiwan, and holds a Ph.D. in Management Information Systems from National Cheng-Chi University, Taiwan. His research interests include IT adoption behavior, electronic commerce, virtual community, NeuroIS, and E-learning.
Jun-Yan Liu received his master’s degree in 2022 from the Graduate Institute of Marketing and Distribution, National Pingtung University, Taiwan. His research interests include marketing, consumer behavior, and user behavior.
Chi-Heng Li received his master’s degree in 2024 from the Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan. He is currently pursuing his Ph.D. at the Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology, Taiwan. His research interests include nursing, virtual reality, and robot-assisted learning.
Yu-Sheng Su received his Ph.D. degree from the Department of Computer Science and Information Engineering, National Central University, Taiwan, in 2010. He is currently an Associate Professor at the Department of Computer Science and Information Engineering, National Chung Cheng University, Taiwan. At the same time, he is a Joint Associate Professor at the Department of Computer Science and Engineering, National Taiwan Ocean University, Taiwan. His research interests include cloud computing, big data analytics, intelligent systems, and the metaverse.
Juan Zhou obtained her Ph.D. degree in informatics from Kyoto University. Her research interests include computer-supported collaborative learning (CSCL), learning analytics (LA), and information avoidance (IA).
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