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Research Article

The effects of technostress, intolerance of uncertainty, and ICT competence on learning burnout during COVID-19: a moderated mediation examination

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Received 15 Dec 2020
Accepted 25 Apr 2022
Published online: 13 May 2022
 

ABSTRACT

During global COVID-19 outbreak, universities in many countries were closed, and students experienced the exclusive online learning as never before. This study aimed to examine the mediating role of Intolerance of Uncertainty (IU) in the effects of university students’ technostress caused by remote learning on three dimensions of learning burnout, namely emotional exhaustion, cynicism, and academic inefficacy, and possible moderating role of gender, ICT competence, and course load in the indirect effects of university students’ technostress on their learning burnout mediated by IU. Altogether 801 Chinese students from 72 universities voluntarily participated in this study by filling out an online questionnaire consisting of Technostress Survey, Maslach Burnout Inventory-Student Survey, and Intolerance of Uncertainty Scale-12. The participants reported relatively low technostress, learning burnout with a moderate level of IU during online learning. Structural equation modelling showed that: 1) technostress positively predicted IU, emotional exhaustion, and academic inefficacy; 2) IU partially mediated the effects of technostress on emotional exhaustion, cynicism, and academic inefficacy. 3) ICT competence moderated the indirect effects of technostress on emotional exhaustion via IU while moderating effects of gender and course load were not found.

Acknowledgments

The authors thank Prof. Jon-chao Hong, Dr. Cixiao Wang for commenting on the original manuscript, all colleagues for distributing surveys, and all the students who participated in the study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/02188791.2022.2071835

Additional information

Funding

This study was partially funded by the National Natural Science Foundation of China (Project Number: 61977005).

Notes on contributors

Guoqing Zhao

Guoqing Zhao is an associate professor in the School of Educational Technology, Faculty of Education at Beijing Normal University. His research interests include technology-enhanced learning, teaching thinking, scientific inquiry learning, and PLC-based teachers’ professional development.

Rongchi Zhao

Rongchi Zhao is a master student in the School of Educational Technology, Faculty of Education at Beijing Normal University. Her research interests include technology-enhanced learning, teaching thinking and scientific inquiry learning.

Xiaomei Yan

Xiaomei Yan is a a lecture in Education Dept of Shanghai Jiaotong University and also a researcher in Research Institution of Science Education at Beijing Normal University. Her research interests include technology-enhanced learning, and scientific inquiry learning.

Simone C. O. Conceição

Simone C. O. Conceição is a professor in the Department of Administrative Leadership, University of Wisconsin-Milwaukee School of Education. Her research interests include adult learning, online education, impact of technology on teaching and learning, learning design, and international education.

Zhuo Cheng

Zhuo Cheng is a master student in the School of Educational Technology, Faculty of Education at Beijing Normal University. His research interests include technology-enhanced learning, teaching thinking and educational statistics.

Qingqing Peng

Qingqing Peng is a master student in the College of Education for the Future at Beijing Normal University. Her research interests include technology-enhanced learning, and scientific inquiry learning.

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