Exploring the link between AI usage intention and digital competence among college PE teachers: A moderated mediation model based on SCT and UTAUT

R Rong Yi D Dinghua Liu (Department of Radiology, Tongji Hospital, Shanghai Frontiers Science Center of Nanocatalytic Medicine, The Institute for Biomedical Engineering & Nano Science, School of Medicine) X Xu Sun B Bo Zhou

Abstract

As artificial intelligence (AI) technologies rapidly integrate into higher education, they impose increasing demands on the teaching approaches and digital competence of physical education teachers. However, the relationship between physical education teachers’ behavioral intention to use AI and their digital competence remains underexplored. This study focuses on college physical education teachers and examines the relationship between their intention to use AI and their digital competence. Grounded in Social Cognitive Theory (SCT) and the Unified Theory of Acceptance and Use of Technology (UTAUT), the study proposes a structural equation model incorporating behavioral intention, self-efficacy, social influence, and digital competence, with gender as a moderating variable. A questionnaire survey was conducted among 479 physical education teachers from ten universities in mainland China, and the model was tested using AMOS and SPSS. The results indicate that teachers’ behavioral intention to use AI is positively associated with their self-efficacy, perceived social influence, and digital competence, with both self-efficacy and social influence serving as significant mediators. Furthermore, self-efficacy is positively related to social influence, while gender does not exert a significant moderating effect on any of the proposed paths. This study contributes to the integrated application of SCT and UTAUT in the context of physical education in higher education and offers theoretical and practical implications for enhancing digital competence and promoting intelligent transformation among college physical education teachers.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 11
Published November 21, 2025
Pages e0334699
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (4)

R

Rong Yi

D

Dinghua Liu

Department of Radiology, Tongji Hospital, Shanghai Frontiers Science Center of Nanocatalytic Medicine, The Institute for Biomedical Engineering & Nano Science, School of Medicine

X

Xu Sun

B

Bo Zhou