A study on students' behavioural intention and use behaviour of artificial intelligence-generated content in physical education: Employing an extended the unified theory of acceptance and use of technology model

Abstract

This study examines factors affecting AIGC acceptance among physical education students using the UTAUT model and perceived risk. Analyzing 414 Chinese students via PLS-SEM reveals that performance expectancy, social influence, facilitating conditions, and perceived risk significantly influence behavioural intention, whereas effort expectancy does not. Both facilitating conditions and behavioural intention positively influence use behaviour, with the impact of facilitating conditions being partially mediated by behavioural intention. Gender does not moderate these relationships. Findings suggest promoting AIGC in sports teaching by enhancing performance expectancy, leveraging social influence, optimizing facilitating conditions, and improving risk education.