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

被引：0
作者：
Wu, Qianjin [1 ,2 ]
Li, Shanshan [2 ]
Xin, Shuang [3 ]
Hou, Qian [4 ]
Li, Ping [4 ]
机构：
[1] Shandong Univ, Sch Phys Educ, Jinan 250061, Shandong, Peoples R China
[2] Sichuan Univ, Sch Phys Educ, Chengdu 610065, Sichuan, Peoples R China
[3] Zhejiang Gongshang Univ, Sch Tourism & Urban Rural Planning, Hangzhou 310018, Zhejiang, Peoples R China
[4] Hunan Normal Univ, Coll Phys Educ, Changsha 410012, Hunan, Peoples R China
来源：
JOURNAL OF HOSPITALITY LEISURE SPORT & TOURISM EDUCATION | 2025年 / 36卷
关键词：
Artificial intelligence-generated content; Physical education; Unified theory of acceptance and use of technology; Partial least squares structural equation modelling; INFORMATION-TECHNOLOGY; FIT INDEXES; RISK; ADOPTION; UTAUT;
D O I：
10.1016/j.jhlste.2025.100547
中图分类号：
G40 [教育学];
学科分类号：
040101 ; 120403 ;
摘要：
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.
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收藏
页数：15
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