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Generative AI acceptance and professional autonomy development among Chinese university physical education teachers:
Xiao Chen1, Qishun Yang2, Mingliang Song1
1School of Football, Wuhan Sports University, Wuhan, China.
Objective:
Generative artificial intelligence (GenAI) is increasingly being integrated into educational settings, reshaping teaching practices and teacher professional development. This study examined whether GenAI acceptance was associated with teacher professional autonomy development (PAD) among university physical education teachers through the indirect roles of teaching innovation and learning motivation, and whether technology anxiety moderated these associations.
Methods:
The study included a preliminary pilot survey and a main questionnaire survey. The pilot survey assessed item clarity, contextual suitability, feasibility, and preliminary reliability. Formal hypothesis testing was based on main-survey data from 1,020 Chinese university physical education teachers. A moderated serial conditional process model was estimated using PROCESS Model 92 with observed composite scores and 5,000 bootstrap resamples.
Results:
GenAI acceptance was significantly associated with PAD (total effect = 0.563, 95% CI [0.512, 0.615]). Teaching innovation and learning motivation showed significant indirect associations, accounting for 20.07% and 15.81% of the total association, respectively. The serial indirect association involving both teaching innovation and learning motivation accounted for an additional 5.15% (effect = 0.029, 95% CI [0.018, 0.041]). Technology anxiety weakened the positive associations between GenAI acceptance and both teaching innovation and learning motivation, with stronger attenuation observed for the teaching innovation association.
Conclusions:
The findings suggest that GenAI acceptance is positively associated with PAD among university physical education teachers and that teaching innovation and learning motivation may represent indirect correlates of this association. Technology anxiety may weaken these associations. Because teaching innovation, learning motivation, and PAD were measured in the same main survey, the findings should be interpreted as regression-based conditional process associations rather than causal, cross-lagged, or developmental effects.