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The chain-mediating roles of generative AI literacy and TPACK in the relationship between AI support and teaching
1Faculty of International Education, Qingdao Hengxing University of Science and Technology, Qingdao, Shandong, China.
Background:
The rapid development of generative artificial intelligence (AI) is reshaping the higher education ecosystem, and the application of AI in teaching is becoming increasingly widespread. However, many teachers still use AI primarily to improve work efficiency rather than integrating it meaningfully into teaching. This study investigated the relationships among AI support, generative AI literacy, TPACK, and teaching practice among university teachers in Shandong Province, China.
Methods:
A structured questionnaire was administered online via Wenjuanxing, yielding 578 valid responses. Data were analyzed using descriptive statistics, Pearson correlation analysis, confirmatory factor analysis (CFA), and structural equation modeling (SEM).
Results:
The results showed that all variables were significantly and positively correlated. AI support had a significant positive effect on both generative AI literacy and teaching practice. Generative AI literacy had a significant positive effect on teachers' TPACK, and TPACK had a significant positive effect on teaching practice. Moreover, generative AI literacy and TPACK played significant chain-mediating roles in the relationship between AI support and teaching practice.
Conclusion:
The findings extend the application of the TPACK framework in AI-enhanced educational contexts and provide empirical evidence for higher education administrators and teachers to strengthen teachers' generative AI literacy and improve technology-integrated teaching practices.
