Investigating the mediating role of TPACK on teachers’ AI competency and their teaching performance in higher education
Xiao Jian Tan, Gary Cheng, Man Ho Ling
Abstract
The growing integration of artificial intelligence (AI) in education has significantly influenced teachers' professional development. While AI offers substantial support for teaching practices and serves as a powerful instructional aid, it also places greater demands on teachers, prompting an urgent need for role transformation and skill enhancement. Therefore, the interplay among teachers' AI competency, technological pedagogical content knowledge (TPACK), and teaching performance has emerged as a critical area of research. This study employed a mixed-methods approach, combining questionnaire surveys with classroom observations, to assess the AI competency, TPACK levels, and teaching performance of 247 university teachers. Structural equation modelling (SEM) was used to analyze their relationships among the core constructs. The results revealed that teachers' AI competency positively predicted their TPACK levels, which in turn positively predicted teaching performance. Furthermore, TPACK was found to mediate the relationship between AI competency and teaching performance. Theoretically, this study elucidates the interconnections among teachers' AI competency, TPACK, and teaching performance, with a particular emphasis on the mediating role of TPACK. Practically, the findings offer implications for the design of professional development programmes aimed at strengthening teachers' AI competency, as well as for the development of data-informed teaching performance evaluation systems. These insights contribute to improving instructional quality and supporting teachers’ continuous professional growth in the era of AI.