Epistemic network analysis of in-service teachers’ competency to teach artificial intelligence for secondary education

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Teachers play a vital role in driving successful artificial intelligence (AI) education. Research on teachers' competency to teach AI (TCAI) is still limited. This study investigated the progression of in-service teachers' AI competency with the Technological Pedagogical Content Knowledge (TPACK) framework using Epistemic Network Analysis (ENA). Seven secondary school teachers who engaged in an AI education project were interviewed over a three-year period of curriculum development and implementation. The differences in ENA patterns in various stages indicated an evolution of teachers’ TPACK over the years. The ENA results also revealed different patterns between experienced and less experienced teachers. Experienced teachers tend to integrate their TPACK components with pedagogical considerations, whereas less experienced teachers focus more on content-related elements. The differences in ENA patterns indicate distinct progression paths with different focuses, highlighting the need to tailor professional development activities for different groups of teachers at various stages. These findings underscore the importance of continuous support and targeted training to enhance teachers' AI competency in AI education.