AI+循證教研與教師實踐性知識發展

AI-Enhanced Evidence-based Teaching Research and the Production of Teachers’ Practical Knowledge

本研究聚焦AI+循證教研與教師實踐性知識生產。文獻綜述AI+循證教研與教師實踐性知識生產的理論依據與實踐路徑，以跨界學習和組織知識創造為理論視角開展質性研究，選取四位參與AI+循證教研的教師作為個案。研究過程借助訪談、文件分析、參與式觀察等方法蒐集資料，探討AI+循證教研如何促進教師實踐性知識發展？本研究發現，教師在參與AI+循證教研過程中發展了關於學生、關於教學、關於教學情境、關於自我以及教育信念五類實踐性知識，並基於組織知識創造理論提出融合AI與循證教研促進知識社會化、外顯化、組合化、內隱化的教師實踐性知識發展可行路徑。本研究發現解釋了AI+循證教研與教師實踐性知識發展的關係，為推進AI+循證教研提供實證基礎。

This study focuses on AI-enhanced evidence-based teaching research and the production of teachers’ practical knowledge. By reviewing the theoretical foundations and practical approaches of AI-enhanced evidence-based teaching research and the production of teachers’ practical knowledge, it conducts a qualitative study from the theoretical perspectives of cross-boundary learning and organizational knowledge creation, selecting four teachers participating in AI-enhanced evidence-based teaching research as cases. During the research process, data are collected through methods such as interviews, physical artifact analysis, and participant observation, and then analyzed via three-level coding to address the research questions: how does AI-enhanced evidence-based teaching research promote the production of teachers’ practical knowledge? This study finds that teachers have developed five categories of practical knowledge– knowledge of students, knowledge of teaching, knowledge of teaching contexts, knowledge of the self, and educational beliefs– through their participation in AI-enhanced evidence-based teaching research. Based on the theory of organizational knowledge creation, a feasible path for the development of teachers’ practical knowledge is proposed, which integrates AI with evidence-based teaching research to facilitate the socialization, externalization, combination, and internalization of knowledge. The research findings explain the relationship between AI-enhanced evidence-based teaching research and the production of teachers’ practical knowledge, providing an empirical basis for advancing AI-enhanced evidence-based teaching research.