教研人員指導教師AI教學使用的教育意義建構分析

Analysis of the Educational Sense-making in Teaching Researchers Guiding Teachers’ Use of AI Teaching

已有研究關注到教師對AI教學使用的認知誤解、誤用、教育意義不足，需要得到教育培訓支持的問題，但鮮有研究關注教研人員如何幫助教師在AI教育政策實施中進行教育意義之建構與實踐。本研究整合課程政策實施意義建構、課程教學決策理論和教師專業學習發展理論，採案例研究方法，選取北京市兩個區各一中學英語教研人員指導的課例，探討教研人員如何指導教師理解AI教學的意義，如何利用AI備課、上課與評價反思，以及由此產生的教學效果及影響因素。結果發現，教研人員能幫助教師理性認識AI工具的性質、類型和教育作用，開展基於數據分析的教學決策、實施和評價活動，進而帶來教學觀念與方式的轉變。然而，教研人員幫助教師理解與實施AI教育政策受個人興趣與課程教學知識、區培訓提供的AI教育應用知識、課堂觀摩得到的實踐知識所影響，亦為AI數據品質與整合、學校組織與教研時間等條件制約。本研究據此提出AI教學應用政策之完善建議。

This study addresses a gap in existing research, which focuses on teachers’ misconceptions, misuse, and insufficient understanding of the educational significance of AI teaching– issues requiring training support– yet rarely examines how teaching researchers guide teachers in constructing educational meaning and practice during AI education policy implementation. Integrating theories of policy implementation sense-making, curriculum making, and teacher professional learning, we conducted a case study of two secondary school English lesson cases guided by teaching researchers from two districts in Beijing. The research explores: (1) how teaching researchers help teachers interpret the value of AI teaching; (2) how they utilize AI for lesson preparation, delivery, and reflective evaluation; and (3) resulting pedagogical effects and influencing factors. Findings reveal that teaching researchers enable teachers to: rationally recognize AI tools’ nature, types, and educational functions; Conduct data-informed instructional decisions, implementation, and evaluation; transform teaching philosophies and methods. Their guidance is influenced by: individual factors: personal interest & pedagogical content knowledge; system support: district-level training on AI applications; practical knowledge: classroom observation experience; constraints: AI data quality/integration, school organization, and limited research time. Based on this, we propose policy refinement strategies for AI teaching implementation.