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<p>The integration of artificial intelligence (AI) technology into teaching and learning has become a focal point of educational research worldwide. Emerging studies have explored AI technological pedagogical content knowledge (AI-TPACK) that teachers should possess. However, these studies have largely overlooked the potential for AI to function independently as an educator. As a result, the existing frameworks for categorizing teachers’ knowledge lack the necessary detail to guide precise improvements in AI-TPACK. To address this gap, we propose a novel AI-TPACK model that distinguishes between the knowledge required for human teachers and that applicable to AI machine teachers, specifically by separating TPK and TPCK into distinct dimensions. Building on this, we developed a corresponding AI-TPACK scale, and collected data from 243 secondary English teachers to validate the model. The scale comprised 23 items across 6 sub-dimensions, including AI-TK, AI-TCK, AI-TPK (machine teacher), AI-TPK (human teacher), AI-TPCK (machine teacher), AI-TPCK (human teacher). Validity and reliability tests indicated that participants in this study were able to discern the innovative AI machine teacher dimensions, with all the indices, including structural validity, convergent validity, discriminant validity, criterion validity and reliability all meet the necessary criteria. With AI capable of serving as a ubiquitous teacher, human teachers need to know how to employ the AI teacher to support their work and leverage their teaching expertise to achieve effective human–machine collaboration. Our model and scale can serve as a tool for teachers and teacher educators to assess the progress of human–machine pedagogical coupling.</p>

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Development of an Artificial Intelligence Technology Pedagogical Content Knowledge (AI-TPACK) Scale for Human and AI Concurrently as Teachers

  • 期刊论文

  • 发表日期：

    2025年9月30日

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  • Xin An,
  • Jiannan Bai,
  • Yushun Li,
  • Ying Zhou,
  • Ching Sing Chai,
  • Jon-Chao Hong

摘要

The integration of artificial intelligence (AI) technology into teaching and learning has become a focal point of educational research worldwide. Emerging studies have explored AI technological pedagogical content knowledge (AI-TPACK) that teachers should possess. However, these studies have largely overlooked the potential for AI to function independently as an educator. As a result, the existing frameworks for categorizing teachers’ knowledge lack the necessary detail to guide precise improvements in AI-TPACK. To address this gap, we propose a novel AI-TPACK model that distinguishes between the knowledge required for human teachers and that applicable to AI machine teachers, specifically by separating TPK and TPCK into distinct dimensions. Building on this, we developed a corresponding AI-TPACK scale, and collected data from 243 secondary English teachers to validate the model. The scale comprised 23 items across 6 sub-dimensions, including AI-TK, AI-TCK, AI-TPK (machine teacher), AI-TPK (human teacher), AI-TPCK (machine teacher), AI-TPCK (human teacher). Validity and reliability tests indicated that participants in this study were able to discern the innovative AI machine teacher dimensions, with all the indices, including structural validity, convergent validity, discriminant validity, criterion validity and reliability all meet the necessary criteria. With AI capable of serving as a ubiquitous teacher, human teachers need to know how to employ the AI teacher to support their work and leverage their teaching expertise to achieve effective human–machine collaboration. Our model and scale can serve as a tool for teachers and teacher educators to assess the progress of human–machine pedagogical coupling.