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<p>As artificial intelligence (AI) becomes increasingly embedded in educational technologies and instructional practices, education programs are expanding offerings focused on AI in education (AIED). However, limited empirical research has examined how these programs conceptualize AI-related content, justify curricular decisions, and enact pedagogy. This qualitative study investigates how AIED programs conceptualize AI literacy, determine curricular priorities, and design instructional experiences for educators. Semi-structured interviews were conducted with faculty members responsible for designing and teaching AIED courses across six higher education institutions. Data were analyzed using thematic analysis informed by AI literacy and AI-TPACK frameworks. Findings indicate that programs consistently emphasize foundational AI literacy, ethical awareness, and critical evaluation of AI tools. Faculty intentionally prioritize interpretive and pedagogical understanding over technical proficiency, reflecting concerns about accessibility, limited instructional time, and teachers’ diverse computational backgrounds. However, attention to subject-specific AI integration was uneven, with relatively few programs explicitly addressing how AI aligns with disciplinary epistemologies and instructional goals. Additionally, educators’ positionality toward AI, such as openness, skepticism, and ethical concern, emerged as an important yet underdeveloped dimension of teacher AI literacy. Pedagogically, programs commonly employ constructivist approaches, including project-based learning, collaborative learning, and reflective practice, to support educators’ sense-making of AI technologies. This study contributes to the literature by illuminating how AIED programs navigate tensions between general AI literacy and discipline-specific integration, and by highlighting the need to more explicitly address AI positionality and subject-specific pedagogy in AIED. Implications are discussed for the design of AIED curricula and for future research on AIED.</p>

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Educating educators for artificial intelligence in education: curricular design and pedagogical approaches

  • 期刊论文

  • 发表日期：

    2026年7月25日

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  • Meina Zhu,
  • Chaoran Wang

摘要

As artificial intelligence (AI) becomes increasingly embedded in educational technologies and instructional practices, education programs are expanding offerings focused on AI in education (AIED). However, limited empirical research has examined how these programs conceptualize AI-related content, justify curricular decisions, and enact pedagogy. This qualitative study investigates how AIED programs conceptualize AI literacy, determine curricular priorities, and design instructional experiences for educators. Semi-structured interviews were conducted with faculty members responsible for designing and teaching AIED courses across six higher education institutions. Data were analyzed using thematic analysis informed by AI literacy and AI-TPACK frameworks. Findings indicate that programs consistently emphasize foundational AI literacy, ethical awareness, and critical evaluation of AI tools. Faculty intentionally prioritize interpretive and pedagogical understanding over technical proficiency, reflecting concerns about accessibility, limited instructional time, and teachers’ diverse computational backgrounds. However, attention to subject-specific AI integration was uneven, with relatively few programs explicitly addressing how AI aligns with disciplinary epistemologies and instructional goals. Additionally, educators’ positionality toward AI, such as openness, skepticism, and ethical concern, emerged as an important yet underdeveloped dimension of teacher AI literacy. Pedagogically, programs commonly employ constructivist approaches, including project-based learning, collaborative learning, and reflective practice, to support educators’ sense-making of AI technologies. This study contributes to the literature by illuminating how AIED programs navigate tensions between general AI literacy and discipline-specific integration, and by highlighting the need to more explicitly address AI positionality and subject-specific pedagogy in AIED. Implications are discussed for the design of AIED curricula and for future research on AIED.