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<p>The integration of artificial intelligence (AI) into K-12 education is gaining momentum for its potential to enhance AI literacy among students. This study, conducted in a professional development program context, analyzed the approaches teachers took to integrate task-specific AIs into science instructions based on what they learned through PD experiences. Specifically, we focused on the approaches teachers highlighted and discussed in their individual Peer Teaching Videos (PTVs), created as the final learning outcomes of the PD. PTVs are 15–20&#xa0;min videos showcasing their AI-integrated science instruction for fellow teachers, produced with guidance from the PD instructor and shared on an online platform. Using constant comparative content analysis of PTVs, along with data from surveys and interviews, we identified three approaches teachers used to engage students with AI. These approaches differed in the positionality and depth of integrating AI in students’ science learning: (1) Trying out AI as a digital tool, (2) Training and testing AI as an inquiry practice partner, and (3) Exploring AI as an epistemic system. Although these approaches were initially developed for integrating task-specific AIs, they hold significant relevance in the context of the current surge in the use of generative AI. Specifically, these findings offer instructional implications for integrating AI not only as a technological tool but also in ways that promote a critical understanding of the epistemic processes and outcomes fostered by engaging with both science and AI.</p>

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Science Teachers’ Approaches to Artificial Intelligence Integrated Science Teaching

  • 期刊论文

  • 发表日期：

    2025年3月19日

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  • Won Jung Kim,
  • Arif Rachmatullah

摘要

The integration of artificial intelligence (AI) into K-12 education is gaining momentum for its potential to enhance AI literacy among students. This study, conducted in a professional development program context, analyzed the approaches teachers took to integrate task-specific AIs into science instructions based on what they learned through PD experiences. Specifically, we focused on the approaches teachers highlighted and discussed in their individual Peer Teaching Videos (PTVs), created as the final learning outcomes of the PD. PTVs are 15–20 min videos showcasing their AI-integrated science instruction for fellow teachers, produced with guidance from the PD instructor and shared on an online platform. Using constant comparative content analysis of PTVs, along with data from surveys and interviews, we identified three approaches teachers used to engage students with AI. These approaches differed in the positionality and depth of integrating AI in students’ science learning: (1) Trying out AI as a digital tool, (2) Training and testing AI as an inquiry practice partner, and (3) Exploring AI as an epistemic system. Although these approaches were initially developed for integrating task-specific AIs, they hold significant relevance in the context of the current surge in the use of generative AI. Specifically, these findings offer instructional implications for integrating AI not only as a technological tool but also in ways that promote a critical understanding of the epistemic processes and outcomes fostered by engaging with both science and AI.