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This chapter examines foundational understanding artificial intelligence’s role in science education, emphasizing preparing K-12 science teachers for digital transformation. Drawing from the Technology Acceptance Model (TAM), Universal Design for Learning principles (UDL), and the technological pedagogical content knowledge framework (TPACK), this chapter explores how AI technologies can support inclusive science education while maintaining student agency and critical thinking skills. Key topics include the historical development of AI from early systems like ELIZA to contemporary generative AI, the importance of AI literacy in teacher preparation and strategies for implementing AI tools across the Substitution, Augmentation, Modification, Redefinition model (SAMR) progression. The chapter emphasizes that effective AI integration must center accessibility, equity, and ethical practice, ensuring that technological advancement translates to educational equity rather than increased barriers for diverse learners. Through practical examples and case studies, this foundational overview provides essential guidance for educators leveraging AI while preserving fundamental goals of science education.

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AI as a Teaching Tool: Empowering Pre-Service Science Teachers Through Conceptual Foundations and Classroom Integration

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  • 发表日期：

    2026年

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  • Tiffanie Zaugg

摘要

This chapter examines foundational understanding artificial intelligence’s role in science education, emphasizing preparing K-12 science teachers for digital transformation. Drawing from the Technology Acceptance Model (TAM), Universal Design for Learning principles (UDL), and the technological pedagogical content knowledge framework (TPACK), this chapter explores how AI technologies can support inclusive science education while maintaining student agency and critical thinking skills. Key topics include the historical development of AI from early systems like ELIZA to contemporary generative AI, the importance of AI literacy in teacher preparation and strategies for implementing AI tools across the Substitution, Augmentation, Modification, Redefinition model (SAMR) progression. The chapter emphasizes that effective AI integration must center accessibility, equity, and ethical practice, ensuring that technological advancement translates to educational equity rather than increased barriers for diverse learners. Through practical examples and case studies, this foundational overview provides essential guidance for educators leveraging AI while preserving fundamental goals of science education.