Citation: Lingli Wu,  Shengbin Lei. Generative AI-Driven Innovative Chemistry Teaching: Current Status and Future Prospects[J]. University Chemistry, ;2025, 40(9): 206-219. doi: 10.12461/PKU.DXHX202503069 shu

Generative AI-Driven Innovative Chemistry Teaching: Current Status and Future Prospects

  • Corresponding author: Lingli Wu,  Shengbin Lei, 
  • Received Date: 18 March 2025
    Accepted Date: 16 May 2025

  • Chemistry serves as a foundational discipline across multiple fields, including chemical engineering, materials science, environmental science, biology, energy, and pharmaceutical sciences. The rapid advancement of generative artificial intelligence (Generative AI, GAI) is significantly transforming the paradigm of chemistry education. This review focuses on the innovative application of GAI in chemistry teaching. We systematically examine the current status of GAI in chemistry education through three key dimensions: instructional design and curriculum development, personalized learning path design, and teaching method reform. Furthermore, we explore innovative approaches of GAI in chemistry teaching, particularly in the integration of multimodal visualization teaching and the implementation of personalized learning strategies for both teachers and students. Finally, we critically analyze the key challenges in GAI-driven innovative chemistry teaching and provide a detailed discussion on future directions, offering valuable insights for the deeper integration of GAI in chemistry education.
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