大学化学 >> 2025, Vol. 40 >> Issue (9): 171-177.doi: 10.12461/PKU.DXHX202502109

所属专题： AI赋能化学教育

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DeepSeek大模型：对无机化学教与学的启示

马亚鲁, 田昀, 马骁飞   

  1. 天津大学理学院化学系, 天津 300354
  • 收稿日期:2025-02-20 录用日期:2025-04-16 发布日期:2025-09-16
  • 通讯作者: 马亚鲁 E-mail:mayalu@tju.edu.cn
  • 基金资助:
    “天津大学人工智能赋能课程建设专项-无机化学与化学分析课程AI辅助”专项基金

DeepSeek Large Model: Implications for Inorganic Chemistry Teaching and Learning

Yalu Ma, Yun Tian, Xiaofei Ma   

  1. Department of Chemistry, School of Science, Tianjin University, Tianjin 300354, China
  • Received:2025-02-20 Accepted:2025-04-16 Published:2025-09-16
  • Contact: Yalu Ma E-mail:mayalu@tju.edu.cn

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摘要： 借助DeepSeek大模型进行模拟学习，挖掘DeepSeek大模型对无机化学教与学的有效元素，思考数智赋能时代下化学课程教与学的创新方向，以应对社会发展对无机化学教学提出的要求和挑战。

关键词: DeepSeek大模型, 无机化学, 教与学, 创新, 挑战

Abstract: This study employs the DeepSeek large model to conduct simulated learning and explores its effective elements in inorganic chemistry education. In the era of digital-intelligent empowerment, it is imperative to reconsider innovative approaches for chemistry curriculum teaching and learning, thereby addressing the evolving requirements and challenges posed by social development in the field of inorganic chemistry education.

Key words: DeepSeek large model, Inorganic chemistry, Teaching and learning, Innovation, Challenge