大学化学 >> 2026, Vol. 41 >> Issue (8): 111-118.doi: 10.12461/PKU.DXHX202507097

教学研究与改革 上一篇    下一篇

AI助教在无机元素化学教学中的应用

韩艳阳, 刘珊珊, 何涛, 冯凯, 杨昕, 李庆忠, 张涛   

  1. 烟台大学化学化工学院, 山东 烟台 264005
  • 收稿日期:2025-07-21 录用日期:2025-10-17 发布日期:2026-08-25
  • 通讯作者: 韩艳阳, 张涛 E-mail:yyhan@ytu.edu.cn;tao.zhang@ytu.edu.cn Yanyang Han, Tao Zhang
  • 基金资助:
    2024年山东省本科教学改革研究面上项目(M2024254)；2024年烟台大学教育教学改革研究一般项目(JYXM2024043Y)；2025年烟台大学教育教学改革研究重点项目(JYXM2025007Z)

Application of AI teaching assistants in elemental inorganic chemistry teaching

Yanyang Han, Shanshan Liu, Tao He, Kai Feng, Xin Yang, Qingzhong Li, Tao Zhang   

  1. College of Chemistry and Chemical Engineering, Yantai University, Yantai 264005, Shandong Province, China
  • Received:2025-07-21 Accepted:2025-10-17 Published:2026-08-25
  • Contact: Yanyang Han, Tao Zhang E-mail:yyhan@ytu.edu.cn;tao.zhang@ytu.edu.cn

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摘要： 随着人工智能技术的快速发展，AI助教在高等教育中的应用逐渐成为教学改革的重要方向。无机元素化学作为一门知识点繁杂、逻辑性强的专业课程，传统教学模式下存在知识点零散、大班教学个性化不足、教师负担过重等问题。本研究以无机元素化学课程为实践对象，系统探索AI助教在课程教学中的创新应用模式。通过构建知识图谱整合碎片化知识点，开发智能问答工具实现24 h实时答疑，并进行学情分析与个性化学习推荐，形成“资源数字化-路径个性化-评价动态化”的全链条教学方案。本研究表明，AI助教为无机元素化学教学提供了资源整合与个性化学习推荐的可行路径，为化学教育的数智化转型提供了实践参考。

关键词: AI助教, 无机元素化学, 教学改革

Abstract: The rapid advancement of artificial intelligence (AI) technology has positioned AI teaching assistants as an increasingly important component of higher education reform. Elemental Inorganic Chemistry, a specialized course characterized by extensive yet fragmented knowledge points and rigorous logical structures, presents inherent challenges in traditional teaching approaches. These include disjointed knowledge delivery, limited personalization in large-class settings, and excessive instructor workloads. This study systematically investigates innovative applications of AI teaching assistants through a practical implementation in an Elemental Inorganic Chemistry course. The research establishes a comprehensive teaching framework integrating “digital resources-personalized pathways-dynamic evaluation” by constructing a knowledge graph to organize fragmented course content, developing an intelligent Q&A system for 24-hour real-time student support, and implementing learning performance analysis with personalized recommendations. These findings suggest that AI teaching assistants offer viable solutions for resource integration and personalized learning in Elemental Inorganic Chemistry, providing practical insights for the digital transformation of chemistry education.

Key words: AI teaching assistant, Elemental inorganic chemistry, Teaching reform