大学化学 >> 2025, Vol. 40 >> Issue (9): 228-237.doi: 10.12461/PKU.DXHX202504052

所属专题： AI赋能化学教育

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基于知识图谱的无机化学实验AI课程构建与教学新形态探索

黄子俊, 邬峰, 皮少锋, 黄赛金, 方正军   

  1. 湖南工程学院材料与化工学院, 湖南 湘潭 411104
  • 收稿日期:2025-04-15 录用日期:2025-06-26 发布日期:2025-09-16
  • 通讯作者: 黄子俊, 方正军 E-mail:huangzijun@hnie.edu.cn;fzj1001@163.com
  • 基金资助:
    湖南省普通高等学校教学改革研究项目(HNJG-20230952,HNJG-2022-0975)；湖南省普通高校青年骨干教师培养对象项目

Knowledge Graph-based Development of AI Curriculum for Inorganic Chemistry Experiments and Exploration of New Teaching Paradigm

Zijun Huang, Feng Wu, Shaofeng Pi, Saijin Huang, Zhengjun Fang   

  1. College of Materials and Chemical Engineering, Hunan Institute of Engineering, Xiangtan 411104, Hunan Province, China
  • Received:2025-04-15 Accepted:2025-06-26 Published:2025-09-16
  • Contact: Zijun Huang, Zhengjun Fang E-mail:huangzijun@hnie.edu.cn;fzj1001@163.com

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摘要： 在教育数字化转型背景下，针对传统无机化学实验教学存在的知识离散、资源整合度低、个性化支持不足等问题，提出“知识图谱+AI”融合模型，构建“概念-操作-资源”三元组网络，实现实验原理、操作规范等要素的结构化映射。通过智能导学系统和动态推理算法，支持个性化学习路径规划及过程性评价。教学实践表明，该模式显著提升学生知识整合效率与创新能力，为实验教学数字化转型提供新路径。

关键词: 知识图谱, 无机化学实验, 实验教学改革, 智能导学系统

Abstract: In the context of educational digital transformation, this study addresses the challenges of fragmented knowledge, low resource integration, and insufficient personalized support in traditional inorganic chemistry experiment teaching. A “Knowledge Graph + AI” integrated model is proposed, which constructs a “concept-operation-resource” triple network to achieve structured mapping of essential elements such as experimental principles and operational standards. Through an intelligent tutoring system and dynamic reasoning algorithms, the model supports personalized learning path planning and formative assessment. Teaching practice demonstrates that this approach significantly enhances students’ knowledge integration efficiency and innovation capabilities, providing a novel pathway for the digital transformation of experimental education.

Key words: Knowledge graph, Inorganic chemistry experiments, Experimental teaching reform, Intelligent tutoring system