大学化学

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知识图谱赋能无机化学一流课程建设与教学应用

高淑娟, 张改清, 李林枝, 曹阳, 李蜂   

  1. 吕梁学院化工与材料工程系, 山西 吕梁 033000
  • 收稿日期:2026-08-15 录用日期:2026-09-15
  • 通讯作者: 高淑娟, 李蜂 E-mail:shujuangao@llu.edu.cn;fengli@llu.edu.cn Shujuan Gao, Feng Li
  • 基金资助:
    2024年山西省一流课程认定项目(K2024083)；山西省教育厅教改项目(J20250273)；山西省基础研究计划资助项目(202303021212289)；山西省人力资源高质量发展重大专项研究课题(SXRLZYYB2555，SXRLZYZD2513)；山西省高等学校大学生创新训练计划项目(s202610812009，s202610812048x)；吕梁学院博士科研启动经费(UP2025112014)

Construction and teaching implementation of a first-class inorganic chemistry course empowered by knowledge graph

Shujuan Gao, Gaiqing Zhang, Linzhi Li, Yang Cao, Feng Li   

  1. Department of Chemical and Materials Engineering, Lyuliang University, Lvliang 033000, Shanxi Province, China
  • Received:2026-08-15 Accepted:2026-09-15
  • Contact: Shujuan Gao, Feng Li E-mail:shujuangao@llu.edu.cn;fengli@llu.edu.cn

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摘要： 在数字化转型背景下，针对无机化学线上课程资源按教材章节组织导致的知识联系不清、检索困难、学习路径单一及反馈不够精准等教学痛点，本文提出基于知识图谱的新形态一流课程建设方案。方案以任务驱动为导向，构建“知识层-活动层-教学层-学习层”四层结构，将教学内容细化为11个模块、7个层级、557个知识点，关联课程资源248项、试题778道及拓展学术资源17项，形成线上自主学习、线下内化提升、课后拓展创新相结合的PRIDE混合式教学模式。借助知识点完成率、掌握率与学习画像，支持教师精准教学与学生个性化学习。实践表明，知识图谱能够有效促进课程知识结构显性化、学习路径可视化、教学干预精准化与评价体系多维化，为化学类专业基础课程数字化转型提供可操作路径。

关键词: 知识图谱, 无机化学, 一流课程, 混合式教学, 个性化学习, 智慧教学

Abstract: To address the problems of unclear knowledge relationships, scattered resources, and insufficient personalized learning in Inorganic Chemistry, a new course construction scheme empowered by knowledge graph was proposed. The teaching content was refined into 11 modules, 7 levels, and 557 knowledge points, which were associated with learning resources and tests. A PRIDE blended teaching model was designed to support autonomous learning, precise teaching, and multi-dimensional evaluation. This practice provides a feasible path for the digital transformation of chemistry courses.

Key words: Knowledge graph, Inorganic chemistry, First-class course, Blended teaching, Personalized learning, Intelligent teaching