大学化学

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基于知识图谱的“AI赋能”无机化学翻转课堂教学模式

张凤玲, 唐克, 徐秀玲, 刘强, 王晓倩   

  1. 浙江中医药大学药学院, 浙江 杭州 311400
  • 收稿日期:2026-04-07 修回日期:2026-04-22
  • 通讯作者: 王晓倩 E-mail:603688804@qq.com Xiaoqian Wang
  • 基金资助:
    浙江中医药大学教育教学改革一般项目(YB25034)

AI-enabled flipped classroom teaching model of inorganic chemistry based on knowledge graph

Fengling Zhang, Ke Tang, Xiuling Xu, Qiang Liu, Xiaoqian Wang   

  1. College of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 311400, Zhejiang Province, China
  • Received:2026-04-07 Revised:2026-04-22
  • Contact: Xiaoqian Wang E-mail:603688804@qq.com

摘要: 无机化学作为中医药院校相关专业的核心基础课程,存在知识点零散抽象、课时有限,以及传统教学中学生被动学习与互动不足等问题。翻转课堂虽能改善学生学习状态、提升综合能力,但存在自主学习效果难追踪、课堂互动深度不足等局限。为破解上述困境,将人工智能技术与无机化学翻转课堂深度融合,构建全过程交互式教学模式。该模式基于“知识图谱构建与AI技术赋能”理念,依托智能教学平台实现课外个性化学习计划定制、课中智能分组引导、课后精准反馈推送,全方位弥补传统翻转课堂缺陷,适配无机化学教学特点与学生学习需求,为中医药院校基础课程教学改革提供实践路径。

关键词: AI赋能, 知识图谱, 翻转课堂, 无机化学, 智能教学

Abstract: Inorganic chemistry serves as a fundamental core course for related majors in traditional Chinese medicine universities. However, it faces several challenges, including fragmented knowledge points, abstract concepts, and limited class hours. Traditional teaching methods often result in passive learning and inadequate student-teacher interaction. While the flipped classroom approach can enhance students' learning engagement and comprehensive abilities, it still presents limitations such as difficulties in tracking autonomous learning outcomes and insufficient depth in classroom interactions. To address these issues, this study proposes an innovative integration of artificial intelligence technology with the inorganic chemistry flipped classroom, establishing a full-process interactive teaching model. This model is based on the concept of “knowledge graph construction and AI technology empowerment”. Relying on an intelligent teaching platform, it customizes personalized after-class learning plans. It facilitates intelligent group guidance during class sessions and enables precise post-class feedback. This approach effectively mitigates the shortcomings of traditional flipped classrooms, aligns with the pedagogical characteristics of inorganic chemistry, meets students' learning needs, and provides a practical pathway for reforming fundamental course instruction in traditional Chinese medicine universities.

Key words: AI empowerment, Knowledge graph, Flipped classroom, Inorganic chemistry, Intelligent instruction