大学化学

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“人工智能+大学化学教学”的研究图景与未来进路——基于CiteSpace的文献计量分析

薛家炜, 樊彦青, 李小娟, 李佳佳, 曾竟   

  1. 新疆师范大学化学化工学院,新疆 乌鲁木齐 830054
  • 收稿日期:2026-02-27 录用日期:2026-04-14
  • 通讯作者: 曾竟 E-mail:zengjing800111@163.com Jing Zeng
  • 基金资助:
    疆维吾尔自治区高校本科教学研究与改革项目(XJGXJGPTB-2024148);第三批国家级一流本科线上线下混合式课程和新疆维吾尔自治区一流本科课程项目资助

Research landscape and future pathways of “artificial intelligence + university chemistry education”: a CiteSpace-based bibliometric analysis

Jiawei Xue, Yanqing Fan, Xiaojuan Li, Jiajia Li, Jing Zeng   

  1. College of Chemistry and Chemical Engineering, Xinjiang Normal University, Urumqi 830054, Xinjiang Uygur Autonomous Region, China
  • Received:2026-02-27 Accepted:2026-04-14
  • Contact: Jing Zeng E-mail:zengjing800111@163.com

摘要: 基于CiteSpace的计量分析发现,国内“人工智能+大学化学教学”研究已形成以教学改革为核心、覆盖教学全流程的体系,学科差异化实践进展显著;国外研究则侧重认知建构与探究设计,在实验室翻转教学、数据科学嵌入等方面特色鲜明。未来应加强跨学科对话,借鉴国外经验,构建学科适配的智能教学模型,并开展长效实证研究,促进学生视角下的深度融合。

关键词: 数字化转型, 高等教育, 人工智能, 化学教育, 教学改革

Abstract: A CiteSpace-based bibliometric analysis reveals that domestic research on “artificial intelligence + university chemistry education” has established a teaching-reform-centered framework encomp-assing the entire instructional process, with significant advancements in discipline-specific applications.In contrast, international research prioritizes cognitive construction and inquiry design, incorporating flipped laboratories and data science integration. Future research directions should enhance interdisciplinary collaboration, leverage international insights to develop discipline-specific intelligent teaching models, conduct longitudinal empirical studies, and foster deeper educational integration from the student perspective.

Key words: Digital transformation, Higher education, Artificial intelligence, Chemistry education, Teaching reform