大学化学 >> 2025, Vol. 40 >> Issue (9): 220-227.doi: 10.12461/PKU.DXHX202503124

所属专题： AI赋能化学教育

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人工智能赋能大学化学教育改革：信息化与智能化素养培养的实践探索

陈良俊1,2, 张裕3, 张志成3, 彭永武1   

  1. 1 浙江工业大学材料科学与工程学院, 杭州 310014;
    2 武汉工程大学材料科学与工程学院, 武汉 430205;
    3 天津大学理学院化学系, 天津 300072
  • 收稿日期:2025-03-27 录用日期:2025-06-19 发布日期:2025-09-16
  • 通讯作者: 张志成, 彭永武 E-mail:zczhang19@tju.edu.cn;ywpeng@zjut.edu.cn
  • 基金资助:
    国家自然科学基金(22375179,22375142)

AI-Empowering Reform in University Chemistry Education: Practical Exploration of Cultivating Informationization and Intelligent Literacy

Liangjun Chen1,2, Yu Zhang3, Zhicheng Zhang3, Yongwu Peng1   

  1. 1 School of Materials Science and Engineering, Zhejiang University of Technology, Hangzhou 310014, China;
    2 School of Materials Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, China;
    3 Department of Chemistry, School of Science, Tianjin University, Tianjin 300072, China
  • Received:2025-03-27 Accepted:2025-06-19 Published:2025-09-16
  • Contact: Zhicheng Zhang, Yongwu Peng E-mail:zczhang19@tju.edu.cn;ywpeng@zjut.edu.cn

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摘要： 为进一步提升人工智能在大学化学教育中的应用价值，并强化学生的信息化与智能化素养，本文提出了一系列教学改革与实践措施。基于对当前化学教育现状的分析，探讨了人工智能、大数据与大模型在化学教学中的深度融合，重点阐述其在提升学生数据处理、智能决策与创新思维能力方面的作用。围绕自适应学习平台、AI赋能的数据分析等前沿技术，本文提出了构建智能教学平台、引入先进数据分析工具、优化学科研究流程、鼓励学生参与跨学科竞赛及推动学科交叉融合等具体策略。实践表明，智能技术与教学改革的深度融合显著提升了学生的自主学习、科研创新与实践应用能力，有助于构建面向未来科技发展的现代化化学教育体系。本研究为高校化学教学的智能化转型提供了重要参考，并展望了未来发展方向。

关键词: 人工智能, 智能化素养, 信息化素养

Abstract: To further enhance the application value of artificial intelligence (AI) in university chemistry education and strengthen students’ information literacy and technological proficiency, this study proposes a series of teaching reforms and practical measures. Based on an analysis of the current state of chemistry education, it explores the deep integration of AI, big data, and large models into chemistry teaching, emphasizing their role in improving students’ data processing, intelligent decision-making, and innovative thinking skills. Focusing on cutting-edge technologies such as adaptive learning platforms and AI-powered data analysis, this study proposes specific strategies, including the development of intelligent teaching platforms, the integration of advanced data analysis tools, the optimization of research processes, the encouragement of student participation in interdisciplinary competitions, and the promotion of cross-disciplinary integration. Practical applications have demonstrated that the deep integration of intelligent technology with teaching reforms significantly enhances students’ self-directed learning, scientific research innovation, and practical application abilities, contributing to the establishment of a modern chemistry education system that aligns with future technological advancements. This study provides valuable insights for the intelligent transformation of chemistry education in universities and outlines potential future research directions.

Key words: Artificial intelligence, Intelligent literacy, Informationization literacy