大学化学 >> 2026, Vol. 41 >> Issue (10): 81-89.doi: 10.12461/PKU.DXHX202510086

教学研究与改革 上一篇    

生成式人工智能赋能物理化学教学改革的创新探索

梁希壮, 仝凤霞   

  1. 烟台大学环境与材料工程学院, 山东 烟台 264005
  • 收稿日期:2025-10-23 录用日期:2025-12-01 发布日期:2026-10-13
  • 通讯作者: 仝凤霞 E-mail:tongfengxia@ytu.edu.cn Fengxia Tong
  • 基金资助:
    国家自然科学基金(22302166, 22402172)；山东省自然科学基金(ZR2023QB034, ZR2023QB031)

Innovative Exploration of Generative AI in Empowering Physical Chemistry Teaching Reform

Xizhuang Liang, Fengxia Tong   

  1. School of Environmental and Materials Engineering, Yantai University, Yantai 264005, Shandong Province, China
  • Received:2025-10-23 Accepted:2025-12-01 Published:2026-10-13
  • Contact: Fengxia Tong E-mail:tongfengxia@ytu.edu.cn

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摘要： 在人工智能技术迅猛发展的时代背景下，如何将传统学科教育与智能技术深度融合，以拓宽学生认知边界，激发创新思维，从而培养适应未来社会的高素质复合型人才，已经成为高等教育改革的重要议题。物理化学作为一门理论体系严密、概念抽象程度高、逻辑关联性强的专业基础课程，长期以来被学生视为学习难点，而传统教学模式在提供个性化学习支持和过程性评价方面存在明显不足。为突破这一教学瓶颈，本研究以学习通泛雅智慧平台为依托，紧扣物理化学学科特点，系统构建了“物理化学”多场景数字题库，并深入探索了生成式人工智能在教学内容智能生成、知识图谱系统性建设以及互动学习模式创新等方面的应用路径。

关键词: 生成式人工智能, 物理化学, 智慧课程, 教学改革

Abstract: In the era of rapid advancements in artificial intelligence technology, the integration of traditional disciplinary education with intelligent technologies to expand the cognitive boundaries and stimulate innovative thinking of students has emerged as a pivotal issue in higher education reform. Physical chemistry, as a fundamental professional course characterized by its rigorous theoretical system, highly abstract concepts, and strong logical coherence, has long been perceived by students as academically challenging. Traditional teaching approaches exhibit notable limitations in providing personalized learning support and formative assessment. To address these pedagogical constraints, this study have systematically developed a multi-scenario digital test bank based on Xuexitong FanYa Smart Platform and the characteristics of physical chemistry. Furthermore, it explores the application of generative artificial intelligence in intelligent content generation, systematic knowledge graph construction, and innovative interactive learning models.

Key words: Generative AI, Physical chemistry, Wisdom curriculum, Teaching reform