创新创业理论研究与实践 ›› 2026, Vol. 9 ›› Issue (8): 56-58.

• 教学革新 • 上一篇    下一篇

人工智能背景下计算物理教学改革探索

刘敏1, 周金健2   

  1. 1.北京化工大学 数理学院 物理系,北京 100029;
    2.北京理工大学 物理学院,北京 100081
  • 出版日期:2026-04-25 发布日期:2026-06-30
  • 作者简介:刘敏(1986—),女,陕西宝鸡人,博士研究生,讲师,研究方向:计算物理方法、材料物性。
  • 基金资助:
    2023年度国家自然科学基金项目“双钙钛矿关联拓扑物态的研究”(12204038); 2025年度国家自然科学基金项目“电声耦合相关物性的计算方法与软件发展”(12574250)

Exploration of Teaching Reform in Computational Physics in the Context of Artificial Intelligence

LIU Min1, ZHOU Jinjian2   

  1. 1. Department of Physics, College of Mathematics and Physics, Beijing University of Chemical Technology, Beijing, 100029, China;
    2. School of Physics, Beijing Institute of Technology, Beijing, 100081, China
  • Online:2026-04-25 Published:2026-06-30

摘要: 在人工智能(AI)背景下,计算物理传统的数值方法讲授结合基础编程练习模式已与前沿知识脱节,教学方法亟待改革。改革的核心方向是将AI技术作为工具与方法,融入计算物理核心教学任务,着力培养学生运用AI解决复杂物理问题的能力。该文从教学内容、教学模式、教学评价三个维度梳理现存问题,基于这些问题深入分析AI赋能计算物理的教学改革路径,并针对性提出实施措施。

关键词: 人工智能, 计算物理, 教学方法, 教学内容, 教学模式, 教学评价

Abstract: Against the backdrop of Artificial Intelligence (AI), the traditional teaching model of computational physics, featuring the teaching of numerical methods combined with basic programming exercises, has become disconnected from cutting-edge knowledge, necessitating an urgent reform of teaching methodologies. The core direction of this reform is to integrate AI technology as both a tool and a methodology into the core teaching tasks of computational physics, striving to cultivate students'ability to solve complex physical problems using AI techniques. This paper identifies the existing problems from three dimensions including teaching content, teaching modes, and teaching evaluation. Based on these problems, it conducts an in-depth analysis of the teaching reform path of AI-empowered computational physics and proposes targeted implementation countermeasures.

Key words: Artificial intelligence, Computational physics, Teaching methodologies, Teaching content, Teaching modes, Teaching evaluation

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