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本文探索利用生成式AI(DeepSeek)构建轻量化物理仿真实验的创新方法,赋能物理教学。研究针对现有虚拟实验资源在课外与情境化实验资源上的不足,提出用户可以通过自然语言描述实验需求,由DeepSeek生成可直接在浏览器中运行的仿真实验的方法,还探讨了目前存在的一些问题及应对方案。本研究为教师快速创建动态演示工具提供有效方法参考,显著降低技术门槛。最后基于此方法,研究提出了三种相关教学模式,为AI融入物理教学提供了可落地的技术路径。
Abstract:This paper explores an innovative approach to developing lightweight physics virtual simulation experiments using generative AI, with DeepSeek as a case study. To address the shortage of extracurricular and contextualized virtual experiment resources, this study proposes a method in which users describe experimental requirements in natural language and DeepSeek generates simulation experiments that can run directly in a web browser. The paper also discusses several existing problems and corresponding solutions. This approach provides a practical reference for teachers to rapidly create dynamic demonstration tools and significantly lowers the technical threshold for developing virtual simulation resources. Based on this method, three related teaching models are further proposed, offering a feasible technical pathway for integrating AI into physics teaching.
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基本信息:
DOI:10.27024/j.wlygc.2025.06.14.02
中图分类号:G434;G633.7
引用信息:
[1]刘启豪,杨晓荣,闫成芳.基于生成式AI的物理虚拟仿真实验开发探索——以DeepSeek为例[J].物理与工程().DOI:10.27024/j.wlygc.2025.06.14.02.
基金信息:
国家级一流本科课程“中学物理教学论”; 西藏自治区一流本科课程“中学物理教学论”; 教育部产学合作协同育人项目(编号:202102538051); 西藏自治区高等学校优秀教学团队“普通物理学教学团队”资助
2026-05-06
2026-05-06
2026-05-06
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