生成式人工智能在物理教学中的应用研究:以Python编程实现静电场仿真为例APPLICATION OF GENERATIVE ARTIFICIAL INTELLIGENCE IN PHYSICS EDUCATION: A CASE STUDY OF ELECTROSTATIC FIELD SIMULATION USING PYTHON PROGRAMMING
叶张胜,杨树林
摘要(Abstract):
本文探讨了生成式人工智能与Python编程在物理教学中的应用,通过生成式人工智能DeepSeek辅助,历经三轮迭代以生成和优化Python代码,开发了一个静电场仿真案例,展现了如何借助生成式人工智能完成静电场仿真和可视化。实践证明,人工智能的引入能够有效降低仿真实验的编程门槛,但生成的仿真系统结果可能与实际物理规律不符,需要人工验证和调整。
关键词(KeyWords): 生成式人工智能;DeepSeek;Python编程;静电场;可视化
基金项目(Foundation): 黄冈市教育科学规划2023年度课题(编号:2023JB14);; 黄冈师范学院教学研究项目(编号:2024CE57)
作者(Author): 叶张胜,杨树林
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