AI技术赋能大学物理教师教学创新实践

AI Technology-Driven Innovative Teaching Practices for University Physics Teachers

摘要: 本文以促进学生全面发展为核心目标，基于穆良柱教授的ETA (Experiment-Theory-Application，实验–理论–应用)物理模型，融合“知识传递、能力提升、价值引领”教育理念开展教学创新。借助AI平台，对课前、课中、课后全流程的教学资料与教学方式进行重构。在教学全程中厚植爱国情怀，培养学生的科学精神与强国之志。以“带电粒子在电场和磁场中的运动”教学为例，该教学模式通过AI技术赋能，显著减轻教师备课负担，实现精准化个性教学；依托虚拟仿真与探究式学习，强化学生科学实践能力；构建了“智能工具–课程思政–能力培养”协同的理工科教学新范式，为高等教育改革提供创新路径。

Abstract: This paper aims to promote the all-round development of students. Based on the (Experiment-Theory-Application) ETA physics model of Liangzhu Mu Professor and the educational concept of “knowledge transmission, ability enhancement, and value guidance”, teaching innovation is carried out. With the help of the AI platform, the teaching materials and methods for the entire process of before, during, and after class are reconstructed. Throughout the teaching process, patriotic sentiments are deeply cultivated, and students’ scientific spirit and aspiration to strengthen the country are nurtured. Taking the teaching of “Motion of Charged Particles in Electric and Magnetic Fields” as an example, this teaching model, empowered by AI technology, significantly reduces the burden of teachers’ lesson preparation, realizes precise and personalized teaching; strengthens scientific practical ability of students through virtual simulation and inquiry-based learning; and builds a new paradigm of engineering and science teaching that is coordinated by “intelligent tools, course-based ideological and political education, ability cultivation”, providing an innovative path for higher education reform.