AI赋能Python仿真在高中物理教学中的应用——以带电粒子在磁场中的运动为例

The Application of AI-Enhanced Python Simulation in High School Physics Teaching—A Case Study of Charged Particle Motion in a Magnetic Field

摘要: 高中物理教学中，带电粒子在磁场中的运动是兼具抽象性与综合性的难点内容。本文以2024年湖北高考物理试题为例，探讨AI技术辅助物理教学的新模式。研究通过构建Python仿真，对复杂物理过程开展可视化呈现与智能分析。不仅完成了题目选项的科学性验证，更具象化呈现了传统教学中难以直观展现的物理过程图景。实践应用表明，这种融合计算思维的教学方法，能够有效提升学生的物理模型建构能力与科学探究素养。本研究为AI物理教育的创新实践提供了可借鉴的具体案例。

Abstract: In high school physics teaching, the motion of charged particles in a magnetic field is a challenging topic characterized by both abstraction and comprehensiveness. Taking the 2024 Hubei College Entrance Examination physics question as an example, this paper explores a novel model of AI-assisted physics instruction. The study employs Python simulation to achieve visual representation and intelligent analysis of complex physical processes. It not only scientifically verifies the question’s answer choices but also vividly presents physical scenarios that are difficult to visualize in traditional teaching. Practical applications demonstrate that this teaching method, integrated with computational thinking, can effectively enhance students’ ability to construct physical models and foster scientific inquiry literacy. This research provides a replicable case study for innovative practices in AI-enhanced physics education.