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“无限大带电平面”与“平板电容器”是《电磁学》静电场部分的两个核心理想模型,然而学生普遍对两者附近场强公式σ/(2ε0)与σ/ε0存在混淆与认知冲突。本文深入剖析了这一认知障碍的根源,指出其源于对“孤立系统”与“耦合系统”电场叠加机制的混淆、对高斯定理应用场景的僵化理解以及对物理图像构建的缺失。基于此,本文提出一套以“模型溯源-原理剖析-图像建构-方法对比”为主线的四步教学改革方案,旨在通过强调电场叠加原理的核心地位、对比不同高斯面选取的物理意义,引导学生自主建构清晰的场分布物理图像,从而从根本上化解认知冲突,提升对静电场核心思想的理解深度和迁移应用能力。
Abstract:The infinite uniformly charged plane and the parallel-plate capacitor are two fundamental idealized models in the electrostatics section of electromagnetism.However,students often confuse the electric-field formulas near these two models, E=σ/(2ε0) and E=σ/ε0, which leads to cognitive conflict.This paper analyzes the origins of this difficulty and shows that it mainly arises from confusion between the field-superposition mechanisms of isolated and coupled systems,a rigid or inappropriate application of Gauss' s law,and insufficient construction of physical pictures of field distributions.On this basis,a four-step instructional reconstruction framework is proposed, following the sequence of "model tracing,principle analysis, physical-picture construction,and methodological comparison." By emphasizing the central role of the superposition principle and comparing the physical meanings of different Gaussian surface choices, this framework guides students to construct a clear physical picture of electric-field distributions.It thereby helps resolve the cognitive conflict at a deeper level and improves students' conceptual understanding of electrostatics as well as their ability to transfer and apply core ideas.
[1]赵凯华,陈熙谋.电磁学[M].4版.北京:高等教育出版社,2018.ZHAO K H, CHEN X M.Electromagnetics[M].4th ed.Beijing:Higher Education Press,2018.(in Chinese)
[2]叶邦角.电磁学[M].合肥:中国科学技术大学出版社,2014.YE B J.Electromagnetics[M].Anhui:University of Science and Technology of China Press,2014.(in Chinese)
[3]张之翔.电磁学千题解[M].2版.北京:科学出版社,2018.ZHANG Z X.Solutions to one thousand electromagnetics problems[M].2nd ed.Beijing:Science Press,2018.(in Chinese)
[4]叶张胜,杨树林.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[J].物理与工程,2025,35(5):169-173.YE Z S,YANG S L.Application of generative artificial intelligence in physics education:A case study of electrostatic field simulation using Python programming[J].Physics and Engineering,2025,35(5):169-173.(in Chinese)
[5]许静平,梁喻博,樊维佳,等.大学物理教学中有关AI赋能的调研和探索[J].物理与工程,2025,35(6):109-112,118.XU J P,LIANG Y B,FAN W J,et al.Research and exploration on AI empowerment in university physics teaching[J].Physics and Engineering, 2025,35(6):109-112,118.(in Chinese)
[6]杨红梅,程伟,江莎,等.大学生物理综合思维能力培养的教改探索[J].物理通报,2025(6):14-19.YANG H M,CHENG W,JIANG S,et al.Exploration on the teaching reform to cultivate university students'comprehensive physics thinking skills[J].Physics Bulletin,2025(6):14-19.(in Chinese)
基本信息:
DOI:10.27024/j.wlygc.2026.01.21.04
中图分类号:O441-4;G642.4
引用信息:
[1]江莎,王佳鑫,李健,等.从孤立到耦合化解带电平面场强认知冲突的教学重构研究——对无限大带电平面与电容器极板附近场强的比较研究[J].物理与工程().DOI:10.27024/j.wlygc.2026.01.21.04.
基金信息:
重庆市高等教育教学改革研究项目(项目批准号:254054,256055,253113); 重庆市研究生教育教学改革研究项目(项目批准号:yjg250119); 重庆邮电大学教育教学改革项目(项目批准号:XJG22106,XKCSZ2521)
2026-08-31
2026-08-31
2026-08-31