生成式AI赋能高中物理教学的积极作用与实践路径

The Positive Role and Practical Path of Generative AI in Empowering High School Physics Teaching

摘要: 高中物理概念抽象、逻辑严密、模型性强，对学生逻辑思维与建模能力要求较高，传统课堂统一化教学模式，难以兼顾分层教学、个性化答疑与情境化探究的教学需求。在教育数字化背景下，生成式人工智能凭借自然语言交互、多模态内容生成、个性化适配、知识结构化梳理等优势，深度赋能高中物理课堂教学与课后自主学习。其能够破解物理概念晦涩、实验受限、答疑滞后、知识零散等教学痛点，丰富课堂教学形式，拓宽教学维度。本文重点阐述生成式AI在高中物理教学中的积极促进作用，结合高中物理课堂教学、实验教学、课后辅导等场景，提出可落地的AI教学实践策略，同时简要概述其现存固有短板，为AI与高中物理教学的深度融合、优化物理课堂教学质量、落实物理核心素养培育提供参考。

Abstract: High school physics features abstract concepts, rigorous logic and strong modeling, which require students’ logical thinking and modeling ability. The unified teaching mode of traditional classrooms is difficult to meet the teaching needs of hierarchical teaching, personalized Q & A and situational inquiry. Under the background of educational digitalization, generative artificial intelligence can deeply empower classroom teaching and independent after-class learning of high school physics by virtue of natural language interaction, multimodal content generation, personalized adaptation and structured knowledge sorting. It can solve the teaching pain points such as obscure physics concepts, limited experiments, delayed Q & A and scattered knowledge, enrich classroom teaching forms and expand teaching dimensions. This paper focuses on the positive role of generative AI in high school physics teaching, and proposes practical AI teaching strategies combined with high school physics classroom teaching, experimental teaching and after-school tutoring scenarios. Meanwhile, it briefly summarizes the existing inherent shortcomings, providing a reference for the in-depth integration of AI and high school physics teaching, the optimization of physics classroom teaching quality, and the cultivation of core physics literacy.