{"title":"生成式人工智能赋能物理教学的特征比较与路径审思—基于中美比较研究的视角","authors":"文可 马, 丽 华, 欣 陈","doi":"10.65976/3080-0374.2026.05.059","DOIUrl":"https://doi.org/10.65976/3080-0374.2026.05.059","url":null,"abstract":"本文通过系统梳理对比中美两国在生成式人工智能(AIGC)赋能物理教学的研究与实践,发现存在显著差异。美国呈现出\"技术工具驱动\"的特征,侧重于开发作为\"认知伙伴\"的生成式导师和沉浸式虚拟实验环境,旨在重塑个体学习体验与赋能高阶思维;中国则体现出\"系统融合导向\",致力于将AIGC深度嵌入本土化教学模式与\"备教练评\"全环节,依托垂直教育大模型构建知识图谱以服务于精准教学与核心素养的双重目标。未来物理教育的智能化转型,需超越单方面技术赋能的追求,在跨文化审视中探寻技术理性与育人价值的平衡。","PeriodicalId":61324,"journal":{"name":"当代教育论坛(校长教育研究)","volume":"2 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147882973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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