ETREducational Theory and Research2995-34482995-3456Art and Technology10.61369/ETR.2026010015ArticleAI 让每一名学生被看见：基础教育“规模化— 个 性化”张力的重构逻辑与治理路径https://artdesignp.com/journal/ETR/4/1/10.61369/ETR.2026010015张金龙2026412026-01-02基础教育中的“规模化管理— 个性化学习”张力源于学生学习过程、认知结构与情绪状态等信息的长期不可见。人工智能为改善这一结构性困境提供了新的可行路径。本文概括 AI 通过多模态感知、学习分析与自适应支持实现学生可见性的三重逻辑，并提出“输入— 中介— 输出”模型，说明其如何在规模化情境中支撑个性化教学。文章进一步凝练数据治理、教师专业重塑与评价制度创新三大治理支柱，指出 AI 的价值在于增强教师能力，使教育由“平均化”迈向“因材施教”。人工智能,规模化管理,个性化学习,学习分析,教育治理

[1] 中共中央、国务院. 关于构建优质均衡的基本公共教育服务体系的意见[Z]. 北京: 人民出版社, 2023.[2]UNESCO. Global Education Monitoring Report 2023: Technology in Education—A Tool on Whose Terms?[R]. Paris: UNESCO, 2023.[3]Zhai X, Chu H C, Chai C S, Jong M S Y. A review of AI education in K–12: The evolving roles of AI and implications for assessment[J]. Computers & Education: Artificial Intelligence, 2023, 4: 100125.[4]Baker R S, Inventado P S. Educational Data Mining and Learning Analytics: Applications to Construction of Student Models and Their Use in Educational Systems[M]//Lang C, Siemens G, Wise A F, Gašević D, eds. The Handbook of Learning Analytics. 2nd ed. Beaumont, AB: SOLAR, 2022.[5] 冯晓英, 王悦, 赵丹, 等. 在线学习中基于多模态数据的情感计算模型及应用研究综述[J]. 电化教育研究, 2023, 44(1): 60-68.[6]Di Mitri D, Schneider J, Specht M, Drachsler H. Multimodal Learning Analytics for Assessing Motor Skills[A]//Mangaroska K, Gašević D, eds. Handbook of Learning Analytics. 2nd ed. Beaumont, AB: SOLAR, 2022.[7]Siemens G. Learning Analytics: The Emergence of a Discipline[J]. American Behavioral Scientist, 2013, 57(10): 1380-1400.[8] 牟艳娜, 胡艺龄. 教育知识图谱：赋能规模化因材施教的底层架构[J]. 现代远程教育研究, 2022, 34(6): 12-21.[9]Van Leeuwen A, Rummel N. Orchestration tools for teachers in the context of learning analytics: A state-of-the-art review[J]. Computers & Education, 2022, 190: 104621.[10]Di Mitri D, Schneider J, Specht M, Drachsler H. Multimodal Learning Analytics for Assessing Motor Skills[A]//Mangaroska K, Gašević D, eds. Handbook of Learning Analytics. 2nd ed. Beaumont, AB: SOLAR, 2022.[11]Molenaar I. Towards hybrid human-AI learning technologies[J]. European Journal of Education, 2022, 57(4): 632-645.[12] 祝智庭, 胡姣. 教育数字化转型的实践逻辑与发展机遇[J]. 电化教育研究, 2022, 43(1): 5-15.[13]OECD. Opportunities, Guidelines and Guardrails for Effective and Equitable Use of AI in Education[R]. Paris: OECD Publishing, 2023.[14] 胡艺龄, 王开泳, 杨现民. 数据驱动的区域教育治理现代化：逻辑、框架与路径[J]. 中国电化教育, 2023(6): 50-58.[15] U . S . D e p a r t m e n t o f E d u c a t i o n , O f f i c e o f E d u c a t i o n a l T e c h n o l o g y . Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations[R]. Washington, DC: U.S. Department of Education, 2023.