GenAI支持的课堂群体专注度识别与反馈:模型构建与实践路径OA
Classroom Group Attention Recognition and Feedback Supported by GenAI:Model Construction and Practical Pathways
随着生成式人工智能在教育领域的广泛应用,课堂教学正经历从经验驱动向数据驱动、人机协同的深层转变,如何实现对学习状态的精准感知与高效反馈,成为智能化教学决策的重要议题.然而,现有研究侧重个体专注度评估、忽视群体互动效应,呈现出"重识别、轻反馈"的局限.为此,文章以课堂群体专注度为切入点,基于对课堂群体专注度监测与教师反馈需求的系统分析,提出构建融合识别、分析、推理与反馈于一体的智能反馈模型,推动生成式人工智能由工具型赋能向伙伴型支持转变.文章旨在为构建可感知、可解释、可协同的课堂教学反馈系统提供理论支撑与实践路径,并通过实证研究检验了其可行性,以期拓展生成式人工智能在课堂教学中的价值边界.
With the widespread application of generative artificial intelligence(GenAI)in education,classroom teaching is undergoing a profound transformation from experience-driven to data-driven and human-machine collaboration.How to realize the precise perception and efficient feedback of learning states has become a critical issue for intelligent instructional decision-making.However,existing studies predominantly focus on individual attention assessment while neglecting group interaction effects,generally revealing the limitation of"valuing recognition over feedback".Therefore,taking classroom group attention as the entry point,this paper systematically analyzed the demands for group attention monitoring and teachers'feedback,and proposed an intelligent feedback model integrating recognition,analysis,reasoning,and feedback,thereby promoting the transformation of GenAI from tool-enabled empowerment to partner-oriented support.The study aimed to provide theoretical foundations and practical pathways for constructing a perceptive,interpretable and collaborative classroom teaching feedback system,and validated its feasibility through empirical research,thereby expanding the value boundary of generative artificial intelligence in classroom instruction.
武法提;郭子涵
北京师范大学 数字学习与教育公共服务教育部工程研究中心,北京 100875北京师范大学 数字学习与教育公共服务教育部工程研究中心,北京 100875
社会科学
生成式人工智能教学反馈群体专注度学习分析
generative artificial intelligenceinstructional feedbackgroup attentionlearning analytics
《现代教育技术》 2026 (5)
108-118,11
本文为国家自然科学基金面上项目"同步直播课堂中基于多模态数据的学习者专注度评估及其演化机制研究"(项目编号:62177008)的阶段性研究成果.
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