同步课堂中基于多模态数据的专注度分析  

Analysis of Concentration Based on Multimodal Data in Synchronous Classrooms

作　　者：武法提[1] 高姝睿 赖松 WU Fati;GAO Shurui;LAI Song

机构地区：[1]北京师范大学教育学部,北京100875 [2]西南大学教育学部,北京100875

出　　处：《现代远程教育研究》2025年第1期93-101,共9页Modern Distance Education Research

基　　金：2021年度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”(62177008)。

摘　　要：同步课堂是践行“三个课堂”的主要方式,已成为促进教育均衡发展的重要举措。及时、准确地掌握学习者的专注度情况并采取有效的措施进行干预,对提升同步课堂教学质量具有重要的意义。然而当前同步课堂中存在异地学生专注状态难反馈、难调节等困境,亟需从技术角度提供精准的专注度分析与反馈方案。为达成同步课堂中学习者专注状态的精确反馈,同步课堂专注度分析要依次解决基于学习者数据的专注度计算、专注度特征间的关联,以及针对不同成因的专注度干预策略等“建模”“关系”“应用”三大核心问题,以实现对学习专注度的调节。为此,可先基于同步课堂中学习者个体的视觉、生理等多模态数据构建数据集,从中提取动作及情感特征,形成专注度评估模型;然后分析群体专注度的内在动态演化机理,构建群体专注度演化自适应模型;最后建立“问题—干预策略”知识图谱,搭建人机智能协同的专注度干预模型以及同步课堂精准教学模型,形成“数据感知—问题诊断—干预策略匹配”的个性化学习服务完整链路,帮助教师找准学习者问题,提升课堂教学效果。后续还需在实际同步课堂场景中对建模指标、分析模型、干预策略的适应性以及师生的接受度等进行检验与优化。Synchronous classrooms,the main approach to implementing the“Three Classrooms”,have become an important measure to promote balanced development of education.Timely and accurate grasp of learners’concentration and taking effective measures for intervention are of great significance for enhancing the teaching quality of synchronous classrooms.However,in current synchronous classrooms,there are difficulties such as the inability to accurately feedback and adjust the concentration status of learners in different locations.There is an urgent need to provide precise concentration analysis and feedback schemes from a technical perspective.In order to achieve accurate feedback on the concentration status of learners in synchronous classrooms,the analysis of concentration in synchronous classrooms needs to sequentially solve the three core issues of“modeling”,“relationship”and“application”,namely the calculation of concentration based on learners’data,the correlation among concentration features,and the intervention strategies for concentration due to different causes,so as to realize the regulation of concentration on learning.To this end,a dataset can be initially constructed based on the multimodal data such as visual and physiological data of individual learners in synchronous classrooms,from which the action and emotion features are extracted to form a concentration assessment model.Subsequently,the intrinsic dynamic evolution mechanism of group concentration is analyzed and an adaptive model for the evolution of group concentration is constructed.Finally,a“problem-intervention strategy”knowledge graph is established,and a concentration intervention model supported by human-machine intelligent collaboration and a precise teaching model for synchronous classrooms are erected,forming a complete chain of personalized learning services of“data perception—problem diagnosis—intervention strategy matching”,which assists teachers in accurately identifying learners’problems and enhancing the

关 键 词：同步课堂 专注度 多模态学习分析 人机协同 个性化学习服务 

分 类 号：G434[文化科学—教育学]