基于多模态数据关联分析的学习成效达成度研究  

Research on Learning Achievement Based on Multimodal Data Association Analysis

作　　者：田文君[1] TIAN Wenjun(Heilongjiang Vocational College,Harbin150080,China)

机构地区：[1]黑龙江职业学院,哈尔滨150080

出　　处：《移动信息》2024年第9期76-78,共3页Mobile Information

基　　金：黑龙江职业学院校级课题:基于信息技术的学习成效达成度评价研究与应用(XJYB2022003)。

摘　　要：课堂是教学的重要环节,科学的数据依据是保证评价结果正确性的关键.文中介绍了研究背景和国内外研究现状,基于课堂达成度分析理论,深度融合新一代信息化技术,采集多模态数据进行分析,搭建了课堂多模态关联评价框架,并基于该框架开展实证研究.以某高职院校某班级为例,通过虚拟空间、物理空间采集课堂教学过程中产生的多模态学习数据,采用人工智能方法处理并分析学习数据,实现课堂行为识别与分析评价.结果显示,与教学活动设计关联的评价框架能更加可靠地为课堂学习达成度分析提供依据,改善课堂教学质量,助力智慧课堂建设.Classroom is an important part of teaching,and scientific data basis is the key to ensure the correctness of evaluation results.This paper introduces the research background and research status at home and abroad.Based on the theory of classroom achievement analysis,deeply integrates new generation information technology,collects multi-modal data for analysis,builds a classroom multi-modal association evaluation framework,and conducts empirical research based on this framework.Taking a class in a higher vocational college as an example,the multi-modal learning data generated in the process of classroom teaching is collected through virtual space and physical space,and artificial intelligence method is used to process and analyze learning data to realize classroom behavior recognition and analysis evaluation.The results show that the evaluation framework associated with teaching activity design can provide a basis for classroom learning achievement analysis more reliably,improve classroom teaching quality,and help smart classroom construction.

关 键 词：多模态数据 课堂达成度 人工智能 课堂行为 

分 类 号：G434[文化科学—教育学]