基于全过程教育数据挖掘的学生画像构建研究  

Research on the Construction of Student Portrait Based on the Whole Process of Education Data Mining

作　　者：宋潼潼 苏盈盈[1] 夏长丽[1] 刘辉[1] 陈洪志 陈霞[1] SONG Tongtong;SU Yingying;XIA Changli;LIU Hui;CHEN Hongzhi;CHEN Xia(College of Basic Medical Sciences,Jilin University,Changchun Jilin,130021,China)

机构地区：[1]吉林大学基础医学院,吉林长春130021

出　　处：《创新创业理论研究与实践》2024年第21期5-8,共4页The Theory and Practice of Innovation and Enterpreneurship

基　　金：吉林大学本科教学改革研究项目“基于对分课堂的BOPPPS融合系统解剖学教学模式构建”;吉林省高等教育教学改革研究课题“医学研究生公共课程考核与管理机制研究”(JLJY202395689359);中国医药学研究生在线教育教学研究课题“医学研究生全方位在线教学质量保障体系的构建与实践”(A_YXC2022-02-03_10)

摘　　要：该文选择学习行为、综合能力和素质发展等行为特征指标,在进行数据预处理后,采用随机森林选择重要特征值,利用改进的熵权法对选中的重要特征值进行赋权,采用聚类分析构建基于全过程教育数据的学生群体画像,探讨基于人工智能技术的学生画像在基础医学教育的应用前景。研究发现:基于人工智能技术的学生画像构建研究能够为基础医学的本科生和研究生教育提供新的改革思路,促进医学教育事业的发展。This study selected behavior characteristic indicators such as learning behavior,comprehensive ability and quality development.After data preprocessing,the random forest was used to select important eigenvalue,the improved entropy weight method was used to weight the selected important eigenvalue,and the cluster analysis was used to construct the student group portrait based on the whole process education data.The application prospect of student portraits based on artificial intelligence technology in basic medical education was discussed.Research has found the research on the construction of student portraits based on artificial intelligence technology provides new reform ideas for undergraduate and graduate education of basic medicine,and promotes the development of medical education.

关 键 词：学生画像 随机森林 基础医学 行为特征 特征指标 聚类分析 

分 类 号：G641[文化科学—高等教育学] G642[文化科学—教育学] R322[医药卫生—人体解剖和组织胚胎学]