摘要
画像技术在当前精准营销中的应用非常广泛,而其在教育领域尤其是在线学习者的特征识别方面研究较少。文章从学习者的一般特征、学习准备、学习风格、行为特征四个方面对学习者进行分析,提出在线学习者画像描述的总体框架。同时,通过机器学习对在线学习行为数据进行挖掘,文章分别从以上四个方面对学习者画像进行建模研究,重点讨论了学习风格的建模过程,并通过对在线学习者个案分析,阐述了学习者画像在指导学习资源精准推荐、评估在线学习者学业失败或退出风险等方面的应用,为个性化教育实施提供了实践案例。
Portrait technology has been widely used in current precision marketing, but it is rarely used in the field of education, especially in the feature recognition of online learners. This paper analyzed the learner from the four aspects oftheir general characteristics, learning preparation, learning style and behavior characteristics, and proposed the general framework of online learners’ portrait description. Excavating online learning behavior data through machine learning, this paper focused on the modeling process of learning style, and expounded the application of learners’ portraits in the aspects of guiding accurate recommendation of learning resources and evaluating online learners’ school failure or exit risks through the case analysis of online learners, which provided practical examples for the implementation of personalized education.
作者
孙发勤
董维春
SUN FA-qin;DONG Wei-chun(School of Journalism and Communication,Yangzhou University,Yangzhou,Jiangsu,China 225009;College of Public Administration,Nanjing Agricultural University,Nanjing,Jiangsu,China 210095)
出处
《现代教育技术》
CSSCI
北大核心
2020年第4期5-11,共7页
Modern Educational Technology
基金
教育部人文社会科学研究一般项目“大规模在线开放课程学习行为分析研究”(项目编号:15YJC880065)的阶段性研究成果。
关键词
个性化教育
学习风格
学习分析
individualized education
learning style
learning analysis
