文章基本信息

标题：An Effective Student Grouping and Course Recommendation Strategy Based on Big Data in Education
本地全文：下载
作者：Yu Guo ; Yue Chen ; Yuanyan Xie 等
期刊名称：Information
电子版ISSN：2078-2489
出版年度：2022
卷号：13
期号：4
页码：197
DOI：10.3390/info13040197
语种：English
出版社：MDPI Publishing
摘要：Personalized education aims to provide cooperative and exploratory courses for students by using computer and network technology to construct a more effective cooperative learning mode, thus improving students’ cooperation ability and lifelong learning ability. Based on students’ interests, this paper proposes an effective student grouping strategy and group-oriented course recommendation method, comprehensively considering characteristics of students and courses both from a statistical dimension and a semantic dimension. First, this paper combines term frequency–inverse document frequency and Word2Vec to preferably extract student characteristics. Then, an improved K-means algorithm is used to divide students into different interest-based study groups. Finally, the group-oriented course recommendation method recommends appropriate and quality courses according to the similarity and expert score. Based on real data provided by junior high school students, a series of experiments are conducted to recommend proper social practical courses, which verified the feasibility and effectiveness of the proposed strategy.