Recommendation Systems for Education: Systematic Review

被引:50
|
作者
Cora Urdaneta-Ponte, Maria [1 ,2 ]
Mendez-Zorrilla, Amaia [1 ]
Oleagordia-Ruiz, Ibon [1 ]
机构
[1] Univ Deusto, Fac Engn, eVIDA Res Grp, Bilbao 48007, Spain
[2] Andres Bello Catholic Univ UCAB, Fac Engn, Ciudad Guayana 08050, Venezuela
关键词
systematic review; recommendation systems; education; machine learning;
D O I
10.3390/electronics10141611
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recommendation systems have emerged as a response to overload in terms of increased amounts of information online, which has become a problem for users regarding the time spent on their search and the amount of information retrieved by it. In the field of recommendation systems in education, the relevance of recommended educational resources will improve the student's learning process, and hence the importance of being able to suitably and reliably ensure relevant, useful information. The purpose of this systematic review is to analyze the work undertaken on recommendation systems that support educational practices with a view to acquiring information related to the type of education and areas dealt with, the developmental approach used, and the elements recommended, as well as being able to detect any gaps in this area for future research work. A systematic review was carried out that included 98 articles from a total of 2937 found in main databases (IEEE, ACM, Scopus and WoS), about which it was able to be established that most are geared towards recommending educational resources for users of formal education, in which the main approaches used in recommendation systems are the collaborative approach, the content-based approach, and the hybrid approach, with a tendency to use machine learning in the last two years. Finally, possible future areas of research and development in this field are presented.
引用
收藏
页数:21
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