Research Overview of Educational Recommender Systems
Liangzhong Cui, Fuliang Guo, Yingjie Liang · Proceedings of the 2nd International Conference on Computer Science and Application Engineering · 2018
Recently1, with the thriving development of various educational resources and platforms, the research hotspot of modernization of education is now changing towards providing personalized educational recommendation services to corresponding learners. Firstly, starting from basic definitions and contents of educational recommender systems, we put forward an analysis of the fundamental structure of educational recommender systems while emphatically expounding different research approaches including user modeling, recommended object modeling, recommendation algorithm design and recommendation effect evaluation, etc. Secondly, with deep going analysis, we further introduced frequently used recommendation approaches including content-based recommendation, collaborative filtering-based recommendation, association rule-based recommendation and hybrid recommendation. Finally, in the last part of the article, by combining problems existing in contemporary educational recommender systems as well as comparing both advantages and disadvantages of the four recommendation approaches, we discussed the directions of research and development of educational recommender systems in the future.