Developments in Educational Recommendation Systems: a systematic review

被引:3
|
作者
Ramos Pinho, Paulo Cesar [1 ]
Barwaldt, Regina [1 ]
Espindola, Dunubia [1 ]
Torres, Marcio [1 ]
Pias, Marcelo [1 ]
Topin, Luiz [1 ]
Borba, Albano [1 ]
Oliveira, Myke [1 ]
机构
[1] Univ Fed Rio Grande FURG, Ctr Ciencias Computacionais C3, Rio Grande, Brazil
关键词
Educational Recommendation System; Pedagogical Context; Personalized Recommendation;
D O I
10.1109/fie43999.2019.9028466
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
This abstract refers to a full paper in the research category. This paper presents a Systematic Review (SR) that. aims at characterising the current scenario of Educational Recommendation Systems (ERS). ERS has recently attracted the attention of researchers in developing methods that contribute to the educational environment. Recommendation systems capable of searching and selecting relevant contents are one of the core technological resources offered to the education sector. Such systems which were initially designed for commercial applications (e.g. e-commerce) have now been used in educational application-driven research. For instance, a teacher might rethink methodologies and practises tailored to a set of pedagogical needs. These resources are enablers for the tools development that contribute to better educational practices. The goal of this SR is to provide an analysis of the current research efforts in the field of educational recommendation systems. With the string search of "educational support" AND "recommendation system" used in four academic databases (Brazil and International) 2016 and 2018. The SR returned 439 papers of which 54 were selected for further analysis. The results show that the profile based filtering technique for recommendation is the most used, occurring 27.78% of the studies. In 44.44% of these studies, the target audience has been the students. Furthermore, the usual evaluation method was experimental achieving 41% of the selected papers. The results demonstrate applications in learning situations as the recommendation of digital resources, related to learning styles and based on ability and performance.
引用
收藏
页数:7
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