Improve Performance of Recommender System in Collaborative Learning Environment based on Learner Tracks
Tang, Qing; Abel, Marie-Hélène; Negre, Elsa (2020), Improve Performance of Recommender System in Collaborative Learning Environment based on Learner Tracks, in Salgado, Ana; Bernardino, Jorge; Filipe, Joaquim, Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - (Volume 3), SciTe Press, p. 270-277. 10.5220/0010214702700277
Type
Communication / ConférenceDate
2020Conference title
12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KMIS 2020)Conference date
2020-11Book title
Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - (Volume 3)Book author
Salgado, Ana; Bernardino, Jorge; Filipe, JoaquimPublisher
SciTe Press
ISBN
978-989-758-474-9
Pages
270-277
Publication identifier
Metadata
Show full item recordAuthor(s)
Tang, QingAbel, Marie-Hélène
Negre, Elsa
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)
Learning with huge amount of open educational resources is challenging, especially when variety resources come from different System of Information Systems (SoIS). How to help learners obtain appropriate resources efficiently in collaborative learning environment is still a rigorous problem of research. This paper proposes a method to calculate learner’s knowledge competency by tracking and analyzing their behaviors in a collaborative learning environment based on SoIS, and combining other basic learner’s information to build a personalized recommender system to help learners select appropriate educational resources to improve their learning efficiencySubjects / Keywords
Online Learning; SoIS; Collaborative Learning Environment; Recommender System; Learner TrackRelated items
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