Open AccessEducational Resources Recommendation System for a heterogeneous Student Group
Author(s) -
Paula Andrea Rodríguez Marín,
Mauricio Giraldo,
Valentina Tabares,
Néstor D. Duque,
Demetrio Arturo Ovalle
Publication year - 2016
Publication title -
advances in distributed computing and artificial intelligence journal
Language(s) - English
Resource type - Journals
ISSN - 2255-2863
DOI - 10.14201/adcaij2016532130
Subject(s) - educational resources , class (philosophy) , computer science , group (periodic table) , order (exchange) , group learning , mathematics education , face (sociological concept) , knowledge management , psychology , artificial intelligence , pedagogy , sociology , social science , chemistry , organic chemistry , finance , economics
In a face-class, where the student group is heterogeneous, it is necessary to select the most appropriate educational resources that support learning for all. In this sense, multi-agent system (MAS) can be used to simulate the features of the students in the group, including their learning style, in order to help the professor find the best resources for your class. In this paper, we present MAS to educational resources recommendation for group students, simulating their profiles and selecting resources that best fit. Obtained promising results show that proposed MAS is able to delivered educational resources for a student group.