Multidimensional Decision Model for Classifying Learners: the case of Massive Online Open Courses (MOOCs)

Imène Brigui-Chtioui 1 Philippe Caillou 2, 3
2 TAO - Machine Learning and Optimisation
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : A new era of learning is arising, due to the development of the digital world and the maturity of web technologies. Massive open online courses (MOOCs) have emerged in this context and are challenging classical learning in spite of boundaries of time and space. They aim to provide good-quality education to masses that cannot be part of traditional university and school learning processes. This emancipation is coupled with a large amount of data collection via learning platforms. These data constitute a great opportunity to study interactions and to profit from this, in order to optimise learning and knowledge transfer. The challenge in creating value is how to represent, analyse and reuse data in order to characterise learners and so lead to better knowledge transfer. We focus, in this article, on the context of MOOC platforms based on Open edX and in particular the IONISx platform . The purpose of this paper is to propose a decision model that takes advantage of the different datasets available on the learning platform in order to classify learners based on their behaviour and expertise. To this end, we propose a multiagent approach that represents human actors using intelligent agents. A coordinator agent implements the multicriteria decision model in order to optimise the learning process. This agent employs clustering algorithms and has an overview of the learning platform that enables it to assist learners and to learn from experiences and about other agents’ behaviour.
Type de document :
Article dans une revue
Journal of Decision Systems, Editions Hermes, 2017, 〈10.1080/12460125.2017.1252235〉
Liste complète des métadonnées

https://hal.inria.fr/hal-01391011
Contributeur : Philippe Caillou <>
Soumis le : mercredi 2 novembre 2016 - 16:58:20
Dernière modification le : jeudi 5 avril 2018 - 12:30:12

Identifiants

Citation

Imène Brigui-Chtioui, Philippe Caillou. Multidimensional Decision Model for Classifying Learners: the case of Massive Online Open Courses (MOOCs) . Journal of Decision Systems, Editions Hermes, 2017, 〈10.1080/12460125.2017.1252235〉. 〈hal-01391011〉

Partager

Métriques

Consultations de la notice

291