Clustering Methods Applied to the Tracking of user Traces Interacting with an e-Learning System

Many research works are carried out on the analysis of traces in a digital learning environment. These studies produce large volumes of usage tracks from the various actions performed by a user. However, to exploit these data, compare and improve performance, several issues are raised. To remedy this, several works deal with this problem seen recently. This research studied a series of questions about format and description of the data to be shared. Our goal is to share thoughts on these issues by presenting our experience in the analysis of trace-based log files, comparing several approaches used in automatic classification applied to e-learning platforms. Finally, the obtained results are discussed.

Authors:

• Larbi Omar
• Elberrichi Zakaria

Keywords:

• Classification
• e-learning platform
• log file
• Trace.

References:

[1] N. Bousbia, "Analyse des traces de navigation des apprenants dans un
environnement de formation dans une perspective de détection
automatique des styles d-apprentissage", PhD thesis in Computer
Science, University Pierre and Marie Curie (France) and Higher
National School of Computer Science, ESI, Algeria, 2011.
[2] M. Charrad, "Une approche générique pour l-analyse croisant contenu et
usage des sites web par des méthodes de bipartitionnement", Presented
for obtaining a doctorate in Computer Science from the CNAM, Paris
and ENSI, University of Manouba, 2010.
[3] W. Hengshan and al., "Design and implementation of a web usage
mining model based on fpgrowth and prefixspan". In: Communications
of the IIMA, 2006.
[4] L. Settouti, Y. Prié, A. Mille, J-C. Marty, "Système ├á base de traces
pour l'apprentissage humain", In: ICTE International Symposium,
Information Technology and Communication in Higher Education and
Enterprise, Toulouse, 2006.
[5] B. Arnaud, "Personnalisation et prise en compte du contexte dans les
modèles conceptuels pour la conception des si", Prise Accounting for
the User Information Systems, Proceedings pecus, Toulouse, 2009.
[6] BENATCHBA, "Application de techniques de data mining pour la
classification automatique des données". Thesis studies to obtain the
engineering degree in Computer Science, 2010.
[7] M. Charrad, "Techniques d-extraction de connaissances appliquées aux
données du web", Master Thesis in Computer Science, National School
of Computer Science, University of Manouba, Tunisia, 2005.
[8] H. BENSEFIA, "Fichiers logs: preuves judiciaires et composant vital
pour forensics", RIST Vol.15 No. 01-02, 2005.
[9] F. Marius, "Data mining, fouille de données: concepts et techniques".
Faculty of Medicine, Marseille, 2006.
[10] P. Giacomini, "Un environnement collaboratif d-enseignement à
distance adapté au profil de l-apprenant". International Journal of
Information Sciences for Decision Making, TICE Mediterranean Sfax
Tunisia, 2008.