Nihad El Ghouch
ABSTRACT
The adaptation of the Computing Environment for Human Learning allows adapting the process of learning to needs, to rhythms of every learner, to styles of learning and to preferences, but they do not guarantee an individualized real time follow-up, by favoring the learning of a domain of the acquisition of the knowledge by a learner.
One of the objectives of the systems based on the acquisition of the knowledge is to build computer systems allowing the sharing and the re-use of the past experiences, to ensure personalized learning in real-time, by basing on the profile and the rhythm of learning of every learner. The approach of Case-Based Reasoning seems to be a good candidate for the sharing and the re-use of the experience. In this article, we are going to present our architecture of a System of Adaptive Learning by using a Dynamic Case-Based Reasoning and the traces of interactions of the learner with the learning system as the support of reasoning.
- Nigel Ford and Sherry Y Chen. Individual differences, hypermedia navigation, and learning: an empirical study. Journal of educational multimedia and hypermedia, 9(4):281--311, 2000 Google Scholar
Digital Library
- Nabila Bousbia, IssamRebai, Jean-Marc Labat, and Amar Balla. Analysing the relationship between learning styles and navigation behaviour in web-based educational system. Knowledge Management & E-Learning: An International Journal (KM&EL), 2(4):400--421, 2010.Google Scholar
- Silvia Schiaffino, Patricio Garcia, and AnaliaAmandi. eteacher: Pro-viding personalized assistance to e-learning students. Computers & Education, 51(4):1744--1754, 2008. Google ScholarDigital Library
- BoyanBontchev and DessislavaVassileva. Courseware adaptation to learning styles and knowledge level. Edited by Anderson Silva, Elvis Pontes, page 1, 2012.Google Scholar
- Jermann, P., Soller, A. et Muehlenbrock, M. (2001). From mirroring to guiding: A review of state of the art technology for supporting collaborative learning. In Proceedings of the First European Conference on Computer-Supported Collaborative Learning (p. 324--331).Google Scholar
- Baudouin, C.; Beney, M. et Chevaillier, P. (2007). Recueil de traces pour le suivi de l'activité d'apprenants en travaux pratiques dans un environnement de réalité virtuelle. STICEF (Numéro spécial Analyse des traces d'interactions dans les EIAH), 14Google Scholar
- professionnelle, cas du brevet de technicien supérieur en contrôle industriel et régulation automatique. Thèse de doctorat, Université Claude Bernard, Lyon 1Google Scholar
- Duverlie, P., Castelain, J., &Farineau, T. (1999). Estimation des coûts en production mécanique. Techniques de l'Ingénieur Mise en forme des matériaux par usinage, base documentaire: TIB510DUO.Google Scholar
- Lieber, J. (2008). Contributions à la conception de systèmes de raisonnement à partir de cas. Thèse d'habilitation à diriger les recherches, Université Henri Poincaré, Nancy.Google Scholar
- Fuchs B., Représentation des connaissances pour le raisonnement à partir de cas: Le système ROCADE. Thèse de doctorat, laboratoire Image Signal Acoustique de CPE Lyon, 1997.Google Scholar
- Grabot, B. (2006). Ordonnancement d'ateliers manufacturiers. Techniques de l'Ingénieur Méthodes de production, base de documentaire: TIB521DUO.Google Scholar
- Mille A., Traces bases reasoning (TBR) definition, illustration and echoes with story telling. Rapport Technique RR-LIRIS-2006-002, LIRIS UMR 5205 CNRS/INSA de Lyon/Université Claude Bernard Lyon1/Université Lumière Lyon 2/Ecole Centrale de Lyon, january 2006.Google Scholar
- Abdelhamid Zouhair, « Raisonnement à partir de cas dynamique multi-agents: application à un système de tuteur intelligent», PhD in computer science, in Cotutelle between the Faculty of Sciences and T and Technologies of Tangier (Morocco) and the University of Le Havre (France), supported in October 2014.Google Scholar
- Haouchine K. M., Remémoration guidée par l'adaptation et maintennace des systèmes de diagnostoc industriel par l'approche du raisonnement à partie de cas, Thèse de doctorat, Laboratoire d'automatique de Besançon, université de Franche-Comté, 2009.Google Scholar
- Finnie G., Sun Z., (2003) R5 model for case-based reasoning, Know. Based Syst. 16, pp 59--65 Google ScholarDigital Library
- S. Loriette-Rougegrez, "Raisonnement à partir de cas pour des évolutions spatiotemporelles de processus", revue internationale degéomatique, vol 8, n° 1--2, pp 207-- 227, 1998Google Scholar
- El Mokhtar En-Naimi and AbdelhamidZouhair, "Intelligent dynamic case based reasoning using multi-agents system in adaptive e-service, e-commerce and e-learning systems", International Journal of Knowledge and Learning, Vol.11, No. 1, pp. 42--57, 2016.Google Scholar
- Felder, R.M. and L.K. Silverman, Learning Styles and Teaching Styles in Engineering Education, Nov. 1987.Google Scholar
- NihadElghouch, YassineZaouiSeghroucheni, El Mokhtar En-naimi, BadrEddine El Mohajir, Mohammed Al Achhab: An application to index the didactic resources in an adaptive learning system: The fifth international Conference onInformation and Communication Technology and Accessibility (CTA'2015) M rr k ch M r cc 21--23 Dec 2015, IEEE Proceedings pp 1--3 (2015).Google Scholar
- EddineMohajir, Mohamed Al Achhab "ALS_CO {LP}: An Adaptive Learning System Based on the Learning Styles of Felder-Silverman and a Bayesian Network": 4th Edition of the International Colloquiumon Information Science and Technology CiSt) 16' octobre 26-24, 2016 Tanger-Asilah).Google Scholar
- http://www.memoireonline.com/07/08/1413/m_modelisation-system-multi-agent-hypermedia-educatif20.htmlGoogle Scholar
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