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Context-Aware Adaptive System For M- Learning Personalization

Abstract : Context-aware mobile learning is becoming important because of the dynamic and continually changing learning settings in learner's mobile environment, giving rise to many different learning contexts that are difficult to apprehend. To provide personalization of learning content, we aim to develop a recommender system based on semantic modeling of learning contents and learning context. This modeling is complemented by a behavioral part made up of rules and metaheuristics used to optimize the combination of pieces of learning contents according to learner's context. All these elements form a new approach to mobile learning.
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Contributor : Fayrouz Soualah-Alila <>
Submitted on : Friday, December 4, 2015 - 4:40:32 PM
Last modification on : Monday, May 4, 2020 - 4:42:03 PM
Document(s) archivé(s) le : Saturday, April 29, 2017 - 4:57:15 AM


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  • HAL Id : hal-01238330, version 1


Fayrouz Soualah-Alila, Christophe Nicolle, Florence Mendes. Context-Aware Adaptive System For M- Learning Personalization. IE14 13 th International Conference on Informatics in Economy Education, Apr 2014, Bucharest, Romania. ⟨hal-01238330⟩



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