6533b825fe1ef96bd1281c0d

RESEARCH PRODUCT

Recommender system for combination of learning elements in mobile environment

F. Soualah-alilaF. MendesChristophe CruzC. Nicolle

subject

spatiotemporal contextmetaheuristics[ INFO.INFO-IU ] Computer Science [cs]/Ubiquitous Computing[INFO.INFO-IU] Computer Science [cs]/Ubiquitous Computing[INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG][ INFO.INFO-LG ] Computer Science [cs]/Machine Learning [cs.LG][INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-MC]Computer Science [cs]/Mobile Computing[INFO.INFO-MC] Computer Science [cs]/Mobile Computing[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]learner's profile[ INFO.INFO-MC ] Computer Science [cs]/Mobile Computingontologym-learningRecommender system

description

5 pages; International audience; The paper presents an ongoing research about the development of a new recommender system dedicated to m-learning. This system is an extension of content based recommender system proposals. It's made of three levels architecture: 1/ a domain model describing the knowledge of teaching, 2/ a user model defining learner's profile and learning's context, 3/ an adaptation model containing rules and metaheuristics, which aims at combining learning modules. Our system takes into account the spatio-temporal context of the learners, the evolution of learner's profile and the dynamic adaptation of modules during the learning process in a mobile environment. The result of the recommendation is one of the best combinations of pieces of training according to mobility constraints of learners and of the know-how of teachers.

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