Nowadays, e-learning offers advantages over traditional learning in terms of independence. Moreover, adaptive e-learning systems take into account learner's profile, such as learning style and level of knowledge, in order to provide the most appropriate learning object. However, the essential challenge is finding and identifying the learning objects from a big corpus while ensuring their independence in different contexts. To overcome these problems of interoperability and accessibility of learning objects, the authors proposed to define a learning semantic Web service for each learning object. This service is an extension of OWLS that encompasses the description of the learning intention and the use of context that characterize a learning object. In this paper, the authors propose a new discovery mechanism based on learning intention and context use guided by the learner's intention and profile in order to offer a personalized learning path. Experimental results prove the efficiency of the proposed approach and approve its notable contribution.

E-learning systems use web service technology to develop distributed applications. Therefore, with the tremendous growth in the number of web services, finding the proper services while ensuring the independence and reusability of the learning objects in a different context has become an important issue and has attracted much interest. This article first proposes an extension of the Ontology Web Language for Services Learning Object (OWLS-LO) model to describe a multi-intentional learning object. This description ensures accessibility to learning objects. This research then presents a service discovery mechanism that uses the new semantic model for service matching. Experimental results show that the proposed semantic discovery mechanism using multi-intention model performs better than discovery mechanism based on single intention.

International audienceIn the present work, we presented a new approach to provide learners with learning paths adapted to their requests. These courses were generated by the composition of the learning semantic Web services. Our approach defined a learning Web service (WS) for each learning object (LO) to overcome the problems of interoperability and accessibility of learning objects. Each WS was represented, in the directory, by a learning semantic Web service (OWLS-LO) to describe a semantic understanding of the object being represented. This semantic approach was described by ontologies

Nowadays, e-learning offers advantages over traditional learning in terms of independence. Moreover, adaptive e-learning systems take into account learner's profile, such as learning style and level of knowledge, in order to provide the most appropriate learning object. However, the essential challenge is finding and identifying the learning objects from a big corpus while ensuring their independence in different contexts. To overcome these problems of interoperability and accessibility of learning objects, the authors proposed to define a learning semantic Web service for each learning object. This service is an extension of OWLS that encompasses the description of the learning intention and the use of context that characterize a learning object. In this paper, the authors propose a new discovery mechanism based on learning intention and context use guided by the learner's intention and profile in order to offer a personalized learning path. Experimental results prove the efficiency of the proposed approach and approve its notable contribution.

This article presents a new approach to provide learners learning paths adapted to their profiles. These courses are generated as the automatic composition of learning services. It is made up of three modules: search module, matching module and composition module. Our approach is based on new model of learning service (SWAP) that extends semantic web service (OWL-S) to describe the semantics of learning modules and facilitated the discovery of learning paths adapted to each learner.