Claire Lecocq

A Framework for the Generation of Adaptive Courses Based on Semantic Metadata

This approach proposes the creation and management of adaptive learning systems by combining component technology, semantic metadata, and adaptation rules. A component model allows interaction among components that share consistent assumptions about what each provides and each requires of the other. It allows indexing, using, reusing, and coupling of components in different contexts powering adaptation. Our claim is that semantic metadata are required to allow a real reusing and assembling of educational component. Finally, a rule language is used to define strategies to rewrite user query and user model. The former allows searching components developing concepts not appearing in the user query but related with user goals, whereas the last allow inferring user knowledge that is not explicit in user model.

A RDF description model for manipulating learning objects

Our claim is that semantic metadata are required to allow a real reusing and assembling of learning objects. Our system is based on three models used to describe the knowledge domain, users and learning objects. In order to automatically process these models and make available basic reasoning capabilities, we have defined mappings to RDF. A prototype is being developed using Sesame, an RDF tool that supports the declarative query language SeRQL. This paper focuses on RDF mappings definition and how to use SeRQL to achieve the functionality required by our approach.

A situation-based delivery of learning resources in pervasive learning

Pervasive learning systems must define new mechanism to deliver the right resource, at the right time, at the right place to the right learner. This means that rich context information has to be considered: time, place, user knowledge, user activity, user environment and device capacity. As context is based on numerous information which may change frequently (coming from a collection of captors), a more aggregate view is defined to work on more abstract objects: the situations. Context information and situation information have to be widespread into all the models of learning systems: context preferences have to be handled in the learner model, well-adapted situation and situation scenarios have to be memorized in learning resource model. The adaptation process is enriched too.

Use cases of heterogeneous learning ontologies

The emergence of new repositories of learning resources based on semantic technology raises the problem of ontologies interoperability. Learning resources are described by a set of metadata which may use different ontologies as referential. To handle the increasing number of heterogeneous ontologies it becomes necessary to develop automatic mapping approach. In this paper we propose to study technical solutions for ontologies handling through two use cases: (1) the comparison between a current learner profile and a target profile and (2) the search of learning resources among distributed repositories.

Experiments in Ubiquitous Computing for Communities of Practice Using Learning Resources

We present in this paper the interest of ubiquitous computing for the so called contextualized forums. These forums allow communities of practice exchanging and sharing experiences or situations already lived by using learning documents to classify these exchanges. These forums contain a lot of information which contribute to improve classical training. We study here ubiquitous computing possibilities to use this type of forums in order to improve professional training to business process by helping the user to put his/her acquisition into practice. The developed application is being tested and works mainly on smartphones.

L'informatique omniprésente pour les communautés de pratique autour de contenus pédagogiques

We present in this paper the interest of ubiquitous computing for the so called contextualized forums. These forums allow communities of practice exchanging and sharing experiences or situations already lived by using learning documents to classify these exchanges. These forums contain a lot of information which contribute to improve classical training. We study here ubiquitous computing possibilities to use this type of forums in order to improve professional training to business process by helping the user to put into practice his/her acquisition. The developed application is being tested and works principally on smartphones.

Distance Evaluation Between a Current and a Target Learner Profile

Nowadays, myriad of Web-based educational systems (WBES) exists, each of them storing their own learners models and resources. Our work is a contribution to ontology-based WBES adaptability. As a first result, we have proposed a solution to measure the distance between two ontologies instances representing two learner profiles: the current one and a target one