Improve the Adaptation Navigation in Educational Cross-systems

The adaptive educational systems include several solutions for providing personalized access to the learning process. The learner's profile constitutes the key element of these solutions. Therefore, an educational system represents the learner's profile by its own syntax, semantic and structure. Each system can have incomplete or partial learner's data. As a consequence, there is a strong need to exchange the learner's profiles between different systems to enhance and enrich the learner's knowledge. However, the data exchange between the learner's profiles implies interoperability problems. In our work, we are interested in the evolving learner's profiles interoperability problem. In this context, we propose an architecture allowing the data exchange of the learner's profile in educational cross-systems in order to improve the adaptation navigation. This architecture is automatically adapted to the learner's profiles that evolve over time. These latter are syntactically, semantically and structurally heterogeneous. The evaluation values show the effectiveness of our approach.