A model driven approach for tracking users' activities within heterogeneous learning environments

This paper suggests a model driven approach dedicated to the management of tracking data resulting from users activities within heterogeneous learning systems based on internet technologies. A generic UML model describing traces allows to structure and to bring semantics to observed data, while a distributed and decentralized architecture makes it easier to share and reuse traces between various tools and services. We then apply this approach to track activities of users working with learning objects deployed into learning management systems and learning object repositories. Finally, we suggest an application to visualize tracking data, together with an advanced search service of learning objects that offers the opportunity to capitalize experiences of a wide community of users