Indexing Learning Scenarios by the Most Adapted Contexts: An approach Based on the Observation of Scenario Progress in Session

Abstract

The BASAR project offers a repository of blended learning scenarios. This project aims to reuse and capitalize good teaching practices. A teacher-designer would have the ability to choose a scenario that matches his needs, to be modified, used and refined. Specializing the scenario to a given context often improves the learning quality. On the other hand, it increases the difficulty to reuse it in a different context. Knowing the appropriate contexts for a scenario is essential for better reusing a part of this scenario or all of it (granularity). So, how can we characterize the learning scenarios with their most appropriate contexts based on the observation of the learning sessions progress in order to enhance scenario retrieval? This paper proposes a multi-faceted approach to index learning scenarios using the context trees formalism. The main objective of this indexing is to facilitate the learning scenarios design by and for reuse.