Titre : Automated generation of pedagogical activities adapted to the learning context 

Auteurs : Gilles Macchia, Patrick Brézillon,  

Revue : Modeling and Using Context 

Numéro : CONTEXT-21 Special Issue 

Volume : 4 

Date : 2021/07/1 

DOI : 10.21494/ISTE.OP.2021.0689 

ISSN : 2514-5711 

Résumé : Most of intelligent tutoring systems orient the learner towards learning objectives that fit an a priori profile. In AI terms, the teacher establishes a task model that the learner must realize according to a given frame of knowledge, methods and tools. The unique feedback from learners comes from their evaluation. For including the learner in the training-design loop, the task model must be replaced by an activity model of the learner realizing the task. This approach improves the acquisition of new knowledge, competences and skills by the learner This acquisition phase depends essentially on the learner’s background. Making the learning context explicit facilitates this knowledge acquisition. Three frames of references are proposed: for learner modeling, for training specifications and for learning activities. Each frame of reference is described by contextual elements usable for all the learners, but instantiable with a specific value for each learner and each step in the training session. This "learner-driven" training is more relevant than the usual “profile-driven” training. 

Éditeur : ISTE OpenScience