Computing the Context Effect for Science Learning

Abstract

International audienceIn science learning, context is an important dimension of any scientific object or phenomenon, and context-dependent variations prove to be as critical for deep understanding as are abstract concepts, laws and rules. The hypothesis presented is that a context gap between two students can be illuminating to highlight the respective general-particular aspects of an object or phenomenon. Furthermore, provoking a perturbation during the learning process to obtain the emergence of such an event could be a productive tutoring strategy. The authors introduce the emergence of context effects as a problem space, to be modeled in the system, and propose a model of the contextual dimension (MazCalc) associated with an analytical view of its modeling, based on a metaphor in physics. A Learning Scenario (Gounouy) has been designed and tested with two groups of learners in Guadeloupe and in Quebec, and MazCalc has been instantiated for this pilot study. Finally, an architecture of a Context-Aware Intelligent Tutoring System is presented, with services to learners, teachers and researchers