Smart Detector of Learner Style

The detection of learner style allows us to know their style preferred. As a result, we can augment the efficiency of their learning. In this paper, we propose to provide a single solution (the appropriate style) more suited to the learner by looking for the path to generate from the initial state of the profile (Resource Data) to the desired objective. In this contribution, we have transformed the search of adopted learner style into an optimization problem. By applying unsupervised learning method, we are looking to optimize the list of tools/exercises of a training course using genetic algorithms.