Improving training performances with the EBAGG metaphor

Florian Jeanne (1) , Indira Thouvenin (1) , Alban Lenglet (1)

1 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]

Augmented feedback has been shown to improve interaction in virtual environments and to facilitate motor learning. Recent studies proposed this type of feedback to guide users, to highlight specific areas or to help them to perform a specific task. They can follow a path, pass through specific waypoints or even mimic an avatar. However these approaches do not show the gap between learners' performance and the desired one. Our hypothesis is that by revealing this gap to the users, they will reduce it step by step and tend to the required performance. Thus, in this paper, we propose a new visual metaphor to guide trainees' gestures by showing trajectory errors instead of showing the path to follow. In a first study we evaluated trainees' improvement by measuring the mentioned gap. First results indicate that our approach allows an enhanced task performance.

Domaines: Synthèse d'image et réalité virtuelle [cs.GR]; Environnements Informatiques pour l'Apprentissage Humain

Florian Jeanne, Indira Thouvenin, Alban Lenglet. Improving training performances with the EBAGG metaphor. Journées de l’Informatique Graphique et de la Réalité Virtuelle(IGRV 2017), Oct 2017, Rennes, France. ⟨hal-01713088⟩