A Model-Driven Engineering Process to Support the Adaptive Generation of Learning Game Scenarios

Pierre Laforcade (1) , Esteban Loiseau (1) , Rim Kacem

1 LIUM - Laboratoire d'Informatique de l'Université du Mans

Adaptation is a key-concern when developing serious games for learning purposes, particularly for people with specific needs. This paper presents a Model-Driven Engineering framework that eases the design and the validation of adaptive learning scenarios. It tackles the personalization issue by helping domain experts and computer scientists in making explicit then in validating the domain elements and rules involved in the adaptation. The framework proposes a metamodeling process based on a metamodel specifying at first the domain elements according to both a 3-incremental-perspective on the resulting scenario, and a 3-dimensions specification of domain elements to use and produce. The framework then proposes to model the game description and the child’s profile as input models for the generator that will produce the adapted scenario as an output model. We applied the framework in the context of the Escape it! project that aims at helping young children with Autistic Syndrome Disorder to learn and generalize visual performance skills.

Mots clés: Serious Games; Adaptation; Learning Game Scenario; Generation; Metamodeling

Domaines: Environnements Informatiques pour l'Apprentissage Humain

Pierre Laforcade, Esteban Loiseau, Rim Kacem. A Model-Driven Engineering Process to Support the Adaptive Generation of Learning Game Scenarios. CSEDU, INSTICC, Mar 2018, Funchal, Madeira, Portugal. pp.67-77. ⟨hal-01740062⟩