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