How to Evaluate Competencies in Game-Based Learning Systems Automatically?

Pradeepa Thomas (1) , Jean-Marc Labat (1) , Mathieu Muratet (1) , Amel Yessad (1)

1 MOCAH - Modèles et Outils en ingénierie des Connaissances pour l'Apprentissage Humain

Serious games are increasingly used in schools, universities or in vocational training. When they are used in the classroom, teachers often have to deal with the lack of tools for monitoring the students during the game and assessing them after the game. So they often tend to add assessment questionnaires to the fun sequence of " learning by playing " , to ensure that students have learned during the session. Our goal is to enable the teacher to do without this type of questionnaires by providing them an automated tool for monitoring and analyzing the actions performed by learners. The system combines an " expert Petri Net " and a domain and game action ontology. Our first experiment conducted on a sample of fifteen students showed that the diagnostic tool gives relatively close results to those of an online assessment questionnaire proposed by the teacher.

Mots clés: Serious games; Game-based learning; Assessment; Petri Nets; User tracking

Domaines: Environnements Informatiques pour l'Apprentissage Humain

Pradeepa Thomas, Jean-Marc Labat, Mathieu Muratet, Amel Yessad. How to Evaluate Competencies in Game-Based Learning Systems Automatically?. 11th international conference on Intelligent Tutoring Systems, Jun 2012, Chania, Greece. pp.168-173, ⟨10.1007/978-3-642-30950-2_22⟩. ⟨hal-01359548⟩