PhD defense, Aous KAROUI

 

Title : Mobile Learning Games: JEM Inventor, an authoring tool based on a nested design approach

 

Jury :

  • Baltasar FERNÁNDEZ-MANJÓN Professeur des Universités, Universidad Computense de Madrid
  • Jean-Marc LABAT Professeur des Universités émérite, Sorbonne Université
  • Jean-Charles MARTY Maître de Conférences HDR, Université Savoie Mont Blanc
  • Margarida ROMERO Professeur des Universités, Université Nice Sophia Antipolis
  • Sébastien GEORGE Professeur des Universités, Le Mans Université – Directeur de thèse
  • Iza MARFISI-SCHOTTMAN Maître de Conférences, Le Mans Université – Co-encadrante de thèse

 

Abstract:

The rise of mobile devices (e.g. tablets, smartphones) and their educational and recreational applications have contributed to the emergence of Mobile Learning Games (MLGs). Indeed, MLGs show great potential for increasing engagement, creativity and authentic learning. Yet, despite their great potential for education, the use of MLGs by teachers, remains very limited. This is partly due to the fact that MLGs are often designed to match a specific learning context, and thus cannot be directly reusable for other contexts. In addition, existing authoring tools are either feature-rich but require a significant investment by teachers to be used, or simple to use but do not offer enough features for the design of MLGs that meet pedagogical needs.

To tackle these problems, we propose JEM Inventor, a MLG authoring tool, based on a nested design approach, intended for teachers, museum curators, or any person without computer skills, wishing to script their own MLG and deploy them on mobile systems.

The nested design approach consists in progressively revealing the functionalities of the authoring tool, according to the complexity level that corresponds to the skills and needs of each user. For our case of study, we offer three design levels in the JEM Inventor tool. Thus, the standard level allows MLGs based on a generic model to be configured, the intermediate level allows customized scenarios to be created, and finally, the expert level allows customized MLGs to be programmed. The nested design model was approved through a series of experimentations with some twenty teachers from a wide range of expertise levels and teaching fields. We also conducted field experimentations with about 1500 students and pupils in order to evaluate the quality of MLGs created with JEM Inventor as well as their impact on learners.