Implicit modeling of learners’ personalities in a game-based learning environment using their gaming behaviors

Abstract

Abstract While the most used method to model the learner’s personality is the self-report using questionnaires, this study presents and validates a newly developed framework for implicitly modeling the learners’ personalities within a game-based learning environment using their gaming behaviors. This framework is based on an online role-playing game for teaching the computer architecture subject and a learning analytics system. To evaluate the efficiency of the proposed framework, an experiment was conducted with forty four participants (34 learners and 11 teachers) in a Tunisian University. The obtained results showed that this framework has a high accuracy level in correctly modeling both the extraversion and openness personality dimensions. In addition, these results highlighted a “good” and “moderate” agreement degree in modeling the extraversion and openness personality dimensions respectively compared to the Big Five Inventory (BFI). The findings of this study can advance research in game-based learning and educational psychology by developing environments which can be used for both learning and modeling learners’ personalities instead of using questionnaires.

Keywords

• Personality
• Learner modeling
• Learning analytics
• Game-based learning
• Gaming behaviors
• Data analysis