Using the Petri Nets for the Learner Assessment in Serious Games

Abstract

Game-based learning or serious games is becoming an important trend in the e-learning research area and seems address several typical e-learning problems such as high dropout rates, due to the lack of motivation to continue studying. In serious games, it is very hard to define and mix the learning situations with the game characteristics, and to integrate an assessment and guidance process of the learner without disturbing the game progress and maintain the intrinsic characteristics of the video game: fun, player motivation, immersion and interaction. In this paper, we consider the serious game as an asynchronous and concurrent system, and we propose an approach based on a Petri net to assess learners and detect misconceptions. In the game design stage, a discussion between domain experts, learning experts, and game designers is engaged in order to identify the actions in the game that imply knowledge acquisition and allow achieving the learning objectives of levels. Therefore, in our approach, the Petri net models only game actions allowing the learner to acquire knowledge. We use the reachability graph of the Petri net to track the learner in order to detect, in real time, the learner’s misconceptions, improve learner assessment and provide an accurate feed back for both the learner and the instructor.