Adaptive Learning in an Educational Game – Adapting Game Complexity to Gameplay Increases Efficiency of Learning

Abstract

This thesis investigates the possibilities of adaptivity in an educational game called Code Red: Triage. This game lets players assume the role of a medical first responder who has to triage victims. A triage is a procedure through which medical personnel can determine the priority of a victim. The first hypothesis of this thesis is that, by making the game adapt itself autonomously to the player, it becomes more efficient. That is, based on how a player performs in the game, the game changes its properties to suit his needs. The second hypothesis is that the player feels more engaged by the game if it adapts itself to his needs. This would be the case because he would be challenged optimally by the adaptations the game makes. The adaptation consists of determining which victim cases should be presented to the player. Each victim has his own complexity, so when a player reaches a particular skill level, slightly more complex victims are presented to him. This idea is implemented in Code Red: Triage and subjected to an experiment in order to falsify the hypotheses. The experiment is comparitive in nature and features two groups: one playing the adaptive version of the game and one (the control group) playing the non-adaptive version. Results from the experiment confirm the hypothesis concerning efficiency: adaptivity in the game lets players gain knowledge faster, i.e., in less time and in less victim cases. Thus, adaptive learning is more efficient than static learning. However, engagement was found not to differ between conditions, disproving the second hypothesis. Nonetheless, these outcomes indicate that adaptivity has promising possibilities for educational games by saving time and effort of the players. Future research should investigate in different possibilities of in-game adaptivity that heighten efficiency or engagement.