AI-driven Player Experience Modeling in Serious Games for Software Engineering

Abstract

Serious games offer great potential for enhancing software engineering education, yet the use of AI-driven Player Experience Modelling (PEM) remains under-explored in this context. This study investigates how AI-enhanced adaptive features such as difficulty adjustment and dynamic guidance affect player engagement and skill acquisition in the programming game Elara. By comparing AI-driven and traditional versions of the game, the research highlights the benefits of personalized gameplay for supporting learning and motivation. The study demonstrates the promise of AI in tailoring educational experiences and calls for future work to incorporate automated player profiling, larger datasets, and emotional state recognition to further improve adaptive learning in serious games.