Eye-Tracking for User Attention Evaluation in Adaptive Serious Games

Abstract

The Ideal Path Score (IPS) developed in this work is able to improve adaptivity of serious games by more accurately estimating performance and need for help based on players’ interactions and eye movements. The automatic personalization of adaptive e-learning systems supports effective learning for users with varying levels of knowledge and skills. Particularly in games, indicators informing adaptivity, like attention and performance of the player, should be assessed non-invasively to avoid interrupting the player’s flow experience and to keep up the immersion. Passive sensors like eye tracking can solve this challenge. This paper presents the concept of the IPS and its integration in an adaptive serious game for image interpretation training. The realized IPS-adaptive game assesses performance and attention of players based on eye movements and interactions with the game.