Evaluating usability of brain signals for content adaptation in intelligent tutoring systems

Abstract

Designing intelligent tutoring systems (ITS) requires appropriate assessment tools to ensure a good usability by learners. In this work we discuss the process of content adaptation in ITS. We study and assess the usability of a brain-activity-based approach to address the issue of content adaptation in ITS. The approach aims at continuously assessing the learners' mental states during a learning task. Results from this investigation are motivating to design future content adaptation architectures of ITS which take advantage from brain signals.