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MENTOR: A Physiologically Controlled Tutoring System

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9146)

Abstract

In this paper we present a tutoring system that automatically sequences the learning content according to the learners’ mental states. The system draws on techniques from Brain Computer Interface and educational psychology to automatically adapt to changes in the learners’ mental states such as attention and workload using electroencephalogram (EEG) signals. The objective of this system is to maintain the learner in a positive mental state throughout the tutoring session by selecting the next pedagogical activity that fits the best to his current state. An experimental evaluation of our approach involving two groups of learners showed that the group who interacted with the mental state-based adaptive version of the system obtained higher learning outcomes and had a better learning experience than the group who interacted with a non-adaptive version.

Keywords

Intelligent tutoring system Engagement Workload Real-time adaptive system EEG Machine learning Experience and affect 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Computer Science and OperationsUniversity of MontrealMontrealCanada

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