Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge
ICALT '01 Proceedings of the IEEE International Conference on Advanced Learning Technologies
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Stoop to Conquer: Posture and Affect Interact to Influence Computer Users' Persistence
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
Balancing Cognitive and Motivational Scaffolding in Tutorial Dialogue
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Decision Tree for Tracking Learner's Emotional State Predicted from His Electrical Brain Activity
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Mixture of gaussian processes for combining multiple modalities
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
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This paper describes an experiment in which we tried to predict the learner's answers from his brainwaves. We discuss the efficiency to enrich the learner model with some electrical brain metrics to obtain some important information about the learner during a test. We conducted an experiment to reach three objectives: the first one is to record the learner brainwaves and his answers to the test questions; the second is to use machine learning techniques to predict guessed and random answers from the learner brainwaves; the third is to implement an agent that transmits the prediction results to an Intelligent Tutoring System. 21 participants were recruited, 45827 recording were collected and we reached a prediction accuracy of 96%.