Towards a Brain-Sensitive Intelligent Tutoring System : Detecting Emotions from Brainwaves
Joint Authors
Source
Advances in Artificial Intelligence
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-06-14
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Information Technology and Computer Science
Science
Abstract EN
This paper proposes and evaluates a multiagents system called NORA that predicts emotional attributes from learners' brainwaves within an intelligent tutoring system.
The measurements from the electrical brain activity of the learner are combined with information about the learner's emotional attributes.
Electroencephalogram was used to measure brainwaves and self-reports to measure the three emotional dimensions: pleasure, arousal, and dominance, the eight emotions occurring during learning: anger, boredom, confusion, contempt curious, disgust, eureka, and frustration, and the emotional valence positive for learning and negative for learning.
The system is evaluated on natural data, and it achieves an accuracy of over 63%, significantly outperforming classification using the individual modalities and several other combination schemes.
American Psychological Association (APA)
Heraz, Alicia& Frasson, Claude. 2011. Towards a Brain-Sensitive Intelligent Tutoring System : Detecting Emotions from Brainwaves. Advances in Artificial Intelligence،Vol. 2011, no. 2011, pp.1-13.
https://search.emarefa.net/detail/BIM-467822
Modern Language Association (MLA)
Heraz, Alicia& Frasson, Claude. Towards a Brain-Sensitive Intelligent Tutoring System : Detecting Emotions from Brainwaves. Advances in Artificial Intelligence No. 2011 (2011), pp.1-13.
https://search.emarefa.net/detail/BIM-467822
American Medical Association (AMA)
Heraz, Alicia& Frasson, Claude. Towards a Brain-Sensitive Intelligent Tutoring System : Detecting Emotions from Brainwaves. Advances in Artificial Intelligence. 2011. Vol. 2011, no. 2011, pp.1-13.
https://search.emarefa.net/detail/BIM-467822
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-467822