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General Information
    • ISSN: 2010-3689 (Online)
    • Abbreviated Title: Int. J. Inf. Educ. Technol.
    • Frequency: Monthly
    • DOI: 10.18178/IJIET
    • Editor-in-Chief: Prof. Dr. Steve Thatcher
    • Executive Editor: Ms. Nancy Y. Liu
    • Abstracting/ Indexing: Scopus (Since 2019), EI(INSPEC, IET), EBSCO, Electronic Journals Library, Google Scholar, Crossref, etc.
    • E-mail: ijiet@ejournal.net
Editor-in-chief
Prof. Dr. Steve Thatcher
CQUniversity, Australia
It is my honor to be the editor-in-chief of IJIET. The journal publishes good-quality papers which focous on the advanced researches in the field of information and education technology. Hopefully, IJIET will become a recognized journal among the scholars in the related fields.

IJIET 2019 Vol.9(10): 678-688 ISSN: 2010-3689
doi: 10.18178/ijiet.2019.9.10.1287

Enhancing the Learning Experience Using Real-Time Cognitive Evaluation

Maher Chaouachi, Imène Jraidi, Susanne P. Lajoie, and Claude Frasson
Abstract—There is increasing evidence that learners’ affective and cognitive states play a key role in the learning process. This suggests that systems which are able to detect these states can dynamically use adapted strategies to increase the pace of the learners’ skill acquisition and improve their learning experience. In this work, we present a novel approach for automatically adapting the learning strategy in real-time according to the learner’s detected mental state. The main goal of the approach is to maintain the learner in a positive state during a lesson by adaptively selecting the best interaction strategy between either using problem solving or worked examples. Two mental indexes, namely, cognitive load and mental engagement were extracted from electroencephalogram (EEG) signals, and used to adapt the system’s interaction. The cognitive load index was developped by training and validating a prediction model on various types of memory and logical tasks. The engagement index was directly computed from the EEG signal frequency bands. An experiment with 14 learners was performed in order to evaluate this approach. The obtained results showed that using the learner’s mental state to adapt the system’s interaction has a positive impact on the learning outcomes, the learning experience and the learners’ reported emotional states.

Index Terms—Adaptive system, mental engagement, cognitive load, EEG, affect, learning performance, learning experience.

M. Chaouachi, I. Jraidi, and S. P. Lajoie are with the Department of Educational and Counselling Psychology, McGill University, 3700 McTavish Street, Montréal, QC H3A 1Y2, Canada (e-mail: maher.chaouachi@mcgill.ca, imene.jraidi@mcgill.ca, susanne.lajoie@mcgill.ca).
C. Frasson is with the Department of Computer Science and Operations Research, University of Montreal, 2920 Chemin de la Tour, Montréal, H3T-1J8 QC, Canada (e-mail: claude.frasson@umontreal.ca).

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Cite: Maher Chaouachi, Imène Jraidi, Susanne P. Lajoie, and Claude Frasson, "Enhancing the Learning Experience Using Real-Time Cognitive Evaluation," International Journal of Information and Education Technology vol. 9, no. 10, pp. 678-688, 2019.

Copyright © 2019 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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E-mail: ijiet@ejournal.net