Abstract
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%.
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Heraz, A., Frasson, C. (2009). Detecting Guessed and Random Learners’ Answers through Their Brainwaves. In: Houben, GJ., McCalla, G., Pianesi, F., Zancanaro, M. (eds) User Modeling, Adaptation, and Personalization. UMAP 2009. Lecture Notes in Computer Science, vol 5535. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02247-0_38
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DOI: https://doi.org/10.1007/978-3-642-02247-0_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02246-3
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