Abstract
The purpose of this work is to analyze the learners’ visual and brain behaviors during clinical reasoning. An experimental study was conducted to record gaze and EEG data of 15 novice medical students as they interacted with a computer-based learning environment in order to treat medical cases. We describe our approach to track the learners’ reasoning process using the visual scanpath followed during the clinical diagnosis and present our methodology to assess the learners’ brain activity using the engagement and the workload cerebral indexes. We determine which visual and EEG features are related to the students’ performance and analyze the relationship between the students’ visual behavior and brain activity.
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Acknowledgments
This work was supported by NSERC (National Science and Engineering Research Council) and SSHRC (Social and Human Research Council) through the LEADS project. We also thank Issam Tanoubi from the University of Montreal for his collaboration in the design of the Amnesia environment.
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Jraidi, I., Khedher, A.B., Chaouachi, M., Frasson, C. (2019). Assessing Students’ Clinical Reasoning Using Gaze and EEG Features. In: Coy, A., Hayashi, Y., Chang, M. (eds) Intelligent Tutoring Systems. ITS 2019. Lecture Notes in Computer Science(), vol 11528. Springer, Cham. https://doi.org/10.1007/978-3-030-22244-4_7
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