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Assessing Students’ Clinical Reasoning Using Gaze and EEG Features

  • Imène JraidiEmail author
  • Asma Ben Khedher
  • Maher Chaouachi
  • Claude Frasson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11528)

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.

Keywords

Eye tracking Scanpath EEG Engagement Workload Clinical reasoning Learning performance 

Notes

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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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Imène Jraidi
    • 1
    Email author
  • Asma Ben Khedher
    • 1
  • Maher Chaouachi
    • 2
  • Claude Frasson
    • 1
  1. 1.Department of Computer Science and Operations ResearchUniversity of MontrealMontrealCanada
  2. 2.Department of Educational and Counselling PsychologyMcGill UniversityMontrealCanada

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