Assessing Students' Clinical Reasoning Using Gaze and EEG Features

被引：2

作者：

Jraidi, Imene ^{[1
]}

Ben Khedher, Asma ^{[1
]}

Chaouachi, Maher ^{[2
]}

Frasson, Claude ^{[1
]}

机构：

[1] Univ Montreal, Dept Comp Sci & Operat Res, Montreal, PQ H3T 1N8, Canada

[2] McGill Univ, Dept Educ & Counselling Psychol, Montreal, PQ H3A 1Y2, Canada

来源：

INTELLIGENT TUTORING SYSTEMS (ITS 2019) | 2019年 / 11528卷

基金：

加拿大自然科学与工程研究理事会;

关键词：

Eye tracking; Scanpath; EEG; Engagement; Workload; Clinical reasoning; Learning performance; ENGAGEMENT;

D O I：

10.1007/978-3-030-22244-4_7

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：47 / 56

页数：10

共 26 条

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