Using Real-Time Physiological and Behavioral Data to Predict Students' Engagement during Problem Solving: A Machine Learning Approach

Using Real-Time Physiological and Behavioral Data to Predict Students' Engagement during Problem Solving: A Machine Learning Approach

The goal of this study was to evaluate whether Electroencephalography (EEG) estimates of attention and cognitive workload captured as students solved math problems could be used to predict success or failure at solving the problems. Students solved a series of SAT math problems while wearing an EEG...

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Bibliographic Details
Main Author: Cirett Galan, Federico M.
Other Authors: Beal, Carole R.
Language:en
Published: The University of Arizona. 2012
Subjects:
Intelligent Tutoring Systems
Machine Learning
physiology
Computer Science
behavior
Electroencephalography
Online Access:http://hdl.handle.net/10150/241971

Internet

http://hdl.handle.net/10150/241971

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