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Predicting affect in an Intelligent Tutoring System Jaques, Natasha
Abstract
In this thesis we investigate the usefulness of various data sources for predicting emotions relevant to learning, specifically boredom and curiosity. The data was collected during a study with MetaTutor, an intelligent tutoring system (ITS) designed to promote the use of self-regulated learning strategies. We used a variety of machine learning and feature selection techniques to predict students‘ self-reported emotions from eye tracking data, distance from the screen, electrodermal activity, and an ensemble of all three sources. We also examine the optimal amount of interaction time needed to make predictions using each source, as well as which gaze features are most predictive of each emotion. The findings provide insight into how to detect when students disengage from MetaTutor.
Item Metadata
| Title |
Predicting affect in an Intelligent Tutoring System
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| Creator | |
| Publisher |
University of British Columbia
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| Date Issued |
2014
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| Description |
In this thesis we investigate the usefulness of various data sources for predicting emotions relevant to learning, specifically boredom and curiosity. The data was collected during a study with MetaTutor, an intelligent tutoring system (ITS) designed to promote the use of self-regulated learning strategies. We used a variety of machine learning and feature selection techniques to predict students‘ self-reported emotions from eye tracking data, distance from the screen, electrodermal activity, and an ensemble of all three sources. We also examine the optimal amount of interaction time needed to make predictions using each source, as well as which gaze features are most predictive of each emotion. The findings provide insight into how to detect when students disengage from MetaTutor.
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| Genre | |
| Type | |
| Language |
eng
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| Date Available |
2014-09-03
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
Attribution-NonCommercial-NoDerivs 2.5 Canada
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| DOI |
10.14288/1.0135541
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| URI | |
| Degree | |
| Program | |
| Affiliation | |
| Degree Grantor |
University of British Columbia
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| Graduation Date |
2014-11
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| Campus | |
| Scholarly Level |
Graduate
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| Rights URI | |
| Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivs 2.5 Canada