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Aligning and Comparing Data on Emotions Experienced during Learning with MetaTutor

Type : Conference Proceedings

Year : 2013

Secondary Title : Proc. of the 16th Conference on Artificial Intelligence in Education (AIED 2013)

Place Published : Memphis, TN

Publisher : Springer Berlin Heidelberg

Volume : 7926

Pages : 61-70

Tertiary Title : Lecture Notes in Computer Science

Date : "jul"

ISBN : 978-3-642-39111-8

Abstract : In this study we aligned and compared self-report and on-line emotions data on 67 college students' emotions at five different points in time over the course of their interactions with MetaTutor. Self-reported emotion data as well as facial expression data were converged and analyzed. Results across channels revealed that neutral and positively-valenced basic and learner-centered emotional states represented the majority of emotional states experienced with MetaTutor. The self-report results revealed a decline in the intensity of positively-valenced and neutral states across the learning session. The facial expression results revealed a substantial decrease in the number of learners’ with neutral facial expressions from time one to time two, but a fairly stable pattern for the remainder of the session, with participants who experienced other basic emotional states, transitioning back to a state of neutral between self-reports. Agreement between channels was 75.6%.

Notes : 10.1007/978-3-642-39112-5_7

Authors : Harley, Jason M. Bouchet, François Azevedo, Roger

Editors : Lane, H. Chad Yacef, Kalina Mostow, Jack Pavlik, Philip

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