Student Emotion, Co-occurrence, and Dropout in a MOOC Context

John Dillon; Nigel Bosch; Malolan Chetlur; Nirandika Wanigasekara; G. Alex Ambrose; Bikram Sengupta; Sidney K. D’Mello

Student Emotion, Co-occurrence, and Dropout in a MOOC Context

John Dillon, Nigel Bosch, Malolan Chetlur, Nirandika Wanigasekara, G. Alex Ambrose, Bikram Sengupta, Sidney K. D’Mello

Research output: Contribution to conference › Paper › peer-review

Abstract

This paper discusses self-reported emotions experienced by students in a Massive Open Online Course (MOOC) learning context. Emotions have been previously shown to be related to learning in classrooms and laboratory studies and have even been leveraged to improve learning. In this study, frequently occurring discrete emotions as well as frequently, co-occurring pairs of emotions were analyzed during learning with a MOOC. Both discrete and co-occurring emotions were related to students dropping out of the course, illustrating the importance of student emotion in a MOOC context.

Original language	English (US)
Pages	353-357
Number of pages	5
State	Published - 2016
Externally published	Yes
Event	9th International Conference on Educational Data Mining, EDM 2016 - Raleigh, United States Duration: Jun 29 2016 → Jul 2 2016

Conference

Conference	9th International Conference on Educational Data Mining, EDM 2016
Country/Territory	United States
City	Raleigh
Period	6/29/16 → 7/2/16

Keywords

Affective computing
Course completion
MOOC

ASJC Scopus subject areas

Computer Science Applications
Information Systems

Library availability

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abstract = "This paper discusses self-reported emotions experienced by students in a Massive Open Online Course (MOOC) learning context. Emotions have been previously shown to be related to learning in classrooms and laboratory studies and have even been leveraged to improve learning. In this study, frequently occurring discrete emotions as well as frequently, co-occurring pairs of emotions were analyzed during learning with a MOOC. Both discrete and co-occurring emotions were related to students dropping out of the course, illustrating the importance of student emotion in a MOOC context.",

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note = "Funding Information: We would like to thank Crystal DeJaegher and Xiaojing Duan in the Office of Digital Learning at the University of Notre Dame for their assistance in the design of this MOOC and collection of these data. D{\textquoteright}Mello was supported by the National Science Foundation (NSF) (DRL 1235958 and IIS 1523091). Any opinions, findings and conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the NSF. Funding Information: We would like to thank Crystal DeJaegher and Xiaojing Duan in the Office of Digital Learning at the University of Notre Dame for their assistance in the design of this MOOC and collection of these data. D?Mello was supported by the National Science Foundation (NSF) (DRL 1235958 and IIS 1523091). Any opinions, findings and conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the NSF. Publisher Copyright: {\textcopyright} 2016 International Educational Data Mining Society. All rights reserved.; 9th International Conference on Educational Data Mining, EDM 2016 ; Conference date: 29-06-2016 Through 02-07-2016",

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language = "English (US)",

pages = "353--357",

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AU - Dillon, John

AU - Bosch, Nigel

AU - Chetlur, Malolan

AU - Wanigasekara, Nirandika

AU - Ambrose, G. Alex

AU - Sengupta, Bikram

AU - D’Mello, Sidney K.

N1 - Funding Information: We would like to thank Crystal DeJaegher and Xiaojing Duan in the Office of Digital Learning at the University of Notre Dame for their assistance in the design of this MOOC and collection of these data. D’Mello was supported by the National Science Foundation (NSF) (DRL 1235958 and IIS 1523091). Any opinions, findings and conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the NSF. Funding Information: We would like to thank Crystal DeJaegher and Xiaojing Duan in the Office of Digital Learning at the University of Notre Dame for their assistance in the design of this MOOC and collection of these data. D?Mello was supported by the National Science Foundation (NSF) (DRL 1235958 and IIS 1523091). Any opinions, findings and conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the NSF. Publisher Copyright: © 2016 International Educational Data Mining Society. All rights reserved.

PY - 2016

Y1 - 2016

N2 - This paper discusses self-reported emotions experienced by students in a Massive Open Online Course (MOOC) learning context. Emotions have been previously shown to be related to learning in classrooms and laboratory studies and have even been leveraged to improve learning. In this study, frequently occurring discrete emotions as well as frequently, co-occurring pairs of emotions were analyzed during learning with a MOOC. Both discrete and co-occurring emotions were related to students dropping out of the course, illustrating the importance of student emotion in a MOOC context.

AB - This paper discusses self-reported emotions experienced by students in a Massive Open Online Course (MOOC) learning context. Emotions have been previously shown to be related to learning in classrooms and laboratory studies and have even been leveraged to improve learning. In this study, frequently occurring discrete emotions as well as frequently, co-occurring pairs of emotions were analyzed during learning with a MOOC. Both discrete and co-occurring emotions were related to students dropping out of the course, illustrating the importance of student emotion in a MOOC context.

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KW - Course completion

KW - MOOC

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ER -

Student Emotion, Co-occurrence, and Dropout in a MOOC Context

Abstract

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Keywords

ASJC Scopus subject areas

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