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 conferencePaper

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 languageEnglish (US)
Pages353-357
Number of pages5
StatePublished - Jan 1 2016
Externally publishedYes
Event9th International Conference on Educational Data Mining, EDM 2016 - Raleigh, United States
Duration: Jun 29 2016Jul 2 2016

Conference

Conference9th International Conference on Educational Data Mining, EDM 2016
CountryUnited States
CityRaleigh
Period6/29/167/2/16

Keywords

  • Affective computing
  • Course completion
  • MOOC

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

Fingerprint Dive into the research topics of 'Student Emotion, Co-occurrence, and Dropout in a MOOC Context'. Together they form a unique fingerprint.

  • Cite this

    Dillon, J., Bosch, N., Chetlur, M., Wanigasekara, N., Ambrose, G. A., Sengupta, B., & D’Mello, S. K. (2016). Student Emotion, Co-occurrence, and Dropout in a MOOC Context. 353-357. Paper presented at 9th International Conference on Educational Data Mining, EDM 2016, Raleigh, United States.