Implicit and explicit emotions in MOOCs

Munira Syed, Malolan Chetlur, Shazia Afzal, G. Alex Ambrose, Nitesh V. Chawla

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Understanding the affect expressed by learners is essential for enriching the learning experience in Massive Open Online Courses (MOOCs). However, online learning environments, especially MOOCs, pose several challenges in understanding the different types of affect experienced by a learner. In this paper, we define two categories of emotions, explicit emotions as those collected directly from the student through self-reported surveys, and implicit emotions as those inferred unobtrusively during the learning process. We also introduce positivity as a measure to study the valence reported by students chronologically, and use it to derive insights into their emotion patterns and their association with learning outcomes. We show that implicit and explicit emotions expressed by students within the context of a MOOC are independent of each other, however, they correlate better with students' behavior compared to their valence.

Original languageEnglish
Title of host publicationEDM 2019 - Proceedings of the 12th International Conference on Educational Data Mining
EditorsCollin F. Lynch, Agathe Merceron, Michel Desmarais, Roger Nkambou
PublisherInternational Educational Data Mining Society
Pages432-437
Number of pages6
ISBN (Electronic)9781733673600
Publication statusPublished - 2019
Externally publishedYes
Event12th International Conference on Educational Data Mining, EDM 2019 - Montreal, Canada
Duration: 2 Jul 20195 Jul 2019

Publication series

NameEDM 2019 - Proceedings of the 12th International Conference on Educational Data Mining

Conference

Conference12th International Conference on Educational Data Mining, EDM 2019
Country/TerritoryCanada
CityMontreal
Period2/07/195/07/19

Keywords

  • Discussion forum
  • Emotions
  • MOOC
  • Surveys
  • Valence

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