On the impact of personality in massive open online learning

Guanliang Chen, Dan Davisy, Claudia Hauff, Geert Jan Houben

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

27 Citations (Scopus)

Abstract

Massive Open Online Courses (MOOCs) have gained considerable momentum since their inception in 2011. They are, however, plagued by two issues that threaten their future: learner engagement and learner retention. MOOCs regularly attract tens of thousands of learners, though only a very small percentage complete them successfully. In the traditional classroom setting, it has been established that personality impacts different aspects of learning. It is an open question to what extent this finding translates to MOOCs: do learners' personalities impact their learning & learning behaviour in the MOOC setting? In this paper, we explore this question and analyse the personality profiles and learning traces of hundreds of learners that have taken a EX101x Data Analysis MOOC on the edX platform. We find learners' personality traits to only weakly correlate with learning as captured through the data traces learners leave on edX.

Original languageEnglish
Title of host publicationProceedings of the 2016 Conference on User Modeling Adaptation and Personalization
EditorsLora Aroyo, Sidney D’Mello
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages121-130
Number of pages10
ISBN (Electronic)9781450343701
DOIs
Publication statusPublished - 2016
Externally publishedYes
EventInternational Conference on User Modelling, Adaptation, and Personalization (was AH and UM) 2016 - Halifax, Canada
Duration: 13 Jul 201617 Jul 2016
Conference number: 24th
https://www.um.org/umap2016/
https://dl.acm.org/doi/proceedings/10.1145/2930238 (Proceedings)

Conference

ConferenceInternational Conference on User Modelling, Adaptation, and Personalization (was AH and UM) 2016
Abbreviated titleUMAP 2016
Country/TerritoryCanada
CityHalifax
Period13/07/1617/07/16
Internet address

Keywords

  • Massive open online learning
  • Personality prediction

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