On the Impact of Personality in Massive Open Online Learning

Guanliang Chen, D.J. Davis, Claudia Hauff, Geert Jan Houben

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

29 Citations (Scopus)


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 publicationUMAP 2016
Subtitle of host publicationProceedings of the 2016 Conference on User Modeling Adaptation and Personalization
PublisherAssociation for Computing Machinery (ACM)
Number of pages10
ISBN (Electronic)978-1-4503-4370-1
ISBN (Print)978-1-4503-4368-8
Publication statusPublished - 13 Jul 2016
Event24th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2016 - Halifax, Canada
Duration: 13 Jul 201617 Jul 2016


Conference24th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2016


  • Massive open online learning
  • Personality prediction

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