Conceptualizing, analyzing, and visualizing massive data on student engagement in moocs: A literature review

Shiyan Jiang, Ji Shen, Yu Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

MOOCs produce massive learning data that can provide insights on how students engage in these environments. This preliminary review examined 80 graphs produced in 20 empirical studies on student engagement in MOOCs. The review focused on the following questions: (1) What data has been collected to analyze student engagement in MOOCs? (2) How has the data been analyzed and visualized? The results show that different data sets were used and student engagement trajectories are often plotted in diverse ways.

Original languageEnglish (US)
Title of host publicationExploring the Material Conditions of Learning
Subtitle of host publicationComputer Supported Collaborative Learning Conference 2015, CSCL 2015 - Conference Proceedings
EditorsOskar Lindwall, Paivi Hakkinen, Timothy Koschmann, Pierre Tchounikine, Sten Ludvigsen
PublisherInternational Society of the Learning Sciences (ISLS)
Pages651-652
Number of pages2
ISBN (Electronic)9780990355076
StatePublished - Jan 1 2015
Event11th International Conference on Computer Supported Collaborative Learning: Exploring the Material Conditions of Learning, CSCL 2015 - Gothenburg, Sweden
Duration: Jun 7 2015Jun 11 2015

Publication series

NameComputer-Supported Collaborative Learning Conference, CSCL
Volume2
ISSN (Print)1573-4552

Conference

Conference11th International Conference on Computer Supported Collaborative Learning: Exploring the Material Conditions of Learning, CSCL 2015
CountrySweden
CityGothenburg
Period6/7/156/11/15

Keywords

  • Analysis of massive data
  • Data visualization
  • Engagement
  • MOOC

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Education

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