Exploring Navigation Styles in a FutureLearn MOOC

  • Lei ShiEmail author
  • Alexandra I. Cristea
  • Armando M. Toda
  • Wilk Oliveira
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12149)


This paper presents for the first time a detailed analysis of fine-grained navigation style identification in MOOCs backed by a large number of active learners. The result shows 1) whilst the sequential style is clearly in evidence, the global style is less prominent; 2) the majority of the learners do not belong to either category; 3) navigation styles are not as stable as believed in the literature; and 4) learners can, and do, swap between navigation styles with detrimental effects. The approach is promising, as it provides insight into online learners’ temporal engagement, as well as a tool to identify vulnerable learners, which potentially benefit personalised interventions (from teachers or automatic help) in Intelligent Tutoring Systems (ITS).


MOOCs Navigation Learning Styles Learning Analytics 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Lei Shi
    • 1
    Email author
  • Alexandra I. Cristea
    • 1
  • Armando M. Toda
    • 2
  • Wilk Oliveira
    • 2
  1. 1.Durham UniversityDurhamUK
  2. 2.University of São PauloSão PauloBrazil

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