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Exploring Navigation Styles in a FutureLearn MOOC

Shi, Lei; Cristea, Alexandra I.; Toda, Armando M.; Oliveira, Wilk

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Authors

Lei Shi

Armando M. Toda

Wilk Oliveira



Contributors

Vivekanandan Kumar
Editor

Christos Troussas
Editor

Abstract

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).

Citation

Shi, L., Cristea, A. I., Toda, A. M., & Oliveira, W. (2020). Exploring Navigation Styles in a FutureLearn MOOC. In V. Kumar, & C. Troussas (Eds.), Intelligent Tutoring Systems (45-55). Springer Verlag. https://doi.org/10.1007/978-3-030-49663-0_7

Acceptance Date Mar 20, 2020
Online Publication Date Jun 8, 2020
Publication Date 2020
Deposit Date Jun 18, 2020
Publicly Available Date Jun 8, 2021
Publisher Springer Verlag
Pages 45-55
Series Number 12149
Book Title Intelligent Tutoring Systems
ISBN 978-3-030-49662-3
DOI https://doi.org/10.1007/978-3-030-49663-0_7
Keywords MOOCs, Navigation, Learning Styles, Learning Analytics