Exploring Navigation Styles in a FutureLearn MOOC

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

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

• 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
• Public URL: https://durham-repository.worktribe.com/output/1628447
• Contract Date: Mar 20, 2020