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Paper detail

Exploring Navigation Styles in a FutureLearn MOOC

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).

preprint2020arXivOpen access
Lei ShiAlexandra I. CristeaArmando M. TodaWilk Oliveira
cs.CYHuman-Computer Interaction
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Lei ShiAlexandra I. CristeaArmando M. TodaWilk Oliveira

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