Exploring Navigation Styles in a FutureLearn MOOC
Lei Shi, Alexandra I. Cristea, Armando M. Toda, Wilk Oliveira

TL;DR
This study analyzes fine-grained navigation styles in MOOCs, revealing their variability and implications for personalized interventions, with potential to enhance learner engagement and support in online education systems.
Contribution
It introduces a detailed method for identifying and analyzing navigation styles in MOOCs, highlighting their instability and impact on learner engagement.
Findings
Sequential navigation style is common, global style is less so
Most learners do not fit into predefined navigation categories
Learners frequently switch styles, affecting engagement
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).
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