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Learners’ web navigation behaviour beyond learning management systems: A way into addressing procrastination in online learning?

Pogorskiy, Eduard; Beckmann, Jens F.

Learners’ web navigation behaviour beyond learning management systems: A way into addressing procrastination in online learning? Thumbnail


Authors

Eduard Pogorskiy



Abstract

The attractiveness of online games, social media, and mobile apps is frequently considered a challenge for online learners. Procrastinatory behaviour is often associated with a relative lack of self-regulatory skills that would otherwise help learners to resist distractions and to progress in learning. This paper reports a pilot study, conducted with 49 online learners, in which we describe the use of a virtual learning assistant as a tool for collecting online learners' web navigation behaviour. As this virtual learning assistant operates as an extension to the Chrome web browser, it is possible that data collection is achieved independently of, and beyond specific learning management systems. Furthermore, the study opens up the possibility of leveraging the collected dataset for visual learning analytics and pattern mining. To demonstrate the potential utility of the virtual learning assistant, we present an example for a detailed examination of a learner's web navigation behaviour. The results of the detailed examination of a single learner's web navigation behaviour over 333 days, presented as a case study, revealed the presence of seasonality in accessing certain web resources and stable sequential patterns in the learner's web navigation that can be associated with procrastinatory behaviour.

Citation

Pogorskiy, E., & Beckmann, J. F. (2022). Learners’ web navigation behaviour beyond learning management systems: A way into addressing procrastination in online learning?. Computers and Education: Artificial Intelligence, 3, https://doi.org/10.1016/j.caeai.2022.100094

Journal Article Type Article
Acceptance Date Aug 21, 2022
Online Publication Date Sep 9, 2022
Publication Date 2022
Deposit Date Sep 12, 2022
Publicly Available Date Nov 10, 2022
Journal Computers and Education: Artificial Intelligence
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 3
DOI https://doi.org/10.1016/j.caeai.2022.100094
Related Public URLs https://www.sciencedirect.com/science/article/pii/S2666920X22000492?utm_campaign=STMJ_AUTH_SERV_PUBLISHED&utm_medium=email&utm_acid=77841987&SIS_ID=&dgcid=STMJ_AUTH_SERV_PUBLISHED&CMX_ID=&utm_in=DM294062&utm_source=AC_

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