Who Are the Students of MOOCs?

  • Clustering in education is important in identifying groups of objects in order to find linked patterns of correlations in educational datasets. As such, MOOCs provide a rich source of educational datasets which enable a wide selection of options to carry out clustering and an opportunity for cohort analyses. In this experience paper, five research studies on clustering in MOOCs are reviewed, drawing out several reasonings, methods, and students’ clusters that reflect certain kinds of learning behaviours. The collection of the varied clusters shows that each study identifies and defines clusters according to distinctive engagement patterns. Implications and a summary are provided at the end of the paper.

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Metadaten
Author details:Mohammad Khalil
URN:urn:nbn:de:kobv:517-opus4-517298
DOI:https://doi.org/10.25932/publishup-51729
ISBN:978-3-86956-512-5
Title of parent work (English):EMOOCs 2021
Subtitle (English):Experience from Learning Analytics Clustering Techniques
Publisher:Universitätsverlag Potsdam
Place of publishing:Potsdam
Publication type:Article
Language:English
Date of first publication:2021/06/30
Publication year:2021
Publishing institution:Universität Potsdam
Publishing institution:Universitätsverlag Potsdam
Release date:2021/09/22
Volume:2021
Number of pages:11
First page:259
Last Page:269
RVK - Regensburg classification:ST 670
Organizational units:Digital Engineering Fakultät / Hasso-Plattner-Institut für Digital Engineering GmbH
DDC classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Peer review:Referiert
Publishing method:Universitätsverlag Potsdam
Open Access / Gold Open-Access
Collection(s):Universität Potsdam / Sammelwerke (nicht fortlaufend) / EMOOCs 2021 / Beiträge
License (German):License LogoCC-BY - Namensnennung 4.0 International
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