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Autor/inn/enLemay, David John; Doleck, Tenzin; Brinton, Christopher G.
TitelSLOAN: Social Learning Optimization Analysis of Networks
QuelleIn: International Review of Research in Open and Distributed Learning, 23 (2022) 4, S.93-122 (30 Seiten)Infoseite zur Zeitschrift
PDF als Volltext kostenfreie Datei Verfügbarkeit 
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
SchlagwörterSocialization; Social Networks; Network Analysis; Computer Mediated Communication; Social Cognition; Information Theory; Educational Technology; MOOCs; Algorithms
AbstractOnline discussion research has mainly been conducted using case methods. This article proposes a method for comparative analysis based on network metrics such as information entropy and global network efficiency as more holistic measures characterizing social learning group dynamics. We applied social learning optimization analysis of networks (SLOAN) to a data set consisting of Coursera courses from a range of disciplines. We examined the relationship of discussion forum uses and measures of network efficiency, characterized by the information flow through the network. Discussion forums vary greatly in size and in use. Courses with a greater prevalence of subject-related versus procedural talk differed significantly in seeking but not disseminating behaviors in massive open online course discussion forums. Subject-related talk was related to higher network efficiency and had higher seeking and disseminating scores overall. We discuss the value of SLOAN for social learning and argue for the experimental study of online discussion optimization using a discussion post recommendation system for maximizing social learning. (As Provided).
AnmerkungenAthabasca University Press. 1200, 10011-109 Street, Edmonton, AB T5J 3S8, Canada. Tel: 780-497-3412; Fax: 780-421-3298; e-mail: irrodl@athabascau.ca; Web site: http://www.irrodl.org
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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