Towards a Social Networks Model for Online Learning & Performance

Autor/inn/en	Chung, Kon Shing Kenneth; Paredes, Walter Christian
Titel	Towards a Social Networks Model for Online Learning & Performance
Quelle	In: Educational Technology & Society, 18 (2015) 3, S.240-253 (14 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1436-4522
Schlagwörter	Social Networks; Online Courses; Educational Technology; Electronic Learning; Correlation; Interpersonal Communication; Interpersonal Relationship; Social Development; Network Analysis; Models; Data Analysis; Information Retrieval; Foreign Countries; Graduate Study; Computer Mediated Communication; Group Discussion; Content Analysis; Statistical Analysis; Data Collection; Database Design; Australia + Suchen Sie Ihr Suchwort? Social network; Soziales Netzwerk; Online course; Online-Kurs; Unterrichtsmedien; Korrelation; Interpersonale Kommunikation; Interpersonal relation; Interpersonal relations; Interpersonelle Beziehung; Zwischenmenschliche Beziehung; Soziale Entwicklung; Netzplantechnik; Analogiemodell; Auswertung; Ausland; Aufbaustudium; Graduiertenstudium; Hauptstudium; Computerkonferenz; Gruppendiskussion; Inhaltsanalyse; Statistische Analyse; Data capture; Datensammlung; Australien
Abstract	In this study, we develop a theoretical model to investigate the association between social network properties, "content richness" (CR) in academic learning discourse, and performance. CR is the extent to which one contributes content that is meaningful, insightful and constructive to aid learning and by social network properties we refer to its structural, position and relationship attributes. Analysis of data collected from an elearning environment shows that rather than performance, social learning correlates with properties of social networks: (i) structure (density, inter-group and intra-network communication) and (ii) position (efficiency), and (iii) relationship (tie strength). In particular, individuals who communicate with internal group members rather than external members express higher tendencies of "content richness" in social learning. The contribution of this study is three-fold: (i) a theoretical development of a social network based model for understanding learning and performance, which addresses the lack of empirical validation of current models in social learning; (ii) the construction of a novel metric called "content richness" as a surrogate indicator of social learning; and (iii) demonstration of how the use of social network analysis and computational text-mining approaches can be used to operationalize the model for studying learning and performance. In conclusion, a useful implication of the study is that the model fosters understanding social factors that influence learning and performance in project management. The study concludes that associations between social network properties and the extent to which interactions are "content-rich" in eLearning domains cannot be discounted in the learning process and must therefore be accounted for in the organizational learning design. (As Provided).
Anmerkungen	International Forum of Educational Technology & Society. Athabasca University, School of Computing & Information Systems, 1 University Drive, Athabasca, AB T9S 3A3, Canada. Tel: 780-675-6812; Fax: 780-675-6973; Web site: http://www.ifets.info
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01