Translating network position into performance: importance of centrality in different network configurations

Srećko Joksimovic, Areti Manataki, Dragan Gaševic, Shane Dawson, Vitomir Kovanovic, Inés Friss De Kereki

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

37 Citations (Scopus)

Abstract

As the field of learning analytics continues to mature, there is a corresponding evolution and sophistication of the associated analytical methods and techniques. In this regard social network analysis (SNA) has emerged as one of the cornerstones of learning analytics methodologies. However, despite the noted importance of social networks for facilitating the learning process, it remains unclear how and to what extent such network measures are associated with specific learning outcomes. Motivated by Simmel's theory of social interactions and building on the argument that social centrality does not always imply benefits, this study aimed to further contribute to the understanding of the association between students' social centrality and their academic performance. The study reveals that learning analytics research drawing on SNA should incorporate both - descriptive and statistical methods to provide a more comprehensive and holistic understanding of a students' network position. In so doing researchers can undertake more nuanced and contextually salient inferences about learning in network settings. Specifically, we show how differences in the factors framing students' interactions within two instances of a MOOC affect the association between the three social network centrality measures (i.e., degree, closeness, and betweenness) and the final course outcome.

Original languageEnglish
Title of host publicationLAK '16 Conference Proceedings
Subtitle of host publicationThe Sixth International Learning Analytics & Knowledge Conference: Enhancing Impact: Convergence of Communities for Grounding, Implementation, and Validation
EditorsShane Dawson, Hendrik Drachsler, Carlyn Penstein Rosé
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages314-323
Number of pages10
ISBN (Electronic)9781450341905
DOIs
Publication statusPublished - 2016
Externally publishedYes
EventInternational Learning Analytics & Knowledge Conference 2016 - University of Edinburgh, Edinburgh, United Kingdom
Duration: 25 Apr 201629 Apr 2016
Conference number: 6th
http://lak16.solaresearch.org/

Conference

ConferenceInternational Learning Analytics & Knowledge Conference 2016
Abbreviated titleLAK 2016
CountryUnited Kingdom
CityEdinburgh
Period25/04/1629/04/16
Internet address

Keywords

  • Academic achievement
  • Ergm
  • Mooc
  • Social network analysis

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