What is the effect of a dominant code in an epistemic network analysis?

Rafael Ferreira Mello, Dragan Gašević

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6 Citations (Scopus)


This paper investigates how different configuration of epistemic network analysis parameters influence the examination of student interactions in asynchronous discussions in online learning environments. Specifically, the paper investigates strategies for dealing by unintended consequences of a dominant node in epistemic network analysis (ENA). In particular, the paper reports on a study that explored the effects of two different strategies including (i) the use of different dimensions calculated with singular value decomposition (SVD), and (ii) exclusion of a dominant code. Our results showed that the use of different SVDs did not change the influence of a dominant code in the graph. On the other hand, the exclusion of the dominant code led to an entirely different configuration in ENA. The practical implications of the results are further discussed.

Original languageEnglish
Title of host publicationAdvances in Quantitative Ethnography
Subtitle of host publicationFirst International Conference, ICQE 2019 Madison, WI, USA, October 20–22, 2019 Proceedings
EditorsBrendan Eagan, Morten Misfeldt, Amanda Siebert-Evenstone
Place of PublicationCham Switzerland
Number of pages11
ISBN (Electronic)9783030332327
ISBN (Print)9783030332310
Publication statusPublished - 2019
EventInternational Conference on Quantitative Ethnography 2019 - The Pyle Center, University of Wisconsin-Madison, Madison, United States of America
Duration: 20 Oct 201922 Oct 2019
Conference number: 1st
https://link.springer.com/book/10.1007/978-3-030-33232-7 (Proceedings)
http://icqe19.org (Website)

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


ConferenceInternational Conference on Quantitative Ethnography 2019
Abbreviated titleICQE 2019
Country/TerritoryUnited States of America
Internet address


  • Dominant code
  • Epistemic network analysis
  • Graph analysis

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