Methods for triangulation and revealing interaction

  • Authors:
  • Vanessa Svihla

  • Affiliations:
  • The University of Texas at Austin, Austin, TX

  • Venue:
  • CSCL'09 Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 2
  • Year:
  • 2009

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Abstract

Quantitative methods in educational research tend to be heavily reductionist and to disregard interaction; most statistical models include an assumption of no interaction. Qualitative methods allow complexity and interaction, but tend not to include representations or otherwise allow the reader to "see" the interaction as the researcher can. By combining traditional qualitative methods with statistical modeling, we are afforded a better opportunity to see aspects of a phenomenon, but not always greater integration; interpretation does not easily emerge from potentially divergent data sets. By including social network analysis, which provides both summary statistics and graphical depiction of interaction we are afforded a better opportunity to examine collaborative work. Furthermore, technology facilitates collection and analysis of change over time in computer supported collaborative work. These methods enable a multifarious view of quantitative data, and allow for interpretation to more naturally emerge from multiple data sets.