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Quantifying Qualities in Collaborative Knowledge Construction: The Analysis of Online Discussions

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Analyzing Interactions in CSCL

Part of the book series: Computer-Supported Collaborative Learning Series ((CULS,volume 12))

Abstract

Several approaches in CSCL research conceptualize and empirically explore the relations between specific qualities of text-based knowledge ­building ­processes in CSCL and successful knowledge construction. In argumentative knowledge construction, for example, a positive relation is assumed to exist between argumentation and individual knowledge construction. In order to test such assumptions and provide findings that are generalizable, the respective qualities must be appropriately quantified. This chapter describes MAQCOD (Multidimensional Approach for the Qualitative Coding of Online Discussions) which allows the theoretical assumptions of relations between qualities of text-based knowledge building processes and knowledge construction to be tested via the development of rules for segmentation and coding and the application of high-level data analysis to already coded data.

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Authors and Affiliations

  1. University of Munich, Leopoldstrasse 13, 80802, München, Germany

    Karsten Stegmann

Authors
  1. Karsten Stegmann
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  2. Frank Fischer
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Correspondence to Karsten Stegmann .

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Editors and Affiliations

  1. Wisconsin Center for Education Research, University of Wisconsin-Madison, W. Johnson Street 1025, Madison, 53706-1796, Wisconsin, USA

    Sadhana Puntambekar

  2. Dept. Educational Sciences, Utrecht University, Heidelberglaan 2, Utrecht, 3584 CS, Netherlands

    Gijsbert Erkens

  3. Graduate School of Education, Rutgers University, Seminary Place 10, New Brunswick, 08901, New Jersey, USA

    Cindy Hmelo-Silver

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Stegmann, K., Fischer, F. (2011). Quantifying Qualities in Collaborative Knowledge Construction: The Analysis of Online Discussions. In: Puntambekar, S., Erkens, G., Hmelo-Silver, C. (eds) Analyzing Interactions in CSCL. Computer-Supported Collaborative Learning Series, vol 12. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-7710-6_12

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