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Quantitative Approach in Measuring Knowledge Convergence in Serious Games

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Games and Learning Alliance (GALA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8605))

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Abstract

Collaborative Serious Games (SG) aims to promote knowledge convergence, the process by which two or more people may reach mutual understanding after having interacted together. However, the analysis of knowledge convergence has been mostly developed in the context of Asynchronous Learning Networks (ALN) in a qualitative approach, but has not been investigated in the context of collaborative Serious Games (SG). The present study aims to investigate students’ knowledge convergence in the particular case of the SG Metavals, using a quantitative approach. The knowledge convergence results of the dyads playing the MetaVals allows to sustain partially the hypothesis of a better performance and Level of Certainty (LC) (H1), a higher symmetry of knowledge (H2) and a higher shared outcome knowledge (H3), after collaboration than in the initial individual phase of the SG.

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Author information

Authors and Affiliations

  1. ESADE Universitat Ramon Llull, 08034, Barcelona, Spain

    Ariadna Padrós

  2. Université Laval, Québec, QC, G1V 0A6, Canada

    Margarida Romero

Authors
  1. Ariadna Padrós
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  2. Margarida Romero
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Corresponding authors

Correspondence to Ariadna Padrós or Margarida Romero .

Editor information

Editors and Affiliations

  1. University of Genova, Genova, Italy

    Alessandro De Gloria

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Padrós, A., Romero, M. (2014). Quantitative Approach in Measuring Knowledge Convergence in Serious Games. In: De Gloria, A. (eds) Games and Learning Alliance. GALA 2013. Lecture Notes in Computer Science(), vol 8605. Springer, Cham. https://doi.org/10.1007/978-3-319-12157-4_29

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  • DOI: https://doi.org/10.1007/978-3-319-12157-4_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12156-7

  • Online ISBN: 978-3-319-12157-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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