Studying participation networks in collaboration using mixed methods

  • Alejandra Martínez
  • Yannis Dimitriadis
  • Eduardo Gómez-Sánchez
  • Bartolomé Rubia-Avi
  • Iván Jorrín-Abellán
  • Jose A. Marcos
Article

Abstract

This paper describes the application of a mixed-evaluation method, published elsewhere, to three different learning scenarios. The method defines how to combine social network analysis with qualitative and quantitative analysis in order to study participatory aspects of learning in CSCL contexts. The three case studies include a course-long, blended learning experience evaluated as the course develops; a course-long, distance learning experience evaluated at the end of the course; and a synchronous experience of a few hours duration. These scenarios show that the analysis techniques and data collection and processing tools are flexible enough to be applied in different conditions. In particular, SAMSA, a tool that processes interaction data to allow social network analysis, is useful with different types of interactions (indirect asynchronous or direct synchronous interactions) and different data representations. Furthermore, the predefined types of social networks and indexes selected are shown to be appropriate for measuring structural aspects of interaction in these CSCL scenarios. These elements are usable and their results comprehensible by education practitioners. Finally, the experiments show that the mixed-evaluation method and its computational tools allow researchers to efficiently achieve a deeper and more reliable evaluation through complementarity and the triangulation of different data sources. The three experiments described show the particular benefits of each of the data sources and analysis techniques.

Keywords

Authentic learning scenarios BSCW Empirical case studies Interaction analysis tool Interpretive evaluation Mixed evaluation methods Situated learning Social network analysis Participatory aspects of learning 

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Copyright information

© International Society of the Learning Sciences, Inc.; Springer Science + Business Media, LLC 2006

Authors and Affiliations

  • Alejandra Martínez
    • 1
  • Yannis Dimitriadis
    • 2
  • Eduardo Gómez-Sánchez
    • 2
  • Bartolomé Rubia-Avi
    • 3
  • Iván Jorrín-Abellán
    • 3
  • Jose A. Marcos
    • 1
  1. 1.Department of Computer Science, ETS de Ingeniería InformáticaUniversidad de ValladolidValladolidSpain
  2. 2.Department of Signal Theory and Communications and Telematics Engineering, ETS de Ingenieros de TelecomunicaciónUniversidad de ValladolidValladolidSpain
  3. 3.Department of Pedagogy, Facultad de Educación y Trabajo SocialUniversidad de ValladolidValladolidSpain

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