Distributed Teaching Presence and communicative patterns in asynchronous learning: Name versus reply networks

  • Authors:

  • Anna Engel;CéSar Coll;Alfonso Bustos

  • Affiliations:

  • University of Barcelona, Department of Developmental and Educational Psychology, Facultad de Psicología, Campus Mundet, P. Vall d'Hebrón, 171, 08035 Barcelona, Spain;University of Barcelona, Department of Developmental and Educational Psychology, Facultad de Psicología, Campus Mundet, P. Vall d'Hebrón, 171, 08035 Barcelona, Spain;University of Barcelona, Department of Developmental and Educational Psychology, Facultad de Psicología, Campus Mundet, P. Vall d'Hebrón, 171, 08035 Barcelona, Spain

  • Venue:
  • Computers & Education
  • Year:
  • 2013

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Abstract

This work explores some methodological challenges in the application of Social Network Analysis (SNA) to the study of Asynchronous Learning Networks (ALN). Our interest in the SNA is situated within the framework of the study of Distributed Teaching Presence (DTP), understood as the exercise of educational influence, through a multi-method approach that integrates structural analysis of the activity and content analysis of the participants' contributions. Within the first of these analyses, our aim is twofold: to present a set of indices of the participants' communicative patterns oriented toward the study of DTP, and to discuss the most appropriate data source for calculating such indices. The indices are illustrated through the analysis of a didactic sequence (DS) based on two data sources: the activity logs (log files) and personal references or allusions to others that can be found in each participant's contributions. Our results show that the proposed set of indices enables the identification of the level of DTP in the ALN as well as of different communicative patterns potentially associated to a higher or lower degree of teaching presence exertion. Furthermore, the results show that the analysis based on explicit references offer an interesting and complementary alternative to the analysis based on the log files.