Making the most of “external” group members in blended and online environments

ABSTRACT Although the importance of boundary spanning in blended and online learning is widely acknowledged, most educational research has ignored whether and how students learn from others outside their assigned group. One potential approach for understanding cross-boundary knowledge sharing is Social Network Analysis (SNA). In this article, we apply four network metrics to unpack how students developed intra- and inter-group learning links, using two exemplary blended case studies in Spain and the UK. Our results indicate that SNA based upon questionnaires can provide researchers some useful indicators for a more fine-grained analysis how students develop these inter- and intra-group learning links, and which cross-boundary links are particularly important for learning performance. The mixed findings between the two case-studies suggest the relevance of pre-existing conditions and learning design. SNA metrics can provide useful information for qualitative follow-up methods, and future interventions using learning analytics approaches.

[1]  Judd Harrison Michael,et al.  Unlocking the Influence of Leadership Network Structures on Team Conflict and Viability , 2009 .

[2]  Jie Lu,et al.  The effect of social interaction on learning engagement in a social networking environment , 2014, Interact. Learn. Environ..

[3]  Robert N. Stern,et al.  Informal Networks and Organizational Crises: An Experimental Simulation , 1988 .

[4]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[5]  P. Kirschner,et al.  Social and Cognitive Factors Driving Teamwork in Collaborative Learning Environments , 2006 .

[6]  Jorge Ávila de Lima Teachers' Professional Development in Departmentalised, Loosely Coupled Organisations: Lessons for School Improvement from a Case Study of Two Curriculum Departments. , 2007 .

[7]  Paul D. Cheney,et al.  The Impact of Group Size and Social Presence on Small-Group Communication , 2006 .

[8]  Tammy Schellens,et al.  Tagging thinking types in asynchronous discussion groups: effects on critical thinking , 2009, Interact. Learn. Environ..

[9]  A. Bakker,et al.  Boundary Crossing and Boundary Objects , 2011 .

[10]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[11]  Wim H. Gijselaers,et al.  Learning at the Crossroads of Theory and Practice: Research on Innovative Learning Practices , 2012 .

[12]  Jonathon N. Cummings,et al.  When Critical Knowledge Is Most Critical , 2011 .

[13]  B. Rienties,et al.  Understanding friendship and learning networks of international and host students using longitudinal Social Network Analysis , 2014 .

[14]  Kara S. Finnigan,et al.  A bridge between worlds: understanding network structure to understand change strategy , 2010 .

[15]  Dirk T. Tempelaar,et al.  In search for the most informative data for feedback generation: Learning analytics in a data-rich context , 2015, Comput. Hum. Behav..

[16]  F. Dochy,et al.  Grasping the dynamic complexity of team learning: An integrative model for effective team learning in organisations , 2010 .

[17]  Ramón Tirado,et al.  The effect of centralization and cohesion on the social construction of knowledge in discussion forums , 2015 .

[18]  B. Rienties,et al.  Understanding (in)formal learning in an academic development programme: A social network perspective , 2014 .

[19]  Bart Rienties,et al.  A Longitudinal Analysis of Knowledge Spillovers in the Classroom , 2012 .

[20]  Akbar Zaheer,et al.  The Embeddedness of Networks: Institutions, Structural Holes, and Innovativeness in the Fuel Cell Industry , 2013, Organ. Sci..

[21]  J. Coleman,et al.  Social Capital in the Creation of Human Capital , 1988, American Journal of Sociology.

[22]  Jörg Raab,et al.  Connecting the dots: social network structure, conflict, and group cognitive complexity , 2012 .

[23]  Tarmo Toikkanen,et al.  The applicability of social network analysis to the study of networked learning , 2011, Interact. Learn. Environ..

[24]  A. Daly,et al.  Relationships in reform: the role of teachers' social networks , 2010 .

[25]  Päivi Häkkinen,et al.  Web-based Cases in Teaching and Learning – the Quality of Discussions and a Stage of Perspective Taking in Asynchronous Communication , 2002, Interact. Learn. Environ..

[26]  Ray Reagans,et al.  Network Structure and Knowledge Transfer: The Effects of Cohesion and Range , 2003 .

[27]  R. Burt,et al.  Social network analysis: foundations and frontiers on advantage. , 2013, Annual review of psychology.

[28]  G. Ahuja Collaboration Networks, Structural Holes, and Innovation: A Longitudinal Study , 1998 .

[29]  D. Krackhardt,et al.  Activating Cross-Boundary Knowledge: The Role of Simmelian Ties in the Generation of Innovations , 2010 .

[30]  E. Giuliani Clusters, networks and firms' product success: an empirical study , 2013 .

[31]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994 .

[32]  E. Hippel Sticky Information and the Locus of Problem Solving: Implications for Innovation , 1994 .

[33]  David Caldwell,et al.  Improving the Performance of New Product Teams , 2007, IEEE Engineering Management Review.

[34]  Timothy T. Baldwin,et al.  The Social Fabric of a Team-Based M.B.A. Program: Network Effects on Student Satisfaction and Performance , 1997 .

[35]  R. Burt Structural Holes and Good Ideas1 , 2004, American Journal of Sociology.

[36]  A. Scherpbier,et al.  Visualising the invisible: a network approach to reveal the informal social side of student learning , 2012, Advances in Health Sciences Education.

[37]  Karina L. Cela,et al.  Social Network Analysis in E-Learning Environments: A Preliminary Systematic Review , 2014, Educational Psychology Review.

[38]  Steven B. Andrews,et al.  Structural Holes: The Social Structure of Competition , 1995, The SAGE Encyclopedia of Research Design.

[39]  David Lazer,et al.  Network Theory and Small Groups , 2004 .