The Open UniversitySkip to content

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

Hernández-Nanclares, Núria; García-Muñiz, Ana and Rienties, Bart (2017). Making the most of “external” group members in blended and online environments. Interactive Learning Environments, 25(4) pp. 467–481.

Full text available as:
PDF (Accepted Manuscript) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview
DOI (Digital Object Identifier) Link:
Google Scholar: Look up in Google Scholar


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.

Item Type: Journal Item
Copyright Holders: 2016 Taylor & Francis
ISSN: 1744-5191
Keywords: blended learning; group learning; knowledge spillovers; structural holes; social networks analysis; higher education
Academic Unit/School: Faculty of Wellbeing, Education and Language Studies (WELS)
Item ID: 45097
Depositing User: Bart Rienties
Date Deposited: 12 Jan 2016 16:51
Last Modified: 01 May 2019 22:44
Share this page:


Altmetrics from Altmetric

Citations from Dimensions

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU