Investigating Patterns of Interaction in Networked Learning and Computer-Supported Collaborative Learning: A Role for Social Network Analysis
IJCCL Volume 2, Number 1, ISSN 1556-1607
The focus of this study is to explore the advances that Social Network Analysis (SNA) can bring, in combination with other methods, when studying Networked Learning/Computer-Supported Collaborative Learning (NL/CSCL). We present a general overview of how SNA is applied in NL/CSCL research; we then go on to illustrate how this research method can be integrated with existing studies on NL/CSCL, using an example from our own data, as a way to synthesize and extend our understanding of teaching and learning processes in NLCs. The example study reports empirical work using content analysis (CA), critical event recall (CER) and social network analysis (SNA). The aim is to use these methods to study the nature of the interaction patterns within a networked learning community (NLC), and the way its members share and construct knowledge. The paper also examines some of the current findings of SNA analysis work elsewhere in the literature, and discusses future prospects for SNA. This paper is part of a continuing international study that is investigating NL/CSCL among a community of learners engaged in a master's program in e-learning.
de Laat, M., Lally, V., Lipponen, L. & Simons, R.J. (2007). Investigating Patterns of Interaction in Networked Learning and Computer-Supported Collaborative Learning: A Role for Social Network Analysis. International Journal of Computer-Supported Collaborative Learning, 2(1), 87-103.
Cited ByView References & Citations Map
Visualizing Dominant Behaviours in Problem-Based Learning Environments: A Case Study Analysis of the HOWARD Platform
Lingyun Huang, Stephen Bodnar, Juan Zheng, Maedeh Kazemitabar & Susanne Lajoie, Faculty of Education, McGill University, Canada; Yuxin Chen, Gurpreet Birk & Cindy Hmelo-Silver, School of Education, Indiana University Bloomington, United States; Juan Pablo Sarmiento & Ricki Goldman, Department of Administration Leadership and Technology, New York University, United States; Jeffrey Wiseman, Center for Medical Education, McGill University, Canada; Lapki Chan, School of Biomedical Sciences, The University of Hong Kong, Hong Kong
E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2017 (Oct 17, 2017) pp. 359–364
A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities
Higinio Mora, Antonio Ferrndez, David Gil & Jess Peral, University of Alicante
The International Review of Research in Open and Distributed Learning Vol. 18, No. 1 (Feb 28, 2017)
Exploring the Roles of Social Participation in Mobile Social Media Learning: A Social Network Analysis
Helmi Norman, Faculty of Science and Technology Bournemouth University Fern Barrow, Talbot Campus, Poole Dorset BH12 5BB United Kingdom; Norazah Nordin & Rosseni Din, Faculty of Education, National University of Malaysia; Mohamad Ally, Center for Distance Education Athabasca University; Huseyin Dogan, School of Design, Engineering, and Computing Faculty of Science and Technology Bournemouth University Fern Barrow, Talbot Campus, Poole Dorset BH12 5BB
The International Review of Research in Open and Distributed Learning Vol. 16, No. 4 (Nov 02, 2015)
Matthew Schmidt, University of Hawaii at Manoa, United States; James Laffey, University of Missouri, United States
TCC 2012 (2012) pp. 41–55
These links are based on references which have been extracted automatically and may have some errors. If you see a mistake, please contact email@example.com.