Publication details
Siete vo vzdelávaní : Možnosti využitia analýzy sociálnych sietí v pedagogickom výskume
| Title in English | Networks in education : Making use of social network analysis in educational research |
|---|---|
| Authors | |
| Year of publication | 2020 |
| Type | Article in Periodical |
| Magazine / Source | Studia paedagogica |
| MU Faculty or unit | |
| Citation | |
| Web | https://www.phil.muni.cz/journals/index.php/studia-paedagogica/article/view/2201/2134 |
| Doi | http://dx.doi.org/10.5817/SP2020-3-6 |
| Keywords | social network analysis; SNA; complex networks; methodology in educational research; social network models; ERGM |
| Description | With its wide range of applications, social network analysis has found its place in a number of scientific fields. In educational research, social network analysis has a potential to uncover and investigate yet unknown configurations of relations between actors in education. This paper provides an introduction to the problematics, techniques, and applications of social network analysis in educational research. It first introduces reader to basic terminology and concepts in social network analysis. On an example of a small network, it demonstrates basic network calculations at both the levels of the individual actors and the network as a whole. Furthermore, the paper provides a brief overview of studies in the field of educational research, which have employed social network analysis. On an example of a fictional classroom and five research questions, the main part of the paper demonstrates application of social network analysis in educational research ranging from cross-sectional descriptive analysis to dynamic inferential analysis. Step by step, it introduces a range of methods followed by interpretation of their results. Apart from centrality, clustering, and connectedness measures, the example contains permutation tests used for significance testing with network data, ERGM (exponential random graph models), and STERGM (separable temporal exponential graph models). Finally, the paper discusses challenges related to application of social network analysis. |
| Related projects: |