Social Network Analysis (SNA) in Educational Studies
Education is a discipline that explores the complex social ecosystem in which human development and learning unfold. The interactions among students within classrooms, the collaborative bonds among teachers, and the multilayered relational networks connecting school organizations with local communities are core mechanisms that shape educational outcomes.
For a long time, mainstream research in educational studies has relied on traditional statistical inference methods that treat individuals as independent units of analysis. [Knopp, K., & Knopp, K (2025)] Conventional analytical tools such as regression analysis, analysis of variance (ANOVA), and structural equation modeling (SEM) all rest on the assumption of independence among observations (i.i.d. assumption). This variable-centric approach has made substantial contributions to revealing the independent causal and correlational relationships between attribute data — such as students’ socioeconomic backgrounds, individual cognitive characteristics, or teachers’ years of experience — and outcome variables such as academic achievement or self-esteem.
The dynamics of educational settings, however, are far from the atomized picture assumed by traditional models.