ABSTRACT | Social networks at school can both enhance and lower the academic attitudes, studying efforts and achievement of students. The negative effects are often more visible: groups with anti-school attitudes may emerge, leaders may promote and enforce these norms and social roles that reward low school engagement may be established. These processes do not only affect students who are members of groups with anti-school attitudes but are consequential for everyone in school, because they may fuel social conflict, bullying and the stigmatization of pro-school attitudes and behaviors. The work of teachers and educational managers, as well as the efficiency of educational institutions could be supported by a thorough understanding of social network dynamics in school settings.
However, research on network processes in education has so far largely ignored the fact that social relations between students are multidimensional. This leaves gaps in our knowledge, as studies tend to focus on the influence of friends on academic outcomes, leaving unexplored the impact of complex social ties. These can be characterized not only by friendship but by conflict, positive and negative perceptions and the attribution of social roles and status. Each dimension may have its distinct role in shaping school social structure and academic outcomes, and so they have to be studied jointly in order to understand the overall impact of social networks in education.
In this talk, I present a research agenda to explore the impact of multidimensional social networks on academic outcomes at different levels of education. First, I show that the highly detailed measurement of social ties between students using standard surveys and novel digital tools is a productive data collection approach. Second, I outline a multivariate statistical procedure to explore the main dimensions of such highly complex data. Third, I present an empirical case study among university students to exemplify how integration in multidimensional social networks is related to academic outcomes. Lastly, I highlight how results from multidimensional dynamic network studies may be used to explore educational policies and interventions that aim to improve school engagement and academic achievement.
BIO | András Vörös is currently a postdoctoral researcher at the Chair of Social Networks at ETH Zürich in Switzerland. His first experience in collecting and analyzing educational social network data is from his Master studies at the Corvinus University of Budapest, where he worked with Károly Takács from the MTA-TK RECENS group. He acquired thorough knowledge of statistical network modeling during his sociology PhD at the University of Oxford, with the supervision of Tom Snijders. He aims to apply his expertise in sociology and network analysis to aid the development of educational policies and interventions that improve academic outcomes.