Abstract
AbstractStudents’ personal learning networks can be a valuable resource of success in higher education: they offer opportunities for academic and personal support and provide sources of information related to exams or homework. We study the determinants of learning networks using a panel study among university students in their first and second year of study. A long-standing question in social network analysis has been whether the tendency of individuals with similar characteristics to form ties is a result of preferences “choice homophily” or rather selective opportunities “induced homophily”. We expect a latent preference for homophilic learning partnerships with regard to attributes, such as gender, ability, and social origin. We estimate recently developed temporal exponential random graph models to control for previous network structure and study changes in learning ties among students. The results show that especially for males, same-gender partnerships are preferred over heterogeneous ties, while chances for tie formation decrease with the difference in academic ability among students. Social origin is a significant factor in the crosssectional exploration but does appear to be less important in the formation of new (strong) partnerships during the course of studies.
Highlights
Social networks have long been acknowledged as a resource for human capital formation (Coleman, 1988)
SAOMs make more restrictive assumptions regarding the form of network change as compared with the temporal exponential random graph models (TERGMs): In a number of micro-steps between two observed time steps, an actor considers whether to create or abrogate one tie at a time in the SAOM
The only important difference relates to the effect of gender homophily, which in this model is important for the creation of new ties and for the stability of existing ties, while the latter effect is not present in all other models
Summary
Social networks have long been acknowledged as a resource for human capital formation (Coleman, 1988). In the context of college students, homophily is often found with regard to race and ethnicity (e.g., Mayer & Puller, 2008), gender (e.g., Godley, 2008), geographic origin (e.g., Lee et al, 2011), or socioeconomic status (e.g., Wimmer & Lewis, 2010) Structural factors such as having the same study program or academic year can predict student tie formation (Pilbeam & Denyer, 2009). Our goal in this paper is to assess to what degree either individual preferences or network structural factors are responsible for segmentation tendencies among students’ learning networks with regard to gender, socioeconomic status, and academic ability. We use recently developed temporal exponential random graph models (TERGMs) controlling for the lagged dependent network structure to study the change in students’ learning relationships
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