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Homophily in the formation and development of learning networks among university students

Published online by Cambridge University Press:  14 April 2020

Hannes Weber*
Affiliation:
Department of Sociology, University of Tubingen, Wilhelmstr. 36, D-72074Tubingen, Germany (e-mails: [email protected], [email protected])
Marc Schwenzer
Affiliation:
Department of Sociology, University of Tubingen, Wilhelmstr. 36, D-72074Tubingen, Germany (e-mails: [email protected], [email protected])
Steffen Hillmert
Affiliation:
Department of Sociology, University of Tubingen, Wilhelmstr. 36, D-72074Tubingen, Germany (e-mails: [email protected], [email protected])
*
*Corresponding author. Email: [email protected]
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Abstract

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Students’ 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.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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