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The Structure of Peers: The Impact of Peer Networks on Academic Achievement

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Abstract

Peer effects are an important contributing factor in the learning process. Most of the prior literature on peer effects focuses on the characteristics of peers rather than examining the structure of peer networks. We attempt to measure not only the impact of peers but also the structure of the peer network. In particular we are interested in the characteristics of students’ study groups along several dimensions: quality, heterogeneity, size and cohesion. Using pre-college characteristics of students and a random assignment into sections in their first year, we construct instruments of the study group measures to control for endogeneity of the network formation. Our OLS and IV estimates suggest that peer quality improves student performance, and that the breadth and cohesion of students’ network positively affects student outcomes. We also find significant heterogeneity of the results depending on network characteristics. Our findings can be used to assist university administrators or professors to choose criteria for sorting students into study groups.

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Notes

  1. Some examples of studies using random assignments include Sacerdote 2001, Zimmerman 2003, Whitmore 2005, Foster 2006, Ammermueller and Pischke 2006, Lyle 2007, 2009, Kremer and Levy 2008, among others.

  2. Perhaps the best example of this is the paper by Carrell et al. (2013), which report results from an experiment where the Air Force Academy sorted students optimally based on the prior peer effects literature (replicating Carrell et al. 2009). They failed to replicate their prior results in part because the ecological unit where they could randomize (i.e. assignment to squad) did not fully align with the ecological unit where peer effects are most salient (i.e. peer groupings within the squad).

  3. Lin et al. (2001) argues that information flows through social networks are one of the elements that may explain why social capital is embedded in the network of social relations, as opposed to embedded in individuals’ human capital.

  4. Epple and Romano (2011) and Sacerdote (2011) provide two general and comprehensive reviews on peer effects in education.

  5. An alternative approach that uses partially overlapping groups to improve the identification of peer effects is followed by De Giorgi et al. (2010), who finds that at college level, peers matter in the choice of major in Italy.

  6. Lin et al. (2001) argues that resources embedded in social networks are a form of capital. Therefore, two students exposed to different study group structures may be exposed to different academic resources, which may lead to different academic outcomes.

  7. For a comprehensive study of social networks and further definitions of cohesiveness beyond local measures, see Jackson (2008).

  8. Poldin et al. (2016) identifies study partners by asking students who they turn to for help in their studies, so that their definition of a study group includes directed relationships that may not reflect group relationships (i.e., students ask a peer for help but they don’t necessarily study together). In contrast, our measure of a study group is constructed by asking students to indicate with whom they actually study.

  9. We tested for non-linearities in the effect of study group size and found no evidence of diminishing marginal returns. We thank an anonymous referee for pointing out this possibility. Results are available upon request.

  10. We were informed by University officials that the process to allocate students in their first-semester sections was random; however, we were not able obtain further information regarding the actual practical procedure to allocate students into each section. In Sect. 5 of this paper, we verify that the initial section-cohort assignment was indeed uncorrelated with initial academic ability (measured by the standardized University entrance exams and high school GPA).

  11. After the first semester, students are free to choose their sections.

  12. Although it is a small sample, our estimates reveal that even in this case some study group measures have enough power to identify statistically significant effects. Therefore, we are confident that we are identifying relevant relationships in our data. Further research with larger samples sizes would be an improvement, as some of the statistically insignificant results might be a result of our small simple size.

  13. In Chile, a passing grade is 4.0 (roughly equivalent to a C- in the U.S.), with a grade of 5.0 equivalent to a B- and 6.0 equivalent to an A-.

  14. PSU is the Spanish acronym for the university entrance exam (Prueba de Seleccion Universitaria).

  15. The R2 of the first stage is 0.452 whilst the partial R2 of the excluded instrument is 0.056; the ratio is approximately 0.124.

  16. The results for heterogeneity and cohesion could be due to the fact that the constructed instrument does not perform well in terms of predicting observed levels of variance and cohesiveness, as indicated by low partial R2 and/or F-test of excluded instruments in the first stage.

  17. Even though observed study group size is endogenous, it can provide information regarding the relationship between group characteristics and academic performance conditional on study group size.

  18. Granovetter (1973) emphasizes the strength of weak ties in the diffusion of information.

  19. We thank an anonymous referee for pointing out the relevance of frequency in the study relationship. However, as we did not collect this information we cannot study its role at this time.

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Acknowledgements

Matias Berthelon would like to thank the financial support received from the Learning Center of Teaching Office (Centro Aprendizaje, Direccion de Docencia) at Universidad Adolfo Ibáñez. Diana Kruger would like to thank funding provided by the Center for Studies of Conflict and Social Cohesion (CONICYT/FONDAP/15130009).

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Authors and Affiliations

  1. Business School, Universidad Adolfo Ibáñez, Av. Padre Hurtado 750, Viña del Mar, Chile

    Matias Berthelon, Diana I. Kruger & Alejandro Montecinos-Pearce

  2. Graduate School of Education, Stanford University, 520 Galvez Mall, CERAS 522, Stanford, CA, 94305, USA

    Eric Bettinger

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  1. Matias Berthelon
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Correspondence to Matias Berthelon.

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Berthelon, M., Bettinger, E., Kruger, D.I. et al. The Structure of Peers: The Impact of Peer Networks on Academic Achievement. Res High Educ 60, 931–959 (2019). https://doi.org/10.1007/s11162-018-09543-7

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