Peer Influence and Educational Preferences: Direct Influence or Access to Friends’ Educational Resources?

Eszter Vit, Sven Lenkewitz, Robert Krause

Research output: Contribution to journalArticlepeer-review

Abstract

While educational preferences can be influenced by friends through various mechanisms, the specific pathways of this influence remain underexplored. This study employs random-coefficient multilevel stochastic actor-oriented models to examine a longitudinal sample of Hungarian students (Nstudents = 493, Nclasses = 21) observed from fifth to seventh grade. The study investigates how friends' preferences and friends' parental resources influence educational preferences while accounting for friends' academic achievement and friendship selection. The analysis identifies distinct pathways through which friends can influence educational preferences. The study suggests that adolescents do not adjust their secondary school track preferences to conform to their friends' preferences but are instead affected by the indirect influence of their friends' parental background. Students who befriend adolescents with highly educated parents are more likely to adjust their preferences toward the academically oriented secondary school track.

Original languageEnglish
Article numbere12789
JournalSocial Development
Volume34
Issue number1
DOIs
StatePublished - Feb 2025

Bibliographical note

Publisher Copyright:
© 2025 John Wiley & Sons Ltd.

Funding

Funding came from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Programme under Grant agreement No 648693 (PI: Károly Takács) and from National Research, Development and Innovation Office (ITM NKFIH), Hungary under Grant FK 137765 (PI: Dorottya Kisfalusi) to Eszter Vit. The computations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at Linköping University, partially funded by the Swedish Research Council through grant agreement no. 2018–05973.Funding came from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation programme under Grant agreement No 648693 (PI: Károly Takács) and from National Research, Development and Innovation Office (ITM NKFIH), Hungary under Grant FK 137765 (PI: Dorottya Kisfalusi) to E.V. The computations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at Linköping University, partially funded by the Swedish Research Council through grant agreement no. 2018–05973. We also thank for the usage of HUN-REN Cloud (https://science-cloud.hu/) that significantly helped us achieve the revised results published in this paper. The responsibility for the content of this publication lies with the authors. The responsibility for the content of this publication lies with the authors. : Funding came from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Programme under Grant agreement No 648693 (PI: Károly Takács) and from National Research, Development and Innovation Office (ITM NKFIH), Hungary under Grant FK 137765 (PI: Dorottya Kisfalusi) to Eszter Vit. The computations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at Linköping University, partially funded by the Swedish Research Council through grant agreement no. 2018–05973. Funding Funding came from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation programme under Grant agreement No 648693 (PI: Károly Takács) and from National Research, Development and Innovation Office (ITM NKFIH), Hungary under Grant FK 137765 (PI: Dorottya Kisfalusi) to E.V. The computations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at Linköping University, partially funded by the Swedish Research Council through grant agreement no. 2018–05973. We also thank for the usage of HUN‐REN Cloud ( https://science‐cloud.hu/ ) that significantly helped us achieve the revised results published in this paper. The responsibility for the content of this publication lies with the authors. The responsibility for the content of this publication lies with the authors.

FundersFunder number
Nemzeti Kutatási Fejlesztési és Innovációs Hivatal
H2020 European Research Council
Horizon 2020648693
Horizon 2020
ITM NKFIHFK 137765
Vetenskapsrådet2018–05973
Vetenskapsrådet

    Keywords

    • aspirations
    • educational preferences
    • expectations
    • multilevel random coefficient stochastic actor-oriented models
    • social networks

    ASJC Scopus subject areas

    • Developmental and Educational Psychology
    • Sociology and Political Science
    • Social Sciences (miscellaneous)

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