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Sitting next to a dropout: Study success of students with peers that came to the lecture hall by a different route

Author

Listed:
  • Daniel Goller
  • Andrea Diem
  • Stefan C. Wolter

Abstract

Higher education brings together students from diverse educational backgrounds, including students, who after dropping out of a first course of study, transferred to an academically less demanding institution. While peers are important contributors to student success, the influence of those dropouts with a knowledge advantage on first-time students is largely unexplored. Using an administrative data set covering every individual in the Swiss higher education system, we study the impact of the presence of academically better prepared students on the study success of first-time students. Our identification strategy relies on conditional idiosyncratic variations in the proportion of returning dropouts in university of applied sciences cohorts. We find negative effects of university dropouts who re-enroll in the same subject on the success of first-time students. In contrast, dropouts who change subjects are positively associated to the success of their new peers. Using causal machine learning methods, we find that the effects (a) are non-linear and (b) vary for different proportions of dropouts in university of applied sciences cohorts.

Suggested Citation

  • Daniel Goller & Andrea Diem & Stefan C. Wolter, 2022. "Sitting next to a dropout: Study success of students with peers that came to the lecture hall by a different route," Economics of Education Working Paper Series 0190, University of Zurich, Department of Business Administration (IBW).
  • Handle: RePEc:iso:educat:0190
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    File URL: http://repec.business.uzh.ch/RePEc/iso/leadinghouse/0190_lhwpaper.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    University dropouts; peer effects; better prepared students; causal machine learning;
    All these keywords.

    JEL classification:

    • A23 - General Economics and Teaching - - Economic Education and Teaching of Economics - - - Graduate
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions

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