Arbeitspapier
What Works? Interventions Aimed At Reducing Student Dropout in Higher Education
High student dropout rates are a continuing concern within higher education and have received considerable attention for decades. Despite numerous proposed interventions, it remains unclear which interventions are effective, and what the pivotal active ingredients are. This paper systematically synthesizes the effects of different interventions on dropout and graduation rates in higher education. Screening around 7250 abstracts of potentially relevant studies, we found 38 (quasi-)experimental studies that met our pre-specified inclusion criteria. We describe the studies in various dimensions and conduct a narrative systematic review as well as a meta-analysis. Our findings indicate a general tendency towards positive effects. Interventions manipulating peer group composition, particularly those adjusting for gender and ability, show the most promising outcomes. We discuss the economic implications of effect sizes and show that they are considerable. This paper contributes to understanding effective strategies for addressing student dropout, providing valuable insights for higher education institutions and policymakers.
- Language
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Englisch
- Bibliographic citation
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Series: IZA Discussion Papers ; No. 16853
- Classification
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Wirtschaft
Higher Education; Research Institutions
Education and Inequality
Education: Other
- Subject
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student dropout
intervention
higher education
meta-analysis
educational economics
efficiency
- Event
-
Geistige Schöpfung
- (who)
-
Ibsen, Kristoffer
Rosholm, Michael
- Event
-
Veröffentlichung
- (who)
-
Institute of Labor Economics (IZA)
- (where)
-
Bonn
- (when)
-
2024
- Last update
-
10.03.2025, 11:43 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Ibsen, Kristoffer
- Rosholm, Michael
- Institute of Labor Economics (IZA)
Time of origin
- 2024
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Returns to higher education and dropouts: A double machine learning approach
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