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Early Identification of College Dropouts Using Machine-Learning: Conceptual Considerations and an Empirical Example

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  • Isphording, Ingo E.

    (IZA)

  • Raabe, Tobias

    (quantilope)

Abstract

Forschungsbericht mit Förderung durch das Bundesministerium für Bildung und Forschung, Bonn 2019 (30 Seiten)

Suggested Citation

  • Isphording, Ingo E. & Raabe, Tobias, 2019. "Early Identification of College Dropouts Using Machine-Learning: Conceptual Considerations and an Empirical Example," IZA Research Reports 89, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izarrs:89
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    File URL: https://ftp.iza.org/report_pdfs/iza_report_89.pdf
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    References listed on IDEAS

    as
    1. Schneider, Kerstin & Berens, Johannes & Oster, Simon & Burghoff, Julian, 2018. "Early Detection of Students at Risk - Predicting Student Dropouts Using Administrative Student Data and Machine Learning Methods," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181544, Verein für Socialpolitik / German Economic Association.
    2. Ralph Stinebrickner & Todd Stinebrickner, 2014. "Academic Performance and College Dropout: Using Longitudinal Expectations Data to Estimate a Learning Model," Journal of Labor Economics, University of Chicago Press, vol. 32(3), pages 601-644.
    3. James W. Perry & Allen Kent & Madeline M. Berry, 1955. "Machine literature searching X. Machine language; factors underlying its design and development," American Documentation, Wiley Blackwell, vol. 6(4), pages 242-254, October.
    4. Oliver Himmler & Robert Jäckle & Philipp Weinschenk, 2019. "Soft Commitments, Reminders, and Academic Performance," American Economic Journal: Applied Economics, American Economic Association, vol. 11(2), pages 114-142, April.
    5. Tyler Ransom & Esteban Aucejo & Arnaud Maurel & Peter Arcidiacono, 2014. "College Attrition and the Dynamics of Information Revelation," 2014 Meeting Papers 529, Society for Economic Dynamics.
    6. Basit Zafar, 2011. "How Do College Students Form Expectations?," Journal of Labor Economics, University of Chicago Press, vol. 29(2), pages 301-348.
    7. Ralph Stinebrickner & Todd R. Stinebrickner, 2014. "A Major in Science? Initial Beliefs and Final Outcomes for College Major and Dropout," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(1), pages 426-472.
    8. Dario Sansone, 2019. "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(2), pages 456-485, April.
    9. Julia Horstschr�er & Maresa Sprietsma, 2015. "The effects of the introduction of Bachelor degrees on college enrollment and dropout rates," Education Economics, Taylor & Francis Journals, vol. 23(3), pages 296-317, June.
    10. Effrosyni Adamopoulou & Giulia Martina Tanzi, 2017. "Academic Drop-Out and the Great Recession," Journal of Human Capital, University of Chicago Press, vol. 11(1), pages 35-71.
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