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Improving the Targeting of Treatment: Evidence from College Remediation

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  • Judith Scott-Clayton
  • Peter M. Crosta
  • Clive R. Belfield

Abstract

At an annual cost of roughly $7 billion nationally, remedial coursework is one of the single largest interventions intended to improve outcomes for underprepared college students. But like a costly medical treatment with non-trivial side effects, the value of remediation overall depends upon whether those most likely to benefit can be identified in advance. Our analysis uses administrative data and a rich predictive model to examine the accuracy of remedial screening tests, either instead of or in addition to using high school transcript data to determine remedial assignment. We find that roughly one in four test-takers in math and one in three test-takers in English are severely mis-assigned under current test-based policies, with mis-assignments to remediation much more common than mis-assignments to college-level coursework. We find that using high school transcript information--either instead of or in addition to test scores--could significantly reduce the prevalence of assignment errors. Further, we find that the choice of screening device has significant implications for the racial and gender composition of both remedial and college-level courses. Finally, we find that if institutions took account of students' high school performance, they could remediate substantially fewer students without lowering success rates in college-level courses.

Suggested Citation

  • Judith Scott-Clayton & Peter M. Crosta & Clive R. Belfield, 2012. "Improving the Targeting of Treatment: Evidence from College Remediation," NBER Working Papers 18457, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:18457
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    References listed on IDEAS

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    Cited by:

    1. Michal Kurlaender, 2014. "Assessing the Promise of California’s Early Assessment Program for Community Colleges," The ANNALS of the American Academy of Political and Social Science, , vol. 655(1), pages 36-55, September.

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    More about this item

    JEL classification:

    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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