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Evaluating Effects of Developmental Education for College Students Using a Regression Discontinuity Design

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  • Brian G. Moss
  • William H. Yeaton

Abstract

Background: Annually, American colleges and universities provide developmental education (DE) to millions of underprepared students; however, evaluation estimates of DE benefits have been mixed. Objectives: Using a prototypic exemplar of DE, our primary objective was to investigate the utility of a replicative evaluative framework for assessing program effectiveness. Research design: Within the context of the regression discontinuity (RD) design, this research examined the effectiveness of a DE program for five, sequential cohorts of first-time college students. Discontinuity estimates were generated for individual terms and cumulatively, across terms. Subjects: Participants were 3,589 first-time community college students. Measures: DE program effects were measured by contrasting both college-level English grades and a dichotomous measure of pass/fail, for DE and non-DE students. Results: Parametric and nonparametric estimates of overall effect were positive for continuous and dichotomous measures of achievement (grade and pass/fail). The variability of program effects over time was determined by tracking results within individual terms and cumulatively, across terms. Applying this replication strategy, DE’s overall impact was modest (an effect size of approximately .20) but quite consistent, based on parametric and nonparametric estimation approaches. A meta-analysis of five RD results yielded virtually the same estimate as the overall, parametric findings. Subset analysis, though tentative, suggested that males benefited more than females, while academic gains were comparable for different ethnicities. Conclusion: The cumulative, within-study comparison, replication approach offers considerable potential for the evaluation of new and existing policies, particularly when effects are relatively small, as is often the case in applied settings.

Suggested Citation

  • Brian G. Moss & William H. Yeaton, 2013. "Evaluating Effects of Developmental Education for College Students Using a Regression Discontinuity Design," Evaluation Review, , vol. 37(5), pages 370-404, October.
    • Handle: RePEc:sae:evarev:v:37:y:2013:i:5:p:370-404
    DOI: 10.1177/0193841X14523620
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    References listed on IDEAS

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    1. Paco Martorell & Isaac McFarlin, 2011. "Help or Hindrance? The Effects of College Remediation on Academic and Labor Market Outcomes," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 436-454, May.
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    3. Ou, Dongshu, 2010. "To leave or not to leave? A regression discontinuity analysis of the impact of failing the high school exit exam," Economics of Education Review, Elsevier, vol. 29(2), pages 171-186, April.
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    5. McCrary, Justin, 2008. "Manipulation of the running variable in the regression discontinuity design: A density test," Journal of Econometrics, Elsevier, vol. 142(2), pages 698-714, February.
    6. Juan Carlos Calcagno & Bridget Terry Long, 2008. "The Impact of Postsecondary Remediation Using a Regression Discontinuity Approach: Addressing Endogenous Sorting and Noncompliance," NBER Working Papers 14194, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Brian G. Moss & Peter Riley Bahr & Leigh Arsenault & Meghan Oster, 2019. "Knowing is Half the Battle, or Is It? A Randomized Experiment of the Impact of Supplemental Notification Letters on Placement Exam Participation, Preparation, and Performance," Research in Higher Education, Springer;Association for Institutional Research, vol. 60(6), pages 737-759, September.

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