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Interpreting the effectiveness of a summer reading program: The eye of the beholder

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  • Reed, Deborah K.
  • Aloe, Ariel M.

Abstract

In applying a methods-oriented approach to evaluation, this study interpreted the effectiveness of a summer reading program from three different stakeholder perspectives: practitioners from the school district, the funding agency supporting the program, and the policymakers considering mandating summer school. Archival data were obtained on 2330 students reading below benchmark in Grades 2–5. After propensity score matching participants to peers who did not attend the summer program, the final sample consisted of 630 students. Pre-to-posttest growth models revealed positive effects in Grades 2–4 (standardized slopes of .40–.54), but fifth graders demonstrated negligible improvement (standardized slope of .15). The standardized mean differences of propensity score matched treatment and control group students indicated null effects in all grade levels (d = −.13 to .05). Achieving proficient reading performance also was not attributable to summer school participation. Findings underscore the importance of operationalizing effectiveness in summative evaluation.

Suggested Citation

  • Reed, Deborah K. & Aloe, Ariel M., 2020. "Interpreting the effectiveness of a summer reading program: The eye of the beholder," Evaluation and Program Planning, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:epplan:v:83:y:2020:i:c:s0149718920301567
    DOI: 10.1016/j.evalprogplan.2020.101852
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    1. Scott Simkins & Stuart Allen, 2000. "Pretesting students to improve teaching and learning," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 6(1), pages 100-112, February.
    2. Clark, William C. & van Kerkhoff, Lorrae & Lebel, Louis & Gallopin, Gilberto, 2016. "Crafting Usuable Knowledge for Sustainable Development," Working Paper Series 16-005, Harvard University, John F. Kennedy School of Government.
    3. Glenn S. Baete & Craig Hochbein, 2014. "Project Proficiency: Assessing the Independent Effects of High School Reform in an Urban District," The Journal of Educational Research, Taylor & Francis Journals, vol. 107(6), pages 493-511, October.
    4. repec:mpr:mprres:7461 is not listed on IDEAS
    5. Eric A. Hanushek & John F. Kain & Steven G. Rivkin, 1998. "Does Special Education Raise Academic Achievement for Students with Disabilities?," NBER Working Papers 6690, National Bureau of Economic Research, Inc.
    6. Rosenbaum, Paul R., 2010. "Design Sensitivity and Efficiency in Observational Studies," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 692-702.
    7. Ho, Daniel E. & Imai, Kosuke & King, Gary & Stuart, Elizabeth A., 2007. "Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference," Political Analysis, Cambridge University Press, vol. 15(3), pages 199-236, July.
    Full references (including those not matched with items on IDEAS)

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