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Improving the Implementation and Effectiveness of Out‐of‐School‐Time Tutoring

Author

Listed:
  • Carolyn J. Heinrich
  • Patricia Burch
  • Annalee Good
  • Rudy Acosta
  • Huiping Cheng
  • Marcus Dillender
  • Christi Kirshbaum
  • Hiren Nisar
  • Mary Stewart

Abstract

School districts are spending millions on tutoring outside regular school day hours for economically and academically disadvantaged students in need of extra academic assistance. Under No Child Left Behind (NCLB), parents of children in persistently low‐performing schools were allowed to choose their child's tutoring provider, and together with school districts, they were also primarily responsible for holding providers in the private market accountable for performance. We present results from a multisite, mixed‐method longitudinal study of the impact of out‐of‐school time (OST) tutoring on student reading and mathematics achievement that link provider attributes and policy and program administration variables to tutoring program effectiveness. We find that many students are not getting enough hours of high‐quality, differentiated instruction to produce significant gains in their learning, in part because of high hourly rates charged by providers for tutoring. We identify strategies and policy levers that school districts can use to improve OST tutoring policy design and launch improved programs as waivers from NCLB are granted.

Suggested Citation

  • Carolyn J. Heinrich & Patricia Burch & Annalee Good & Rudy Acosta & Huiping Cheng & Marcus Dillender & Christi Kirshbaum & Hiren Nisar & Mary Stewart, 2014. "Improving the Implementation and Effectiveness of Out‐of‐School‐Time Tutoring," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 33(2), pages 471-494, March.
    • Handle: RePEc:wly:jpamgt:v:33:y:2014:i:2:p:471-494
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    File URL: http://hdl.handle.net/10.1002/pam.21745
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    Cited by:

    1. Ballestar, María Teresa & Mir, Miguel Cuerdo & Pedrera, Luis Miguel Doncel & Sainz, Jorge, 2024. "Effectiveness of tutoring at school: A machine learning evaluation," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    2. Cortes, Kalena E. & Kortecamp, Karen & Loeb, Susanna & Robinson, Carly D., 2024. "A Scalable Approach to High-Impact Tutoring for Young Readers: Results of a Randomized Controlled Trial," IZA Discussion Papers 16712, Institute of Labor Economics (IZA).
    3. Hickey, Andrea J. & Flynn, Robert J., 2020. "A randomized evaluation of 15 versus 25 weeks of individual tutoring for children in care," Children and Youth Services Review, Elsevier, vol. 109(C).

    More about this item

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality

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