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The Impressive Effects of Tutoring on PreK-12 Learning: A Systematic Review and Meta-Analysis of the Experimental Evidence

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  • Andre Nickow
  • Philip Oreopoulos
  • Vincent Quan

Abstract

Tutoring—defined here as one-on-one or small-group instructional programming by teachers, paraprofessionals, volunteers, or parents—is one of the most versatile and potentially transformative educational tools in use today. Within the past decade, dozens of preK-12 tutoring experiments have been conducted, varying widely in their approach, context, and cost. Our study represents the first systematic review and meta-analysis of these and earlier studies. We develop a framework for considering different types of programs to not only examine overall effects, but also explore how these effects vary by program characteristics and intervention context. We find that tutoring programs yield consistent and substantial positive impacts on learning outcomes, with an overall pooled effect size estimate of 0.37 SD. Effects are stronger, on average, for teacher and paraprofessional tutoring programs than for nonprofessional and parent tutoring. Effects also tend to be strongest among the earlier grades. While overall effects for reading and math interventions are similar, reading tutoring tends to yield higher effect sizes in earlier grades, while math tutoring tends to yield higher effect sizes in later grades. Tutoring programs conducted during school tend to have larger impacts than those conducted after school.

Suggested Citation

  • Andre Nickow & Philip Oreopoulos & Vincent Quan, 2020. "The Impressive Effects of Tutoring on PreK-12 Learning: A Systematic Review and Meta-Analysis of the Experimental Evidence," NBER Working Papers 27476, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:27476
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    Cited by:

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    2. Bonesrønning, Hans & Finseraas, Henning & Hardoy, Ines & Iversen, Jon Marius Vaag & Nyhus, Ole Henning & Opheim, Vibeke & Salvanes, Kari Vea & Sandsør, Astrid Marie Jorde & Schøne, Pål, 2022. "Small-group instruction to improve student performance in mathematics in early grades: Results from a randomized field experiment," Journal of Public Economics, Elsevier, vol. 216(C).
    3. Carlana, Michela & La Ferrara, Eliana, 2021. "Apart but Connected: Online Tutoring and Student Outcomes during the COVID-19 Pandemic," IZA Discussion Papers 14094, Institute of Labor Economics (IZA).
    4. Jo Blanden & Matthias Doepke & Jan Stuhler, 2022. "Education inequality," CEP Discussion Papers dp1849, Centre for Economic Performance, LSE.
    5. Haelermans, Carla & Jacobs, Madelon & van Vugt, Lynn & Aarts, Bas & Abbink, Henry & Smeets, Chayenne & van der Velden, Rolf & van Wetten, Sanne, 2021. "A full year COVID-19 crisis with interrupted learning and two school closures: The effects on learning growth and inequality in primary education," Research Memorandum 021, Maastricht University, Graduate School of Business and Economics (GSBE).
    6. Donald Ipperciel, 2022. "What Should the Future of Learning Look Like? Looking Back, Looking Forward," International Journal of Higher Education, Sciedu Press, vol. 11(5), pages 1-51, October.
    7. Verónica Cabezas & José Ignacio Cuesta & Francisco Gallego, 2021. "Does Short-Term School Tutoring have Medium-Term Effects? Experimental Evidence from Chile," Documentos de Trabajo 565, Instituto de Economia. Pontificia Universidad Católica de Chile..
    8. Harry Anthony Patrinos, 2022. "Learning loss and learning recovery," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 49(2), pages 183-188, June.
    9. Hardt, David & Nagler, Markus & Rincke, Johannes, 2022. "Can peer mentoring improve online teaching effectiveness? An RCT during the COVID-19 pandemic," Labour Economics, Elsevier, vol. 78(C).
    10. Hashibul Hassan & Asad Islam & Abu Siddique & Liang Choon Wang, 2021. "Telementoring and homeschooling during school closures: A randomized experiment in rural Bangladesh," Munich Papers in Political Economy 13, Munich School of Politics and Public Policy and the School of Management at the Technical University of Munich.
    11. Noam Angrist & Peter Bergman & Moitshepi Matsheng, 2022. "Experimental evidence on learning using low-tech when school is out," Nature Human Behaviour, Nature, vol. 6(7), pages 941-950, July.
    12. Werner, Katharina & Woessmann, Ludger, 2021. "The Legacy of COVID-19 in Education," IZA Discussion Papers 14796, Institute of Labor Economics (IZA).
    13. de Ree, Joppe & Maggioni, Mario A. & Paulle, Bowen & Rossignoli, Domenico & Ruijs, Nienke & Walentek, Dawid, 2023. "Closing the income-achievement gap? Experimental evidence from high-dosage tutoring in Dutch primary education," Economics of Education Review, Elsevier, vol. 94(C).
    14. Francisco Gallego & Philip Oreopoulos & Noah Spencer, 2023. "The Importance of a Helping Hand in Education and in Life," Documentos de Trabajo 575, Instituto de Economia. Pontificia Universidad Católica de Chile..
    15. 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).
    16. Dan Goldhaber & Thomas J. Kane & Andrew McEachin & Emily Morton & Tyler Patterson & Douglas O. Staiger, 2022. "The Consequences of Remote and Hybrid Instruction During the Pandemic," NBER Working Papers 30010, National Bureau of Economic Research, Inc.
    17. Lucas Gortazar & Claudia Hupkau & Antonio Roldan, 2023. "Online tutoring works: experimental evidence from a program with vulnerable children," CEP Discussion Papers dp1908, Centre for Economic Performance, LSE.
    18. Falch, Ranveig, 2022. "How do people trade off resources between quick and slow learners?," European Economic Review, Elsevier, vol. 150(C).
    19. Boruchowicz, Cynthia & Parker, Susan W. & Robbins, Lindsay, 2022. "Time use of youth during a pandemic: Evidence from Mexico," World Development, Elsevier, vol. 149(C).

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    JEL classification:

    • I2 - Health, Education, and Welfare - - Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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