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Scaling up experiments to reduce educational inequality

Published online by Cambridge University Press:  16 September 2020

STEPHEN W. RAUDENBUSH
STEPHEN W. RAUDENBUSH*
Affiliation:
University of Chicago Department of Sociology, Harris School of Public Policy, and Committee on Education, University of Chicago, Chicago, IL, USA
*
*Correspondence to: University of Chicago Department of Sociology, Harris School of Public Policy, and Committee on Education, University of Chicago, Chicago, IL, USA. E-mail: [email protected]
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Abstract

For educational researchers, Al-Ubaydli et al. raise a crucial question: How can the science of scaling experimental innovations contribute to school improvement? By assessing how particular innovative programs work, why, for whom and under what conditions, experimenters test theories: about how children and youth learn, about how adults can collaborate to create the required learning opportunities and about how policy can supply the required incentives and resources to support such effective collaboration. My focus in this response article thus shifts from the perspective of innovators who hope to scale their interventions to the perspective of practitioners who face the challenge of adopting, adapting or borrowing ideas from experimental studies and harmonizing those ideas with expert clinical judgment.

Type
Articles
Information
Behavioural Public Policy , Volume 5 , Special Issue 1: Field Experiments and Public Policy , January 2021 , pp. 60 - 70
Copyright
Copyright © The Author(s) 2020. Published by Cambridge University Press

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References

Bryk, A. S., Sebring, P., Allensworth, E., Luppescu, S. and Easton, J. (2010), Organizing schools for improvement: Lessons from Chicago, Chicago: University of Chicago Press.Google Scholar
Cohen, D. K. and Moffitt, S. L. (2009), The Ordeal of Inequality: Did Federal Regulation Fix the Schools? Cambridige, MA: Harvard University Press.CrossRefGoogle Scholar
Cohodes, S., Setren, E. and Walters, C. R. (2019), Can Successful Schools Replicate? Scaling up Boston's Charter School Sector (No. w25796), National Bureau of Economic Research.Google Scholar
Coleman, J. S., Campbell, E. Q., Hobson, C. J., McPartland, J., Mood, A. M., Weinfeld, F. D. and Robert, L. (1966), ‘York.’, Equality of Educational Opportunity, (1966).Google Scholar
Cunha, F. and Heckman, J. (2007), ‘The technology of skill formation’, American Economic Review, 97(2): 31–47.CrossRefGoogle Scholar
Dewey, J. (1929), The Sources of a Science of Education, New York: Horace Liveright.Google Scholar
Duursma, E., Augustyn, M. and Zuckerman, B. (2008), ‘Reading aloud to children: the evidence’, Archives of Disease in Childhood, 93(7): 554–557.CrossRefGoogle ScholarPubMed
Fryer, R. G. Jr (2014), ‘Injecting charter school best practices into traditional public schools: Evidence from field experiments’, The Quarterly Journal of Economics, 129(3): 1355–1407.CrossRefGoogle Scholar
Gelman, R. and Brenneman, K. (2004), ‘Science learning pathways for young children’, Early Childhood Research Quarterly, 19(1): 150–158.CrossRefGoogle Scholar
Graf, E., Garofalo, L., Hundertmark, A. C., Montague, G. L., Polash, N. M., Suskind, E. and Suskind, D. L. (2017), ‘Using formative research to develop a hospital-based perinatal public health intervention in the US: The Thirty Million Words Initiative Newborn Parent Education Curriculum’, Journal of Early Hearing Detection and Intervention, 2(1): 2–11.Google Scholar
Hassrick, E. M., Raudenbush, S. W. and Rosen, L. (2017), The Ambitious Elementary School: Its Conception, Design, and Implications for Educational Equality, University of Chicago Press.CrossRefGoogle Scholar
Kendeou, P., Van den Broek, P., White, M. J. and Lynch, J. S. (2009), ‘Predicting reading comprehension in early elementary school: The independent contributions of oral language and decoding skills’, Journal of Educational Psychology, 101(4): 765.CrossRefGoogle Scholar
National Reading Panel, National Institute of Child Health, Human Development, National Reading Excellence Initiative, National Institute for Literacy, United States Public Health Service, & United States Department of Health (2000), Report of the National Reading Panel: Teaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction: Reports of the subgroups, National Institute of Child Health and Human Development, National Institutes of Health.Google Scholar
Neal, D. A. (2018), Information, Incentives, and Education Policy, Harvard University Press.CrossRefGoogle Scholar
Spybrook, J. (2014), ‘Detecting Intervention Effects Across Context: An Examination of the Precision of Cluster Randomized Trials’, The Journal of Experimental Education, 82(3): 334–357CrossRefGoogle Scholar
Spybrook, J., Shi, R. and Kelcey, B. (2016), ‘Progress in the past decade: an examination of the precision of cluster randomized trials funded by the U.S. Institute of Education Sciences’, International Journal of Research & Method in Education, 39(3): 255–267CrossRefGoogle Scholar
Swanson, E., Vaughn, S., Wanzek, J., Petscher, Y., Heckert, J., Cavanaugh, C., … Tackett, K. (2011), ‘A synthesis of read-aloud interventions on early reading outcomes among preschool through third graders at risk for reading difficulties’, Journal of learning disabilities, 44(3): 258–275.CrossRefGoogle ScholarPubMed