Can Online Off-The-Shelf Lessons Improve Student Outcomes? Evidence from A Field Experiment

C. Kirabo Jackson () and Alexey Makarin

No 22398, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: There has been a proliferation of websites that warehouse instructional materials designed to be taught by teachers in a traditional classroom. While this new technology has revolutionized how most teachers plan their lessons, the potential benefits of this innovation are unknown. To present evidence on this, we analyze an experiment in which middle-school math teachers were randomly given access to high-quality “off-the-shelf” lessons. Only providing teachers with online access to the lessons increased students’ math achievement by 0.06 of a standard deviation, but providing teachers with online access to the lessons along with supports to promote their use increased students’ math achievement by 0.09 of a standard deviation. Benefits were much larger for weaker teachers, suggesting that weaker teachers compensated for skill deficiencies by substituting the lessons for their own efforts. Survey evidence suggests that these effects were mediated by both improvements in lesson quality and teachers having more time to engage in other tasks. We rationalize these results with a multitask model of teaching. The intervention is more scalable and cost effective than most policies aimed at improving teacher quality, suggesting a real benefit to making high-quality instructional materials available to teachers on the internet.

JEL-codes: I20 J0 J48 (search for similar items in EconPapers)
Date: 2016-07
New Economics Papers: this item is included in nep-edu, nep-exp, nep-ger, nep-lma and nep-ure
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Published as Kirabo Jackson & Alexey Makarin, 2018. "Can Online Off-the-Shelf Lessons Improve Student Outcomes? Evidence from a Field Experiment," American Economic Journal: Economic Policy, vol 10(3), pages 226-254.

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Journal Article: Can Online Off-the-Shelf Lessons Improve Student Outcomes? Evidence from a Field Experiment (2018)
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