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One-To-One Technology and Student Outcomes

Listed author(s):
  • Hull, Marie C.

    ()

    (University of North Carolina, Greensboro)

  • Duch, Katherine

    (One Minus Beta Analytics)

New technologies offer many promises to improve student learning, but efforts to bring them to the classroom often fail to produce improvements to student outcomes. A notable exception to this pattern is one-to-one laptop programs. While early evaluations of these programs have been encouraging, they are costly to implement, and no study has investigated the impact of a one-to-one technology program implemented on a large scale over a multiyear period. With administrative school data, this paper uses a differences-in-differences strategy to evaluate the impact of a one-to-one laptop program implemented in a midsize school district. We find that while short-term impacts of the program were modest, math scores improved by 0.15–0.17 standard deviations in the medium term (4–5 years post-implementation). We also investigate heterogeneity in impacts on test scores and the impact of the program on several measures of student behavior.

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File URL: http://ftp.iza.org/dp10886.pdf
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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 10886.

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Length: 53 pages
Date of creation: Jul 2017
Handle: RePEc:iza:izadps:dp10886
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  1. Esteban Aucejo & Teresa Romano, 2014. "Assessing the effect of school days and absenceson test score performance," LSE Research Online Documents on Economics 60498, London School of Economics and Political Science, LSE Library.
  2. Daniel O. Beltran & Kuntal K. Das & Robert W. Fairlie, 2008. "Home computers and educational outcomes: evidence from the NLSY97 and CPS," International Finance Discussion Papers 958, Board of Governors of the Federal Reserve System (U.S.).
  3. Jacob L. Vigdor & Helen F. Ladd & Erika Martinez, 2014. "Scaling The Digital Divide: Home Computer Technology And Student Achievement," Economic Inquiry, Western Economic Association International, vol. 52(3), pages 1103-1119, 07.
  4. Fiorini, M., 2010. "The effect of home computer use on children's cognitive and non-cognitive skills," Economics of Education Review, Elsevier, vol. 29(1), pages 55-72, February.
  5. Petra E. Todd & Kenneth I. Wolpin, 2003. "On The Specification and Estimation of The Production Function for Cognitive Achievement," Economic Journal, Royal Economic Society, vol. 113(485), pages 3-33, February.
  6. Ofer Malamud & Cristian Pop-Eleches, 2011. "Home Computer Use and the Development of Human Capital," The Quarterly Journal of Economics, Oxford University Press, vol. 126(2), pages 987-1027.
  7. Bulman, G. & Fairlie, R.W., 2016. "Technology and Education," Handbook of the Economics of Education, Elsevier.
  8. Rodrigo Belo & Pedro Ferreira & Rahul Telang, 2014. "Broadband in School: Impact on Student Performance," Management Science, INFORMS, vol. 60(2), pages 265-282, February.
  9. Derek Neal & Diane Whitmore Schanzenbach, 2010. "Left Behind by Design: Proficiency Counts and Test-Based Accountability," The Review of Economics and Statistics, MIT Press, vol. 92(2), pages 263-283, May.
  10. repec:nbr:nberch:13934 is not listed on IDEAS
  11. Aucejo, Esteban M. & Romano, Teresa Foy, 2016. "Assessing the effect of school days and absences on test score performance," Economics of Education Review, Elsevier, vol. 55(C), pages 70-87.
  12. Aaron Chatterji, 2017. "Innovation and American K-12 Education," NBER Working Papers 23531, National Bureau of Economic Research, Inc.
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