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Computers and student learning: bivariate and multivariate evidence on the availability and use of computers at home and at school

  • Thomas Fuchs
  • Ludger Wossmann

We estimate the relationship between computers and students’ educational achievement in the international student-level PISA database. Bivariate analyses show a positive correlation between achievement and computer availability both at home and at school. However, once we control extensively for family background and school characteristics, the relationship gets negative for home computers and insignificant for school computers. Thus, mere availability of computers at home seems to distract students from effective learning. But achievement shows a positive conditional relationship with computer use for education and communication at home and an inverted U-shaped relationship with computer and internet use at school.

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Article provided by ULB -- Universite Libre de Bruxelles in its journal Brussels economic review.

Volume (Year): 47 (2004)
Issue (Month): 3-4 ()
Pages: 359-386

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Handle: RePEc:bxr:bxrceb:y:2004:v:47:i:3-4:p:359-385
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  1. Borghans Lex & Weel Bas ter, 2003. "Are computer skills the new basic skills? The returns to computer, writing and math skills in Britain," Research Memorandum 005, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
  2. Woessmann, Ludger, 2004. "How Equal Are Educational Opportunities? Family Background and Student Achievement in Europe and the United States," IZA Discussion Papers 1284, Institute for the Study of Labor (IZA).
  3. Jere R. Behrman & Mark R. Rosenzweig, 2002. "Does Increasing Women's Schooling Raise the Schooling of the Next Generation?," American Economic Review, American Economic Association, vol. 92(1), pages 323-334, March.
  4. Thomas Fuchs & Ludger Wößmann, 2007. "What accounts for international differences in student performance? A re-examination using PISA data," Empirical Economics, Springer, vol. 32(2), pages 433-464, May.
  5. Wooldridge, Jeffrey M., 2001. "Asymptotic Properties Of Weighted M-Estimators For Standard Stratified Samples," Econometric Theory, Cambridge University Press, vol. 17(02), pages 451-470, April.
  6. Lindbeck, Assar & Snower, Dennis J, 2000. "Multitask Learning and the Reorganization of Work: From Tayloristic to Holistic Organization," Journal of Labor Economics, University of Chicago Press, vol. 18(3), pages 353-76, July.
  7. Entorf, Horst & Gollac, Michel & Kramarz, Francis, 1999. "New Technologies, Wages, and Worker Selection," Journal of Labor Economics, University of Chicago Press, vol. 17(3), pages 464-91, July.
  8. Dinardo, J.E. & Pischke, J.S., 1996. "The Returns to Computer Use Revisited: Have Pencils Changed the Wage Structure Too?," Working papers 96-12, Massachusetts Institute of Technology (MIT), Department of Economics.
  9. Ludger Woesmann, 2003. "Schooling Resources, Educational Institutions and Student Performance: the International Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(2), pages 117-170, 05.
  10. Bruce Sacerdote, 2000. "The Nature and Nurture of Economic Outcomes," NBER Working Papers 7949, National Bureau of Economic Research, Inc.
  11. Moulton, Brent R., 1986. "Random group effects and the precision of regression estimates," Journal of Econometrics, Elsevier, vol. 32(3), pages 385-397, August.
  12. Angrist, Joshua & Lavy, Victor, 2001. "New Evidence on Classroom Computers and Pupil Learning," IZA Discussion Papers 362, Institute for the Study of Labor (IZA).
  13. Rouse, Cecilia Elena & Krueger, Alan B., 2004. "Putting computerized instruction to the test: a randomized evaluation of a "scientifically based" reading program," Economics of Education Review, Elsevier, vol. 23(4), pages 323-338, August.
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