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The Effectiveness of English Secondary Schools for Pupils of Different Ability Levels

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  • Lorraine Dearden
  • John Micklewright
  • Anna Vignoles

Abstract

'League table' information on school effectiveness in England generally relies on either a comparison of the average outcomes of pupils by school, e.g. mean exam scores, or on estimates of the average value added by each school. These approaches assume that the information parents and policy-makers need most to judge school effectiveness is the average achievement level or gain in a particular school. Yet schools can be differentially effective for children with differing levels of prior attainment. We present evidence on the extent of differential effectiveness in English secondary schools, and find that even the most conservative estimate suggests that around one quarter of schools in England are differentially effective for students of differing prior ability levels. This affects an even larger proportion of children as larger schools are more likely to be differentially effective.
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Suggested Citation

  • Lorraine Dearden & John Micklewright & Anna Vignoles, 2011. "The Effectiveness of English Secondary Schools for Pupils of Different Ability Levels," Fiscal Studies, Institute for Fiscal Studies, vol. 32(2), pages 225-244, June.
    • Handle: RePEc:ifs:fistud:v:32:y:2011:i::p:225-244
    DOI: j.1475-5890.2011.00134.x
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    File URL: http://hdl.handle.net/10.1111/j.1475-5890.2011.00134.x
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    References listed on IDEAS

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    1. Victor Lavy & M. Daniele Paserman & Analia Schlosser, 2012. "Inside the Black Box of Ability Peer Effects: Evidence from Variation in the Proportion of Low Achievers in the Classroom," Economic Journal, Royal Economic Society, vol. 122(559), pages 208-237, March.
    2. Harvey Goldstein & Simon Burgess & Brendon McConnell, 2007. "Modelling the effect of pupil mobility on school differences in educational achievement," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(4), pages 941-954, October.
    3. Joshua D. Angrist & Kevin Lang, 2004. "Does School Integration Generate Peer Effects? Evidence from Boston's Metco Program," American Economic Review, American Economic Association, vol. 94(5), pages 1613-1634, December.
    4. Esther Duflo & Pascaline Dupas & Michael Kremer, 2011. "Peer Effects, Teacher Incentives, and the Impact of Tracking: Evidence from a Randomized Evaluation in Kenya," American Economic Review, American Economic Association, vol. 101(5), pages 1739-1774, August.
    5. Lavy, Victor & Paserman, Daniele & Schlosser, Analila, 2008. "Inside the Black of Box of Ability Peer Effects: Evidence from Variation in Low Achievers in the Classroom," Foerder Institute for Economic Research Working Papers 275712, Tel-Aviv University > Foerder Institute for Economic Research.
    6. Figlio, David N. & Page, Marianne E., 2002. "School Choice and the Distributional Effects of Ability Tracking: Does Separation Increase Inequality?," Journal of Urban Economics, Elsevier, vol. 51(3), pages 497-514, May.
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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Are schools effective? It depends on how good you are
      by kevin denny in Kevin Denny: Economics more-or-less on 2011-08-01 13:11:46

    Citations

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    Cited by:

    1. Loviglio, Annalisa, 2023. "School Quality beyond Test Scores: The Role of Schools in Shaping Educational Outcomes," IZA Discussion Papers 16111, Institute of Labor Economics (IZA).
    2. Smyth, Emer & McCoy, Selina, 2011. "Improving Second-level Education: Using Evidence for Policy Development," Papers EC5, Economic and Social Research Institute (ESRI).
    3. Sushmita Nalini Das, 2014. "Do "Child-Friendly" Practices affect Learning? Evidence from Rural India," DoQSS Working Papers 14-03, Quantitative Social Science - UCL Social Research Institute, University College London.
    4. Doris, Aedin & O'Neill, Donal & Sweetman, Olive, 2019. "Good Schools or Good Students? The Importance of Selectivity for School Rankings," IZA Discussion Papers 12459, Institute of Labor Economics (IZA).
    5. Brendan Houng & Moshe Justman, 2013. "Comparing Least-Squares Value-Added Analysis and Student Growth Percentile Analysis for Evaluating Student Progress and Estimating School Effects," Melbourne Institute Working Paper Series wp2013n07, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    6. Moshe Justman & Brendan Houng, 2013. "A Comparison Of Two Methods For Estimating School Effects And Tracking Student Progress From Standardized Test Scores," Working Papers 1316, Ben-Gurion University of the Negev, Department of Economics.

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    JEL classification:

    • I2 - Health, Education, and Welfare - - Education

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