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The Economics of Tracking in Education

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  • Betts, Julian R.

Abstract

Tracking refers to the practice of dividing students by ability or achievement. Students may be tracked within schools by placing them into different classrooms based on achievement, which is the typical practice in countries such as the United States or Canada. Alternatively, students could be streamed into different schools, with either vocational or academic emphases, as has been practiced commonly in Europe. Proponents of tracking argue that tracking can increase the efficiency of schooling by focusing on the needs of distinct groups of students. Opponents' main concerns relate to perpetuating and aggravating inequality. Evaluating effects of tracking on average student achievement and the distribution of achievement is difficult, in part because of variations from study to study and from country to country in the characteristics of the tracking system. Early work, largely in the United States and Britain, used variation across and within schools, and often found that tracking increased inequality in achievement. But more recent work in the United States has questioned these findings, suggesting that careful attention to endogenous placement of students into classrooms and endogenous use of tracking across schools changes results dramatically. Experimental studies on within-school tracking in the United States have produced mixed results, and one experiment in Kenya suggests that tracking can boost the achievement of both low-achieving and high-achieving students. A large body of work now uses geographical variation across regions, countries, grades, and time to identify the effects of tracking. These studies for the most part suggest that tracking aggravates inequality in outcomes. These results are fairly strong, and may be identifying the more dramatic effects that obtain when students are separated into vocational schools and more academically oriented schools, as opposed to the effects of within-school tracking. The paper concludes with an outline of how future research might better categorize and rigorously evaluate the real-world nuances of tracking.

Suggested Citation

  • Betts, Julian R., 2011. "The Economics of Tracking in Education," Handbook of the Economics of Education, Elsevier.
  • Handle: RePEc:eee:educhp:3-07
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    References listed on IDEAS

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    Cited by:

    1. Bauer, Philipp C. & Riphahn, Regina T., 2013. "Institutional determinants of intergenerational education transmission — Comparing alternative mechanisms for natives and immigrants," Labour Economics, Elsevier, vol. 25(C), pages 110-122.
    2. Piopiunik, Marc, 2014. "The effects of early tracking on student performance: Evidence from a school reform in Bavaria," Economics of Education Review, Elsevier, vol. 42(C), pages 12-33.
    3. Avitabile,Ciro & Bobba,Matteo & Pariguana,Marco, 2015. "High school track choice and financial constraints : evidence from urban Mexico," Policy Research Working Paper Series 7427, The World Bank.
    4. John, Katrin & Thomsen, Stephan L., 2015. "School-track environment or endowment: What determines different other-regarding behavior across peer groups?," Games and Economic Behavior, Elsevier, vol. 94(C), pages 122-141.
    5. Bastian Ravesteijn & Hans van Kippersluis & Mauricio Avendano & Pekka Martikainen & Hannu Vessari & Eddy van Doorslaer, 2017. "The Impact of Later Tracking on Mortality by Parental Income in Finland," Tinbergen Institute Discussion Papers 17-030/V, Tinbergen Institute.
    6. De Fraja, Gianni & Martínez-Mora, Francisco, 2014. "The desegregating effect of school tracking," Journal of Urban Economics, Elsevier, vol. 80(C), pages 164-177.
    7. Miroslava Federicova & Filip Pertold & Michael L. Smith, 2016. "Children Left Behind: Self-confidence of Pupils in Competitive Environments," CERGE-EI Working Papers wp574, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    8. repec:eee:jhecon:v:57:y:2018:i:c:p:206-220 is not listed on IDEAS
    9. Miller, Luke C. & Mittleman, Joel, 2012. "High Schools That Work and college preparedness: Measuring the model's impact on mathematics and science pipeline progression," Economics of Education Review, Elsevier, vol. 31(6), pages 1116-1135.
    10. Lundborg, Petter & Majlesi, Kaveh, 2018. "Intergenerational transmission of human capital: Is it a one-way street?," Journal of Health Economics, Elsevier, vol. 57(C), pages 206-220.
    11. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves, 2014. "Endogenous peer effects: local aggregate or local average?," Journal of Economic Behavior & Organization, Elsevier, vol. 103(C), pages 39-59.
    12. repec:eee:juecon:v:100:y:2017:i:c:p:54-64 is not listed on IDEAS
    13. Julian R. Betts & Youjin Hahn & Andrew C. Zau, 2015. "Can Testing Improve Student Learning? An Evaluation of the Mathematics Diagnostic Testing Project," Monash Economics Working Papers 31-15, Monash University, Department of Economics.
    14. Biewen, Martin & Tapalaga, Madalina, 2017. "Life-cycle educational choices in a system with early tracking and ‘second chance’ options," Economics of Education Review, Elsevier, vol. 56(C), pages 80-94.

    More about this item

    Keywords

    Tracking; Ability Grouping; Streaming; Pedagogy; Curriculum; Human Capital; Vocational Education;

    JEL classification:

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

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