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Do Single-Sex Schools Enhance Students’ STEM (Science, Technology, Engineering, and Mathematics) Outcomes?

Author

Listed:
  • Hyunjoon Park

    (Department of Sociology and Education, University of Pennsylvania)

  • Jere R. Behrman

    (Department of Economics and Sociology, University of Pennsylvania)

  • Jaesung Choi

    (Department of Economics, University of Pennsylvania)

Abstract

Despite women’s significant improvement in educational attainment, underrepresentation of women in Science, Technology, Engineering, and Mathematics (STEM) college majors persists in most countries. We address whether one particular institution – single-sex schools – may enhance female – or male – students’ STEM careers. Exploiting the unique setting in Korea where assignment to all-girls, all-boys or coeducational high schools is random, we move beyond associations to assess causal effects of single-sex schools. We use administrative data on national college entrance mathematics examination scores and a longitudinal survey of high school seniors that provide various STEM outcomes (mathematics and science interest and self-efficacy, expectations of a four-year college attendance and a STEM college major during the high school senior year, and actual attendance at a four-year college and choice of a STEM major two years after high school). We find significantly positive effects of all-boys schools consistently across different STEM outcomes, whereas the positive effect of all-girls schools is only found for mathematics scores.

Suggested Citation

  • Hyunjoon Park & Jere R. Behrman & Jaesung Choi, 2012. "Do Single-Sex Schools Enhance Students’ STEM (Science, Technology, Engineering, and Mathematics) Outcomes?," PIER Working Paper Archive 12-038, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    • Handle: RePEc:pen:papers:12-038
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    References listed on IDEAS

    as
    1. Jackson, C. Kirabo, 2012. "Single-sex schools, student achievement, and course selection: Evidence from rule-based student assignments in Trinidad and Tobago," Journal of Public Economics, Elsevier, vol. 96(1), pages 173-187.
    2. Alison L. Booth & Patrick Nolen, 2012. "Gender differences in risk behaviour: does nurture matter?," Economic Journal, Royal Economic Society, vol. 122(558), pages 56-78, February.
    3. Victor Lavy & Analia Schlosser, 2011. "Mechanisms and Impacts of Gender Peer Effects at School," American Economic Journal: Applied Economics, American Economic Association, vol. 3(2), pages 1-33, April.
    4. Victor Lavy & Analía Schlosser, 2011. "Corrigendum: Mechanisms and Impacts of Gender Peer Effects at School," American Economic Journal: Applied Economics, American Economic Association, vol. 3(3), pages 268-268, July.
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    Cited by:

    1. Massimo Anelli & Giovanni Peri, 2015. "Peers’ Composition Effects in the Short and in the Long Run: College Major, College Performance and Income," Working Papers 078, "Carlo F. Dondena" Centre for Research on Social Dynamics (DONDENA), Università Commerciale Luigi Bocconi.
    2. Doris, Aedín & O’Neill, Donal & Sweetman, Olive, 2013. "Gender, single-sex schooling and maths achievement," Economics of Education Review, Elsevier, vol. 35(C), pages 104-119.
    3. Shulamit Kahn & Donna Ginther, 2017. "Women and STEM," NBER Working Papers 23525, National Bureau of Economic Research, Inc.
    4. Marianne Bernatzky & Alejandro Cid, 2014. "Brecha de género en la educación secundaria," Documentos de Trabajo/Working Papers 1406, Facultad de Ciencias Empresariales y Economia. Universidad de Montevideo..
    5. Choi, Jaesung & Park, Hyunjoon & Behrman, Jere R., 2015. "Separating boys and girls and increasing weight? Assessing the impacts of single-sex schools through random assignment in Seoul," Social Science & Medicine, Elsevier, vol. 134(C), pages 1-11.

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    More about this item

    Keywords

    Africa; Economic Shocks; Child Schooling;
    All these keywords.

    JEL classification:

    • N37 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Africa; Oceania
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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