Commentary on the Chapter by Penner and CadwalladerOlsker, “Gender Differences in Mathematics and Science Achievement Across the Distribution: What International Variation Can Tell Us About the Role of Biology and Society”

Part of the Advances in Mathematics Education book series (AME)

Abstract

In their chapter, Penner and CadwalladerOlsker combine TIMSS data with country data from the United Nations, World Bank, and other resources to give two primary results related to mathematics performance by sex. First, they cast doubt on the utility of biological causes as an effective explanation of gender differences in mathematics performance on the TIMSS. Second, since gender differences in math scores depend on social factors, they investigate which country-level factors matter most in explaining those differences. The argument provides far greater insight to the question of gender and mathematics than simple comparison studies, establishing an excellent model for future research. At the same time, the results are macro-level results for a field that has struggled historically with macro-level solutions, thus raising the issue of the implications of this work for addressing gender equity.

Keywords

Gender Difference Quantile Regression Mathematics Achievement Gender Equity Mathematics Performance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Condron, D. (2011). Egalitarianism and educational excellence: Compatible goals for affluent countries? Educational Researcher, 40(2), 47–55. CrossRefGoogle Scholar
  2. Favreau, O. E., & Everett, J. C. (1996). A tale of two tails. American Psychologist, 51(3), 268–269. CrossRefGoogle Scholar
  3. Grattan-Guinness, I. (2000). The rainbow of mathematics: A history of the mathematical sciences. New York: W. W. Norton & Company. Google Scholar
  4. Hanna, G. (1989). Mathematics achievement of girls and boys in grade eight: Results from twenty countries. Educational Studies in Mathematics, 20(2), 225–232. CrossRefGoogle Scholar
  5. Holland, V. (2003). Underachieving boys: Problems and solutions. Support for Learning, 13, 174–178. CrossRefGoogle Scholar
  6. Howley, C. (2002). Understanding the circumstance of rural schooling: The parameters of respectful research. In S. Henderson (Ed.), Understanding achievement in science and mathematics in rural schools (pp. 11–16). Lexington: Appalachian Rural Systemic Initiative. Google Scholar
  7. Howley, A. A. & Howley, C. B. (1999). The transformative challenge of rural context. Educational Foundations, 14(4), 73–85. Google Scholar
  8. Klein, R., & Johnson, J. (2010). On the use of locale in understanding the mathematics achievement gap. In P. Brosnan, D. B. Erchick, & L. Flevares (Eds.), Proceedings of the 32nd annual meeting of the North American chapter of the international group for the psychology of mathematics education (pp. 489–496), Columbus, Ohio, USA, October 28–31, 2010. The Ohio State University. Google Scholar
  9. Lubinski, D., & Benbow, C. (1992). Gender differences in abilities and preferences among the gifted: Implications for the math-science pipeline. Current Directions in Psychological Science, 1, 61–66. CrossRefGoogle Scholar
  10. Scott, J. (1998). Seeing like a state: How certain schemes to improve the human condition have failed. New Haven: Yale University Press. Google Scholar
  11. Theobald, P. (1995). Teaching the commons: Place, pride, and the renewal of community. Boulder: Westview Press. Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Ohio UniversityAthensUSA

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