, Volume 45, Issue 3, pp 305–324 | Cite as

The role of family background and school resources on elementary school students’ mathematics achievement

  • Yuko Nonoyama-TarumiEmail author
  • Kathleen Hughes
  • J. Douglas Willms
Open File


This article compares the effects of family background and school resources on fourth-grade students’ math achievement, using data from the 2011 Trends in International Mathematics and Science Study (TIMSS). In order to ameliorate potential floor effects, it uses relative risk and population attributable risk to examine the effects of family background and low levels of school resources. Four findings stand out: (1) the percentage of vulnerable students decreases as GDP increases, but this relationship weakens at higher levels of GDP; (2) the relative risk associated with low socioeconomic status is positively related to GDP, but the relative risk associated with low school resources is unrelated to GDP; (3) the population attributable risk associated with some of the family and school risk factors tends to fall with rising GDP, but varies considerably amongst countries; and (4) family background effects are stronger than school resource effects in low- and high-income countries.


Relative risk Population attributable risk Mathematics achievement Family background School resources 


  1. Allen, M. J., & Yen, W. M. (2002). Introduction to measurement theory. Long Grove, IL: Waveland Press.Google Scholar
  2. Baker, D., Goesling, B., & LeTendre, G. (2002). Socioeconomic status, school quality, and national economic development: A cross-national analysis of the “Heyneman-Loxley Effect” on mathematics and science achievement. Comparative Education Review, 46, 291–312.CrossRefGoogle Scholar
  3. Bowles, S., & Levin, H. M. (1968). The determinants of scholastic achievement: An appraisal of some recent evidence. The Journal of Human Resources, 2, 3–24.CrossRefGoogle Scholar
  4. Chudgar, A., & Luschei, T. F. (2009). National income, income inequality, and the importance of schools: A hierarchical cross-national comparison. American Educational Research Journal, 46(3), 626–658.CrossRefGoogle Scholar
  5. Coleman, J., Campbell, E. Q., & Hobson, C. J. (1966). Equality of educational opportunity. Washington, DC: US Government Printing Office.Google Scholar
  6. Gamoran, A., & Long, D. (2007). Equality of educational opportunity: A 40-year retrospective. In R. Teese, S. Lamb, & M. Duru-Bellat (Eds.), International studies in educational inequality, theory and policy (pp. 23–48). Dordrecht: Springer.CrossRefGoogle Scholar
  7. Hanushek, E. A., & Luque, J. A. (2003). Efficiency and equity in schools around the world. Economics of Education Review, 22(5), 481–502.CrossRefGoogle Scholar
  8. Harris, D. N. (2007). Diminishing marginal returns and the production of education: An international analysis. Education Economics, 15(1), 31–53.CrossRefGoogle Scholar
  9. Heyneman, S. P., & Loxley, W. (1983). The effect of primary-school quality on academic achievement across twenty-nine high-and low-income countries. American Journal of Sociology, 88, 1162–1194.CrossRefGoogle Scholar
  10. Ilie, S., & Lietz, P. (2010). School quality and student achievement in 21 European countries. In D. Hastedt & M. von Davier (Eds.), Issues and methodologies in large-scale assessments (pp. 57–84). Princeton: IEA-ETS Research Institute.Google Scholar
  11. Kyriakides, L., Campbell, R. J., & Gagatsis, A. (2000). The significance of the classroom effect in primary schools: An application of Creemers’ comprehensive model of educational effectiveness. School Effectiveness and School Improvement, 11(4), 501–529.CrossRefGoogle Scholar
  12. Levin, H. H., & Belfield, C. R. (2002). Families as contractual partners in education. UCLA Law Review, 49, 1799–1824.Google Scholar
  13. Martin, M. O., & Mullis, I. V. S. (Eds.) (2012). Methods and procedures in TIMSS and PIRLS 2011. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.Google Scholar
  14. Mortimore, P., Sammons, P., Stoll, L., Lewis, D., & Ecob, R. (1988). School matters. Wells, Somerset: Open Books.Google Scholar
  15. Nonoyama-Tarumi, Y., & Willms, J. D. (2010). The relative and absolute risks of disadvantaged family background and low levels of school resources on student literacy. Economics of Education Review, 29(2), 214–224.CrossRefGoogle Scholar
  16. Riddell, A. R. (1989a). An alternative approach to the study of school effectiveness in the third world countries. Comparative Education Review, 33(4), 481–497.CrossRefGoogle Scholar
  17. Riddell, A. R. (1989b). Response to Heyneman. Comparative Education Review, 33(4), 505–506.CrossRefGoogle Scholar
  18. Tramonte, L., & Willms, J. D. (2010). Cultural capital and its effects on education outcomes. Economics of Education Review, 29(2), 200–213.CrossRefGoogle Scholar
  19. WHO [World Health Organization] (2011). WHO report on the global tobacco epidemic, 2011: Warning about the dangers of tobacco. Geneva: WHO Press.Google Scholar
  20. Willms, J. D. (2010). School composition and contextual effects on student outcomes. Teachers College Record, 112(4), 1008–1037.Google Scholar

Copyright information


Authors and Affiliations

  • Yuko Nonoyama-Tarumi
    • 1
    Email author
  • Kathleen Hughes
    • 2
  • J. Douglas Willms
    • 2
  1. 1.Waseda Institute for Advanced StudyWaseda UniversityTokyoJapan
  2. 2.Canadian Research Institute for Social PolicyUniversity of New BrunswickFrederictonCanada

Personalised recommendations