Sex Differences in Mathematical Reasoning Ability at Age 13: Their Status 20 Years Later

Sex Differences in Mathematical Reasoning Ability at Age 13: Their Status 20 Years Later
Camilla P. Benbow, David Lubinski, Daniel L. Shea, and Hossain Eftekhari-Sanjani; 2000


Abstract

Reported is the 20-year follow-up of 1,975 mathematically gifted adolescents (top 1%) whose assessments at age 12 to 14 revealed robust gender differences in mathematical reasoning ability. Both sexes became exceptional achievers and perceived themselves as such; they reported uniformly high levels of degree attainment and satisfaction with both their career direction and their overall success. The earlier sex differences in mathematical reasoning ability did predict differential educational and occupational outcomes. The observed differences also appeared to be a function of sex differences in preferences for (a) inorganic versus organic disciplines and (b) a career-focused versus more balanced life. Because profile differences in abilities and preferences are longitudinally stable, males probably will remain more represented in some disciplines, whereas females are likely to remain more represented in others. These data have policy implications for higher education and the world of work.

Sex Differences in Mathematical Reasoning:

Sex Differences in Mathematical Reasoning in Gifted Students

>Mills, Ablard, and Strumpf (1993) documented sex differences among intellectually gifted students in mathematical reasoning as early as second grade (average d =  .43). Robinson et al. (1996) reported sex differences in mathematical precocity before kindergarten (average d = .37). More significantly, these latter sex differences were maintained following exposure to mathematical enrichment opportunities aimed at both males and females. Males gained more than females did on quantitative and visuospatial measures after an average of 28 biweekly intervention sessions (Robinson, Abbott, Berninger, Busse, & Mukhopadhyah, 1997).

The implications of these differences, and especially of the disparate ratios at the top for the math-science education pipeline, are clear: Given an early advantage in these fundamental quantitative skills, a greater number of males than females will qualify for advanced training in disciplines that place a premium on mathematical reasoning. As Hedges and Nowell (1995) stated, ‘‘Sex differences in variance and mean lead to substantially fewer females than males who score in the upper tails of the mathematics and science distributions and hence are poised to succeed in the sciences. The achievement of fair representation of women in science will be much more difficult if there are only one-half to one-seventh as many women as men who excel in the relevant abilities’’ (p. 45).

Other cognitive and noncognitive sex differences expand our understanding of the factors that influence the way precocious youth develop in math. Table 1 contains data on abilities and values of gifted students in the Midwest who were identified by SMPY from 1988 to 1991 and who attended a special summer program (Lubinski & Benbow, 1992). Again, sex differences in mathematical reasoning ability were consistently observed (average d = .84), but sex differences in the SAT-V were not observed. Table 1 includes other cognitive measures of general intelligence and specific abilities. No meaningful differences were observed among scores on the Advanced Raven Progressive Matrices (Lubinski & Benbow, 1992), which is a nonverbal measure of general intelligence. There were, however, substantial differences in spatial and mechanical reasoning abilities (average d = .92). In addition to these differences in specific abilities, there were also sex differences in vocational interests and values. Table 1 presents the differences in values. As can be seen, males are higher on theoretical values, and females are higher on social values, among other trends. Strongly held theoretical values are characteristic of physical scientists, while social values are negatively correlated with interests in the physical sciences (Achter, Lubinski, Benbow, & Eftekhari-Sanjani, 1999). Similar preference distinctions between males and females have been found using the Strong Interest Inventory (Lubinski & Benbow, 2006), with the SMPY males having stronger investigative and realistic interests and the SMPY females having stronger social interests (Achter, Lubinski,&Benbow, 1996, Appendix B, p. 76). Thus, it appears that early differences in mathematical skills may occur along with other factors relevant to the development of scientific expertise.<

D.F. Halpern, C.P Benbow, D.C. Geary et al.; The science of sex differences in science and mathematics; 2007

http://134.173.180.115/berger/pdf/Halpern2007.SciSexDif.Pub.pdf

[Schließlich ist es so, dass sich unter den Hochbegabten nicht bloß Männer durchschnittlich mehr für die "harten Wissenschaften" interessieren, sondern sich diese auch von ihren Begabungsprofilen bzw. kognitiven Fähigkeiten her durchschnittlich besser für die "harten Wissenschaften" eignen.]