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Cited by 253Career Development and DiversityEducation, Achievement, and GiftednessGender and Technology in Education

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Gender differences in individual variation in academic grades fail to fit expected patterns for STEM

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O’Dea, R. E., Lagisz, M., Jennions, M. D., Nakagawa, S.·2018·Nature Communications
DOI 10.1038/s41467-018-06292-0PMC PMC6156605
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Abstract

Fewer women than men pursue careers in science, technology, engineering and mathematics (STEM), despite girls outperforming boys at school in the relevant subjects. According to the 'variability hypothesis', this over-representation of males is driven by gender differences in variance; greater male variability leads to greater numbers of men who exceed the performance threshold. Here, we use recent meta-analytic advances to compare gender differences in academic grades from over 1.6 million students. In line with previous studies we find strong evidence for lower variation among girls than boys, and of higher average grades for girls. However, the gender differences in both mean and variance of grades are smaller in STEM than non-STEM subjects, suggesting that greater variability is insufficient to explain male over-representation in STEM. Simulations of these differences suggest the top 10% of a class contains equal numbers of girls and boys in STEM, but more girls in non-STEM subjects.

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Fig. 1 Predicted distributions of school grades of girls (red) and boys (blue). a The grade distribution overlaps represent the prediction that, when all grades are considered, girls on average earn higher grades and are less variable than boys, although there are more highly performing boys than girls at the upper end of the achievement distribution. b In non-STEM subjects, the difference in mean grades between girls and boys may be even more pronounced in favour of girls, which, coupled with similar variability, should result in many more highly performing girls than boys at the upper end of the achievement distribution. c In contrast, for STEM grades, we expected less difference between boys and girls mean grades and more grade variability for boys, resulting in boys dominating at both the top and bottom of the achievement distribution
Fig. 1 Predicted distributions of school grades of girls (red) and boys (blue). a The grade distribution overlaps represent the prediction that, when all grades are considered, girls on average earn higher grades and are less variable than boys, although there are more highly performing boys than girls at the upper end of the achievement distribution. b In non-STEM subjects, the difference in mean grades between girls and boys may be even more pronounced in favour of girls, which, coupled with similar variability, should result in many more highly performing girls than boys at the upper end of the achievement distribution. c In contrast, for STEM grades, we expected less difference between boys and girls mean grades and more grade variability for boys, resulting in boys dominating at both the top and bottom of the achievement distributionCC BY · PubMed Central
Fig. 2 Main meta-analytic results. Results of analyses on a ratios of the grade means, b ratios of grade variabilities, and c coefficients of variations for girls (red) and boys (blue). Diamonds and circles represent meta-analytic estimates of mean effect sizes, and their 95% confidence intervals are drawn as whiskers. In a, natural logarithm of response ratio (lnRR) represents the average difference between girls’ and boys’ mean grades; positive values of lnRR indicate lower boys’ mean grades. In b, natural logarithm coefficient of variation ratio (lnCVR) represents the average difference in grade variation between boys and girls; negative values of lnCVR indicate greater male variance. In c, natural logarithms of the coefficient of variation (lnCVs) are shown for boys and girls to illustrate grade variation by gender; more negative values of lnCV indicate less variation. Data and code for reproducing this figure are available at refs. 52,53
Fig. 2 Main meta-analytic results. Results of analyses on a ratios of the grade means, b ratios of grade variabilities, and c coefficients of variations for girls (red) and boys (blue). Diamonds and circles represent meta-analytic estimates of mean effect sizes, and their 95% confidence intervals are drawn as whiskers. In a, natural logarithm of response ratio (lnRR) represents the average difference between girls’ and boys’ mean grades; positive values of lnRR indicate lower boys’ mean grades. In b, natural logarithm coefficient of variation ratio (lnCVR) represents the average difference in grade variation between boys and girls; negative values of lnCVR indicate greater male variance. In c, natural logarithms of the coefficient of variation (lnCVs) are shown for boys and girls to illustrate grade variation by gender; more negative values of lnCV indicate less variation. Data and code for reproducing this figure are available at refs. 52,53CC BY · PubMed Central
Fig. 3 Inferred relative distributions of academic abilities of girls (red) and boys (blue). a STEM and b non-STEM school subjects, c the proportion of girls in each percentile. The relative mean and variance for each gender are based on the results of the meta-regression of school grades for school pupils, with subject as a moderator. In a and b, dashed vertical lines indicate cutoff points, above which 25%, 5% and 1% of top-scoring pupils can be found. The proportion of girls to boys across the distribution is shown in c, where values to the right on the x-axis correspond to the right tail of the achievement distributions. f:m values represent ratios of top-scoring girls to boys above each cutoff point (i.e, f:m > 1 = more females; f:m < 1 = more males). Data and code for reproducing this figure are available at refs. 52,53
Fig. 3 Inferred relative distributions of academic abilities of girls (red) and boys (blue). a STEM and b non-STEM school subjects, c the proportion of girls in each percentile. The relative mean and variance for each gender are based on the results of the meta-regression of school grades for school pupils, with subject as a moderator. In a and b, dashed vertical lines indicate cutoff points, above which 25%, 5% and 1% of top-scoring pupils can be found. The proportion of girls to boys across the distribution is shown in c, where values to the right on the x-axis correspond to the right tail of the achievement distributions. f:m values represent ratios of top-scoring girls to boys above each cutoff point (i.e, f:m > 1 = more females; f:m < 1 = more males). Data and code for reproducing this figure are available at refs. 52,53CC BY · PubMed Central
Fig. 4 PRISMA diagram showing the process of locating studies included in this meta-analysis. The full list of included studies, and the list of studies excluded at the stage of full-text screening, are available in Supplementary Data 1 and 2
Fig. 4 PRISMA diagram showing the process of locating studies included in this meta-analysis. The full list of included studies, and the list of studies excluded at the stage of full-text screening, are available in Supplementary Data 1 and 2CC BY · PubMed Central

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Research works printed but not linked: 2

  1. OECD. STEM workers receive a significant earnings premium over other workers with the same level of education: private wage and salary, workers aged 25 and over. https://doi.org/10.1787/eco_surveys-usa-2012-graph47-en (2012). · DOI
  2. Lackey, L. W. & Lackey, W. J. Grade inflation: potential causes and solutions. Int. J. Eng. Educ. 22, 130–139 (2006).

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Metadata

Authors
O’Dea, R. E., Lagisz, M., Jennions, M. D., & Nakagawa, S.
Affiliations
  • Australian National University (AU)
  • UNSW Sydney (AU)
Corresponding author
  • O’Dea, R. E.
  • Nakagawa, S.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2018-09-25
Volume
9
Issue
1
Pages
3777-3777
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-018-06292-0
PMC
PMC6156605
OpenAlex
W2890559011
Cited by
253
References
54
Citations by year
2026: 16 · 2025: 23 · 2024: 25 · 2023: 22 · 2022: 31 · 2021: 37 · 2020: 78 · 2019: 14 · 2018: 4
FWCI
66.07
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • ANU Open Research (Australian National University) (submittedVersion)
Topics
  • Social Sciences › Psychology › Applied Psychology › Career Development and Diversity
  • Social Sciences › Psychology › Developmental and Educational Psychology › Education, Achievement, and Giftedness
  • Social Sciences › Gender Studies › Gender and Technology in Education
Keywords
gender differences, student grades, individual differences, STEM careers, gender gap in science, variance, mean and variance, high-achieving students, girls' academic performance
MeSH terms
Academic Performance, Adolescent, Adult, Child, Engineering, Female, Humans, Male, Mathematics, Motivation, Sex Factors, Students, Technology, Models, Statistical, Sex Distribution, Young Adult, Datasets as Topic

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