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Sex differences in tech tilt: Support for investment theories

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  • Coyle, Thomas R.

Abstract

This study examined sex differences in tech tilt, based on within-subject differences in technical abilities (e.g., mechanical and electrical) and academic abilities (math or verbal) on the Armed Services Vocational Aptitude Battery (ASVAB). The within-subject differences produced two types of tilt: tech tilt (tech > academic), indicating stronger technical abilities, and academic tilt (academic > tech), indicating stronger academic abilities. Tech tilt was correlated with math and verbal abilities on college aptitude tests (SAT, ACT, PSAT) and with jobs and college majors in STEM (science, technology, engineering, and math) and humanities. Males showed a tech tilt bias, and females showed an academic tilt bias. The tilt biases persisted after controlling for general intelligence (g). Tech tilt correlated negatively with academic abilities on the college aptitude tests (SAT, ACT, PSAT), with larger effects for females. In addition, relations of tech tilt with STEM jobs and majors were generally larger (and more often significant) for males, but only for tech tilt based on technical and verbal abilities. The negative relations of tech tilt with academic abilities on the college aptitude tests are consistent with investment theories, which predict that investment in one ability (technical) comes at the expense of competing abilities (academic). The sex differences in tech tilt and STEM support trait complexes involving abilities, interests, and vocational preferences (e.g., people versus things). Future research should examine whether spatial abilities and vocational interests mediate relations of tech tilt with sex and STEM criteria.

Suggested Citation

  • Coyle, Thomas R., 2020. "Sex differences in tech tilt: Support for investment theories," Intelligence, Elsevier, vol. 80(C).
    • Handle: RePEc:eee:intell:v:80:y:2020:i:c:s0160289620300155
    DOI: 10.1016/j.intell.2020.101437
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    References listed on IDEAS

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    1. Coyle, Thomas R., 2019. "Tech tilt predicts jobs, college majors, and specific abilities: Support for investment theories," Intelligence, Elsevier, vol. 75(C), pages 33-40.
    2. Coyle, Thomas R., 2018. "Non-g residuals of group factors predict ability tilt, college majors, and jobs: A non-g nexus," Intelligence, Elsevier, vol. 67(C), pages 19-25.
    3. Peter Arcidiacono & Esteban Aucejo & Ken Spenner, 2012. "What happens after enrollment? An analysis of the time path of racial differences in GPA and major choice," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 1(1), pages 1-24, December.
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    1. Coyle, Thomas R., 2022. "Sex differences in spatial and mechanical tilt: Support for investment theories," Intelligence, Elsevier, vol. 95(C).
    2. Becker, David & Coyle, Thomas R. & Minnigh, Tyler L. & Rindermann, Heiner, 2022. "International differences in math and science tilts: The stability, geography, and predictive power of tilt for economic criteria," Intelligence, Elsevier, vol. 92(C).
    3. Coyle, Thomas R., 2022. "Processing speed mediates the development of tech tilt and academic tilt in adolescence," Intelligence, Elsevier, vol. 94(C).
    4. Dunkel, Curtis S. & Madison, Guy, 2022. "The possible role of field independence/dependence on developmental sex differences in general intelligence," Intelligence, Elsevier, vol. 91(C).
    5. Li, Dai & Wang, Yizhen & Li, Lantian, 2023. "Educational choice has greater effects on sex ratios of college STEM majors than has the greater male variance in general intelligence (g)," Intelligence, Elsevier, vol. 96(C).
    6. Coyle, Thomas R., 2023. "Sex differences in tech tilt and academic tilt in adolescence: Processing speed mediates age-tilt relations," Intelligence, Elsevier, vol. 100(C).
    7. Coyle, Thomas R. & Greiff, Samuel, 2021. "The future of intelligence: The role of specific abilities," Intelligence, Elsevier, vol. 88(C).
    8. Coyle, Thomas R., 2021. "White-Black differences in tech tilt: Support for Spearman's law and investment theories," Intelligence, Elsevier, vol. 84(C).

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    Keywords

    Tech tilt; Ability tilt; STEM; ASVAB; SAT; ACT; PSAT;
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