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Tech tilt predicts jobs, college majors, and specific abilities: Support for investment theories

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  • Coyle, Thomas R.

Abstract

Specific cognitive abilities include ability tilt, based on within-subject differences in math and verbal scores on standardized tests (e.g., SAT, ACT). Ability tilt yields math tilt (math > verbal), which predicts STEM (science, technology, engineering, math) criteria, and verbal tilt (verbal > math), which predicts humanities criteria. The current study examined a new type of tilt: tech tilt, based on within-subject differences in technical scores and academic scores (math or verbal) on the Armed Services Vocational Aptitude Battery. (Technical scores tapped vocational skills for electronics, mechanics, cars, and tools.) The difference yielded two types of tilt: tech tilt (tech > academic) and academic tilt (academic > tech). Tech tilt was correlated with math and verbal scores on college aptitude tests (SAT, ACT, PSAT), ability tilt on the college tests, and STEM and humanities criteria (college majors and jobs). Tech tilt correlated negatively with academic abilities (math or verbal) on the college tests and predicted STEM criteria. In addition, academic tilt (math or verbal) predicted the analogous type of tilt on the college tests. The effects replicated using different analytical approaches (e.g., regressions and structural equation modeling) and after controlling for g. The negative effects of tech tilt with academic abilities support investment theories, which predict that investments in one domain (non-academic and technical) come at the expense of investments in competing domains (academic). In addition, the effects demonstrate the validity of vocational aptitudes, extending prior research on ability tilt, which focuses on academic aptitudes. Future research should consider factors that moderate the effects of tech tilt (e.g., life history and ability level) as well as other types of tilt (e.g., spatial tilt).

Suggested Citation

  • 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.
    • Handle: RePEc:eee:intell:v:75:y:2019:i:c:p:33-40
    DOI: 10.1016/j.intell.2019.04.002
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    References listed on IDEAS

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    1. 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.
    2. Lang, Jonas W. B. & Bliese, Paul D., 2012. "I–O Psychology and Progressive Research Programs on Intelligence," Industrial and Organizational Psychology, Cambridge University Press, vol. 5(2), pages 161-166, June.
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    Cited by:

    1. Coyle, Thomas R., 2022. "Sex differences in spatial and mechanical tilt: Support for investment theories," Intelligence, Elsevier, vol. 95(C).
    2. Coyle, Thomas R., 2020. "Sex differences in tech tilt: Support for investment theories," Intelligence, Elsevier, vol. 80(C).
    3. 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).
    4. 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).
    5. Coyle, Thomas R. & Greiff, Samuel, 2021. "The future of intelligence: The role of specific abilities," Intelligence, Elsevier, vol. 88(C).
    6. Coyle, Thomas R., 2021. "White-Black differences in tech tilt: Support for Spearman's law and investment theories," Intelligence, Elsevier, vol. 84(C).
    7. Coyle, Thomas R., 2022. "Processing speed mediates the development of tech tilt and academic tilt in adolescence," Intelligence, Elsevier, vol. 94(C).
    8. Wai, Jonathan & Lakin, Joni M. & Kell, Harrison J., 2022. "Specific cognitive aptitudes and gifted samples," Intelligence, Elsevier, vol. 92(C).

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