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Processing speed mediates the development of tech tilt and academic tilt in adolescence

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  • Coyle, Thomas R.

Abstract

Tilt represents a pattern of specific abilities and is based on within subject differences between two abilities, indicating strength in one ability (e.g., technical) and weakness in another ability (e.g., academic). The current study examined age differences in tilt, processing speed, and general intelligence (g) in adolescence for 13- to 17-year-olds. Tilt was measured using the Armed Services Vocational Aptitude Battery and was based on differences in technical (mechanical and electrical) and academic abilities (math or verbal). These differences yielded tech tilt (technical > academic) and academic tilt (academic > technical). Older ages correlated with greater tech tilt and academic tilt and with faster processing speed. In addition, processing speed strongly mediated age-tilt relations. The mediating effects of processing speed (on age-tilt relations) were partly related to g. The results supported investment theories, which assume that age-related increases in speed accelerate the acquisition of specific abilities that produce tilt. Adding g to the model supported cascade theories, which assume that age-related increases in speed boost general abilities (e.g., g), which in turn accelerate the acquisition of specific abilities related to tilt. Future research should examine different types of tilt and factors that influence tilt such as developmental period and ability specialization.

Suggested Citation

  • Coyle, Thomas R., 2022. "Processing speed mediates the development of tech tilt and academic tilt in adolescence," Intelligence, Elsevier, vol. 94(C).
    • Handle: RePEc:eee:intell:v:94:y:2022:i:c:s0160289622000290
    DOI: 10.1016/j.intell.2022.101648
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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., 2020. "Sex differences in tech tilt: Support for investment theories," Intelligence, Elsevier, vol. 80(C).
    3. Blum, Diego & Holling, Heinz, 2017. "Spearman's law of diminishing returns. A meta-analysis," Intelligence, Elsevier, vol. 65(C), pages 60-66.
    4. Coyle, Thomas R., 2021. "White-Black differences in tech tilt: Support for Spearman's law and investment theories," Intelligence, Elsevier, vol. 84(C).
    5. Tourva, Anna & Spanoudis, George, 2020. "Speed of processing, control of processing, working memory and crystallized and fluid intelligence: Evidence for a developmental cascade," Intelligence, Elsevier, vol. 83(C).
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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., 2023. "Sex differences in tech tilt and academic tilt in adolescence: Processing speed mediates age-tilt relations," Intelligence, Elsevier, vol. 100(C).
    3. Coyle, Thomas R. & Greiff, Samuel, 2023. "Carbon is to life as g is to _____: A review of the contributions to the special issue on specific abilities in intelligence," Intelligence, Elsevier, vol. 101(C).

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