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To predict the future, consider the past: Revisiting Carroll (1993) as a guide to the future of intelligence research

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  • Wilhelm, Oliver
  • Kyllonen, Patrick

Abstract

There is a widely held consensus in the field of intelligence research that the broad factors identified by Cattell, Horn, and Carroll are an adequate summary of individual differences in human cognitive abilities. Most researchers would agree that the redundancy among these factors is best accounted for by an overarching general factor. We think the best way to acknowledge major accomplishments is to build upon them with the goal to challenge the status quo. Here we want to do so by discussing six broad ability factors that are either considered in Carroll's epochal book or could be candidates for future inclusions to the list of established cognitive ability factors: fluid intelligence, crystallized intelligence, cognitive speed, creativity, social and emotional intelligence, and collaborative problem solving. We conclude with four pleas: reunite correlational and experimental research, enrich construct interpretations, reunite educational and psychological measurement of maximal cognitive effort, and reconsider the sampling of indicators and content validity.

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  • Wilhelm, Oliver & Kyllonen, Patrick, 2021. "To predict the future, consider the past: Revisiting Carroll (1993) as a guide to the future of intelligence research," Intelligence, Elsevier, vol. 89(C).
    • Handle: RePEc:eee:intell:v:89:y:2021:i:c:s0160289621000696
    DOI: 10.1016/j.intell.2021.101585
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    References listed on IDEAS

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    1. Wim van der Linden, 2007. "A Hierarchical Framework for Modeling Speed and Accuracy on Test Items," Psychometrika, Springer;The Psychometric Society, vol. 72(3), pages 287-308, September.
    2. Chuderski, Adam, 2019. "Even a single trivial binding of information is critical for fluid intelligence," Intelligence, Elsevier, vol. 77(C).
    3. Karl Holzinger & Frances Swineford, 1937. "The Bi-factor method," Psychometrika, Springer;The Psychometric Society, vol. 2(1), pages 41-54, March.
    4. Borghans, L. & Golsteyn, B.H.H. & Heckman, James & Humphries, John Eric, 2011. "Identification problems in personality psychology," Research Memorandum 025, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    5. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    6. Ben Weidmann & David J. Deming, 2021. "Team Players: How Social Skills Improve Team Performance," Econometrica, Econometric Society, vol. 89(6), pages 2637-2657, November.
    7. Jeffrey Mo, 2017. "Collaborative problem solving," PISA in Focus 78, OECD Publishing.
    8. Christoph Riedl & Young Ji Kim & Pranav Gupta & Thomas W. Malone & Anita Williams Woolley, 2021. "Quantifying collective intelligence in human groups," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(21), pages 2005737118-, May.
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    Cited by:

    1. Walker, Dana L. & Palermo, Romina & Callis, Zoe & Gignac, Gilles E., 2023. "The association between intelligence and face processing abilities: A conceptual and meta-analytic review," Intelligence, Elsevier, vol. 96(C).
    2. Feraco, Tommaso & Cona, Giorgia, 2022. "Differentiation of general and specific abilities in intelligence. A bifactor study of age and gender differentiation in 8- to 19-year-olds," Intelligence, Elsevier, vol. 94(C).
    3. Procopio, Francesca & Zhou, Quan & Wang, Ziye & Gidziela, Agnieska & Rimfeld, Kaili & Malanchini, Margherita & Plomin, Robert, 2022. "The genetics of specific cognitive abilities," Intelligence, Elsevier, vol. 95(C).
    4. Haier, Richard J., 2021. "Are we thinking big enough about the road ahead? Overview of the special issue on the future of intelligence research," Intelligence, Elsevier, vol. 89(C).
    5. Callis, Zoe & Gerrans, Paul & Walker, Dana L. & Gignac, Gilles E., 2023. "The association between intelligence and financial literacy: A conceptual and meta-analytic review," Intelligence, Elsevier, vol. 100(C).

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