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On the dimensionality of crystallized intelligence: A smartphone-based assessment

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  • Steger, Diana
  • Schroeders, Ulrich
  • Wilhelm, Oliver

Abstract

Crystallized intelligence (gc) is a prominent factor in consensual theories on the structure of intelligence. Although declarative knowledge is arguably a core aspect of gc, little is known about the dimensionality of knowledge in adults; the proposed dimensional models vary broadly from unidimensionality, to three-dimensional models (science, humanities, and civics), to a six-dimensional model with an overarching g-factor. While previous studies were mostly based on narrow item samples once administered to a specific sample within a restricted time frame, we used a smartphone-based approach to investigate the dimensionality of knowledge based on a large set of items administered to a heterogeneous sample. More specifically, questions were randomly drawn from a pool of 4050 items from 34 subject domains such as chemistry, arts, and politics and administered to an age- and ability-heterogeneous sample of 1117 participants. We calculated Weighted Likelihood Estimates separately for each domain and then estimated a series of principal component analyses with increasing number of factors. The component solution at different levels match models reported in previous studies on the dimensionality of knowledge. We conclude that the dimensionality of declarative knowledge highly depends on the item and person sample. Finally, we discuss different approaches to model gc, give advice on the measurement of gc in general and discuss weaknesses and strengths of mobile assessments.

Suggested Citation

  • Steger, Diana & Schroeders, Ulrich & Wilhelm, Oliver, 2019. "On the dimensionality of crystallized intelligence: A smartphone-based assessment," Intelligence, Elsevier, vol. 72(C), pages 76-85.
  • Handle: RePEc:eee:intell:v:72:y:2019:i:c:p:76-85
    DOI: 10.1016/j.intell.2018.12.002
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    References listed on IDEAS

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    1. Ulrich Schroeders & Oliver Wilhelm & Gabriel Olaru, 2016. "Meta-Heuristics in Short Scale Construction: Ant Colony Optimization and Genetic Algorithm," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-19, November.
    2. Hartung, Johanna & Doebler, Philipp & Schroeders, Ulrich & Wilhelm, Oliver, 2018. "Dedifferentiation and differentiation of intelligence in adults across age and years of education," Intelligence, Elsevier, vol. 69(C), pages 37-49.
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    4. Do, Ben-Roy, 2009. "Research on Unproctored Internet Testing," Industrial and Organizational Psychology, Cambridge University Press, vol. 2(1), pages 49-51, March.
    5. Joseph Henrich & Steve J. Heine & Ara Norenzayan, 2010. "The Weirdest People in the World?," RatSWD Working Papers 139, German Data Forum (RatSWD).
    6. Thomas Warm, 1989. "Weighted likelihood estimation of ability in item response theory," Psychometrika, Springer;The Psychometric Society, vol. 54(3), pages 427-450, September.
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    Cited by:

    1. Goecke, B. & Weiss, S. & Steger, D. & Schroeders, U. & Wilhelm, O., 2020. "Testing competing claims about overclaiming," Intelligence, Elsevier, vol. 81(C).
    2. Rozgonjuk, Dmitri & Schmitz, Florian & Kannen, Christopher & Montag, Christian, 2021. "Cognitive ability and personality: Testing broad to nuanced associations with a smartphone app," Intelligence, Elsevier, vol. 88(C).
    3. Schroeders, Ulrich & Watrin, Luc & Wilhelm, Oliver, 2021. "Age-related nuances in knowledge assessment," Intelligence, Elsevier, vol. 85(C).

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