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Should students be smart, curious, or both? Fluid intelligence, openness, and interest co-shape the acquisition of reading and math competence

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  • Lechner, Clemens M.
  • Miyamoto, Ai
  • Knopf, Thomas

Abstract

Developmental theories of intelligence in the tradition of Cattell's investment theory posit that gains in crystallized intelligence (gc) depend mainly on fluid intelligence (gf) but also on a range of so-called intellectual investment traits, such as Openness to Experience and interest in a subject area. However, the relative predictive power of, and the precise nature of the interplay between, gf and different intellectual investment traits remains incompletely understood. In this study, we use large-scale, multi-wave data on secondary school students from the German National Educational Panel Study (NEPS; N = 4646) to investigate how gf, Openness, and subject-specific interest relate to baseline levels and change over two years in gc in two domains, reading and math. Results of latent-variable models revealed that gf and interest, and to a lesser extent, Openness, predicted higher initial levels and stronger gains over two years in reading competence and mathematical competence. Moreover, results yielded strong support for the notion that gf interacts synergistically with interest in reading and math in producing (gains in) reading competence and mathematical competence. In other words, gf and interest cross-fertilize each other, with students who have both high gf and high interest showing the highest rate of skill and knowledge acquisition. Our findings contribute to developmental theories of intelligence by providing further support for the claim that gf and intellectual investment traits are both essential for the development of gc—and by showing that the interplay between gc and investment traits is interactive and synergistic in nature.

Suggested Citation

  • Lechner, Clemens M. & Miyamoto, Ai & Knopf, Thomas, 2019. "Should students be smart, curious, or both? Fluid intelligence, openness, and interest co-shape the acquisition of reading and math competence," Intelligence, Elsevier, vol. 76(C), pages 1-1.
    • Handle: RePEc:eee:intell:v:76:y:2019:i:c:4
    DOI: 10.1016/j.intell.2019.101378
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    References listed on IDEAS

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    1. Andreas Klein & Helfried Moosbrugger, 2000. "Maximum likelihood estimation of latent interaction effects with the LMS method," Psychometrika, Springer;The Psychometric Society, vol. 65(4), pages 457-474, December.
    2. O'Connell, Michael, 2018. "The power of cognitive ability in explaining educational test performance, relative to other ostensible contenders," Intelligence, Elsevier, vol. 66(C), pages 122-127.
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    1. Saß, Steffani & Schütte, Kerstin & Kampa, Nele & Köller, Olaf, 2021. "Continuous time models support the reciprocal relations between academic achievement and fluid intelligence over the course of a school year," Intelligence, Elsevier, vol. 87(C).
    2. Laible, Marie-Christine & Anger, Silke & Baumann, Martina, 2020. "Personality Traits and Further Training," IAB-Discussion Paper 202034, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

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