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Working memory capacity and strategy use on the RAPM

Author

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  • Jarosz, Andrew F.
  • Raden, Megan J.
  • Wiley, Jennifer

Abstract

Despite many studies showing that high working memory capacity (WMC) individuals perform better on analytic reasoning and problem-solving tasks, the cognitive mechanisms underlying these relationships are still under debate. The present work explored the link between WMC and performance on a popular test of fluid intelligence (gF), the Raven's Advanced Progressive Matrices (RAPM; Raven, Raven, & Court, 1998), with the goal of assessing whether strategies might play a mediating role in the WMC and gF relationship. Using think-aloud protocols to assess strategies, it was determined that individual differences in strategy use on the RAPM partially mediated the relationship between WMC and performance. In addition, evidence suggested that participants decreased their use of constructive matching strategies as item difficulty increased. Finally, think-aloud protocols provided evidence for a third, hybrid strategy: isolate-and-eliminate. This new strategy goes beyond constructive matching and response elimination, utilizing aspects of each.

Suggested Citation

  • Jarosz, Andrew F. & Raden, Megan J. & Wiley, Jennifer, 2019. "Working memory capacity and strategy use on the RAPM," Intelligence, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:intell:v:77:y:2019:i:c:s0160289619301692
    DOI: 10.1016/j.intell.2019.101387
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    References listed on IDEAS

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    1. Jastrzębski, Jan & Ciechanowska, Iwona & Chuderski, Adam, 2018. "The strong link between fluid intelligence and working memory cannot be explained away by strategy use," Intelligence, Elsevier, vol. 66(C), pages 44-53.
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    Cited by:

    1. Jastrzębski, Jan & Ociepka, Michał & Chuderski, Adam, 2020. "Fluid reasoning is equivalent to relation processing," Intelligence, Elsevier, vol. 82(C).
    2. Li, Chenyu & Ren, Xuezhu & Schweizer, Karl & Wang, Tengfei, 2022. "Strategy use moderates the relation between working memory capacity and fluid intelligence: A combined approach," Intelligence, Elsevier, vol. 91(C).
    3. Liu, Yaohui & Zhan, Peida & Fu, Yanbin & Chen, Qipeng & Man, Kaiwen & Luo, Yikun, 2023. "Using a multi-strategy eye-tracking psychometric model to measure intelligence and identify cognitive strategy in Raven's advanced progressive matrices," Intelligence, Elsevier, vol. 100(C).
    4. Raden, Megan J. & Jarosz, Andrew F., 2022. "Strategy Transfer on Fluid Reasoning Tasks," Intelligence, Elsevier, vol. 91(C).

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