Humans are nature’s most intelligent and prolific users of external props and aids (such as written texts, slide-rules and software packages). Here we introduce a method for investigating how people make active use of their task environment during problem-solving and apply this approach to the non-verbal Raven Advanced Progressive Matrices test for fluid intelligence. We designed a click-and-drag version of the Raven test in which participants could create different external spatial configurations while solving the puzzles. In our first study, we observed that the click-and-drag test was better than the conventional static test at predicting academic achievement of university students. This pattern of results was partially replicated in a novel sample. Importantly, environment-altering actions were clustered in between periods of apparent inactivity, suggesting that problem-solvers were delicately balancing the execution of internal and external cognitive operations. We observed a systematic relationship between this critical phasic temporal signature and improved test performance. Our approach is widely applicable and offers an opportunity to quantitatively assess a powerful, although understudied, feature of human intelligence: our ability to use external objects, props and aids to solve complex problems.
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The routines/code that were used to perform the statistical analyses in this study are available from the corresponding author upon request. For the routine/code that was used for simulating the dual-mode and single-mode problem-solvers see Supplementary Code.
The data that support the findings of this study are available from the corresponding author upon request.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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The authors received no specific funding for this work. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
Supplementary Methods, Supplementary Results, Supplementary Tables 1 and 2, Supplementary Note, Supplementary Figs 1–10, and Supplementary References
An explanation of how the Supplementary Code can be run.
An excel file that allows simulations of the data, noted in the SI and described in the SI Guide.