Normative data for 144 compound remote associate problems
Open accessAbstract
We have developed and tested 144 compound remote associate problems. Across eight experiments, 289 participants were given four time limits (2 sec, 7 sec, 15 sec, or 30 sec) for solving each problem. This paper provides a brief overview of the problems and normative data regarding the percentage of participants solving, and mean time-to-solution for, each problem at each time limit. These normative data can be used in selecting problems on the basis of difficulty or mean time necessary for reaching a solution.
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The RAT dataset from Bowden and Jung-Beeman is widely used.
“For the Remote Associates Test (RAT), we employed a widely-used dataset from Bowden and Jung-Beeman [11].”
From Human Creativity in the Age of LLMs: Randomized Experiments on Divergent and Convergent Thinking (2025) · cites this paper as [11]
The Abstract (page not available in our copy) says Bowden and Jung-Beeman developed 144 RAT-like problems and made them available with normative data, supporting the identification of the dataset. It describes RAT and RAT-like problems as used in many studies, but does not establish that their particular dataset was already widely used. (LLM, conf=0.84)
Experimental — accuracy not yet measuredConvergent thinking involves narrowing down possibilities to find a single correct solution.
“convergent thinking involves narrowing down these possibilities to find a single correct solution [11, 12, 13, 60].”
From Decoupling of Usefulness and Novelty: Evaluating the Impact of Generative AI on Design Outputs and Novice Designers' Creative Thinking (2026) · cites this paper as [13]
The Results and Discussion section says each compound remote associate problem has a single-word, unambiguous solution, supporting the single-solution part of the claim. The paper does not define convergent thinking or say that it involves narrowing down possibilities. (LLM, conf=0.82)
Experimental — accuracy not yet measured
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Exploring the Effect of Red and Blue on Cognitive Task Performances
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- Authors
- Bowden, E. M., & Jung-Beeman, M.
- Affiliations
- Northwestern University (US)
- Corresponding author
- Bowden, Edward M.
- Venue
- Behavior Research Methods, Instruments, & Computers
- Published
- 2003-11
- Volume
- 35
- Issue
- 4
- Pages
- 634-639
- ISSN
- 0743-3808 (ISSN-L)
- 1532-5970
- OpenAlex
- W2013214147
- Cited by
- 649
- References
- 21
- Citations by year
- 2026: 26 · 2025: 36 · 2024: 38 · 2023: 48 · 2022: 40 · 2021: 50 · 2020: 37 · 2019: 50 · 2018: 56 · 2017: 35 · 2016: 41 · 2015: 37 · 2014: 34 · 2013: 31 · 2012: 23
- FWCI
- 2.85
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Behavior Research Methods, Instruments, & Computers (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Creativity in Education and Neuroscience
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Social Sciences › Psychology › Applied Psychology › Psychological Testing and Assessment
- Keywords
- reference values, solution time, problem difficulty, problem selection, divergent thinking, creative problem solving
- MeSH terms
- Association Learning, Humans, Problem Solving, Reference Values, Time Factors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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