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Abstract

To investigate individual differences in creativity as measured with a complex problem-solving task, we developed a computational model of the remote associates test (RAT). For 50 years, the RAT has been used to measure creativity. Each RAT question presents three cue words that are linked by a fourth word, which is the correct answer. We hypothesized that individuals perform poorly on the RAT when they are biased to consider high-frequency candidate answers. To assess this hypothesis, we tested individuals with 48 RAT questions and required speeded responding to encourage guessing. Results supported our hypothesis. We generated a norm-based model of the RAT using a high-dimensional semantic space, and this model accurately identified correct answers. A frequency-biased model that included different levels of bias for high-frequency candidate answers explained variance for both correct and incorrect responses. Providing new insight into the nature of creativity, the model explains why some RAT questions are more difficult than others, and why some people perform better than others on the RAT.

Keywords

remote associates test word frequency creativity word association individual differences associative processes language semantic memory

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References

Bowden

E. M.

Jung-Beeman

(2003). Normative data for 144 compound remote associate problems. Behavior Research Methods, Instruments, & Computers, 35, 634–639.

Bowers

K. S.

Regehr

Balthazard

Parker

(1990). Intuition in the context of discovery. Cognitive Psychology, 22, 72–110.

Cai

D. J.

Mednick

S. A.

Harrison

E. M.

Kanady

J. C.

Mednick

S. C.

(2009). REM, not incubation, improves creativity by priming associative networks. Proceedings of the National Academy of Sciences, USA, 106, 10130–10134.

Fodor

E. M.

(1999). Subclinical inclination toward manic-depression and creative performance on the Remote Associates Test. Personality and Individual Differences, 27, 1273–1283.

Forbach

G. B.

Evans

R. G.

(1981). The Remote Associates Test as a predictor of productivity in brainstorming groups. Applied Psychological Measurement, 5, 333–339.

Griffiths

T. L.

Steyvers

Firl

(2007). Google and the mind: Predicting fluency with PageRank. Psychological Science, 18, 1069–1076.

Harkins

S. G.

(2006). Mere effort as the mediator of the evaluation-performance relationship. Journal of Personality and Social Psychology, 91, 436–455.

Isen

A. M.

Daubman

K. A.

Nowicki

G. P.

(1987). Positive affect facilitates creative problem-solving. Journal of Personality and Social Psychology, 52, 1122–1131.

Kray

L. J.

Galinsky

A. D.

Wong

E. M.

(2006). Thinking within the box: The relational processing style elicited by counterfactual mind-sets. Journal of Personality and Social Psychology, 91, 33–48.

10.

Kucera

Francis

W. N.

(1967). Computational analysis of present day American English. Providence, RI: Brown University Press.

11.

Landauer

T. K.

Dumais

S. T.

(1997). A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review, 104, 211–240.

12.

Mednick

M. T.

Andrews

F. M.

(1967). Creative thinking and level of intelligence. Journal of Creative Behavior, 1, 428–431.

13.

Mednick

S. A.

(1962). The associative basis of the creative process. Psychological Review, 69, 220–232.

14.

Nelson

D. L.

McEvoy

C. L.

Schreiber

T. A.

(1998). The University of South Florida word association, rhyme and word fragment norms, 1999. Retrieved from http://w3.usf.edu/FreeAssociation/

15.

Roberts

Pashler

(2000). How persuasive is a good fit? A comment on theory testing. Psychological Review, 107, 358–367.

16.

Sitton

S. C.

Pierce

E. R.

(2004). Synesthesia, creativity and puns. Psychological Reports, 95, 577–580.

17.

Steyvers

Shiffrin

R. M.

Nelson

D. L.

(2004). Word association spaces for predicting semantic similarity effects in episodic memory. In Healy

A. F.

(Ed.), Experimental cognitive psychology and its applications (pp. 237–249). Washington, DC: American Psychological Association.

18.

Topolinski

Reber

(2010). Gaining insight into the “aha” experience. Current Directions in Psychological Science, 19, 402–405.

19.

Topolinski

Strack

(2008). Where there’s a will—there’s no intuition: The unintentional basis of semantic coherence judgments. Journal of Memory and Language, 58, 1032–1048.

20.

Topolinski

Strack

(2009). Scanning the “fringe” of consciousness: What is felt and what is not felt in intuitions about semantic coherence. Consciousness and Cognition, 18, 608–618.

21.

Vul

Pashler

(2007). Incubation benefits only after people have been misdirected. Memory & Cognition, 35, 701–710.

22.

Ward

Thompson-Lake

Ely

Kaminski

(2008). Synaesthesia, creativity and art: What is the link? British Journal of Psychology, 99, 127–141.

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The Road Not Taken

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