Creativity and fluid intelligence

 

Finally, Brazilians take the stage, in the form of Paulistano Ricardo Primi, who gives a creative take on creativity, looking at the difficult-to-measure genre of figural drawing. Brazil needs to figure more in international intelligence research, particularly on the large matter of genetic differences, since Brazil’s history is very different from that of the US, and the contrast can provide a test of cultural explanations for black/white intelligence differences. That bigger project will have to wait, but here is what they have done on their drawing task, also using Bootstrap to test model fit.

 

CREATIVITY AND FLUID INTELLIGENCE: MIXTURE GROWTH MODELING OF INTRA INDIVIDUAL PATTERNS OF PERFORMANCE DURING A DIVERGENT THINKING TASK OF FIGURAL DRAWING

Ricardo Primi 1 , Nelson Hauck-Filho 1 , Tatiana de Cássia Nakano 2

1 Universidade São Francisco, rprimi@mac.com.

2 PUC-Campinas.

https://www.researchgate.net/profile/Ricardo_Primi

 

This study examines the association of fluid intelligence and creativity. In divergent thinking tests it is common to observe that later responses tend to be more creative than earlier ones – this is called serial order effect. Recent view of the role of executive function on divergent production predicts that high fluid intelligence subjects will have creative responses already in the beginning of divergent thinking tasks. This indicates a central role of executive functions –inhibiting common less creative responses and management interference on idea production.

Most studies observing these relationships are done in verbal tasks. This research tests if this relationship can be found on divergent productions of figural drawings. Participants in the present study were 585 children and high school students with ages from 7 to 17 (mean = 11.11 years, SD = 2.02; 52.5% female). All participants provided demographic information on a self-report questionnaire, and undertook a cognitive assessment battery (verbal, abstract, logic and numeric reasoning) supplemented by a creativity task, whose data we analyzed in the present study.

This creativity task consisted of 10 stimuli, which participants were required to complete using paper and pencil. Independent raters subsequently coded each resulting drawing in a scale from 1 to 5 to reflect the extent to which it approached a set of criteria defining creative responses. Data analysis was conducted using Mplus 7.11. Factor growth mixture modelling were performed in order to detect groups of potentially differing patterns of performance (ratings) from the first to the last stimulus of the task.

Bayesian Information Criterion (BIC) and the Bootstrap Likelihood Ratio Test (BLRT) suggested that a three-class solution was a better fit to the data (entropy = .77) when compared to alternative 1-, 2-, and 4-class solutions. Latent classes revealed a large group (83.36%) of individuals with initially modest scores and descending performances along the 10 stimuli, as well as two small groups of individuals with high initial scores—one (12.52%) with a descending performance, and the other (4.12%) with a stable high performance across the whole task.

Last two groups have significantly higher scores in Gf. This study shows that executive processes of top down voluntary control are important components for production of creative responses. This demonstrates a higher role of intelligence on creative idea production. It shows a high role of fluid intelligence in idea production.