The question brings us back to the main problem identified
in our previous blog on creativity, namely how to measure it? Although both constructs, intelligence and creativity, lack a widely accepted definition, we have valid and reliable tests
of intelligence, which on the other hand
do not exist for creativity. This must be kept in mind when reviewing the intelligence
– creativity relationship.
Theoretical background
The interpretation and explanation of the creativity-intelligence relationship mainly depends
on the research area scholars are coming from. Intelligence researchers usually
consider creative cognition simply as part of their intelligence model. Even Guilford, who is
considered the initiator of modern creativity research, placed
creativity within the broad range of subcomponents of intelligence. In the structure-of-intellect
(SOI) morphological model of
intelligence, divergent thinking is just one of the operations proposed
(Guilford, 1967).
Guilford’s theory never had a major influence on
intelligence research. But even in models that have emerged during the past decades and are regarded as
the consensus psychometric-based models for understanding the structure of
human intelligence, the Cattell–Horn Gf–Gc and the Carroll Three-Stratum model
(McGrew, 2009), creativity is seen as one of the second and first stratum
factors. Figure 1 shows the factors
that contribute to creativity in the Cattell–Horn–Carroll (CHC) theory of cognitive
abilities, which represents a broad umbrella term for a synthesis of
the two models. The broad factors of fluid reasoning (Gf) and long-term storage and retrieval (Glr) are seen as main components of creative cognition. Gf is defined as the use of mental operations to solve novel problems that
cannot be performed automatically. Drawing inferences,
generating and testing hypothesis, problem solving, extrapolating, and
transforming information, inductive and
deductive reasoning are of central importance in this process. Glr (also dubbed TSR, Glm and Gr – broad retrieval ability) refers to the ability to store
and consolidate new information in long-term memory and later fluently retrieve
it. The most prominent narrow abilities related to creativity are: Ideational fluency (FI), Associational fluency (FA),
Expressional fluency (FE), Word
fluency (FW), Figural fluency (FF), Figural flexibility (FX), Sensitivity to problems (SP), Originality/creativity (FO).
Figure 1. Schematic representation of creativity
related factors in the integrated Cattell–Horn–Carroll (CHC) model of human
cognitive abilities. Gf = fluid reasoning (intelligence); Glr (Gr,TSR, Glm) =
Long-term storage and retrieval; GR = deductive reasoning; I = induction; RQ =
Quantitative reasoning, RP = Piagetian reasoning; RE = speed of reasoning; MA =
associative memory; MM = meaningful memory; M6 = Free-recall memory; FI =
ideational fluency, FA = associational fluency; FE = expressional fluency; N =
naming facility; FW = word fluency; FF = figural fluency; FX = figural
flexibility; SP = sensitivity to problems; FO = originality/creativity; L1 =
learning abilities.
On the other hand, creativity researchers have postulated
that intelligence and creativity are independent psychological phenomena (e.g.,
Torrance, 1972; Wallach and Kogan, 1965). Such radical positions always require explanations, hence they provide opportunities for new theories, some of which are are difficult to test using empirical methods.
Sternberg (2012) for example proposed that creativity is a
habit that can be explained in a theoretical framework of investment. The idea
is to buy low and sell high in the realm of ideas. Creative individuals have
the ability to pick up ideas that are unknown or have been abandoned, but have the potential to grow,
they transform them and make them attractive
for a broad community – the consumers. In that way they acquire a creative
habit. This process requires six distinct but interrelated resources:
intellectual abilities, knowledge, styles of thinking, personality, motivation,
and environment. The most important intellectual skills are the analytic
ability to see problems and to see which ideas are potentially worth pursuing
and a practical ability to sell the ideas to the consumers. The theory is
rather broad and it is difficult verify it using a psychometric approach.
Most often the intelligence-creativity relation was
explained by the threshold hypothesis, which assumes that above-average
intelligence represents a necessary condition for high-level creativity. Hence,
stronger average associations between intelligence and creativity should be observed
among less intelligent individuals than among more intelligent ones (Guilford,
1967). Creativity scholars perceived this relation as an argument for the distinctiveness
of both constructs – intelligence and creativity (Karwowski et al., 2016). However,
such relationships (lower correlations at higher ability levels) are not new
in intelligence research. They correspond with Spearman’s (1927) law of diminishing returns (SLODR), which predicts that the g factor will
account for a smaller proportion of individual differences in cognitive tests
scores at higher levels of ability because its structure is more differentiated
and g is a weaker contributor to cognitive performance. However when applying
contemporary methods (non-linear g-loadings, or skewed g assumptions) to test SLODR, the obtained results are not as straightforward as with more traditional (splitting) methods. The obtained
findings call into question the empirical support for SLODR (Murray et al.,
2013).
Recent research
The easiest way to show that the constructs of intelligence and creativity are independent is by correlating tests of intelligence with
creativity tests. The review papers by Kim (2005) and by Batey and Furnham
(2006) showed that the correlations are small and heterogeneous. Kim in his
analysis included 447 correlation coefficients from 21 studies and 45,880
participants. The mean correlation coefficient was r = .174 (95% CI = .165 –
.183). Another finding was that the correlation coefficients were extremely heterogeneous: Q(446) = 937.058, p < .0001. With respect to the threshold theory no
significant differences in correlations between those with an IQ greater or
lower than 120 points were observed (.201 versus .234). The analysis of
moderator variables revealed significant differences related to the tests used
to measure creativity and intelligence, creativity subscales (originality,
fluency, flexibility and figural redefinition), whereas no differences were
observed with respect to sex, verbal/nonverbal tests and IQ levels (IQ below
100, between 100 – 120, 120 –135 and above 135). The authors concluded that: “…the negligible relationship between
creativity and IQ scores indicates that even students with low IQ scores can be
creative” (Kim, 2005, p. 65). A similar conclusion, suggesting a dichotomy
between creativity and intelligence, was also put forward in the review by
Batey and Furnham (2006).
Recent research employing more sophisticated methodology and
analysis but also different theoretical paradigms has tried to further
elucidate the intelligence-creativity relation. Jauk et al. (2013) tested the threshold
theory in a sample of 297 participants by means of segmented regression
analysis. This method allows for the detection of a threshold in continuous data.
Thresholds of creative potential varied as a function of criteria: for a more
easy criterion of ideational originality (i.e., two original ideas) the threshold was around 100 IQ points, whereas a threshold of 120 IQ points emerged
when the criterion was more demanding (i.e., many original ideas). A threshold around 85 IQ points was found for a purely quantitative
measure of creative potential (i.e., ideational fluency). The authors concluded
that their study confirmed the threshold hypothesis for the creativity –
intelligence relationship and further showed that this relation depends on the
applied measure of creative potential. A similar finding was reported by Karwowski
et al. (2016), who tested the threshold
hypothesis with the necessary condition
analysis. The author concluded that intelligence is necessary but not sufficient for creative
cognition. Further support for the threshold theory of creativity was provided by a magnetic
resonance spectroscopy study by Jung et al. (2009). However, the results must
be taken with caution given the diversity of findings reported in a meta-analyses
of neuroimaging studies on creativity. The authors related the concentration of
the N-acetyl-aspartate (NAA) neurometabolite with measures of
creativity. Different patterns of correlations between NAA and a composite
creativity index (ratings provided by independent judges) were found in higher
verbal ability versus lower verbal ability participants. Another shortcoming of
the study is that verbal ability can be regarded as a measure of crystalized
intelligence but not fluid intelligence, which was used as the indicator of
intelligence in the previously mentioned studies.
A different strand of research focused on the possibility to
investigate components of executive functioning in relation to fluid
intelligence and creativity. Nusbaum and Silvia (2011) for instance showed that
the creativity-intelligence relationship was moderated by executive switching
(how often people switched from one idea category to a new idea) and clustering
(how many uses are in a category). A latent variable analysis showed that
intelligence significantly predicted
switching – more intelligent individuals made significantly more category
changes but they didn't have more ideas per category. Furthermore, more
intelligent individuals when provided with an effective strategy for an unusual uses task performed better than
those of average intelligence. The authors concluded: “…that divergent thinking is more convergent than modern creativity
theories presume” (Nusbaum and Silvia, 2011, p. 36).
In yet another study by Benedek et al. (2014), the executive
abilities of updating, shifting, and inhibition were related to intelligence
and creativity within a latent variable model approach. The main findings were
that intelligence was predicted by updating, whereas creativity was predicted
by updating and inhibition. The authors suggested that updating is the central
mechanism underlying the correlation of intelligence and creativity.
It seems that recent research suggests that models of
intelligence such as the CHC, which
regard creativity as a subcomponent of intelligence,
might be a more adequate approach to study creativity – at least from a
psychometric perspective.
References
Batey, M., &
Furnham, A. (2006). Creativity, Intelligence, and Personality: A Critical
Review of the Scattered Literature. Genetic, Social, and General Psychology
Monographs, 132(4), 355–429. https://doi.org/10.3200/MONO.132.4.355-430
Benedek, M.,
Jauk, E., Sommer, M., Arendasy, M., & Neubauer, A. C. (2014). Intelligence,
creativity, and cognitive control: The common and differential involvement of
executive functions in intelligence and creativity. Intelligence, 46, 73–83. https://doi.org/10.1016/j.intell.2014.05.007
Guilford, J. P. (1967). The nature of human intelligence.
New York: McGraw-Hill.
Jauk, E.,
Benedek, M., Dunst, B., & Neubauer, A. C. (2013). The relationship between
intelligence and creativity: New support for the threshold hypothesis by means
of empirical breakpoint detection. Intelligence, 41(4), 212–221.
https://doi.org/10.1016/j.intell.2013.03.003
Jung, R. E., Gasparovic,
C., Chavez, R. S., Flores, R. A., Smith, S. M., Caprihan, A., & Yeo, R. A.
(2009). Biochemical Support for the “Threshold” Theory of Creativity: A
Magnetic Resonance Spectroscopy Study. Journal of Neuroscience, 29(16),
5319–5325. https://doi.org/10.1523/JNEUROSCI.0588-09.2009
Karwowski, M.,
Dul, J., Gralewski, J., Jauk, E., Jankowska, D. M., Gajda, A., … Benedek, M.
(2016). Is creativity without intelligence possible? A Necessary Condition
Analysis. Intelligence, 57, 105–117. https://doi.org/10.1016/j.intell.2016.04.006
Kim, K. H. (2005). Can only intelligent people be creative? Journal of Secondary Gifted
Education, 16, 57−66.
McGrew, K. S.
(2009). CHC theory and the human cognitive abilities project: Standing on the
shoulders of the giants of psychometric intelligence research. Intelligence,
37(1), 1–10. https://doi.org/10.1016/j.intell.2008.08.004
Murray, A. L.,
Dixon, H., & Johnson, W. (2013). Spearman’s law of diminishing returns: A
statistical artifact? Intelligence, 41(5), 439–451.
https://doi.org/10.1016/j.intell.2013.06.007
Nusbaum, E. C.,
& Silvia, P. J. (2011). Are intelligence and creativity really so
different?☆Fluid intelligence, executive processes,
and strategy use in divergent thinking. Intelligence, 39(1), 36–45. https://doi.org/10.1016/j.intell.2010.11.002
Sternberg, R. J.
(2012). The Assessment of Creativity: An Investment-Based Approach. Creativity
Research Journal, 24(1), 3–12. https://doi.org/10.1080/10400419.2012.652925
Torrance, E.
(1972). Can we teach children to think creatively? Journal of Creative Behaviour,
6, 114–143.
Wallach, M. A.,
& Kogan, N. (1965). Modes of thinking in young children: A study of the creativity-intelligence
distinction. New York: Holt, Rinehart, & Winston.
Hi I have read your post and i think it's useful.Thanks for the sharing this website. it is very useful professional knowledge.
ReplyDeletehttps://blog.mindvalley.com/fluid-reasoning/
Free from Herpes just in 2 weeks
ReplyDeleteThe best herbal remedy
You can contact him
r.buckler11 {{@gmail}} com,, .......
Good bless
ReplyDeleteIntelligence can certainly be an asset in various pursuits, but it's not the sole determining factor for success or achievement. How File Parse Many factors, including creativity, perseverance, emotional intelligence, and practical skills, also contribute to a person's ability to excel in their chosen field.
ReplyDelete