ArticlePDF Available

Why Creativity Isn’t in IQ Tests, Why it Matters, and Why it Won’t Change Anytime Soon Probably



Creativity is a part of most theories of intelligence—sometimes a small part and sometimes a large part. Yet even IQ tests that assess aspects of intelligence that supposedly reflect creative abilities do not actually measure creativity. Recent work has argued that intelligence and creativity are more conceptually related than we have thought. In addition, creativity offers a potential way to counter issues of test bias from several different angles. That said, inherent difficulties in measuring creativity and inherent sluggishness in the test industry mean the odds are small that creativity will find its way into IQ tests as currently defined. However, there remain other potential possibilities in related fields.
J. Intell. 2015, 3, 59-72; doi:10.3390/jintelligence3030059
Journal of
ISSN 2079-3200
Why Creativity Isn’t in IQ Tests, Why it Matters, and Why it
Won’t Change Anytime Soon Probably
James C. Kaufman
Department of Educational Psychology, Neag School of Education, University of Connecticut,
2131 Hillside Road, Storrs, CT 06269-3007, USA; E-Mail:
Academic Editor: Robert J. Sternberg
Received: 18 June 2015 / Accepted: 28 July 2015 / Published: 7 August 2015
Abstract: Creativity is a part of most theories of intelligence—sometimes a small part and
sometimes a large part. Yet even IQ tests that assess aspects of intelligence that supposedly
reflect creative abilities do not actually measure creativity. Recent work has argued that
intelligence and creativity are more conceptually related than we have thought. In addition,
creativity offers a potential way to counter issues of test bias from several different angles.
That said, inherent difficulties in measuring creativity and inherent sluggishness in the test
industry mean the odds are small that creativity will find its way into IQ tests as currently
defined. However, there remain other potential possibilities in related fields.
Keywords: IQ testing; creativity; intelligence; creativity assessment
1. Introduction
There are many challenges facing IQ testing, and how the field responds will likely determine the
extent of their continued use in the future. A small sampling of issues includes how tests can incorporate
technological advances (indeed, most intelligence tests are oddly stuck in the hard-copy era), how test
developers can respond to such challenges as the RTI (Response to Intervention) movement, and how
trainers can encourage intelligent testing [1]. There are broader concerns, however, which are rooted in
some of the same basic questions that have been asked for the last century. Do IQ tests actually measure
intelligence? How well do they predict real-world success? Do IQ tests reflect current beliefs about the
vast expanse of intellectual abilities?
J. Intell. 2015, 3 60
In some ways, it is unfair to expect one test—whether we mean an IQ test, an academic achievement
test, or an admissions test such as the SATs or GREs—to account for everything. We wouldn’t expect
one blood test to yield a diagnosis for all possible diseases. Yet in common perception and often in
practice, we allow a handful of scores to determine virtually everything about a person.
In an ideal world, every child being assessed would be given a complete battery of cognitive and
non-cognitive tests, just as any college applicant would be evaluated on a portfolio of past work, scores,
recommendations, interviews, and essays. Both IQ tests and college admission tests are often defended
by saying they are only intended to be used as part of a complete work-up; I’ve called this argument the
Lucky Charms paradox [2]. In commercials, a child is portrayed eating Lucky Charms as part of
a nutritious breakfast, complete with orange juice, scrambled eggs, yogurt, and toast. When seen this
way, Lucky Charms is a good thing. But in real life, mornings are frenetic and filled with oversleeping
kids, hurried showers, and a quick bowl or two of Lucky Charms gulped down before the school bus.
Despite the best intentions, Lucky Charms become the only source of breakfast nutrition.
Moving from breakfast cereal to tests, the SATs are often the only numbers given weight for most
college admissions. Low GRE scores can keep students with otherwise exceptional records out of top
graduate schools. And IQ tests, all by themselves, hold a tremendous amount of power. It is common for
students to be initially recommended for gifted programs but then denied if their IQ score is one point
lower than the cut-off [3,4].
IQ can take on a literally life-or-death role given that an IQ of 70 is the cutoff for whether a prisoner
can be executed [5]. Even though technically a classification of Intellectual Disability (Mental
Retardation) requires both an IQ and a measure of adaptive behavior (such as the Vineland—II) to be
below 70, in reality it is the IQ test that bears the burden of determining a criminal’s fate [6]. Further,
sometimes a live-or-die verdict rests on less than 1 IQ point. IQ test norms get out of date at the rate of
0.3 points per year, and many researchers and clinicians argue that a person’s IQ must be adjusted by
0.3 points for each year the norms are out of date (Flynn, 2009)—even if that adjustment produces an
IQ of 69.4 or 70.7. As Cecil Reynolds and his colleagues argue: “The importance of understanding and
assessing mental retardation in criminal defendants has become critical, indeed a true matter of life and
death, in capital felony cases. No one’s life should depend on when an IQ test was normed” [7]. Even
more pertinent, in this high-tech age brimming with sophisticated theories of intelligence, creativity, and
non-cognitive variables, how can key decisions like gifted placements or capital punishment verdicts
rest almost exclusively on g, and be able to be overturned by a point or two?
With power comes responsibility. What aspects of intelligence are not measured by intelligence tests?
Here there is natural divergence between IQ test developers and intelligence theorists, yet at least one
construct is present in all theories but still omitted from any IQ test: Creativity.
2. Creativity in IQ-Related Theories and IQ Tests
Most current IQ tests use the Cattell-Horn-Carroll (CHC) model [1] either explicitly or implicitly
within their theoretical frame work [8]. Given that CHC is the theory most commonly used in IQ tests
and is also the most frequently used non-g perspective used in creativity-intelligence studies, I will
primarily focus on this theory.
J. Intell. 2015, 3 61
The CHC model is an outgrowth of the Cattell-Horn Gf-Gc theory of fluid and crystallized
intelligence [9] and Carroll’s (1993) Three-Stratum Theory [10]. Much of current CHC theory is most
rooted in Horn’s expanded model (e.g., [11]). Although Gf would seem to be a natural match with
creativity abilities, with its emphasis on novel problem-solving, creativity is placed as part of Glr
(Long-term storage and retrieval) in the current CHC model [12,13].
Someone high in Glr is able to store information in long-term memory and then retrieve it when
needed [14]. Glr is used when you learn the name of your daughter’s fifth-grade teacher and then again
when you remember the name of your own fifth-grade teacher. You are still using Glr when you help
your daughter with her homework and can recall your own long-ago knowledge of the state capitals and
then link this memory of Sacramento being the capital of California with last night’s news story about
the lottery winner living in Sacramento.
Glr has two distinct components: learning efficiency (how well you can both learn and retain new
information) and fluency (the ability to rapidly recall many things). There are many “narrow” abilities
underneath these two components; one such ability is Idea Production, which can include five types of
fluency (associational, expressional, ideational, word, and figural), figural flexibility, and originality [15].
Fluency, which is this usage refers to the ability to generate many different ideas; flexibility, or the
ability to generate many different categories of ideas; and originality, which is generating particularly
rare and unusual ideas, are also key components in creativity. They represent a large portion of
Guilford’s Divergent Production [16] within his Structure of Intellect model.
Although Glr is measured in many current IQ tests, the focus is rarely on fluency (and never on
flexibility or originality). The Woodcock-Johnson IV Tests of Oral Language [17] include Retrieval
Fluency. The Woodcock-Johnson IV Tests of Achievement (WJ-IV; [18]) include three Fluency subtests
(Sentence Reading, Math Facts, and Science Writing) in the core battery and Word Reading Fluency in
the extended battery. The Kaufman Test of Educational Achievement-3 (KTEA-3; [19]) includes nine
Fluency subtests: Word Recognition, Silent Reading, Decoding, Math, Writing, Associational, Reading,
Oral, and Academic. The NEPSY-II [20] includes Design Fluency and Word Generation (which was
originally called Verbal Fluency). Yet most of these subtests are measuring the broader type of fluency,
which is less related to creativity. As J.C. Kaufman et al. [15] discuss, the only four subtests that measure
fluency in a creativity-relevant way are the WJ IV’s Retrieval Fluency, the KTEA-3’s Associational
Fluency, and the two NEPSY-II subtests. Although recent studies have found that Glr does indeed predict
creativity [21,22], the construct as measured by IQ tests is far removed from conceptions of creativity.
The CHC model is certainly not the only (or necessarily best) theory of intelligence. The PASS model
(Planning, Attention, Simultaneous, and Successive) [23], a cognitive processing approach rooted in the
neuropsychological work of Luria [24], is also often used in IQ tests. Creativity likely lies in the Planning
component [25]. Tests that use the PASS model do measure Planning, but such assessments have not
included anything explicitly related to creativity. In addition, there are several theories that are not (yet)
represented in IQ tests that have much to offer.
J. Intell. 2015, 3 62
3. Creativity in Other Theories of Intelligence
Guilford’s [16] Structure of Intellect model is not as popular as it once was, but it represented a
pioneering step forward. The model introduced the concepts of both divergent and convergent thinking,
which are parts of many modern theories of creativity (e.g., [26]).
A modern theory of intelligence that emphasizes creativity is Sternberg’s [27–29] theory of successful
intelligence. An earlier version, the Triarchic Theory of Intelligence [30], proposed three intelligences:
Analytic, Practical, and Creative. The revised theory comprises three subtheories. Most related to
creativity is the experiential subtheory, which focuses on how people adjust to novelty and automatize
information processing. Although many measures of Sternberg’s theories have been created and used
for college admissions [31], they have been not yet been incorporated into IQ tests (see, e.g., [32]).
Gardner’s well-known theory of multiple intelligences [33,34] (encompassing interpersonal,
intrapersonal, spatial, naturalistic, language, logical-mathematical, bodily-kinesthetic, and musical)
includes a wide range of abilities that would require differing amounts of creativity. Further, Gardner’s
Creating Minds [35] contains case studies of eminent creative individuals who embody his intelligences.
Although Gardner’s work has had extensive influence in the schools, his ideas have also not yet been
incorporated into IQ tests.
4. The Relationship between Creativity and Intelligence
There have been hundreds of papers devoted to this topic, and given that my emphasis is on creativity
as part of intelligence (as opposed to creativity representing a different construct from intelligence),
I will only briefly review this literature. Most studies on the topic tend to assume a generalist perspective
on both intelligence (typically using group-based tests of g) and creativity (typically using divergent
thinking tests). Creativity and intelligence, under these circumstances, tend to correlate at a small but
significant level [36,37].
Many argue that the two constructs are more closely related than such studies would indicate.
Silvia [38,39] suggests the relationship is underestimated because the studies are limited by only looking
at observable scores (i.e., performance on an intelligence test). Jung [40] notes that intelligence can be
seen as problem solving at an everyday level (e.g., [41]), whereas creativity may represent problem
solving for less common issues (e.g., [42]). Others argue that creativity and intelligence are both
cognitive functions [43] or that divergent thinking is simply an executive cognitive function [44].
Much of the more recent work on creativity and intelligence has focused more on Gf instead of g or
Gc. Benedek, et al. [45] studied underlying executive functions behind both divergent thinking and Gf.
They found that the ability to notice small changes (called updating; [46]) predicted both Gf and
divergent thinking; the ability to stifle a natural response (or inhibition) also predicted divergent thinking.
Other studies have used metaphor creation as a creativity measure instead of divergent thinking and a
spectrum of CHC components instead of just g and have found much higher relationships between
creativity and intelligence than past studies (i.e., [47,48]).
A pair of studies by Silvia and colleagues indicated that the relationship between Gf and creativity is
mediated by other cognitive mechanisms. Nusbaum and Silvia [49] found that Gf predicted creativity
but also predicted how well people could use a more efficient strategy to improve their scores. Beaty
J. Intell. 2015, 3 63
and Silvia [50] studied divergent thinking over time. Participants in the sample with higher Gf produced
creative initial ideas but slowed over time; in comparison, those participants with lower Gf showed much
more improvement in their idea generation when given more time. Looking broadly at these studies
suggests that the basic approach to seeing how creativity and intelligence relate to each other may not
be enough. Creativity and intelligence show an intricate relationship with many cognitive and situational
mediators. It may be instinctually appealing to consider them as completely different concepts, but some
have argued that this separation can hurt children who are being assessed [51].
5. Why is Creativity Important? The Issue of Bias
Even if one readily accepts that creativity is a part of intelligence and that it is not satisfactorily
measured on IQ tests, there is the larger question of whether creativity’s absence is cause for concern.
It is easy to list the many positive outcomes connected with creativity, but most components of
intelligence would have their own list of beneficial associations. As I have argued elsewhere [52,53],
creativity has particular implications for fairness and non-biased assessment.
IQ tests have been criticized in two different ways for being biased. A common layperson criticism
approach is to note the significant differences that occur between males and females (although such
differences are much more present in standardized achievement tests) and among ethnic groups. Some
researchers argue that these measures reflect actual differences [54]. Others point to the discrepancy
between socioeconomic status and opportunities across ethnicities [27], whereas still others argue that
current ability measures do not incorporate enough aspects of intelligence to truly reflect a person's
“global” ability [29].
Another proposed explanation is stereotype threat. A multitude of studies (see, e.g., [55]) have found
that individuals feel stress when placed in a situation where they run the risk of confirming a negative
stereotype about their group (e.g., ethnicity). This stress can then cause poor performance [56,57]. People
can be aware of stereotypes about intelligence when they do not endorse such views; indeed, even people
who are the targets of such stereotypes are cognizant of these views. An example of a manifestation
might be if an African American test-taker is aware of these stereotypes and is worried about confirming
such negative views and, as a result, feels added stress. Such added stress may increase cognitive load
and reduce working memory [58], thereby leading to lowered test performance.
Beyond simply focusing on group differences, there is a psychometric approach to bias that offers a
more nuanced approach. In this method, the question is whether a test might be measuring different
things in different groups. For example, a test may measure vocabulary in Caucasians, but measure
something else (such as exposure to American culture) in a Hispanic American population [59,60].
If a test measures something different from its intended purpose for specific groups, then it can be
considered to be biased against such groups. A measure can be considered to be fair to the extent any
resultant score only reflects (a) variables associated with the construct being measured, and (b) random
variance from error. If any systematic error occurs because of a person’s group membership and, thus,
that person receives a lower score, then the test is biased [61].
Creativity may be a reason why some groups systematically get items incorrect. Several scholars [62–64]
have suggested that Caucasians approach some tasks (such as hearing a story and then recounting
J. Intell. 2015, 3 64
specific details) in the way that the test creators intended. In contrast, African Americans may emphasize
the narrative in the story and answer more creatively. Such answers would then be marked incorrect.
Creativity also may help with the issue of test bias in other ways. If stereotype threat is a reason why
some groups receive lower IQs, it is worth noting that creativity tests and rated work tend to show no
differences across ethnicity [65–67]. However, African Americans see themselves as more creative than
Caucasians in several domains [68]. In another study, African Americans and Caucasians were asked to
provide self-ratings on both intelligence and creativity [69]. There was an interaction with education;
among less-educated individuals, ethnic differences were notably higher for intelligence than creativity.
Among the higher-educated individuals, African Americans rated themselves higher for creativity than
did Caucasians; the opposite effect was found for intelligence. The result of these findings may be that
given the higher self-concept that African Americans have for creativity, an IQ test that includes
creativity may reduce stereotype threat. Further, there is a strong chance that the ethnicity gap noted in
IQ tests would not be found in items emphasizing creativity.
6. Creativity and IQ Tests: Possibilities, Realities, and Ironies
Although the field of creativity has been around for more than 65 years and has been especially fertile
over the last two decades, measurement is still a tricky subject. The most common assessment remains
divergent thinking, much as it was in the 1950s. Researchers often use either the Torrance Tests of
Creative Thinking (TTCT; [70]) or a comparable measure based on Guilford’s [16] ideas [71]. Such tests
are traditionally scored for fluency, flexibility, and originality (all abilities that would theoretically
comprise Glr).
Could a subtest that measures divergent thinking (“Creative Fluency”) be added to an IQ test? Instead
of asking test-takers to name many different examples from a category (such as types of flowers), could
they be asked more open-ended questions such as uses for a pencil or what might happen if people could
fly? Certainly, it would be possible to score such responses for fluency; just as IQ test examiners are
highly trained as to what constitutes a correct answer, so too are TTCT scorers trained to reliably
determine if a response is relevant (and thus counts for fluency) or irrelevant [72].
Even scoring for originality would be possible. The TTCT has a matrix of responses and points are
assigned based on the rarity of response. In research studies, all responses are pooled and originality is
scored based on the frequency a particular answer is given. Such matrices would be easy to compile
during test standardization; one such matrix was applied to determine the originality of responses on the
Verbal Fluency subtest of the McCarthy Scales of Children’s Abilities [73]. Just as current IQ tests have
responses that carry different weights based on “correctness”, so too could a scoring system be
implemented that assigns increased points for more rare responses. Such an assessment could also be
translated on-line without notable changes to the process [74].
There are criticisms of divergent thinking, of course. Even its supporters agree that it is only one
aspect of creativity [75]. The broad verbal-figural categories are not dissimilar to the early atheoretical
Verbal-Performance structure of past Wechsler scales (e.g., [76]). The validity of such measures has
been both challenged [77] and defended [78]. Adding divergent thinking to IQ tests would probably be
the easiest possibility, but not necessarily the optimal choice. Indeed, consider that one common criticism
J. Intell. 2015, 3 65
of IQ tests is that they have largely remained stagnant over the last century [32]. The selection of a
creativity measure primarily rooted in work more than six decades old may not be a step forward.
Another popular measure of creativity is the Consensual Assessment Technique [79,80], in which
actual creative products are rated by content experts. Such experts tend to agree at strikingly high rates,
even if they represent different areas of expertise [81,82] or a different amount of expertise [83,84]. Only
pure novices do not show agreement with experts [85,86].
This method would be impractical on a large scale for reasons of time and cost, but an important
take-away is that an expert’s opinion carries a certain amount of weight. Just as an examiner need not
be an expert in motivation or personality to make valuable notes about a child’s behavior during the test,
particular care can be made to note responses that are notably original, aesthetically pleasing, humorous,
or clever. Such behavioral observations are consistent with a teacher using slight variations from a
typical lesson plan to allow student creativity to develop [87].
Even the Consensual Assessment Technique could eventually be utilized on a larger scale. Computers
can be trained to grade essays – not to mention to play chess and develop unique recipes [72]. There is
no reason to assume that given enough programming, computers could not be trained to mimic human
raters in evaluating creative work (at least creative writing). How might computers be trained? Consider
the many textual analysis programs (e.g., WordNet, Linguistic Integrative Word Count, and Latent
Semantic Analysis) that use advanced computational modeling techniques to assess semantic patterns
and associations. Many of these models are based on self-learning algorithms, meaning that there is
minimal training time and that the ability to detect whatever construct is being examined improves with
experience. Some of the programs (such as Latent Semantic Analysis) are already being used to
automatically score essays based on human feedback; this same basic principle can be applied to creative
writing. Just as current systems have trained computer programs to mimic experts in grading essays for
writing quality, grammar, and sentence structure, so too can programs be trained to detect creativity.
Infinite facets of a writing sample can be detected (across many possible dimensions, from adjective
placement to language choice) and then associated with multiple ratings by experts of the creative aspects
of the product. The program could then learn which features are associated with creativity, and to what
extent. Certainly, the ability to calculate distances between words or concepts should allow for
sophisticated originality scores in divergent thinking-type measures.
I have used creative writing as a main example because I think we are the closest to being able to best
measure that domain on a large scale. However, the Consensual Assessment Technique has been used
in many others domains, from taking photographs [88] to music compositions [89] to deriving
mathematical equations [90] to dramatic performance [91] to answering science questions [92] to
cooking [93] to everyday problem-solving [94]. In addition, ratings of different creative products within
the same domain tend to be consistent by person [80,95].
Ideally, a multitude of possible domains could be measured to provide a broad perspective on a
person’s creativity. Although it would be simpler to use a domain-general measure of creativity, there
has been a strong movement toward domain-specificity [85,96,97].
Unfortunately, these types of initiatives take money and the willingness to take risks. Test publishers
may have the former, but most have shown no indication of the latter. On some level, this is
understandable; IQ tests are a business, like making dental floss, and the people making the decisions—even
those with backgrounds in psychology or education—do not seem to have the burning passion to advance
J. Intell. 2015, 3 66
the field. It is easy to criticize other people for not spending money, taking chances, or investing in the
future. Yet, ironically, what is preventing creativity from being included in IQ tests is a lack of creativity
on the part of publishers.
7. The Future of Creativity -and IQ -Assessment?
No matter how much some groups want to keep the status quo, progress moves forward regardless.
Video games continue to grow in popularity, both as an activity and a business. There has been a growing
interest in the relationship between video games and creativity [98]. Some studies show a link between
playing video games and being creative [99,100]. But these are only the start.
Valerie Shute and her colleagues [101–103] have begun what they call “stealth assessment” in video
games. They have created a game called Physics Playground, in which the player draws objects on the
screen. The drawings then become animated and interact with other objects in the game; as the game
progresses, there are a series of puzzles and problems that can be solved by drawing different objects.
Shute and her colleagues can quietly test how well the players learn and understand physics—as well as
their creativity. Levels can be solved in many different ways, and a player can attempt multiple solutions.
It is thus possible to generate scores for fluency, flexibility, and originality (as well as related constructs,
such as humor or aesthetics; [101]).
Shute and her colleagues’ work is still at a starting point. There are years of work in continued
development, validation, and expansion. The possibilities discussed earlier—especially the use of
computerized scoring to make large scale Consensual Assessment Technique feasible—are also likely
far away from being a reality. Unfortunately, we are many years removed from a time where researchers
such as David Wechsler (or my parents, Alan and Nadeen Kaufman) drove the field. The publishers are
the ones with all of the power, and the dominating company, Pearson, is only now slowly translating its
existing instruments into computerized format with Q-interactive (see, e.g., [104]).
It used to be that the costs of creating and standardizing a test were so prohibitive that a huge publisher
was a necessity. Things can change. There are some aspects of testing that need a face-to-face
component [1], but on-line assessment will nonetheless be suitable for many purposes. Collaboration
with programmers and using MTurk to obtain a large standardization sample may enable academics or
independent companies to tackle the type of new approaches—creative approaches, and ones that also
measure creativity—that current industry leaders are unwilling to consider.
The author would like to thank Alan S. Kaufman for his suggestions on an earlier draft.
Conflicts of Interest
The author declares no conflict of interest.
1. Kaufman, A.S. IQ Testing 101; Springer Publishing Company: New York, NY, USA, 2009.
J. Intell. 2015, 3 67
2. Kaufman, J.C.; Kaufman, A.S. It can be very tempting to throw out the baby with the bathwater:
A father-and-son commentary on Does IQ really predict job performance? Appl. Dev. Sci. 2015, 19,
doi:10.1080/10888691.2015.1008922, in press.
3. Pfeiffer, S.I. (Ed.). Handbook of Giftedness in Children. Psychoeducational Theory, Research and
Best Practices; Springer Science + Business Media: New York, NY, USA, 2008.
4. McClain, M.C.; Pfeiffer, S. Identification of gifted students in the United States today: A look at
state definitions, policies, and practices. J. Appl. Sch. Psychol.2012, 28, 59–88.
5. Kelly, B.; Resnick, P. A single IQ score over 70 supports finding of no intellectual disability,
despite conflicting test results and expert testimony. J. Am. Acad. Psychiatry Law 2014, 42,
6. Kaufman, A.S. “In What Way Are Apples and Oranges Alike?” A Critique of Flynn’s
Interpretation of the Flynn Effect. J. Psychoeduc. Assess. 2010, 28, 382–398.
7. Reynolds, C.R.; Niland, J.; Wright, J.E.; Rosenn, M. Failure to apply the Flynn correction in death
penalty litigation: Standard practice of today maybe, but certainly malpractice of tomorrow.
J. Psychoeduc. Assess. 2010, 28, 477–481.
8. Keith, T.Z.; Reynolds, M.R. Cattell-Horn-Carroll abilities and cognitive tests: What we’ve learned
from 20 years of research. Psychol. Sch. 2010, 47, 635–650.
9. Horn, J.L.; Cattell, R.B. Refinement and test of the theory of fluid and crystallized intelligence.
J. Educ. Psychol. 1966, 57, 253–270.
10. Carroll, J.B. Human Cognitive Abilities: A Survey of Factor-Analytic Studies; Cambridge
University Press: New York, NY, USA, 1993.
11. Horn, J.L.; Blankson, N. Foundations for better understanding of cognitive abilities.
In Contemporary Intellectual Assessment: Theories, Tests, and Issues, 2nd ed.; Flanagan, D.P.,
Harrison, P.L., Eds.; Guilford: New York, NY, USA, 2005; pp. 41–68.
12. Schneider, W.J.; McGrew, K.S. The Cattell-Horn-Carroll model of intelligence. In Contemporary
Intellectual Assessment: Theories, Tests, and Issues, 3rd ed.; Flanagan, D.P., Harrison, P.L., Eds.;
Guilford Press: New York, NY, USA, 2012; pp. 99–144.
13. Schneider, W.J. Flanagan, D.P. The relationship between theories of intelligence and intelligence
tests. In Handbook of Intelligence: Evolutionary Theory, Historical Perspective, and current
Concepts; Goldstein, S., Princiotta, D., Naglieri, J.A, Eds.; Springer: New York, NY, USA, 2015;
pp. 317–340.
14. Flanagan, D.P.; Ortiz, S.O.; Alfonso, V.C. Essentials of Cross Battery Assessment, 3rd ed.; Wiley:
Hoboken, NJ, USA, 2013.
15. Kaufman, J.C.; Kaufman, S.B.; Lichtenberger, E.O. Finding creativity on intelligence tests via
divergent production. Can. J. Sch. Psychol. 2011, 26, 83–106.
16. Guilford, J.P. The Nature of Human Intelligence; McGraw-Hill: New York, NY, USA, 1967.
17. Schrank, F.A.; Mather, N.; McGrew, K.S. Woodcock-Johnson IV Tests of Oral Language;
Riverside: Rolling Meadows, IL, USA, 2014.
18. Schrank, F.A.; Mather, N.; McGrew, K.S. Woodcock-Johnson IV Tests of Achievement; Riverside:
Rolling Meadows, IL, USA, 2014.
19. Kaufman, A.S.; Kaufman, N.L. Kaufman Test of Educational Achievement, 3rd ed.; NCS Pearson:
Bloomington, MN, USA, 2014.
J. Intell. 2015, 3 68
20. Korkman, M.; Kirk, U.; Kemp, S. NEPSY, 2nd ed.; Psychological Corporation: San Antonio, TX,
USA, 2007.
21. Avitia, M.J.; Kaufman, J.C. Beyond g and c: The relationship of rated creativity to long-term
storage and retrieval (glr). Psychol. Aesthet. Creativity Arts 2014, 8, 293–302.
22. Silvia, P.J.; Beaty, R.E.; Nusbaum, E.C. Verbal fluency and creativity: General and specific
contributions of broad retrieval ability (Gr) factors to divergent thinking. Intelligence 2013, 41,
23. Das, J.P.; Naglieri, J.A.; Kirby, J.R. Assessment of Cognitive Processes: The PASS Theory of
Intelligence; Allyn & Bacon: Boston, MA, USA, 1994.
24. Luria, A.R. The functional organization of the brain. Sci. Am. 1970, 222, 66–78.
25. Naglieri, J.A.; Kaufman, J.C. Understanding intelligence, giftedness, and creativity using PASS
theory. Roeper Rev. 2001, 23, 151–156.
26. Finke, R.A.; Ward, T.B.; Smith, S.M. Creative Cognition: Theory, Research, and Applications.
MIT Press: Cambridge, MA, USA, 1992.
27. Sternberg, R.J. Successful Intelligence; Plume: New York, NY, USA, 1997.
28. Sternberg, R.J. The theory of successful intelligence. Rev. General Psychol. 1999, 3, 292–316.
29. Sternberg, R.J.; Kaufman, J.C.; Grigorenko, E.L. Applied Intelligence; Cambridge University
Press: Cambridge, UK, 2008.
30. Sternberg, R.J. Beyond IQ: A Triarchic Theory of Human Intelligence; Cambridge University
Press: New York, NY, USA, 1985.
31. Sternberg, R.J.; Coffin, L.A. Admitting and developing ‘‘new leaders for a changing world’’.
N. Engl. J. High. Educ. 2010, 24, 12–13.
32. Sternberg, R.J.; Kaufman, J.C. Innovation and intelligence tests: The curious case of the dog that
didn’t bark. Eur. J. Psychol. Assess. 1996, 12, 167–174.
33. Gardner, H. Intelligence Reframed: Multiple Intelligences for the 21st Century; Basic Books:
New York, NY, USA, 1999.
34. Gardner, H. Multiple Intelligences: New Horizons; Perseus: New York, NY, USA, 2006.
35. Gardner, H. Creating Minds; Basic Books: New York, NY, USA, 1993.
36. Barron, F.; Harrington, D.M. Creativity, intelligence, and personality. Annu. Rev. Psychol. 1981,
32, 439–476.
37. Kim, K.H. Can only intelligent people be creative? J. Second. Gift. Educ. 2005, 16, 57–66.
38. Silvia, P.J. Another look at creativity and intelligence: Exploring higher-order models and probable
confounds. Personal. Individual Differ. 2008, 44, 1012–1021.
39. Silvia, P.J. Creativity and intelligence revisited: A latent variable analysis of Wallach and Kogan
1965. Creativity Res. J. 2008, 20, 34–39.
40. Jung, R.E. Evolution, creativity, intelligence, and madness: “Here Be Dragons”. Front. Psychol.
2014, 5, 784, doi:10.3389/fpsyg.2014.00784.
41. Kaufman, S.B.; DeYoung, C.G.; Reis, D.L.; Gray, J.R. General intelligence predicts reasoning
ability even for evolutionarily familiar content. Intelligence 2011, 39, 311–322.
42. Simonton, D.K. Creativity and discovery as blind variation: Campbell’s (1960) BVSR model after
the half-century mark. Rev. General Psychol. 2011, 15, 158–174.
J. Intell. 2015, 3 69
43. Silvia, P.J. Intelligence and creativity are pretty similar after all. Educ. Psychol. Rev. 2015, 1–8,
44. Gilhooly, K.J.; Fioratou, E.; Anthony, S.H.; Wynn, V. Divergent thinking: Strategies and executive
involvement in generating novel uses for familiar objects. Br. J. Psychol. 2007, 98, 611–625.
45. Benedek, M.; Jauk, E.; Sommer, M.; Arendasy, M.; Neubauer, A.C. Intelligence, creativity, and
cognitive control: the common and differential involvement of executive functions in intelligence
and creativity. Intelligence 2014, 46, 73–83.
46. Miyake, A.; Friedman, N.P. The Nature and Organization of Individual Differences in Executive
Functions: Four General Conclusions. Curr. Dir. Psychol. Sci. 2012, 21, 8–14.
47. Beaty, R.E.; Silvia, P.J. Metaphorically speaking: Cognitive abilities and the production of
figurative language. Memory Cogn. 2013, 41, 255–267.
48. Silvia, P.J.; Beaty, R.E. Making creative metaphors: the importance of fluid intelligence for
creative thought. Intelligence 2012, 40, 343–351.
49. Nusbaum, E.C.; Silvia, P.J. Are intelligence and creativity really so different? Fluid intelligence,
executive processes, and strategy use in divergent thinking. Intelligence 2011, 39, 36–45.
50. Beaty, R.E.; Silvia, P.J. Why do ideas get more creative across time? An executive interpretation
of the serial order effect in divergent thinking tasks. Psychol. Aesthet. Creativity Arts 2012, 6,
51. Kaufman, S.B. Ungifted: Intelligence Redefined; Basic Books: New York, NY, USA, 2013.
52. Kaufman, J.C. Non-Biased Assessment: A Supplemental Approach. In Comprehensive Handbook
of Multicultural School Psychology; Frisby, C.L., Reynolds, C.R., Eds.; Wiley: Hoboken, NJ,
USA, 2005.
53. Kaufman, J.C. Using creativity to reduce ethnic bias in college admissions. Rev. General Psychol.
2010, 14, 189–203.
54. Jensen, A.R. The g Factor: The Science of Mental Ability; Praeger: Westport, CT, USA, 1998.
55. Nguyen, H.D. Ryan, A.M. Does stereotype threat affect test performance of minorities and
women? A meta-analysis of experimental evidence. J. Appl. Psychol. 2008, 93, 1314–1334.
56. Steele, C. A threat in the air: How stereotypes shape intellectual identity and performance.
Am. Psychol. 1997, 52, 613–629.
57. Steele, C.; Aronson, J. Stereotype threat and the intellectual performance of African Americans.
J. Personal. Soc. Psychol. 1995, 69, 797–811.
58. Schmader, T.; Johns, M. Converging evidence that stereotype threat reduces working memory
capacity. J. Personal. Soc. Psychol. 2003, 85, 440–452.
59. Reynolds, C.R. Methods for detecting and evaluating cultural bias in neuropsychological tests.
In Handbook of Cross-Cultural Neuropsychology; Fletcher-Janzen, E., Strickland, T.L.,
Reynolds, C.R., Eds.; Springer: New York, NY, USA, 2000; pp. 249–285.
60. Reynolds, C.R.; Lowe, P.A.; Saenz, A.L. The problem of bias in psychological assessment. In The
Handbook of School Psychology; Reynolds, C.R., Gutkin, T.B., Eds.; Wiley: New York, NY, USA,
1999; pp. 549–596.
61. Mackintosh, N. IQ and Human Intelligence; Oxford University Press: Oxford, UK, 1998.
62. Heath, S.B. Ways with Words; Cambridge University Press: Cambridge, UK, 1983.
63. Kaufman, J.C. Creativity 101; Springer: New York, NY, USA, 2009.
J. Intell. 2015, 3 70
64. Manly, J.J.; Miller, S.W.; Heaton, R.K.; Byrd, D.; Reilly, J.; Velasquez, R.J.; Saccuzzo, D.P.;
Grant, I.; the HIV Neurobehavioral Research Center (HNRC) Group. The effect of Black
acculturation on neuropsychological test performance in normal and HIV positive individuals.
J. Intl. Neuropsychol. Soc. 1998, 4, 291–302.
65. Glover, J.A. Comparative levels of creative ability in Black and White college students.
J. Gen. Psychol. 1976, 128, 95–99.
66. Glover, J.A. Comparative levels of creative ability among elementary school children.
J. Gen. Psychol. 1976, 129, 131–135.
67. Kaufman, J.C.; Baer, J.; Gentile, C.A. Differences in gender and ethnicity as measured by ratings
of three writing tasks. J. Creative Behav. 2004, 38, 56–69.
68. Kaufman, J.C. Self-reported differences in creativity by gender and ethnicity. J. Appl.
Cogn. Psychol. 2006, 20, 1065–1082.
69. Ivcevic, Z.; Kaufman, J.C. The can and cannot do attitude: How self estimates of ability vary across
ethnic and socioeconomic groups. Learn. Individual Differ. 2013, 27, 144–148.
70. Torrance, E.P. The Torrance Tests of Creative Thinking Norms-Technical Manual Figural
(Streamlined) Forms A & B; Scholastic Testing Service: Bensenville, IL, USA, 2008.
71. Kaufman, J.C.; Plucker, J.A.; Baer, J. Essentials of Creativity Assessment; Wiley: New York, NY,
USA, 2008.
72. Kaufman, J.C. Creativity 101, 2nd ed.; Springer: New York, NY, USA, in press.
73. Kaufman, N.L.; Kaufman, A.S. Creativity in children with minimal brain dysfunction.
J. Creative Behav. 1980, 14, 73, doi:10.1002/j.2162-6057.1980.tb00228.x.
74. Hass, R.W. Feasibility of online divergent thinking assessment. Comput. Hum. Behav. 2015, 46,
75. Torrance, E.P.; Cramond, B. Needs of creativity programs, training, and research in the schools of
the future. Res. Sch. 2002, 9, 5–14.
76. Wechsler, D. Manual for the Wechsler Intelligence Scale for Children—Revised (WISC-R);
The Psychological Corporation: New York, NY, USA, 1974.
77. Baer, J. How divergent thinking tests mislead us: Are the Torrance Tests still relevant in the 21st
century? The Division 10 debate. Psychol. Aesthet. Creativity Arts 2011, 5, 309–313.
78. Kim, K.H. The APA 2009 Division 10 debate: Are the Torrance Tests of Creative Thinking still
relevant in the 21st century? Psychol. Aesthet. Creativity Arts 2011, 5, 302–308.
79. Amabile, T.M. Creativity in Context; Westview Press: Boulder, CO, USA, 1996.
80. Kaufman, J.C.; Baer, J. Beyond new and appropriate: Who decides what is creative? Creativity Res. J.
2012, 24, 83–91.
81. Kaufman, J.C.; Gentile, C.A.; Baer, J. Do gifted student writers and creative writing experts rate
creativity the same way? Gift. Child Q. 2005, 49, 260–265.
82. Baer, J.; Kaufman, J.C.; Riggs, M. Rater-domain interactions in the Consensual Assessment
Technique. Intl. J. Creativity Problem Solving 2009, 19, 87–92.
83. Baer, J.; Kaufman, J.C.; Gentile, C.A. Extension of the consensual assessment technique to
nonparallel creative products. Creativity Res. J. 2004, 16, 113–117.
J. Intell. 2015, 3 71
84. Kaufman, J.C.; Baer, J.; Cropley, D.H.; Reiter-Palmon, R.; Sinnett, S. Furious activity vs.
understanding: How much expertise is needed to evaluate creative work? Psychol. Aesthet.
Creativity Arts 2013, 7, 332–340.
85. Kaufman, J.C.; Baer, J.; Cole, J.C. Expertise, domains, and the Consensual Assessment Technique.
J. Creative Behav.2009, 43, 223–233.
86. Kaufman, J.C.; Baer, J.; Cole, J.C.; Sexton, J.D. A comparison of expert and nonexpert raters using
the Consensual Assessment Technique. Creativity Res. J. 2008, 20, 171–178.
87. Beghetto, R.A.; Kaufman, J.C.; Baer, J. Teaching for Creativity in the Common Core Classroom;
Teachers College Press: New York, NY, USA, 2014.
88. Dollinger, S.J. Creativity and conservatism. Personal. Individual Differ. 2007, 43, 1025–1035.
89. Priest, T. Self-evaluation, creativity, and musical achievement. Psychol. Music 2006, 34, 47–61.
90. Baer, J. Divergent thinking is not a general trait: A multi-domain training experiment.
Creativity Res. J. 1994, 7, 35–46.
91. Myford, C.M. The Nature of Expertise in Aesthetic Judgment: Beyond Inter-Judge Agreement.
Unpublished Doctoral Dissertation, University of Georgia, Athens, Greece, 1989.
92. Kaufman, J.C.; Evans, M.L.; Baer, J. The American Idol Effect: Are students good judges of their
creativity across domains? Empir. Stud. Arts 2010, 28, 3–17.
93. Horng, J.S.; Lin, L. The development of a scale for evaluating creative culinary products.
Creativity Res. J. 2009, 21, 54–63.
94. Reiter-Palmon, R.; Mumford, M.D.; Threlfall, K.V. Solving everyday problems creatively: The
role of problem construction and personality type. Creativity Res. J. 1998, 11, 187–197.
95. Kaufman, J.C.; Lee, J.; Baer, J.; Lee, S. Captions, consistency, creativity, and the consensual
assessment technique: New evidence of validity. Think. Skills Creativity 2007, 2, 96–106.
96. Kaufman, J.C. Counting the muses: Development of the Kaufman-Domains of Creativity Scale
(K-DOCS). Psychol. Aesthet. Creativity Arts 2012, 6, 298–308.
97. Kaufman, J.C.; Baer, J. Intelligent testing with Torrance. Creativity Res. J. 2006, 18, 99–102
98. Green, G.P.; Kaufman, J.C. (Eds.). Videogames and Creativity; Academic Press: San Diego, CA,
USA, 2015.
99. Hamlen, K. Children’s choices and strategies in video games. Comput. Hum. Behav. 2011, 27,
100. Jackson, L.A.; Witt, E.A.; Games, A.I.; Fitzgerald, H.E.; von Eye, A.; Zhao, Y. Information
technology use and creativity: Findings from the children and technology project. Comput.
Hum. Behav. 2012, 28, 370–376.
101. Kim, Y.J.; Shute, V.J. Opportunities and challenges in assessing and supporting creativity in video
games. In Videogames and Creativity; Green, G.P., Kaufman, J.C., Eds.; Academic Press: San Diego,
CA, USA, 2015; pp. 101–123.
102. Shute, V.J.; Ventura, M. Measuring and Supporting Learning in Games: Stealth Assessment;
MIT Press: Cambridge, MA, USA, 2013.
103. Shute, V.J.; Ventura, M.; Kim, Y.J. Assessment and learning of informal physics in Newton’s
Playground. J. Educ. Res. 2013, 106, 423–430.
J. Intell. 2015, 3 72
104. Dumont, R.; Viezel, K.D.; Kohlhagen, J.; Tabib, S. A review of Q-interactive assessment
technology. NASP Commun. 2014, 43, 8–12.
© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article
distributed under the terms and conditions of the Creative Commons Attribution license
... Intelligence and creativity are distinct constructs, although they may also be interrelated (Karwowski et al., 2016;Kim et al., 2010). However, creativity has not been included in intelligence test batteries, either nationally or even internationally, thus limiting a more complete assessment of an individual's cognitive potential (Kaufman, 2015;Pfeiffer, 2018). Therefore, considering that intelligence and creativity are considered the key skills for the 21st century (Organization for Economic Cooperation and Development [OECD], 2020), it is necessary to find ways to integrate both dimensions to gain a broader understanding of the cognitive potential of children. ...
... The need to create a battery of tests for assessing intelligence combined with creativity is made quite clear when focusing on the need to understand the different areas in which a child may have greater or lesser difficulty, thus enabling better diagnoses than a total IQ result (Kaufman, 2015(Kaufman, , 2016. This is highlighted, for example, in the area of special education and, more specifically, in the identification of students with high skills or giftedness, which requires students to have complete diagnoses in order to access specific educational programs (Alencar & Fleith, 2005;Renzulli & Renzulli, 2010). ...
... It is the same in our country, where intelligence tests are predominant in the list of instruments approved by SATEPSI (2020). However, the evaluation of creativity has not been included in the test batteries to allow a more complete and integrated cognitive assessment, either abroad or within Brazil (Kaufman, 2015;Pfeiffer, 2018), thus greatly limiting the ability to evaluate an individual's potential. ...
Full-text available
It is essential that intelligence assessment be integrated with creativity, although no instruments in Brazil do so. This research investigated the item difficulty and validity and reliability of the Bateria de Avaliação Intelectual e Criativa Infantil (BAICI) to address this gap. The first sample consisted of 612 children (54% M) aged 7 to 12 years, and the second sample consisted of 377 students (56% M), some of whom (N = 164) were already identified as exhibiting high skills/giftedness. Item analysis indicated the need to adjust the BAICI items. The results of a MANCOVA indicated that the BAICI exhibits evidence of validity with external variables because the group of gifted children was significantly distinguished from the group of students attending regular schools on tests of vocabulary, speed, logical thinking, and creativity. The study concludes that the BAICI has psychometric qualities that can be used in the psychological assessment of children.
... Digital, game-based creativity assessments have been highlighted as a potential means to address many of the above-mentioned issues (Kaufman, 2015;Rafner et al., 2021;. Three arguments support the usage of digital games to measure creativity. ...
For decades, researchers have struggled with measurement problems related to the construct validity of divergent and convergent thinking in creativity assessments. In response, some have called for battery-based approaches. Recently, digital games have emerged as a potential alternative, offering increased scalability and improved ecological validity. This article presents CREA: a new, scalable, game-based assessment suite. CREA includes crea.tiles and crea.blender, non-verbal games featuring both divergent and convergent thinking modes, as well as crea.ideas – the Alternative Uses Task, a standard test of divergent thinking, and crea.logic – a test of abstract reasoning. The novel convergent and divergent thinking game modes are constructed within the same contextual environment and with theoretically motivated differences in game-prompts to understand and generalize from the emerging elicited behaviors. In this study, 408 participants completed the CREA suite and selected validation measures, representing the largest game-based validation study to date. Both convergent and discriminant validity is demonstrated for crea.tiles with respect to standard tests, with correlations ranging from r = .1–.4. Having CREA freely accessible, we aim to broaden the accessibility of creativity assessment to researchers, educators, and the general public and through this scaleup validate the rich creative behavioral patterns observed in this study.
... 1087) and indeed innovative research and findings. This kind of thinking is beyond the well-established tests that suggest how intelligence is measurable (Kaufman 2015). ...
Full-text available
Successful scientists need to think carefully about the particular aspect of the world around them they are investigating. They build on what is known in their area of science to identify how they might examine the issue or problem they are concerned with to offer further insights. Through investigating natural phenomena, they can solve problems and communicate new ways of looking at the world. Their work serves to address global and societal challenges and often offers improved ways of living. The ways that scientists’ work can have implications for educational processes designed to prepare would-be scientists or scientifically aware citizens of the future. Eliciting reflections from experienced scientists recounting how they came to develop their scientific intellect, expertise and problem-solving know-how is useful to inform science education. This article reports on an aspect of a larger project involving 24 scientists specialising in biological or physical science research from Higher Education Institutions, located in either Manchester, Oxford or London. The study adopts a retrospective phenomenographical methodology and applies two fresh theoretical perspectives to eight in-depth interviews with professional scientists working in university departments involved in ground-breaking research. Conversations with the scientists were framed to explore the nature and extent of formal and informal learning influences affecting the development of their inventiveness and expertise in becoming scientists. The reified perspectives collated here show how a range of experiences have afforded expert scientists the opportunity to apply their intellectual capabilities. These kinds of demonstrable abilities have enabled them to scientifically contribute to being able to solve real-world problems. Additionally, a cross-case analysis of scientists’ reported learning experiences could inform science education policy and practice.
... Considering general or mathematical creativity as one of the potential criteria while admitting students to college, graduate schools, and gifted education programs can reduce bias in education (Kaufman, 2015). ...
Full-text available
The purpose of this systematic review is to reveal the research findings that suggest instructional practices to foster the creativity of students in mathematics. Although several studies have investigated the effects of various instructional practices influencing the mathematical creativity of students, little is known about how the findings of this collective body of research contribute to the understanding of what instructional practices should be integrated into a mathematic classroom to further foster the mathematical creativity of students. In this systematic review, the knowledge of instructional practices that foster the mathematical creativity of students were categorized under two main factors including: 1) discipline-specific instructional practices and 2) general instructional practices. The discipline-specific instructional practices were problem-solving, problem-posing, open-ended questions, multiple solution tasks, tasks with more than one correct answer, modeling/model-eliciting activities, technology integration, extendable tasks, and emphasizing abstractness of mathematics. The general instructional practices were providing students with ample time to think creatively about real-world related mathematical problems in a judgment free and collaborative classroom environment so that they take risks to share their mathematical ideas and use informal words. Integrating all of these instructional practices into mathematics classrooms can provide opportunities for students to discover their potential creative abilities in mathematics.
... The illusion, inherited from the intelligence research, of finding a "g" factor of creativity and an accompanying measure to assess it (Piffer, 2012) has been forsaken in favor of a more precise theoretical and empirical understanding of the creativity construct, of the related phenomenology, and of the relationship with other closely related constructs (see, for example, the study of serendipity, wonder, inspiration, possibility, etc.; Glăveanu, 2018Glăveanu, , 2019Mastria, Agnoli, Corazza, Grassi, & Franchin, 2022;Ross & Vallee-Tourangeau, 2021). The awareness that intelligence and creativity represent two separate constructs has definitively taken root because of the common effort of the creativity research community to understand the relationship between the two (Corazza & Lubart, 2020;Karwowski et al., 2016;Kaufman, 2015;Weiss, Steger, Schroeders, & Wilhelm, 2020). In addition, creative cognition begun to find its own place within the domain of human cognition (Benedek & Fink, 2019), supported by a more precise understanding of the functional brain mechanisms underlying specific creative behaviors (in particular idea generation, Beaty, Seli, & Schacter, 2019;Benedek, 2018), giving rise to the creativity neuroscience approach (Saggar, Volle, Uddin, Chrysikou, & Green, 2021). ...
... C. Kaufman, 2019) or divergent thinking tests, measures of creative potential which ask students to answer hypothetical open-ended questions with many different responses (Acar & Runco, 2019). Although both of these techniques offer a certain amount of information, we believe neither would offer enough additional reliable valid information to convince most skeptics who work with high-stakes assessment (e.g., J. C. Kaufman, 2015Kaufman, , 2016. ...
The measurement of human intelligence is a landmark accomplishment in psychology; yet this advance came with negative outcomes, such as social injustice. In this chapter, we explore the history of IQ test development with particular attention to the degree to which the early pioneers and later leaders viewed the malleability (or fixedness) of intelligence. We cover the views of Binet, Terman, Wechsler, and subsequent test authors on key topics such as definitions of intelligence, theoretical models, and application, interpretation, limitations of, and concerns about their newly created or revised measures.
... Bernold, Spurlin, and Anson (2007) found that persistence and GPA in engineering can be predicted by how students prefer to learn new material, wherein students who approach problems from a "why?" (i.e., prefers listening and discussing ideas in an environment that encourages divergent thinking and subjectivity) or a "what if?" perspective (i.e., prefers hands-on trial-and-error and thought-provoking discussions in an environment that encourages originality) are more likely to have lower GPAs and leave engineering than students who approach problems with a more concrete "what?" (i.e., prefers critiquing information, creating theories from abstract facts, and verifying data) or "how?" perspective (i.e., prefers solo experimentation involving straightforward, objective thinking that leads to a measurable product). Further, extensive evidence suggests that diversity in gender, sexual orientation, and ethnicity improve the productivity and creativity of teams (Hülsheger, Anderson, & Salgado, 2009;Milliken & Martins, 2016;Payne, 1990;Stahl, Maznevski, Voigt, & Jonsen, 2010); this has resulted in increased calls for creativity to be used as an admissions factor for colleges and gifted education programs (Kaufman, 2010(Kaufman, , 2015Luria, O'Brien, & Kaufman, 2016). ...
Full-text available
Executive functioning (EF) is a set of high-level cognitive skills, including planning, organizing, prioritizing, logical and contextual thinking, understanding, working memory, and self-monitoring. Though these skills are critical for academic success across fields, engineering education may be especially demanding for those with poor EF. One potential resource that may help to buffer against the negative effects of poor EF on academic achievement is divergent thinking. This study examined the role of divergent thinking as a moderating variable in the relationship between EF and academic achievement in engineering education. Undergraduate engineering students completed a self-report scale of EF and tests assessing figural and verbal divergent thinking, across multiple study sessions. Participants’ GPA was obtained from the university registrar's office. Participant data (N = 199) were analyzed using correlational analysis and a multiple moderation model. Results showed that EF scores and engineering GPA were significantly negatively correlated, and that figural (yet not verbal) divergent thinking moderated the association. A greater frequency of behaviors reflecting problems with overall daily EF was associated with lower GPA for those with relatively lower figural divergent thinking ability. Thus, figural divergent thinking may be one personal resource that can be leveraged to enhance academic achievement in engineering students with poor EF.
Full-text available
Immersive virtual reality (IVR) takes advantage of exponential growth in our technological abilities to offer an array of new forms of entertainment, learning opportunities, and even psychological interventions and assessments. The field of creativity is a driving force in both large-scale innovations and everyday progress, and imbedding creativity assessment in IVR programs has important practical implications for future research and interventions in this field. Creativity assessment, however, tends to either rely on traditional concepts or newer, yet cumbersome methods. Can creativity be measured within IVR? This study introduces the VIVA, a new IVR-based visual arts creativity assessment paradigm in which user create 3D drawings in response to a prompt. Productions are then rated with modern extensions of a classic product-based approach to creativity assessment. A sample of 67 adults completed the VIVA, further scored using item-response modeling. Results demonstrated the strong psychometric properties of the VIVA assessment, including its structural validity, internal reliability, and criterion validity with relevant criterion measures. Together, this study established a solid proof-of-concept of the feasibility of measuring creativity in IVR. We conclude by discussing directions for future studies and the broader importance and impact of this line of work for the field of creativity and virtual reality.
Full-text available
O presente trabalho teve como objetivo desenvolver uma versão informatizada da Bateria de Avaliação Intelectual e Criativa para Adultos (BAICA) e verificar sua equivalência com a versão impressa, composta por seis subtestes. Participaram do primeiro estudo 10 pessoas e, do segundo, 72; em ambos, os participantes tinham entre 18 e 32 anos. Durante o estudo 1 buscou-se identificar os processos cognitivos usados pelos participantes e compará-los com os esperados para cada instrumento, além de colher feedback sobre o funcionamento da bateria. Os resultados indicaram que o instrumento informatizado avalia os processos esperados. Durante o segundo estudo a versão informatizada foi aplicada em 24 pessoas e os resultados foram comparados com o de 48 pessoas que realizaram a versão impressa. A comparação entre os grupos apontou diferenças significativas entre todos os subtestes, com exceção do pensamento viso espacial. Concluiu-se que apesar de uma versão informatizada da BAICA ser viável, ela não é equivalente à versão impressa.
The field of giftedness legitimates itself on the basis of correlations of gifted-identification measures with future success that do not mean what they often are taken to mean. When one views the inadequacies of these correlations, the field turns out to be much like the emperor who had no clothes. This essay reviews some of the assumptions upon which the legitimacy of much of the field, at least in practice, bases itself, and concludes that because many assumptions are inadequate, so are certain widespread practices of the field. In particular, the fact that measures used in gifted identification predict future success, as measured by conventional societally sanctioned indices of success, does not suggest that those measures actually are complete or even adequate for gifted identification. Society needs new directions for theory, research, and practice.
Full-text available
Many games offer players opportunities to express their creativity, from posting their clever solutions in online forums, to beating particular boss levels, to creating their own levels using built-in level editors. Yet there is scant evidence supporting the link between video games and creativity. This is partially due to the difficulty of measuring creativity. In this chapter, we will (a) review the current literature on creativity, (b) discuss affordances of video games for creativity development using popular commercial games as examples, and (c) illustrate how one can assess and support creativity using creativity assessments in our game, Physics Playground (formerly known as Newton's Playground), as an example.
An overview and introduction to Cross-Battery Assessment
Theories of intelligence are not all theories of the same thing. Rather, they tend to be theories of different aspects of intelligence. To make matters worse, the theorists who propose these theories almost never make it clear just what aspects of intelligence their theories embrace. Consequently, it is difficult to know in what respects the claims of the various theories are complementary, and in what respects these claims are antagonistic. The end result is a continual state of “theory warfare” in which different kinds of theories are pitted against each other, whether or not they are truly competitive.