Creativity is a phenomenon whereby something new and somehow valuable is formed. The created item may be intangible (such as an idea, a scientific theory, a musical composition, or a joke) or a physical object (such as an invention, a literary work, or a painting).
Scholarly interest in creativity is found in a number of disciplines: engineering, psychology, cognitive science, education, philosophy (particularly philosophy of science), technology, theology, sociology, linguistics, business studies, songwriting, and economics, covering the relations between creativity and general intelligence, personality type, mental and neurological processes, mental health, or artificial intelligence; the potential for fostering creativity through education and training; the maximization of creativity for national economic benefit, and the application of creative resources to improve the effectiveness of teaching and learning.
Creative ability was measured in a study using convergent tasks, which require a single correct answer, and divergent tasks, which requires producing many different answers of varying correctness. Two types of convergent tasks used were, the first being a remote associates tasks, which gave the subject three words and asked what word the previous three words are related to. The second type of convergent thinking task were insight problems, which gave the subjects some contextual facts and then asked them a question requiring interpretation.
For the remote associates tasks, the convergent thinkers correctly solved more of the five remote associates problems then did those using divergent thinking. This was demonstrated to be significantly different by a one-way ANOVA. In addition, when responding to insight problems, participants using convergent thinking solved more insight problems than did the control group, however, there was no significant difference between subjects using convergent or divergent thinking.
For the divergent thinking tasks, although together all of the divergent tasks demonstrated a correlation, they were not significant when examined between conditions.
Assessing individual creative ability
There was a creativity quotient developed similar to the intelligence quotient (IQ). It makes use of the results of divergent thinking tests (see below) by processing them further. It gives more weight to ideas that a radically different from other ideas in the response.
J. P. Guilford’s group, which pioneered the modern psychometric study of creativity, constructed several tests to measure creativity in 1967:
Plot Titles, where participants are given the plot of a story and asked to write original titles.
Quick Responses is a word-association test scored for uncommonness.
Figure Concepts, where participants were given simple drawings of objects and individuals and asked to find qualities or features that are common by two or more drawings; these were scored for uncommonness.
Unusual Uses is finding unusual uses for common everyday objects such as bricks.
Remote Associations, where participants are asked to find a word between two given words (e.g. Hand _____ Call)
Remote Consequences, where participants are asked to generate a list of consequences of unexpected events (e.g. loss of gravity)
Building on Guilford’s work, Torrance developed the Torrance Tests of Creative Thinking in 1966. They involved simple tests of divergent thinking and other problem-solving skills, which were scored on:
Fluency – The total number of interpretable, meaningful, and relevant ideas generated in response to the stimulus.
Originality – The statistical rarity of the responses among the test subjects.
Elaboration – The amount of detail in the responses.
Such tests, sometimes called Divergent Thinking (DT) tests have been both supported and criticized.
Considerable progress has been made in automated scoring of divergent thinking tests using semantic approach. When compared to human raters, NLP techniques were shown to be reliable and valid in scoring the originality (when compared to human raters). The reported computer programs were able to achieve a correlation of 0.60 and 0.72 respectively to human graders.
Semantic networks were also used to devise originality scores that yielded significant correlations with socio-personal measures. Most recently, an NSF-funded team of researchers led by James C. Kaufman and Mark A. Runco combined expertise in creativity research, natural language processing, computational linguistics, and statistical data analysis to devise a scalable system for computerized automated testing (SparcIt Creativity Index Testing system). This system enabled automated scoring of DT tests that is reliable, objective, and scalable, thus addressing most of the issues of DT tests that had been found and reported. The resultant computer system was able to achieve a correlation of 0.73 to human graders.
Some researchers have taken a social-personality approach to the measurement of creativity. In these studies, personality traits such as independence of judgement, self-confidence, attraction to complexity, aesthetic orientation, and risk-taking are used as measures of the creativity of individuals. A meta-analysis by Gregory Feist showed that creative people tend to be “more open to new experiences, less conventional and less conscientious, more self-confident, self-accepting, driven, ambitious, dominant, hostile, and impulsive.” Openness, conscientiousness, self-acceptance, hostility, and impulsivity had the strongest effects of the traits listed. Within the framework of the Big Five model of personality, some consistent traits have emerged. Openness to experience has been shown to be consistently related to a whole host of different assessments of creativity. Among the other Big Five traits, research has demonstrated subtle differences between different domains of creativity. Compared to non-artists, artists tend to have higher levels of openness to experience and lower levels of conscientiousness, while scientists are more open to experience, conscientious, and higher in the confidence-dominance facets of extraversion compared to non-scientists.
An alternative are biographical methods. These methods use quantitative characteristics such as the number of publications, patents, or performances of a work. While this method was originally developed for highly creative personalities, today it is also available as self-report questionnaires supplemented with frequent, less outstanding creative behaviors such as writing a short story or creating your own recipes. For example, the Creative Achievement Questionnaire, a self-report test that measures creative achievement across 10 domains, was described in 2005 and shown to be reliable and valid when compared to other measures of creativity and to independent evaluation of creative output. Besides the English original, it was also used in a Chinese, French, and German-speaking version. It is the self-report questionnaire most frequently used in research.
Creativity and intelligence
The potential relationship between creativity and intelligence has been of interest since the late 1900s, when a multitude of influential studies – from Getzels & Jackson, Barron, Wallach & Kogan, and Guilford – focused not only on creativity, but also on intelligence. This joint focus highlights both the theoretical and practical importance of the relationship: researchers are interested not only if the constructs are related, but also how and why.
There are multiple theories accounting for their relationship, with the 3 main theories as follows:
Threshold Theory – Intelligence is a necessary, but not sufficient condition for creativity. There is a moderate positive relationship between creativity and intelligence until IQ ~120.
Certification Theory – Creativity is not intrinsically related to intelligence. Instead, individuals are required to meet the requisite level intelligence in order to gain a certain level of education/work, which then in turn offers the opportunity to be creative. Displays of creativity are moderated by intelligence.
Interference Theory – Extremely high intelligence might interfere with creative ability.
Sternberg and O’Hara proposed a framework of 5 possible relationships between creativity and intelligence:
Creativity is a subset of intelligence
Intelligence is a subset of creativity
Creativity and intelligence are overlapping constructs
Creativity and intelligence are part of the same construct (coincident sets)
Creativity and intelligence are distinct constructs (disjoint sets)
Creativity as a subset of intelligence
A number of researchers include creativity, either explicitly or implicitly, as a key component of intelligence.
Examples of theories that include creativity as a subset of intelligence
Gardner’s Theory of multiple intelligences (MIT) – implicitly includes creativity as a subset of MIT. To demonstrate this, Gardner cited examples of different famous creators, each of whom differed in their types of intelligences e.g. Picasso (spatial intelligence); Freud (intrapersonal); Einstein (logical-mathematical); and Gandhi (interpersonal).
Sternberg’s Theory of Successful intelligence (see Triarchic theory of intelligence) includes creativity as a main component, and comprises 3 sub-theories: Componential (Analytic), Contextual (Practical), and Experiential (Creative). Experiential sub-theory – the ability to use pre-existing knowledge and skills to solve new and novel problems – is directly related to creativity.
The Cattell–Horn–Carroll theory includes creativity as a subset of intelligence. Specifically, it is associated with the broad group factor of long-term storage and retrieval (Glr). Glr narrow abilities relating to creativity include: ideational fluency, associational fluency, and originality/creativity. Silvia et al. conducted a study to look at the relationship between divergent thinking and verbal fluency tests, and reported that both fluency and originality in divergent thinking were significantly affected by the broad level Glr factor. Martindale extended the CHC-theory in the sense that it was proposed that those individuals who are creative are also selective in their processing speed Martindale argues that in the creative process, larger amounts of information are processed more slowly in the early stages, and as the individual begins to understand the problem, the processing speed is increased.
The Dual Process Theory of Intelligence posits a two-factor/type model of intelligence. Type 1 is a conscious process, and concerns goal directed thoughts, which are explained by g. Type 2 is an unconscious process, and concerns spontaneous cognition, which encompasses daydreaming and implicit learning ability. Kaufman argues that creativity occurs as a result of Type 1 and Type 2 processes working together in combination. The use of each type in the creative process can be used to varying degrees.
Intelligence as a subset of creativity
In this relationship model, intelligence is a key component in the development of creativity.
Theories of creativity that include intelligence as a subset of creativity
Sternberg & Lubart’s Investment Theory. Using the metaphor of a stock market, they demonstrate that creative thinkers are like good investors – they buy low and sell high (in their ideas). Like under/low-valued stock, creative individuals generate unique ideas that are initially rejected by other people. The creative individual has to persevere, and convince the others of the ideas value. After convincing the others, and thus increasing the ideas value, the creative individual ‘sells high’ by leaving the idea with the other people, and moves onto generating another idea. According to this theory, six distinct, but related elements contribute to successful creativity: intelligence, knowledge, thinking styles, personality, motivation, and environment. Intelligence is just one of the six factors that can either solely, or in conjunction with the other five factors, generate creative thoughts.
Amabile’s Componential Model of Creativity. In this model, there are 3 within-individual components needed for creativity – domain-relevant skills, creativity-relevant processes, and task motivation – and 1 component external to the individual: their surrounding social environment. Creativity requires a confluence of all components. High creativity will result when an individual is: intrinsically motivated, possesses both a high level of domain-relevant skills and has high skills in creative thinking, and is working in a highly creative environment.
Amusement Park Theoretical Model. In this 4-step theory, both domain-specific and generalist views are integrated into a model of creativity. The researchers make use of the metaphor of the amusement park to demonstrate that within each of these creative levels, intelligence plays a key role:
To get into the amusement park, there are initial requirements (e.g., time/transport to go to the park). Initial requirements (like intelligence) are necessary, but not sufficient for creativity. They are more like prerequisites for creativity, and if an individual does not possess the basic level of the initial requirement (intelligence), then they will not be able to generate creative thoughts/behaviour.
Secondly are the subcomponents – general thematic areas – that increase in specificity. Like choosing which type of amusement park to visit (e.g. a zoo or a water park), these areas relate to the areas in which someone could be creative (e.g. poetry).
Thirdly, there are specific domains. After choosing the type of park to visit e.g. waterpark, you then have to choose which specific park to go to. Within the poetry domain, there are many different types (e.g. free verse, riddles, sonnet, etc.) that have to be selected from.
Lastly, there are micro-domains. These are the specific tasks that reside within each domain e.g. individual lines in a free verse poem / individual rides at the waterpark.
Creativity and intelligence as overlapping yet distinct constructs
This possible relationship concerns creativity and intelligence as distinct, but intersecting constructs.
Theories that include Creativity and Intelligence as Overlapping Yet Distinct Constructs
Renzulli’s Three-Ring Conception of Giftedness. In this conceptualisation, giftedness occurs as a result from the overlap of above average intellectual ability, creativity, and task commitment. Under this view, creativity and intelligence are distinct constructs, but they do overlap under the correct conditions.
PASS theory of intelligence. In this theory, the planning component – relating to the ability to solve problems, make decisions and take action – strongly overlaps with the concept of creativity.
Threshold Theory (TT). A number of previous research findings have suggested that a threshold exists in the relationship between creativity and intelligence – both constructs are moderately positively correlated up to an IQ of ~120. Above this threshold of an IQ of 120, if there is a relationship at all, it is small and weak. TT posits that a moderate level of intelligence is necessary for creativity.
In support of the TT, Barron reported finding a non-significant correlation between creativity and intelligence in a gifted sample; and a significant correlation in a non-gifted sample. Yamamoto in a sample of secondary school children, reported a significant correlation between creativity and intelligence of r = .3, and reported no significant correlation when the sample consisted of gifted children. Fuchs-Beauchamp et al. in a sample of preschoolers found that creativity and intelligence correlated from r = .19 to r = .49 in the group of children who had an IQ below the threshold; and in the group above the threshold, the correlations were r = <.12. Cho et al. reported a correlation of .40 between creativity and intelligence in the average IQ group of a sample of adolescents and adults; and a correlation of close to r = .0 for the high IQ group. Jauk et al. found support for the TT, but only for measures of creative potential; not creative performance. Much modern day research reports findings against TT. Wai et al. in a study using data from the longitudinal Study of Mathematically Precocious Youth – a cohort of elite students from early adolescence into adulthood – found that differences in SAT scores at age 13 were predictive of creative real-life outcomes 20 years later. Kim’s meta-analysis of 21 studies did not find any supporting evidence for TT, and instead negligible correlations were reported between intelligence, creativity, and divergent thinking both below and above IQ's of 120. Preckel et al., investigating fluid intelligence and creativity, reported small correlations of r = .3 to r = .4 across all levels of cognitive ability. Creativity and intelligence as coincident sets Under this view, researchers posit that there are no differences in the mechanisms underlying creativity in those used in normal problem solving; and in normal problem solving, there is no need for creativity. Thus, creativity and Intelligence (problem solving) are the same thing. Perkins referred to this as the ‘nothing-special’ view. Weisberg & Alba examined problem solving by having participants complete the 9-dot problem (see Thinking outside the box#Nine dots puzzle) – where the participants are asked to connect all 9 dots in the 3 rows of 3 dots using 4 straight lines or less, without lifting their pen or tracing the same line twice. The problem can only be solved if the lines go outside the boundaries of the square of dots. Results demonstrated that even when participants were given this insight, they still found it difficult to solve the problem, thus showing that to successfully complete the task it is not just insight (or creativity) that is required. Creativity and intelligence as disjoint sets In this view, creativity and intelligence are completely different, unrelated constructs. Getzels and Jackson administered 5 creativity measures to a group of 449 children from grades 6-12, and compared these test findings to results from previously administered (by the school) IQ tests. They found that the correlation between the creativity measures and IQ was r = .26. The high creativity group scored in the top 20% of the overall creativity measures, but were not included in the top 20% of IQ scorers. The high intelligence group scored the opposite: they scored in the top 20% for IQ, but were outside the top 20% scorers for creativity, thus showing that creativity and intelligence are distinct and unrelated. However, this work has been heavily criticised. Wallach and Kogan highlighted that the creativity measures were not only weakly related to one another (to the extent that they were no more related to one another than they were with IQ), but they seemed to also draw upon non-creative skills. McNemar noted that there were major measurement issues, in that the IQ scores were a mixture from 3 different IQ tests. Wallach and Kogan administered 5 measures of creativity, each of which resulted in a score for originality and fluency; and 10 measures of general intelligence to 151 5th grade children. These tests were untimed, and given in a game-like manner (aiming to facilitate creativity). Inter-correlations between creativity tests were on average r = .41. Inter-correlations between intelligence measures were on average r = .51 with each other. Creativity tests and intelligence measures correlated r = .09. Working memory and the cerebellum Vandervert described how the brain's frontal lobes and the cognitive functions of the cerebellum collaborate to produce creativity and innovation. Vandervert's explanation rests on considerable evidence that all processes of working memory (responsible for processing all thought) are adaptively modeled for increased efficiency by the cerebellum. The cerebellum (consisting of 100 billion neurons, which is more than the entirety of the rest of the brain) is also widely known to adaptively model all bodily movement for efficiency. The cerebellum's adaptive models of working memory processing are then fed back to especially frontal lobe working memory control processes where creative and innovative thoughts arise. (Apparently, creative insight or the "aha" experience is then triggered in the temporal lobe.) According to Vandervert, the details of creative adaptation begin in "forward" cerebellar models which are anticipatory/exploratory controls for movement and thought. These cerebellar processing and control architectures have been termed Hierarchical Modular Selection and Identification for Control (HMOSAIC). New, hierarchically arranged levels of the cerebellar control architecture (HMOSAIC) develop as mental mulling in working memory is extended over time. These new levels of the control architecture are fed forward to the frontal lobes. Since the cerebellum adaptively models all movement and all levels of thought and emotion, Vandervert's approach helps explain creativity and innovation in sports, art, music, the design of video games, technology, mathematics, the child prodigy, and thought in general. Essentially, Vandervert has argued that when a person is confronted with a challenging new situation, visual-spatial working memory and speech-related working memory are decomposed and re-composed (fractionated) by the cerebellum and then blended in the cerebral cortex in an attempt to deal with the new situation. With repeated attempts to deal with challenging situations, the cerebro-cerebellar blending process continues to optimize the efficiency of how working memory deals with the situation or problem. Most recently, he has argued that this is the same process (only involving visual-spatial working memory and pre-language vocalization) that led to the evolution of language in humans. Vandervert and Vandervert-Weathers have pointed out that this blending process, because it continuously optimizes efficiencies, constantly improves prototyping attempts toward the invention or innovation of new ideas, music, art, or technology. Prototyping, they argue, not only produces new products, it trains the cerebro-cerebellar pathways involved to become more efficient at prototyping itself. Further, Vandervert and Vandervert-Weathers believe that this repetitive "mental prototyping" or mental rehearsal involving the cerebellum and the cerebral cortex explains the success of the self-driven, individualized patterning of repetitions initiated by the teaching methods of the Khan Academy. The model proposed by Vandervert has, however, received incisive critique from several authors. REM sleep Creativity involves the forming of associative elements into new combinations that are useful or meet some requirement. Sleep aids this process. REM rather than NREM sleep appears to be responsible. This has been suggested to be due to changes in cholinergic and noradrenergic neuromodulation that occurs during REM sleep. During this period of sleep, high levels of acetylcholine in the hippocampus suppress feedback from the hippocampus to the neocortex, and lower levels of acetylcholine and norepinephrine in the neocortex encourage the spread of associational activity within neocortical areas without control from the hippocampus. This is in contrast to waking consciousness, where higher levels of norepinephrine and acetylcholine inhibit recurrent connections in the neocortex. It is proposed that REM sleep adds creativity by allowing "neocortical structures to reorganize associative hierarchies, in which information from the hippocampus would be reinterpreted in relation to previous semantic representations or nodes." Affect Some theories suggest that creativity may be particularly susceptible to affective influence. As noted in voting behavior, the term "affect" in this context can refer to liking or disliking key aspects of the subject in question. This work largely follows from findings in psychology regarding the ways in which affective states are involved in human judgment and decision-making. Positive affect relations According to Alice Isen, positive affect has three primary effects on cognitive activity: Positive affect makes additional cognitive material available for processing, increasing the number of cognitive elements available for association; Positive affect leads to defocused attention and a more complex cognitive context, increasing the breadth of those elements that are treated as relevant to the problem; Positive affect increases cognitive flexibility, increasing the probability that diverse cognitive elements will in fact become associated. Together, these processes lead positive affect to have a positive influence on creativity. Barbara Fredrickson in her broaden-and-build model suggests that positive emotions such as joy and love broaden a person's available repertoire of cognitions and actions, thus enhancing creativity. According to these researchers, positive emotions increase the number of cognitive elements available for association (attention scope) and the number of elements that are relevant to the problem (cognitive scope). Various meta-analyses, such as Baas et al. (2008) of 66 studies about creativity and affect support the link between creativity and positive affect. Creativity and artificial intelligence Jürgen Schmidhuber's formal theory of creativity postulates that creativity, curiosity, and interestingness are by-products of a simple computational principle for measuring and optimizing learning progress. Consider an agent able to manipulate its environment and thus its own sensory inputs. The agent can use a black box optimization method such as reinforcement learning to learn (through informed trial and error) sequences of actions that maximize the expected sum of its future reward signals. There are extrinsic reward signals for achieving externally given goals, such as finding food when hungry. But Schmidhuber's objective function to be maximized also includes an additional, intrinsic term to model "wow-effects." This non-standard term motivates purely creative behavior of the agent even when there are no external goals. A wow-effect is formally defined as follows. As the agent is creating and predicting and encoding the continually growing history of actions and sensory inputs, it keeps improving the predictor or encoder, which can be implemented as an artificial neural network or some other machine learning device that can exploit regularities in the data to improve its performance over time. The improvements can be measured precisely, by computing the difference in computational costs (storage size, number of required synapses, errors, time) needed to encode new observations before and after learning. This difference depends on the encoder's present subjective knowledge, which changes over time, but the theory formally takes this into account. The cost difference measures the strength of the present "wow-effect" due to sudden improvements in data compression or computational speed. It becomes an intrinsic reward signal for the action selector. The objective function thus motivates the action optimizer to create action sequences causing more wow-effects. Irregular, random data (or noise) do not permit any wow-effects or learning progress, and thus are "boring" by nature (providing no reward). Already known and predictable regularities also are boring. Temporarily interesting are only the initially unknown, novel, regular patterns in both actions and observations. This motivates the agent to perform continual, open-ended, active, creative exploration. According to Schmidhuber, his objective function explains the activities of scientists, artists, and comedians. For example, physicists are motivated to create experiments leading to observations obeying previously unpublished physical laws permitting better data compression. Likewise, composers receive intrinsic reward for creating non-arbitrary melodies with unexpected but regular harmonies that permit wow-effects through data compression improvements. Similarly, a comedian gets intrinsic reward for "inventing a novel joke with an unexpected punch line, related to the beginning of the story in an initially unexpected but quickly learnable way that also allows for better compression of the perceived data." Schmidhuber argues that ongoing computer hardware advances will greatly scale up rudimentary artificial scientists and artists[clarification needed] based on simple implementations of the basic principle since 1990. He used the theory to create low-complexity art and an attractive human face. Creativity across cultures Creativity is viewed differently in different countries. For example, cross-cultural research centred on Hong Kong found that Westerners view creativity more in terms of the individual attributes of a creative person, such as their aesthetic taste, while Chinese people view creativity more in terms of the social influence of creative people e.g. what they can contribute to society. Mpofu et al. surveyed 28 African languages and found that 27 had no word which directly translated to 'creativity' (the exception being Arabic). The principle of linguistic relativity, i.e. that language can affect thought, suggests that the lack of an equivalent word for 'creativity' may affect the views of creativity among speakers of such languages. However, more research would be needed to establish this, and there is certainly no suggestion that this linguistic difference makes people any less (or more) creative; Africa has a rich heritage of creative pursuits such as music, art, and storytelling. Nevertheless, it is true that there has been very little research on creativity in Africa, and there has also been very little research on creativity in Latin America. Creativity has been more thoroughly researched in the northern hemisphere, but here again there are cultural differences, even between countries or groups of countries in close proximity. For example, in Scandinavian countries, creativity is seen as an individual attitude which helps in coping with life's challenges, while in Germany, creativity is seen more as a process that can be applied to help solve problems. Source from Wikipedia