8

Creative problem solving

Creative insight can take the form of noticing similarities between things that you (or perhaps nobody) had ever noticed before. In other words it is a kind of creative analogical problem solving. “Aha! Now I see why this printer is sticking! It’s the same as the problem I had with the vacuum cleaner!” The analogy could be much more significant, though: “Aha! Now I see why the speed of light is constant irrespective of the relative motion of the observer!” One view of creativity is that it involves a novel and often insightful combination of pre-existing ideas. Using similarities between concepts or objects is most often seen in literature and the arts. In literature it is often manifest in the use of metaphor and simile. We have already seen the metaphor used by Cotton (2014): “Guilt is the toothache of the soul”; and that used by Ashton (2015) to describe an attribute of creative individuals: “Confidence is a bridge. Certainty is a barricade.”

The street artist Banksy uses metaphor as satire in much of his graffiti, such as an angel wearing a flak jacket and pigeons carrying placards saying “migrants go home” and looking menacingly at a small African migrant bird. Combinations of ideas are not restricted to the arts: “It is obvious that invention or discovery, be it in mathematics or anywhere else, takes place by combining ideas” (Hadamard, 1945/1996, p. 29). Mednick (1962, p. 221) said much the same thing some years later when he stated that creative thinking involved “the forming of associative elements into new combinations which either meet specified requirements or are in some way useful”. It is very likely that Ada, Lady Lovelace, was able to combine her knowledge of mathematics with what she learned from corresponding with Charles Babbage about his analytical engine to see the potential applications as a general purpose computer, and to write an algorithm for calculating Bernoulli numbers (arguably one of the first computer algorithms).

It may or may not be obvious that combining ideas is the mother of invention but it is not uncommon. Table 8.1 has some examples of biomimicry where nature can be the analogical source of ideas to solve problems, such as using the shape of a kingfisher’s beak to help design the nose of the Japanese Shinkansen bullet train.

Some of these sources have no obvious surface similarity to the target on the surface but we can nevertheless see that there is an underlying similarity in each case. Water pumps, for example, are man-made mechanical devices usually made of metal and wood. Water is drawn in through an inlet pipe and forced out through an outlet pipe by the action of a revolving metal or rubber armature or by the action of a piston. The heart is not made of metal, has no pipes, and does not have an internal revolving armature of any kind. In fact, the operating principles of water pumps and the heart are entirely different, and yet we have no problem with seeing the heart as a pump. As pointed out in Chapter 3, there are differences between the source and target that do not matter and similarities that do matter.

Table 8.1 Mappings of natural phenomena to technological innovations

Source	Maps to	Target	Analogiser
burrs sticking to dog’s fur		Velcro	Georges de Mestral
bones of human ear operated by thin and delicate membrane		telephone	Alexander Graham Bell
water pumps		the heart	William Harvey

Breaking free of self-imposed constraints

Creative problem solving is usually seen as breaking free of self-imposed constraints:

There are also constraints imposed by the environment or culture. Up until the beginning of the 20th century it was difficult getting recognition for your work if you were a woman. Emmy Noether has been described by celebrated mathematicians including Einstein as the most important woman in the history of mathematics. She developed theories of symmetry in physics and in abstract algebra among many other areas. Her particular cultural constraint was that she was not allowed to teach officially at university, although she taught unpaid, as the view among many at the University of Göttingen was that allowing a woman to be a salaried lecturer would apparently lead to something like the collapse of civilisation.

Copernicus was able to produce a simpler model of the movements of planets than that of Ptolemy some 14 centuries earlier by putting the Sun rather than the Earth at the centre of the known universe. However, this system maintained a 2,000-year-old constraint that the planets must move in circles as a circle was a perfect shape. Some 60 years after Copernicus, Kepler found that the only way to properly explain the movements of the planets was to assume they orbited in ellipses, which went against everything he had assumed: “Who am I, Johannes Kepler, to destroy the divine symmetry of the circular orbits!” (quoted in Koestler, 1970, p. 208). Indeed, there may be great resistance to new ideas or alternative representations of a problem.

Indeed it can sometimes cost you your life if you go against received wisdom and put forward a contrary view from before the time of Galileo (who lost his) to those who suffered in Mao Zedong’s Cultural Revolution. Others suffer mere ridicule, from Turner Prize winners to scientists who try to overturn accepted ideas, such as Barry J. Marshall and J. Robin Warren who argued that Helicobacter pylori was a major cause of stomach ulcers. They were not taken seriously until Marshall published results of what happened when he infected himself with the bacterium. As Koestler points out, society has to be ready to accept a new revolutionary idea that anyone dares to put forward in science and the arts, from superstring theory to half sheep in formaldehyde.

Rather than break free of constraints, either self-imposed or imposed by a society’s self-evident beliefs, some artists deliberately impose them on themselves to enhance their creativity. This can be seem in so-called lipogrammatic novels written without using a particular letter of the alphabet, such as Gadsby by Ernest V. Wright (1939) and La Disparition by Georges Perec (1969), both written without using the letter “e” (see also Biskjaer & Halskov, 2011).

Studying creativity

Creativity has been studied from a variety of perspectives. Some writers argue that it is or has been hard to define (e.g., Plucker, Beghetto, & Dow, 2004; Runco, 2004; Sweller, 2009) and others that the definition is straightforward (Feist, 2004; Lubart & Guignard, 2004). Part of the reason for this inconsistency is the fact that different people examine creativity from different angles. Thus some define creativity in terms of creative products, some in terms of creative individuals, some in terms of personality profiles, some in terms of cognitive processes. Indeed, Amabile (1996) devotes an entire chapter to the “Meaning and Measurement of Creativity”. There is, however, a general agreement that creativity involves the ability to produce work that is novel, “non-obvious” (Simonton, 2011), high in quality (as judged by appropriate observers) and appropriate – a useful, correct or valuable response to task constraints (Amabile, 1996). The task is also deemed to be heuristic rather than algorithmic, the latter involving the kind of processes appropriate to everyday problem solving and well-defined problems rather than creative problem solving – what Lubart and Mouchiraud (2003) refer to as “canned” problem solving using pre-established learned procedures or schemas. Creative problem solving also tends to involve divergent thinking rather than convergent, although a blend of both may be needed to produce a creative product.

Of course, there are occasions when an individual might produce something or think of something that is novel and insightful for them personally. Someone might invent something and then search through patent libraries only to find that it has been invented already by someone else. There is therefore a distinction to be made between personal creativity and public creativity. Boden (1992, 1996) has called the first of these two senses psychological creativity or P-creativity, and the second historical creativity or H-creativity. A somewhat similar distinction is captured by the terms big-C creativity and little-c creativity. Little-c creativity is involved in everyday problem solving and in the ability to adapt to change. Big-C creativity is the kind of creativity that wins prizes or awards or lasting fame (Simonton, 2012b). The latter is the kind that is novel, valued by society, and high in quality, although little-c and Big-C creativity form a continuum from the mundane to the exalted.

Creative individuals

A sculpture such as Walking Madonna by Elizabeth Frink, a song such as “Every Breath You Take” by The Police, a symphony such as Beethoven’s Ninth, a device such as Gutenberg’s printing press, a film such as Casablanca by Michael Curtiz – all are creative products that are appreciated by the culture into which they were born. In order to understand how such creative products came about, one way is to study the people who created them. The first to attempt this was Galton (1869) who wrote about “hereditary genius”, although by the 1892 edition he regarded this title as unfortunate. To him “a person who is a genius is deemed as – A man endowed with superior faculties” (p. vii) (women do not therefore come under this definition, although the Brontës as a family are mentioned). His view was that genius was something men were genetically endowed with in a variety of fields (judges, statesmen, commanders, men of science, painters, divines and oarsmen, among others). That said, “[it] appears to be very important to success in science, that a man should have an able mother” (p. 196).

A discussion of creative individuals relates to the extent to which creativity is a generalisable skill or an attribute of someone skilled in a particular domain. Opinions differ but the differences depend on what is being measured. Kaufman and Baer (2004) titled one section of their chapter “How domain specific skills and traits may appear to be domain general”. A later chapter in the same book is titled “Why creativity is domain-general, why it looks domain-specific, and why the distinction does not matter” (Plucker & Beghetto, 2004). An analysis of novel ideas, artefacts or inventions suggests domain specificity whereas successfully improving students’ achievement in educational settings (where little-c creativity may be important) requires domain general skills. Creativity at the “genius” level comes through long experience, skill and knowledge – expertise, in short. For example, Kaufman and Baer (2004) argue that creativity is linked to specific domains and even to specific tasks (see also Lubart and Guignard, 2004). Looking at a more mundane level than that of creative geniuses, they claim there is little correlation between judgements of creativity in artefacts from different domains produced by the same person, but there is evidence of higher correlations among task-specific tasks than domain-specific tasks. In short, Lubart and Guignard (2004, p. 15) argue that “Hawking and Madonna should keep their day jobs.”

Since Galton there have been many studies of eminent, creative individuals by looking at their biographies – the historiometric approach (e.g., Cattell & Drevdahl, 1955; Eysenck, 1995; Gardner, 1993; Roe, 1952) – their creative products and how they arose (e.g., Ashton, 2015; Simonton, 2015; Weisberg, 1986) and their occasional psychopathology (e.g., Acar & Runco, 2012; Carson, 2014; Ludwig, 1995; Simonton, 2014). Some of the anecdotes arising from the autobiographical approach led Wallas (1926) to the conclusion that creative thinking went through a series of stages, namely preparation, incubation, illumination (also called “inspiration” or insight) and verification.

Preparation

Preparation involves data gathering and familiarisation with the topic such as how to get a heavier than air machine to fly under its own power, how to compose a musical, how to create a new molecule with specific properties and so on. According to Simon (1966), biographies of famous scientists demonstrate how much background work is done investigating the problem space with much trial and error search through a vast space of alternative hypotheses. Both Weisberg (1986) and Damian and Simonton (2011) give the example of the many preliminary sketches produced by Picasso during the creation of Guernica. Ashton (2015) outlines the range of practical and theoretical knowledge the Wright brothers accumulated as they attempted to design and fly the first aeroplane. There was much combining, deletion and reworking of elements to produce the final version of both Guernica and the Flyer. Each recombination then underwent some critical analysis to produce the next version. Simonton discusses the ways in which Galileo went about his work (Simonton, 2012a) and provides a detailed account of Edison’s work trying to perfect the first viable light bulb (Simonton, 2015).

Looked at in this way, the early stages of the creative process are no different from any other type of problem solving that involves a search through a problem space. There are often intermediate solutions that have to be evaluated in the light of new constraints that emerge which may eliminate non-viable solutions. Indeed, the process often involves finding out what the constraints are.

Incubation

One possible outcome of all this work is an impasse. As we saw in the previous chapter, the research on insight has shown that some types of problem solving can lead to a blockage and that further work just leads to a mental rut leading nowhere. Some of the anecdotes in the literature on creative ideas seem to suggest that taking a break from the work allowed unconscious processes to operate while the person was engaged in an unrelated activity, such as going for a walk or simply daydreaming. The most cited cases are those of Kekulé and Poincaré. Kekulé claimed that the structure of the benzene molecule on which he had been working and getting nowhere came to him as he was daydreaming; Poincaré, who had given up on some arithmetic problems he was working on, suddenly saw that they were related to non-Euclidean geometry as he was walking beside the sea. Paul McCartney claims he composed the melody of Yesterday in a dream. The lyrics took a long time to come until some single words came to him that would fit and allowed him to complete the song (the working title up till then was apparently “Scrambled Eggs”).

Smith and Blankenship (1991) induced a mental set or fixation prior to getting participants to generate responses to the Remote Associates Test (RAT) in a number of experiments. For example, the triad “river-note-blood” was paired with distractors such as “lake-music-wound” – related associates – or with unrelated associates such as “omen-April-grouch”. The solution to this particular RAT was “bank”. They found that a period of incubation allowed the participants in the fixation conditions to find the solution, but no incubation effect was found for those who are not subjected to the fixation manipulation. They argued that the effect was due to fixation “losing its potency” which in turn relates to the much earlier view put forward by Simon (1966) of “selective forgetting” during incubation. Using a similar procedure (although without including an incubation period), Storm, Angello and Bjork (2011) conclude that “creative cognition may rely not only on one’s ability to remember but also on one’s ability to forget” (p. 1292).

Illumination (insight)

As we have seen, following an impasse we may, if we are lucky, suddenly see the answer or the route to the answer. At this point the incubation period, assuming there is one, comes to an abrupt end with a sudden insight or illumination.

Verification and evaluation

The final stage of Wallas’s system is one where solutions are evaluated or verified. It’s one thing to come up with an insight into what would happen if you chased a beam of light, as Einstein reportedly did in his teens, but quite another to prove it, which he eventually did 7 years later. Verification means checking to see if the solution or artefact is an appropriate one given the nature of the problem the engineer or artist or poet has imposed upon herself. Andrew Miles spent 6 years trying to prove Fermat’s Last Theorem and eventually presented it at a conference in 1993. However, there was a flaw in his proof. Over a year later, on 19 September 1994, he discovered how to get round the flaw and published the final proof in 1995.

For a somewhat simpler and less time-consuming verification of an insight, try the problem at the beginning of Activity 8.1 before reading the solution and its verification.

The traditional insightful answer is that he juggled the balls. That way only one ball was in his hand at any one time. However, the laws of physics are against him, since every action has an equal and opposite reaction, using a force to throw a ball into the air produces an equal force in the opposite direction. Try standing on a set of bathroom scales with a heavy book at waist height and watch what happens to the needle when you raise the book quickly up to shoulder height.

Evaluation of artistic creations can vary greatly depending on culture and subculture. Not everyone likes or values drone music or the music of Strauss, paintings involving mixed media and elephant dung may leave some bemused, while the painters Fragonard and Vermeer were unappreciated when they lived and Van Gogh sold only one painting during his life. “If judgements of value can change with time, then judgements of creativity can change too. An act which is judged creative by one generation may not seem so to the next” (Hayes, 1989, p. 278).

Testing creativity

Following the measures of IQ as indicators of academic potential, various tests have been produced to measure one’s ability to engage in creative problem solving. Although most psychometric tests can give an indication of someone’s potential, they do not generally measure whether that potential is realised. The same is true of measures of “creativity” (hence the scare quotes). One measure was produced by Guilford (1950) to assess what he referred to as “divergent production”, what we now refer to as divergent thinking. This kind of thinking is usually seen as being opposed to convergent thinking with convergent thinkers preferring problems where there is a single correct answer. Divergent thinkers prefer problems that can have a variety of possible, and hopefully novel, solutions. Activity 8.2 gives some examples of the types of questions used in measures of divergent thinking.

The tests were an attempt to measure four main aspects of what was assumed to constitute creativity: fluency, originality, flexibility and elaboration.

• Fluency: Fluent thinkers should produce many responses to the stimuli.
• Originality: The number of unexpected or statistically infrequent answers among them provided one measure of the originality of a person’s thinking. Another was how remotely the answer was associated with the stimulus where respondents had to generate additional responses after their initial answer. A third measure was the extent to which judges rated the response as being “clever” (Acar & Runco, 2015).
• Flexibility: The number of times respondents switched categories in response to an item was a measure of flexibility.
• Elaboration: The degree of detail in any response.

Despite attempts to measure creativity in the same way as one measures abilities or personality traits, a clear relationship between such measures of creativity and creative accomplishments in real life has not always been found. That is, divergent thinkers may not be H-creative. Okuda, Runco, and Berger (1991) found that problem finding was more predictive of creative accomplishments than other measures of creativity such as divergent thinking. It is also possible to arrive at a novel solution to a problem using convergent thinking.

Another feature of creativity research is that there appear to be some personality variables that are shared among creative individuals from whatever field. Fürst, Ghisletta and Lubart (2014) produced a hierarchical account of creative behaviour by linking the cognitive processes to the Big Five personality traits framework. Thus creative individuals tend to achieve high scores on Openness to experience, which includes fantasy, intellectual curiosity, a preference for novelty and variety, and so forth along with an inability to inhibit irrelevant ideas. Extraversion tends to be associated with measures of creativity and divergent thinking. High scores on Neuroticism are associated with artistic creativity but less so with scientific creativity. Conscientiousness tends to be more associated with scientists than artists but lower scores on this measure have been found to be associated with highly creative scientists (Feist, 1998). Finally Agreeableness is a trait that is not associated with creative individuals who are generally less socialised, less tolerant and less deferent than less creative individuals. Based on these personality profiles and on the cognitive processes linked to them, Fürst et al. (2014) developed three overarching personality “super-factors”: Divergence, Convergence and Plasticity, which were linked to Extraversion and Openness, along with Inspiration and Positive Affect. Plasticity and Divergence were found to be associated with the Generation aspect of creative problem solving and Convergence predicted the Selection processes (see the next section).

Theories of creativity: generation, evaluation and selection

Outside of the research on special individuals, theories of the origin of creativity generally belong to the business-as-usual view of creativity and insight. Most involve some form of generate–evaluate–select process. For example, Finke, Ward and Smith (1996) argue that creative cognition is an essential property of normal human cognition. Their Geneplore model assumes various general cognitive processes including generation of initial ideas, based on relatively incomplete mental representation of the task called pre-inventive structures, and exploration of those candidate ideas. The generative processes are largely unconscious and involve retrieving information (structures) from long-term memory, synthesising or transforming those existing structures to create new ones, essentially a form of between-domain analogical transfer. Exploration involves exploring the attributes of the mental structures in the pre-inventive stage, evaluating them from different perspectives including the practical and/or conceptual limitations they imply.

Bink and Marsh (2000) produced a general framework for creative behaviour based on Geneplore and other similar models (e.g., Runco & Chand, 1995). The framework includes the two main aspects: Generation and Selection. Generation encompasses those aspects associated with divergent thinking including fluency, flexibility and originality. Selection includes evaluation of ideas generated, criticism, formalisation, and elaboration of ideas – essentially these involve convergent rather than divergent thinking.

A stage of idea generation forms part of a theory of creativity based on Darwinian evolution where ideas are generated in a trial and error process out of which variants are selected for further evaluation (Simonton, 1999; Sweller, 2009). Simonton (2011, 2012c) has championed Campbell’s (1960) account of creativity as Blind Variation and Selective Retention (BVSR). Campbell regarded creativity as the outcome of blind and serendipitous generation of ideas. “As long as the probabilities of any generated responses are decoupled from their utilities, the responses are blind without the necessity of being random” (Simonton, 2011, p. 169). While this may be the case, particularly in the arts, much creative endeavour is goal oriented (“How do I make a wind-up radio?”). Simonton refers to a “blindness–sightedness” continuum involving the admixture of chance and expertise in creativity.

Another view of the relation between evolution and creativity is provided by Sweller (2009) who regards creativity as a form of random generate-and-test activity but one that relies on a huge information store (e.g., expertise). He not only sees an analogy between evolution and creativity but also points out that “evolution by natural selection not only created humans, it presumably also created human creativity” (Sweller, 2009, p. 12).

Lee and Johnson-Laird (2004) argue that there are three algorithms that can be involved in creative problem solving, although their view is that much problem solving is a creative process anyway, as it often involves the generation of ideas that are novel for the individual (P-creativity). They also point out that much problem solving involves experiencing a series of problems allowing the solver to explore the problem space and gain experience of tactics (their experiment used matchstick “shape” problems where new shapes had to be produced by moving matches). Different algorithms can be used depending on the level of experience:

1. 1  A neo-Darwinian algorithm, in which individuals unfamiliar with a problem type may at first randomly choose steps and then evaluate their consequences. The algorithm includes two stages: one in which ideas are generated through arbitrary combinations and modifications of existing elements, and a second where they are evaluated to filter out inappropriate ideas and select viable ones. The selected ideas may be recycled through the generative stage.
2. 2  A neo-Lamarckian algorithm uses long-term memory and experience to constrain the generation of ideas. Since constraints have already been applied, any variants created are likely to be of potentially equal value, so creative production becomes a question of selection from among those variants. In their experiments, their participants did not often use this algorithm, or at least not without false steps.
3. 3  A multi-stage algorithm is the result of acquiring tactical knowledge about the problem. The focus shifts to the generative stage and constraints are applied to both the generation and evaluation stages.

Lee and Johnson-Laird pose the question of whether these strategic changes constitute insight, or possibly a series of small insights. However, whether such insights in matchstick puzzles constitutes creativity is a moot point.

The variation–selection views of creativity have been criticised by various researchers. The blind variation aspect of Simonton’s theory has been particularly criticised (e.g., Gabora, 2007; Sternberg, 1998; Weisberg, 2000). Ohlsson (2011, p. 73) has argued that “variation-selection, as applied to creativity, is not an explanatory principle but a logical necessity. If the solution does not work, the problem solver has only two choices: generate another solution – that is, vary the approach – or give up.”

Can creativity be taught?

If we know the processes involved in creative problem solving, then it is presumably possible that creativity can be taught or enhanced – a view espoused by many (e.g., DeHaan, 2009; Livingston, 2010; Marquis & Henderson, 2015; Schlee & Harich, 2014; Simonton, 2012c; Sternberg, 2015; Treffinger & Isaksen, 2005). One just has to look at the number of books at Amazon.com about how to boost your creative potential and/or business innovation to realise this, and there are countless companies that will help you do it.

CoRT

There have been several programmes and curricula that offer to enhance creative problem solving often aimed particularly at business processes but also at education. De Bono (1967) introduced the concept of “lateral thinking” to an unsuspecting world, essentially pointing out the need to shift from one inappropriate problem representation to a new one to break out of an impasse. He went on to develop a series of thinking courses. The CoRT Thinking Tools course has six topics and includes 60 lessons. The first list in Information Box 8.1 shows the six topics, and the second indicates the thinking tools involved in the first topic. The course has been very widely used and there is much anecdotal evidence of its effectiveness, however relatively little research has been published. The website http://www.cortthinking.com/front-page-experimental-research-and-graphs lists a number of experiments and references three studies by Edwards and Baldauf in the 1980s (Edwards & Baldauf, 1983, 1986, 1987).

Synectics

Synectics (the fusion of disparate unrelated ideas) uses “metaphorical processes to make the familiar strange and the strange familiar” (Gordon, 1961). It tends to be used by companies seeking to innovate and involves a sequence of steps shown in Information Box 8.2.

There is relatively little in the way of published research on the effectiveness of synectics but plenty of papers about the techniques. Meador (1994) found no difference in creativity scores among gifted children between those who received training in synectics and those who did not, however non-gifted children improved their creativity scores after synectics training. Two short papers from Iran (Aiamy & Haghani, 2012; Tajari & Tajari, 2011) compared traditional teaching with synectics training with school students. Both found an increase in creativity scores (Torrance Tests of Creative Thinking, 1966) for those with synectics training using a pre-and post-testing paradigm.

Creative Problem Solving (CPS) – Osborn–Parnes

CPS, or Creative Problem Solving, is a phrase adopted by Osborn (1952, 1953) and elaborated by Parnes (1967a, 1967b) to describe a system whose aim is to enhance creative problem solving – again mainly in business contexts. The Osborn–Parnes model of Creative Problem Solving has gone through various versions and has now reached version 6.1 (Treffinger, Isaksen, & Stead-Dorva, 2006). The method encourages divergent problem solving at various stages especially at the problem definition (problem framing), data exploration, idea generation and solution finding stages. Information Box 8.3 describes one early version and the most recent.

Some of these stages were reframed as components of an overall strategy (Isaksen & Treffinger, 1991; Treffinger & Isaksen, 1992) to allow greater flexibility in how the individual components might be used for different problems. The latest version includes these in a graphic with the three main components shown as being linked in a circle rather than as a sequence of stages (Information Box 8.4).

These programmes, aimed at boosting creative potential, are systematic ways of generating potential solutions to found problems. They are in a sense algorithms for generating problem solving heuristics due to the way they structure the stages or components.

Sternberg (2015) has argued that despite the voluminous literature on teaching for creativity and despite the evidence that it can raise educational achievement (Sternberg, Torff, & Grigorenko, 1998), it does not appear to be happening. Sternberg et al. (2014) found that scaling up the earlier Sternberg, Torff and Grigorenko study seemed to be ineffective. Sternberg (2015) puts this down to three main influences: standardised testing, teacher education, and entrenchment. Standardised testing mitigates against the production of creative answers; this is particularly true when the testing involves multiple choice questions. Teacher education is implicated because teachers teach new teachers how to do things so the form of teaching is perpetuated. Entrenchment means that people are unwilling to change how they do things. In assessments where the examiners are expecting specific answers, creative answers are not going to do well.

Summary

Creativity is a many-splendoured thing and can be investigated from a number of points of view.

1. 1  Creative insights can occur by breaking free of constraints, either some kind of mental set or through the influence of society or domain-specific “self-evident” beliefs.
2. 2  Creativity involves work that is novel, “non-obvious”, high in quality, and a useful, correct or valuable response to task constraints (Amabile, 1996).
3. 3  Creative insights can be personal and small scale (P-creativity or little-c creativity) or can be novel and valued by society (H-creativity or Big-C creativity).
4. 4  Three main approaches have been discussed:
   • Special person view: This sees creativity as the province of “genius” or at least of experts with a wealth of knowledge. This is Big-C domain-specific creativity. Being domain-specific the methods used by artists, writers and scientists are likely to be very different (Simonton, 2012c).
   • Personality trait view: This is domain-general and can be investigated by looking at the personalities and aptitudes of individuals (openness to experience, motivation, divergent thinking, etc.) including their psychopathology. This view covers both Big-C and little-c creativity.
   • Creativity as teachable view: This involves teaching techniques to enhance creativity – using heuristics to produce creative products (mainly little-c creativity).
5. 5  Wallas suggested four stages of creativity (preparation, incubation, illumination and verification) to explain some of the anecdotal accounts of creative insights.
6. 6  There are many articles about how to promote creativity in education, but not many on how well interventions work or whether they are actually happening.