Several studies have suggested that the insight in problem solutions occurs unexpectedly following impasse, and that it is predominantly preconceptional (Ghiselin, 1954; Koestler, 1989; Wallas, 1926; Metcalfe & Wiebe, 1987; Schooler, Ohlsson, & Brooks, 1993; Hadamard, 1954). Both anecdotal reports of prominent thinkers (Poincare, 1952; Polanyi, 1967) and empirical research (Bowers, Regehr, Balthazard, & Parker, 1990; Metcalfe, 1986) provide evidence to support James’s (1890) claim that most of the insight occurs in the absence of words, and that it is only afterwards translated into language. Although we have previously discussed the
importance of verbal and visual stimuli in problem solving, most studies suggest that language overshadows insight (Schooler, Ohlsson, & Brooks, 1993) and that verbalisation during a creative act may cause creators to favour the manipulation of information from working memory over the information to be retrieved from long term memory. Reports from several studies on cognitive activity relying on nonreportable processes indicate vulnerability to verbalisation, i.e. learning (Reber, 1989); implicit memory (Schacter, 1987) in automated motor skills (Norman & Shallice, 1986) and creativity (Finke, 1990).
3.1.1 Visual Analogy in Insight Problem Solving
In insight problem solving, analogies have usually been used to convey a representation of the problem’s solution (the source), to which the actual problem solution can be mapped (the target). The insight problems have been cued with both verbal and visual analogies. The most relevant studies are summarised below. Analogical reasoning facilitated by visual hints has been shown to be effective in insight problem solving particularly in the case of Dunker’s radiation problem (Dunker & Lees, 1972). Findings have shown that this verbal problem can be successfully solved when visual diagrams are used as hints for the target while highlighting that they are not equally effective. For instance, consistent with previous findings, Gick and Holyoak (1983) and Pedone et al. (2001) showed that the static diagrams representing arrows converging on a focal point did not lead to a higher success than for the control group. In contrast, Beveridge and Parkins (1987) used transparent blue plastic strips, hinged together at one end, to simulate the motion and arrows to suggest the lines of force. While extending the same idea of apparent motion through animated arrows, Pedone, Hummel and Holyoak (2001) also employed longer sequences of diagrams to represent more problem states between the initial and the final state. Such visual analogies containing references to lines of force for capturing the insight for problem solving, (i.e., convergence principle for the radiation problem), were particularly effective in supporting their transfer to the target solution. We speculate that this is due to the fact that visual representations of lines of force allow immediate, non-mediated access to image schema (see Section 2.2.1.2). Catrambone et al. (2006) also argue that the limited effectiveness of the static diagrams is due to their failure to convey a spatial schema of force, whereas animated arrows are better suited to eliciting it. Catrambrone et al. (2006) further explored the role of perceptual kinaesthetic information in analogical reasoning in the radiation
problem. They showed that verbally enacting the general story as a source of analogical transfer while using wooden blocks to simulate it leads to significantly higher spontaneous transfer than both sketch and verbal conditions. This suggests that enactment made the kinaesthetic features more salient. Another insight problem where visual hints where successfully used is the 8-coin problem (Ormerod, MacGregor, & Chronicle, 2002) described in more detail in Section 2.3.4 of the previous chapter. The task requires an array of coins to be arranged by moving only two of them so that in the solution, each coin touches exactly three others. The primary insight for solving the problem requires a shift to moving the coins in three rather than two dimensions (i.e., stacking), and since this leads to two groups of coins, an additional insight is grouping. The research discussed above represents a few studies that explore visual hints in insight problem solving, and they suggest that when perceptual information is captured by the artefacts, either kinetically or kinaesthetically, their success rate is higher than when verbal hints alone are offered.
3.1.2 Visual Analogy in Creative Problem Solving
Eminent examples of scientific discoveries made by analogy have been documented throughout human history. The best known example of using remote analogy (Weisberg, 1988) or spontaneous analogising (Ball, Ormerod, & Morley, 2004) is Archimedes’s discovery (3rd century B.C.) of how to measure the volume of irregular forms. The king had asked Archimedes to determine if his crown was made of pure gold, as he had ordered, or if it contained other substitute materials. At the time, the weight per volume of pure gold was known; however, the numerous details of organic forms made it impossible to measure the crown’s volume accurately. The solution was not found until one day when Archimedes stepped into a bath and noticed that the volume of water spilling onto the floor increased as he lowered his body into the bath. The analogy suggested immersing the crown in a container of water and then measuring its accurate volume in order to answer the king’s question. Analogies are defined in terms of the similarities between the elements of the target, i.e. the mass/volume of gold in the crown, and the elements of the source, i.e. mass/volume of water displacement (Tijus & Brézillon, 2008). Based on these similarities between the source/base and the target information, cognitive psychologists have classified analogies as local, regional or remote (Weisberg, 1988). Other categorisation identifies analogies within a domain,
& Schunn, 2009). While analogies within a domain are particularly efficient in supporting creative thinking (Perkins, 1981) and problem solving (Mayer, 1999), analogies between domains support innovation and originality (Christensen & Schunn, 2009) when they capture similarities at both structural and conceptual levels. Analogies are used to explore, study, and explain phenomena in the natural world. Leonardo da Vinci studied birds in flight, various animals, and the movements of snakes, which led to various inventions (e.g., helicopter – birds, tank – tortoise, wormgear – worms) (Wamsley & Atalay, 2009). Some of these analogies can be classified as regional. Another example of using a local type of analogy is the development of the pointillist style in painting. Claude Monet’s impressionistic paintings inspired Paul Signac to scientifically experiment with the perception of colours on his canvases (Clement & Houzé, 1999). The brushstrokes were reduced to small dots of pure colour with the intention that they should blend in the eyes of viewers rather than on the canvas. The used analogy comes from the same field of painting and is classified as a local or within domain analogy.