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Thinking Skills and Creativity 6 (2011) 138– 142

Contents lists available at ScienceDirect

Thinking Skills and Creativity

j o ur nal homep age : ht tp : / /www.e lsev ier .com/ locate / tsc

ook reviews

eview of Creative Model Construction in Scientists and Students: The Role of Imagery, Analogy, and Mental Simulation,ohn Clement. (2009)

Many of us are comfortable with the belief that analogy plays an important role in the creativity process. But the ongoingebate as regards the existence of mental imagery has some of us feeling uncomfortable in relation to the mental images –he visions and simulations – we see and use. Some of us may simply need the assurance of the ‘experts’, who presumablyan tell us whether or not what we are seeing is some kind of ‘epiphenomena’. Some of us hope the pragmatist within us,ho often makes good use of mental imagery, will somehow convince our inner grumbling realist that what is useful might

ctually be real.Much of our (dis)comfort and grumbling might be resolved by reading John Clement’s outstanding analysis of the problem

olving and model construction activities of scientists and students. Clement’s analysis suggests that mental imagery – whichan itself emerge in the form of an analogy – is often very useful, and possibly even real. In fact, a close reading of Johnlement’s wonderful book, Creative Model Construction in Scientists and Students: The Role of Imagery, Analogy, and Mentalimulation, may allow some of us to finally admit that, yes, we too have dynamic visions – we too can generate analogies,estructure problems and run simulations in our minds eye.

The reality is that many of the problems scientists and students face are novel problems that require novel solutionsnd iterative, enquiry based learning. Clement makes good use of novel physics problems in his research. He then uses therotocols of scientists and students who respond to these problems as the basis for his analysis of the nonformal and formaleasoning processes that people bring to bear on a novel problem.

Importantly, Clement’s analysis points to a largely under-analysed and partially hidden world of qualitative and non-ormal, but powerful reasoning processes grounded in imagery and concrete, runnable, perceptual motor schemas that areery often used by scientists and students when they face novel problems. This contrasts with the view of scientists asbstract thinkers who use only formal logic and mathematics to solve problems. A further insight from Clement’s analysis ishat these nonformal, concrete and imagery-based problem solving processes often precede or work iteratively with moreormal, abstract, mathematical processes.

For instance, in a fascinating analysis of how students and scientists went about solving a novel physics problem usingprings (i.e., which of two springs, a narrow or a wide spring, would stretch more when an identical force was applied to it),lement details five stages and multiple mental and physical acts that facilitated the building of a model as to the workings ofprings. Some scientists began by attempting to describe mathematical workings based on known formulas, which ultimatelyailed to distinguish in particular the specific workings of narrow and broad springs. This led many to construct analogiesnd mental imagery that helped them to build a better understanding of the problem (e.g., comparing the stretch in a narrownd wide spring to the bend in a short and a long piece of wire). While many of these analogies and mental images wereound to have faults (e.g., the bending wire analogy does not help one to achieve the insight that springs work via torsion),he conflict generated as a result of failed thought experiments or failed mental simulations were often catalysts for theeveloped of further, more refined analogies and mental imagery, which helped some scientists and students to move fromimple qualitative descriptions (Stage 1) to tentative explanatory models (Stage 2), and from here to fully imageable andpatiotemporally integrated models incorporating torsion effects (Stage 3). For the rare thinker who invested their timend energy and intelligence further – Clement himself spent months on the problem – these Stage 3 integrated, imageableodels could be translated into models with increasingly geometrical levels of precision (Stage 4). Ultimately, through an

terative process of generative abduction, model evaluation, schema alignment, and mathematization, some scientists (inhis case Clement himself) worked to develop a quantitative model of the spring problem that was built upon increasinglydequate qualitative models (Stage 5).

Consistent with the reasoning of Shepard (1984) and Kosslyn (Kosslyn, 1994; Kosslyn, Thompson, & Ganis, 2006; Shepard,984), Clement considers imagery a natural way to represent perceptual properties such as shape, relative position, surfaceexture, geometrical structure, motion trajectories, and certain types of causal relationships (e.g., spatiotemporal constraintsn any system of objects). Notably, schema driven imagistic simulation is central to Clement’s theory of imagery based

871-1871/$ – see front matter

Book reviews 139

creative and constructive thinking in science. Schema driven imagistic simulation can participate in reasoning operationsand in thought experiments, which often extend schemas to cases outside their normal domain of application and tapimplicit knowledge in the schema (e.g., spatiotemporal knowledge that emerges in the context of imagistic simulation).Flexible perceptual activation of perceptual/motor schemas may also contribute to flexible analogy generation or access tonew ideas via association; and divergent ideas can also be modulated by imagistic transformations. Dual simulations canbe run simultaneously to compare and contrast models, and imagery can be used to represent multiple model constrainsefficiently. For example, similar to the processes described by Watson (1968) with regard to his discovery of the doublehelix, Clement considers how a chemist in trying to imagine what ion could be reacting with a certain crystal surface mightfirst imagine the configurations of atoms on the surface of the substrate; then imagine the size of an ion that could reactwith it; then choose a candidate molecule of a known shape; then rotate the image of the molecule in several directions toexamine if the molecule could fit into the shape of the substrate.

Thus, according to Clement, imagistic simulation is a powerful tool that scientists and students can make good use of:it can be used to generate, evaluate, and modify models in a very flexible and efficient way. Furthermore, while it is oftenassumed that scientists and students think and act in different ways when solving problems, deeper insights into the waysin which imagery, analogy, and mental simulation are used by scientists and students can help to inform teachers as to thecommon ground and the common tools that bolster creativity, reasoning, and explanatory model construction in scientistsand students alike. These insights may also have implications for teaching practice. For instance, when teaching sciencein the classroom, instead of aiming only for students to acquire static symbolic structures, the goal of instruction mightbe the development of dynamically runnable mental models of both observable phenomena and mechanisms operating“beneath” the observable phenomena being studied. Also, because many of the scientists and students in Clement’s researchused hand motions while reporting that they were running imagistic simulations, it may be that depictive hand motions,as an indicator of mental simulation processes, are an important undervalued means of communication that can contributeto both the content and process goals of teachers. In a similar vein, Clement notes how drawings, an obvious means ofcommunication that may enhance students’ use of imagery, are generally underused in the classroom. Overall, Clementbelieves that imagery enhancement techniques may be a powerful instructional tool but he also recognizes the need forfurther research in the area.

Clement also recognises the limitations in his method of analysis and he is aware that he infers certain imagery processesfrom his protocols that remain somewhat speculative and open to critical reanalysis. He highlights many processes that arestill poorly understood, including the detailed nature of imagery representations, imagery simulations and transformations,and how these are connected to the navigation and hand–eye manipulation systems; how different types of analogy, imagery,and mental simulation are sequenced and coordinated and controlled by mind and brain; how these mental operations arecoordinated with the design and implementation of real experiments (e.g., how thought experiments inform real experi-ments and vice versa); how these processes can be aided, impeded, or complemented by those from social interactions, andby external representations; how emotions can aid in or interfere with the creative process, etc. Although Clement arguesthat a certain amount of volatility at the level of elemental simulations and transformations may percolate upward andsupport more creative nonformal reasoning, model construction, and model application processes, experimental work isneeded to clarify and explain how this process might work. Clement’s qualitative analysis of protocols was certainly genera-tive – he generated a large set of candidate cognitive processes that may be critical for our understanding of creative modelconstruction – and he does an excellent job of working with this large set of cognitive processes to generate hypotheses anda preliminary theory as to workings of imagery, analogy, and mental simulation in the creative process. However, he alsorecognises that further experimental work is needed to hone in on individual hypotheses.

On another level of analysis, the great variety of cognitive processes Clement observes and the radical flexibility withwhich these cognitive processes are used by the scientists and students in his research leads Clement to ask the question:How can we hope to find any consistent processes underlying such diverse and creative behaviour? He believes that apredictive theory of creativity may be possible at a certain grain size, specifically, at a macro rather than a micro level ofanalysis (e.g., by reference to hypotheses about the rate of problem transformations at earlier versus later stages of theproblem solving process). But Clement is somewhat pessimistic about deterministic theories of creativity. One reason forthis is because he now questions the certainty and stability of physical symbol systems.

“The very units of knowledge are less predictable because they have some flexible dynamic autonomy, in contrast tostatic symbol data structures. This kind of plasticity in knowledge, discernable even in infants, is presumably what ledPiaget to search for biological metaphors for knowledge and reasoning rather than mechanical ones, and it is anotherreason for being sceptical about the possibility of a fully deterministic theory” (pp. 571–572).

It seems surprising at this point in the book that Clement does not have an aha moment and perhaps by associationrecognise four things: First, in the closing section of his book Clement is grappling with the distinction between mechanisticand organismic metaphors as a foundation stone for his model of creativity (Pepper, 1942). Second, he is grappling withhow time, change, and development are best represented and analysed in cognitive science. Third, Clement appears to be

gravitating toward an organismic and dynamic systems perspective, a perspective that is increasingly well established incognitive science and which may in its current form help to inform his model of how imagery, analogy, and mental simulationparticipate in the process of creativity and in the process of skill development (Fischer & Bidell, 2006; Fischer, Stewart, &

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40 Book reviews

tein, 2008; van Geert & Fischer, 2009). Fourth, none of these models have truly incorporated mental imagery and mentalimulation in their scheme. Herein lies a niche for the creative mind.

eferences

ischer, K. W., & Bidell, T. R. (2006). Dynamic development of action, thought, and emotion. In W. Damon, & R. M. Lerner (Eds.), Theoretical models of humandevelopment. Handbook of child psychology (6th ed., Vol. 1, pp. 313–399). New York: Wiley.

ischer, K. W., Stewart, J., & Stein, Z. (2008). Process and skill: Analyzing dynamic structures of growth. In F. Riffert, & H. J. Sander (Eds.), Researching withwhitehead: System and adventure (pp. 327–367). Munich: Verlag Karl Alber.

osslyn, S. M. (1994). Image and brain: The resolution of the imagery debate. Cambridge, MA; London: MIT Press.osslyn, S. M., Thompson, W. L., & Ganis, G. (2006). The case for mental imagery. Oxford; New York: Oxford University Press.epper, S. C. (1942). World hypotheses, a study in evidence. Berkeley and Los Angeles: University of California Press.hepard, R. N. (1984). Ecological constraints on internal representation—Resonant kinematics of perceiving, imagining, thinking, and dreaming. Psychological

Review, 91(4), 417–447.an Geert, P., & Fischer, K. W. (2009). Dynamic systems and the quest for individual-based models of change and development. In P. Spencer, M. C. S.

Thomas, & J. L. McClelland (Eds.), Toward a unified theory of development: Connectionism and dynamic systems theory re-considered (pp. 313–336). OxfordUniversity Press.

atson, J. (1968). The double helix: A personal account of the discovery of the structure of DNA. London: Weidenfeld and Nicolson.

Michael Hogan ∗

School of Psychology, NUI, Galway, Ireland

∗ Tel.: +353 91493455; fax: +353 91521355.E-mail address: michael.hogan@nuigalway.ie

URL: http://www.nuigalway.ie/psychology/m hogan page.htm

8 September 2010

Available online 12 February 2011oi:10.1016/j.tsc.2011.01.003

he Future of Education, K. Egan. Yale University Press (2008). 191 pp., $25.65, ISBN 978-0-300-11046-3

Kieran Egan is one of a small band of truly original thinkers in the realm of educational futurology. Not for him a tinkeringf the status quo, or even something as semi-radical as ‘thinking schools’. The subtitle of this fascinating book is ‘Reimaginingur Schools from the Ground Up’, and that is exactly what he attempts. The clichéd phrase ‘thinking outside the box’ is muchverused, but it is exactly what Egan encourages us to do.

Egan begins with the thought-provoking comparison of today’s educational system with the ancient Greeks’ habit ofasing their foreign policy on examining the entrails of sacrificed animals. As he observes, any contemporary Greek warrioraving the temerity to question such a policy would have been met with incredulity. The implication is that anyone daringo question the value of schools as they currently exist is likely to be met with a similar reaction.

By drawing such an analogy, Egan graphically highlights for us the often unquestioned belief that learning certain kindsf knowledge makes one a more virtuous person. He goes on to point out that current views tend to perceive the purposef schooling to be a combination of socialisation, academic advancement and child development, the success of which willepend upon achieving a proper balance. Reflecting the analysis of Zvi Lamm, Egan concludes that these intentions aresually likely to be in conflict with each other, as well as each being inherently flawed in itself. Socialisation can lead to

ndoctrination; the academic curriculum founders on what knowledge is most worth teaching and the barriers of literacy;uman development is inextricably tied to culture and social experience and differs from individual to individual. To hisind, the best that can be said for schools is that their attempts to combine these defective ideas may help to prevent any

ne of them from causing too much damage.The metaphors continue to mount up throughout this book in a highly entertaining and illuminating manner. It is full of

are asides that seem to be going off at a tangent, only to hit home with a punch line that delivers a key message. Anyoneho has heard Kieran Egan speak will recognise this rhetorical device, which is much more common in a good lecture than

n most academic texts. It often means suspending one’s judgement and following where the stories take us, but the ultimateestination makes the journey well worthwhile.

Egan’s main thesis is that education is a process in which something good is done to the mind. Its purpose, therefore, shoulde to help build in each individual a cultural and symbolic storehouse within which everyone has their own cognitive toolkit.here Egan differs from others who have previously espoused, and are currently championing, the cognitive revolution,

s in his identification of five “operating systems” that he believes should make up this toolkit. Somatic understanding

ntails getting to know how our body works and establishing our place in the world. It is maximised by “stimulation andevelopment of the senses, of humour, and of the emotions.” Mythic understanding is concerned with the development of

anguage and, in particular, its use in listening to and telling stories. Romantic understanding relates to the development andses of literacy, particularly in constructing a vivid sense of the reality in which we find ourselves. Philosophic understanding