Tuesday, March 18, 2008

Educational Perspectives

Chapter Six in the book Creativity by Mark A. Runco is titled Educational Perspectives. It looks at education and creativity from a number of angles. I am an art educator who teaches at a middle school in Western New York. What was most interesting to read about was the idea of creativity and teacher expectations.

Runco (2007) stated “The implicit theories about children’s creativity held by teachers are extremely important because they lead directly to expectations, and expectations are very powerful influences on students’ behavior” (p. 184). This statement fascinates me because I have experienced the influence of my expectations on my students. Being an art teacher, I want to foster the most creative learning environment that I can for my students. However, sometimes a child’s reputation will precede them and then my expectations of that child change. It is strange that despite my best efforts, sometimes a student’s behavior can effect my expectations of them and in turn have an adverse effect on their creative performance. I, and all educators, should give each child a level playing field, so to speak. Sometimes, I underestimate the impact of my expectations and attitude toward students. It is interesting to think that their performance in my class is a direct reflection of what I expect from them. I am trying to become more aware of this with each passing day in the classroom. Colleagues talk about how the “good” kids always do well and the “bad” kids always perform poorly. Could this be because the “bad” kids are labeled that way and expected to perform sub par and so they fulfill that expectation?

There is truth to the theory of teacher expectations and creativity. I try to be as unbiased as I can in the classroom, expecting the same level of behavior and performance from all of my students. Especially in the art classroom, many children think that they need to possess some form of innate artistic talent, that they cannot learn the skills they need to perform well. This is exactly how some people view creativity. In my classroom, it is emphasized that creativity and artistic skill can be learned and that art class is the place to learn it. Runco (2007) also talked about how people in the United States view creativity and child performance compared to how the Asian culture views creativity and performance. In the U.S., performance is attributed to innate talent. In Asian culture, performance is viewed as a “reflection of motivation and effort” (Runco, p. 187). I believe that the American culture would greatly benefit from the Asian perspective of performance. Young people are very quick to use the excuse of “I am not artistically talented”. This is also true in subjects such as math, science and music. Students’ achievement would greatly increase if they looked at performance as a reward for hard work and motivation. If teachers set their expectations of hard work and motivation high, their students will rise to meet them.

Runco, M. A (2007). Creativity theories and themes: Research, development and practice.
-- Melanie Baehre, Graduate Student

Monday, March 17, 2008

Cognition versus creativity: a musical example

What cognitive processes occur when a pianist sits down to play Bach’s Prelude in C? Bach wrote the piece approximately 250 years ago, and left “directions” for how to play it via a musical score: basically, coded pen marks on lined paper. Today a pianist can learn the piece by following Bach’s directions and by pulling on his own domain expertise. There is little doubt that several cognitive skills will be called upon to execute the tasks: translating the meaning of symbols on the paper to certain keys on the piano, choosing the best fingers to use, making decisions about phrasing and articulation, and putting the knowledge together into a chain of movement that sounds, in the end, like music (hopefully, Bach’s Prelude). There is a certain amount of intelligence needed to achieve the performance of a such a piece of music. Was there a need for creativity?

Next, consider that the same performer wished to “do his own thing”. He has probably played the piano for some time, has listened throughout his life to music in a variety of styles. There are patterns of key strokes that his fingers have grown accustomed to executing, as a result of hours of practice. So he approaches the piano keyboard with many influences and engrained techniques. He also has certain preferences and a level of physical agility. What will be the result of this pianist attempting to improvise a song based on the Bach Prelude? Is this a more creative endeavor than the task of learning the piece as Bach wrote it? And are the skills needed similar, different, or a combination of the two? Furthermore, will a simple determination on the player’s part to produce something original yield a creative result? What will be the role of the subconscious?

The improviser has a greater chance of producing an original song if he is an expert in his field and has a large amount of domain knowledge. The larger the pool of knowledge (inputs), the more combinations he may be able to generate (for diverging). And with more experience, an improviser might also have an edge in recognizing good combinations (for converging). Of course, he might also fall into habitual modes of operating and produce similar products over and over.
However, this brings up an interesting point: in the view of Welling (in press), all new combinations are constructed from and therefore dependent on previously known elements. Does this constitute creativity? Is recombination really a valid part of the creative process?

Perhaps what really matters is how far we push the envelope. A recombination at an elemental level could have millions of permutations, and certainly from among them there might be something not seen before. If creativity is evaluated by the resultant product, it might seem that an uncreative, cognitive, linear process could result in something novel and useful.

But how can we handle the daunting test of filtering through so many variations? It’s just not efficient (or possible) to evaluate them all one by one. A computer is limited as well, as it would have to be programmed to recognize novelty and that is usually what’s unknown. We may know novelty when we see it, but computers don’t work that way! Also, returning to the pianist, how does he cope with the pressure of generating musical variations within the constraints of an improvised performance? Is it possible for him to think quickly enough to plan and execute every note?

Enter the role of intuition and the subconscious. At one level, the subconscious provides the script for the everyday routines we do. For a pianist, certain movements can get ingrained over time, and that allows him to think at a higher level of musicality while his fingers execute the technical procedures. But that also means that an attempt to be creative through improvised playing could turn out to be just a stale reiteration of notes. Again, a new combination doesn’t guarantee creativity. There has to be more.

Sometimes a musician has a feeling of being in a flow, or a feeling of metacognition. He has tapped into a higher level of processing, and he is both directing and being directed. He ceases to struggle as entire pre-assembled chunks of data emerge ready to be inserted into the improvisation. It is not a conscious process completely. It often feels like the process just “happens”. Somehow, despite conscious limitations in cognition, the musician’s mind is able to rapidly combine and evaluate perhaps thousands of musical combinations in a very short time. How is this possible?

Perhaps what seems like random outputs from our subconscious into our conscious are the signs of a hidden operating system that works below our level of awareness. At its best, it seems to serve as “judge, jury and executioner”, producing well-formulated ideas that evoke an “a-ha!”. But we don’t get all the steps along with it--just the final idea. That void can leave us with the impression that the solution was “magical”.

If we cannot connect the dots through logic, does it mean that the solution is illogical? It only implies that the steps are unknown. It also means that there is much to learn about “non-traditional” intelligences and we should keep an open mind about the things we don’t yet understand.

Please feel free to listen to the link for a musical example: The song begins on track 4 with the Bach Prelude in C presented as it was originally composed. Then the piece begins again with new material added in (composed by the performer ahead of time). The piece concludes at track 5 with a full, freestyle improvisation based on the first two measures of the prelude. Listen to see if you can “hear” the cognitive and/or creative processes occurring. Arrangement and performance by Pam Szalay.

-- Pam Szalay, Graduate Student

Wednesday, March 12, 2008


Since Stanley Kubrick’s 2001: A Space Odyssey (1968), and the rebellion of computer system HAL 9000 against it’s human peers in outer space, there has been an almost morbid desire to one day see the rising of sentient artificial machines (terminator, AI, I-robot, etc.) capable not only of high order cognitive processes but moreover, of emotion, affective and creative behavior. According to artificial intelligence guru Hugo de Garis, who has worked extensively with neural networks, genetic algorithms and self-evolvable hardware, he claims that we are not far from producing artificial brains that will be infinitely more intelligent that we humans may consciously be (Satinover, 2001).

Within the field of creativity, it is starting to be acknowledged that it will be difficult to get further insight into the underlying principles of creativity from further psychological experimentation. Hence, despite the flashes of fiction and fantasy (which day-to-day are more real), AI becomes an immensely rich field of study that indeed might yield new insight into the understanding of the creative phenomenon. The main reasons for the above claim are that we have the possibility to observe models of both structure and function of the brain (where creativity lives in the human being) that have been dark areas of exploration for cognitive science in past decades (of course, brain imaging revolution in neuroscience opens another door to the exploration of the human mind). Secondly, an advantage of AI for the study of cognitive functions, even over neuroscience brain imaging experiments, is that there is no ethical issue concerning experimentation and manipulation of variables, which is the case of brain scientific research in humans and non-human species.

Now, there are two main questions with regard to AI and creativity. The first and possibly the sexier one is, are AI models (machines) capable of human creativity? The second question is, how do existing AI models of creativity, though imperfect, help us understand human creativity? I would say that with the evidence we have today, the answer to the first question is no, but AI models have been capable of replicating some aspects of human creativity, specially regarding the production of products that meet the criteria of novelty and usefulness (Hennessey & Amabile, 1988; Stein, 1974; Boden, 1998). With regard to the second question, and derived from evidence from the first question, the limitations of the AI models in capturing the essence of human creative behavior cast light on those critical components of human creativity that are unique to the specie (for now…).

Boden (1998) provides a good framework to analyze AI models and creativity. She says that there a three types of creativity: (i) combinatorial process (mainly operationalized with analogies), (ii) exploratory (within a conceptual space) and (iii) transformational, or shifts in the conceptual space so that a new conceptual space allows alternatives that would have been otherwise impossible in the old one. If we observe closer the above types of creativity described, it resembles Kirton’s (1976) adaptive–innovative continuum where the first two types of creativity would fall into the adaptive end of the continuum, in other words, producing novelty within the prevailing system while the third into the innovative type of creativity by redefining the system.

With regard to combinatorial processes, there are AI models capable of generating analogies and relationships to generate novel products as judged by humans. This is the case of JAPE (among several models), a model that relies on domain mapping processes for generating jokes and riddles that yield fairly and reliable humorous results. Nonetheless, the problem with this model is that the domains and algorithms by which the model seeks analogies to create novel combinations are predetermined by the programmer and remain unaltered once the combination has been done (Boden, 1998). This is clearly not the case of human associative process in which, as an effect of the analogical process, the elements combined are modified from its original state. More over, the model is incapable of innovating to incorporate different analogical domains from those that were initially pre-programmed so the degree of novelty is rather constricted.

There is another set of analogical models such as COPYCAT, in which through a bottom-up computing fashion (learns as it computes), it is capable of finding context sensitive analogies to derive novel solutions. Nonetheless, how does such model know what are relevant contextual domains to draw significant analogies? As already said, this illuminates the complexity of the analogical (associative) process, which has been recognized to be a crucial cognitive process in creative thinking (Runco, 2007). The same has been confirmed by neuro-imaging studies that capture the activity of the associative cortices while subjects perform creative tasks (mainly prefrontal lobe activity) and also while they incubate on tasks (almost the whole brain!) (Stein, 2007).

The type of creativity that AI has been most successful in replicating is the type of exploratory creativity, where novelty is a result from digging deeper within a conceptual space. In this sense, computational power, combination and the ability to scan huge databases of information allow models to reach for concepts, ideas and/or products that would have been practically impossible for the human mind to reach, due to our natural limitation of working memory’s capacity and ability to retrieve information and hold it online (Dietrich, 2004; Stein, 2007).
This is the case of the BACON models geared towards scientific discovery that have been able to explore exhaustibly their conceptual spaces (mathematics and physics) and replicate historical breakthrough concepts such as finding Kepler’s law, Boyles’s law and Ohm’s law among others. In addition, some of these models have even produced new breakthroughs in the field of mathematics that have led to scientific patents.
However, there are two drawbacks to the above example. The first of these is that there is a bias or manipulation from the experimenter in wanting to model to find something and hence directing its efforts towards that goal that is preconceived by the experimenter. In this, since the model has no way to know with out its human partner that it has reached, rediscovered or discovered a breakthrough concept. The second drawback is derived from the latter, which is it lacks a mechanism of making meaning out of what is finding and assigning value to the different options. This is extremely important for it is depicting a crucial aspect of the creative process in humans that is beyond the computational power of combinations and permutations. Accordingly, it seems that what defines creativity is the mechanism by which we judge novelty and usefulness and negotiate our perception of novelty and usefulness with society for acceptance (Simonton's 5th “P”, persuasion).

In another vein of thought, AI experiments reveal that seeking novelty by breaking out of the conceptual space is also a distinctive characteristic of human creativity. For example, model/machine EMI is capable of reproducing and composing music that resembles Mozart or Bach (or Charlie Parker), and its compositions may be judged to be even composed by Mozart or Bach in tests of blind judgments by humans. Yet, EMI is incapable of breaking out of the particular style of either composer at will. The same is true to the model AARON, which is capable of producing artwork of human pictures (even painting them) that have been regarded as true pieces of artwork and exhibited in galleries around the world. Nonetheless, although each picture is unique, each of them is with no doubt bound to a certain style that the model cannot break away. This is why the third type of creativity has been the most difficult to model in AI, transformational creativity.

Even so, there are a few models that have been able to perform transformational creativity that is, defining new conceptual spaces with each iteration or production. This is the case of models based on genetic algorithms, basically blind variation of components and in this case in particular, variations in the heuristics or sets of rules by which the model produces combinations. With this kind of model, it is possible to have products that by no means resemble their previous iteration, hence truly define a newly conceptual space (like if the EMI machine was capable of composing like Mozart and then by free choice, do it like Miles Davis!). Nevertheless, the question is, how does the model know that the newly conceptual space is of any value at all (either to the model or to humans)? We could think that a set of values could be pre-programmed into the model but with that, we are already killing a priori potential novel landscapes and moreover, by definition, the set of pre-assigned values will not be valid for the new conceptual space.

This is the major drawback of AI models and at the same time a big insight to human creativity, the ability to have self-criticism and evaluate (give meaning) upon a set of relevant and contextual criteria. In other words, it is crucial to creativity the ability by which we can generate novel set of criteria to appreciate a new conceptual space and shift of paradigm. In this sense, what we like or what we dislike, why we get aroused by a piece of artwork or music or why we get excited with a new scientific breakthrough has to do with our emotional appreciation and perception of our inner and outer world and the latter, has not been replicated by any AI model up to date. Perhaps, an AI model is capable of breaking the conceptual space to yield transformational creative products but we are certain that the machine doesn’t jump in excitement when it does so, it is not aware that it has done so and furthermore, has no specific purpose to the creation.

The latter might be the most crucial aspect of human creativity, the overall drive and purpose of creator even when he deliberately allows chance to rule his creative process. Somehow, his purpose and motives are embedded in the creation and we, as observers, are able to appreciate it. Personally I get thrilled and mesmerized that something novel and useful was the output of the human mind.

Regardless of the past imperfections in AI models, the field keeps moving forward in full thrust in its quest to replicate the human brain. Perhaps a holistic approach, as opposed to trying to replicate individual cognitive functions, might yield the expected result of a sentient model/machine (hence capable of creativity!). This is the case of the BLUE BRAIN project (SEED magazine, February 2008). In the basement of Lausanne University in Switzerland a group of neurologist and computer scientists, with the use of supercomputers, have already replicated successfully a two-week-old rat neocortical column containing 10.000 neurons (built a artificial neural network). The only thing stopping them to scale their project up is computing power and energy. Nonetheless, Henry Markram, head of the project is confident that in the next years they will be able to scale up their project to produce the first conscious machine and he says: “I think it will be just as interesting, perhaps more interesting, if we can’t create a conscious computer. Then the question will be: What are we missing? Why is this not enough?” Personally I have mixed feelings if I want to see conscious machines in my lifetime but to be honest, curiosity devours me.


Boden, M. A. (1998). Creativity and artificial intelligence. Artificial Intelligence, 103, 347-356.
Dietrich, A. (2004). The cognitive neuroscience of creativity. Psychonomic Bulletin & Review, 11(6), 1011-1026.

Hennessey, B. A., & Amabile, T. M. (1988). Story-telling: A method for assessing children’s creativity. Journal of Creative Behavior, 22, 235-246.

Kirton, M. J. (1976). Adaptors and innovators: A description and measure. Journal of applied psychology, 61, 622-629.

Stein, K. (2007). The genius engine: Where memory, reason, passion, violence, and creativity intersect in the human brain. Hoboken, NJ: John Wiley & Sons, Inc.

Satinover, J. (2001). The quantum brain: The search for freedom and the next generation of man. New York: John Wiley & Sons, Inc.

Stein, M. I. (1974). Stimulating creativity. Individual procedures. New York: Academic Press.

Runco, M. A (2007). Creativity theories and themes: Research, development and practice.

-- Diego Uribe, Graduate Student

Saturday, March 8, 2008

Culture and Creativity

Each of us is a product of our culture. Culture has a major impact on our development, values, thinking, and behavior. Collectivism vs. individualism is one of the major differences between cultures throughout the world. In a collectivist society, loyalty to the larger in-group is given in exchange for the group’s protection. Typical of people in Asia and the East is the search for guidance from their in-group, either from respected authority figures or from instilled traditions from the past. Eastern values allow certain personalities to exist and inhibit others. In the West, individuality is encouraged, rewarded and expected. A person must care for his own self and his immediate family; this teaching being a result of a well established work ethic. Playfulness and humor may be acceptable only in certain groups (e.g., children) and are often looked down upon when actual work needs to be done. Of course this is a generalization; there are Westerners who have collectivist tendencies, just as there are Easterners who are individualistic.

Creativity has a cultural context. Our backgrounds, instilled values, and upbringing influence our creativity. Varying cognitive skills may be developed to adapt to a particular environment since different skills are valued in a range of cultures. Eastern and Western cultures each have creative potential, but because of the different domains and behaviors, these potentials cannot be directly compared. The same criteria for ranking and standards do not apply to all cultures. Creativity in and of itself can be difficult to measure, and when comparing creativity between cultures, this task becomes even more confusing. Perhaps the place where one is born has a major impact on the perceived level of creativity one develops.

-- Terry Reding, Graduate Student

Wednesday, March 5, 2008

A New Eco-sociological Perspective to Understanding Creativity

Figure 1

Figure 2

Figure 3

Figure 4

A New Model
Every day we interact with different domains, their products, and their processes. The model of creativity that is presented here is an attempt to help identify a sustainable cycle of creativity. Before I go on any further, I would like to preface this brief article acknowledging that there is no set way to look at creativity. Resources and dynamic exchanges direct the efforts of a creative product; further complicating this are the cultures within which the product is made. This model attempts to provide a new eco-sociological perspective to what has been a relatively stable method of understanding creativity (see Figure 1).

In 1961, Mel Rhodes developed the 4 P’s of creativity. Here I advocate for a fifth P of persuasion to include in the model. As this model attempts to capture, persuasion plays a very integral part in a product (the physical manifestation of an idea) being adopted into a domain of the press. Depending on the level of the domain, Runco (2006) identified social factors that can support, undermine, or do neither for its acceptance into a given domain. If the product gains acceptance into either one of the domains, then it becomes a part of the press, where it becomes either internalized by the person in the form of a value or a perception (p. 162) of the press or as a tangible tool as a part of the process (see Figure 2).

Runco makes a strong statement towards the end of the chapter that recognizes that creativity exists within cultures and within those cultures are organizations. Expanding upon this statement, I would argue that the press should be separated by various domains to address what shapes a person’s perception and what influences the creative product. These domains are containers that hold all the relevant data, meant in the broadest sense to include all forms of viable capital including natural, social, personal, and man-made. The boundaries and scopes of these domains limit the creativity that is able to seen at the lower levels. For example, the environmental laws of the United States, which exist within a governmental domain, limit the amount of lead paint that can be used in children’s toys.

In 2007, The U.S. Consumer Product Safety Commission and Kids II, Inc. recalled 35,000 units of Baby Einstein Color Blocks due to excessive levels of lead paint. (Affairs, 2007) With manufacturers in China, any standard, none of which I am aware, of lead paint appears acceptable. Because the product was developed in another culture, which is not as aware of lead paint’s effects as the US, and the two governments do not regulate the amount of lead similarly, the product was not acceptable for sale.

This creativity model recognizes that effort needs to be undertaken by the two governments to handle the lead paint issue if the product is to enter the desired domain of its consumer. However, the use of lead paint is unacceptable in the natural domain since it contaminates waterways, and there is a general consensus in the cultural level that lead paint should not even be used in the product.

Arguably, this graphic model is over-simplified, and the previous example is limited. However, this model is not limited. There are at least 5 different worldviews about nature that would change this model appearance, such as the worldview developed by Rhodes that seemed to ignore it altogether or Isaksen, Dorval, and Treffinger (2000) breakdown of the press to include the natural environment as only a small consideration in the press.

A Systematic Flow: Fire
This representation to the left is an example of how a creative product such as fire might have been developed. 15,000 years ago, the Aborigines are thought to have landed in Australia. They brought with them their own value systems and fire. Because it was a useful item that was accepted because it was useful, testable, easily used, effective, adaptable, fire was extensively to settle the northern outback. The Aborigines have been recognized for using it for communication, cooking, clearing land, and controlling wildfires. With all of these benefits, there has come a price. Some researchers have pointed to the extensive use of fire by the Aborigines as being one of the major reasons for the extinction of a giant emu-like bird and either creating or speeding up the desertification of northern Australia. Due to the changes in climate and prey by their use of fire, their culture and other domains had to adapt to the very processes and product that they used (see Figure 3).

A Simple Flow: The Memo
Suzanne, an intern, writes a memo to her supervisor telling her about a trend that she notices from MTV and how they might be able to capitalize upon it. Upon receipt, her supervisor reads it and tosses the piece of paper into the trash. Suzanne comes from another culture than her boss who looked at her idea with disdain. The influences of the various domains started the trend from culture that Suzanne noticed and believed to be of value to her organization. Using the established processes such as using a piece of paper to write her idea, she sent the memo to her boss, who is within the higher organizational domain. The memo ends up trashed where it degrades in the natural environment. During the process of degradation, the paper becomes a part of another cycle some time at a future date (see Figure 4).

Isaksen, S. G., Dorval, K. B., & Treffinger, D. J. (2000). Creative approaches to problem solving. Dubuque, IA: Kendall/Hunt Publishing Company.

Rhodes, M. (1987). An analysis of creativity. In S. G. Isaksen, ed., Frontiers of creativity research: Beyond the basics. Buffalo, NY: Bearly Limited.

Runco, M. A. (2006). Creativity: Theories and themes: Research, development, and practice. Burlington: Academic Press.

-- Aaron Gilbee, Graduate Student

Tuesday, March 4, 2008

Making explicit the mental and personality relationships between the problem and solution.

Ever since my first day of courses in the creative studies program, I have noticed the struggle between logic and emotion that is tapped when a truly creative solution is developed. This graphic model is my own depiction of what I expect the relationships to be and helps me to understand the interdependency between the most crucial concepts discussed in courses. I treat key concepts as being distinct but related to a larger whole.

Before I continue, I have one main caveat. My background is in Communications, with an emphasis in Public Relations and Broadcasting, so there might be muddling and confusion of these concepts and their relationships. These relationships were identified during a reading log write up over chapter 1 of Runco's Creativity Theories and Themes: Research, Development and Practice in CRS 580. I offer this model up for discussion and debate for further modification.

At first the process of deriving solutions appears easy. Once a problem is found, a solution is enacted. However, the solution may not be the right one because a person had not considered affective side of a solution or he never considered the rationale behind his decision. It is notable that change initiatives that are based upon pure cognition or pure emotion result in failure. When based upon pure emotion, solutions will face challengers that will comment that how the solution was not well thought out; vice versa, solutions based on pure thought will counter resistance from people who feel the solution is "too cold". (Please take these following examples lightly) In recent politics for example, President Bush has been satirized by comedians for relying on "his gut" and not considering the consequences of his actions by the more intellectual Left. On the flip side, movements, such as Six Sigma, tend to frustrate people as being too logical and handling complex situation too simply. This comes from my personal experience as a son of a government employee who went through numerous black belt changes. When approaching a solution, there are two main routes: pure rationality expressed through cognition or pure emotion represented through affect. Granted that this is an oversimplification, but this distinction was identified by Jung when he identified the thinker and feeler types. Based upon this personality preference, a person will approach a problem in a very logical manner or have a gut feeling as to what the solution might be.

By making the distinction in the personality preference, one can identify the appropriate line of self-questioning that fits with a certain approach. For thinkers, meta-cognition addresses how they came to the thoughts that become a part of solution. For feelers, mindfulness should be able to clarifying why they felt what they felt. Under stress conditions, this might flip. Before arriving at a solution, there should be a balance struck between cognition and affect to develop a full understanding of the solution. The processes of Wallace's creative cognition cycle (preparation, incubation, illumination, and verification) appear here. In my limited exposure to Wallace's work, I get the impressions that incubation can be seen as the process of intuition and that illumination as the process of insight. Both processes to appear to be subconscious. Explanations of the incubation stage describe it as an "unconscious processing of information", which would benefit the feeler to develop their solutions and help them to rationalize their emotions. Essentially giving them a period of cooling off so that they can collect their thoughts and maybe identify important relationships they had not seen before. Explanations of illumination, or referred to as insight, describe it as the process of applying one domain's mental framework over another. At the end of the insight, it is accompanied by emotional catharsis. By allowing the processes of insight and intuition the time to develop, the following solution could be verified among peers.

Jung, C. G. (1933). Psychological types. New York: Harcourt.

Runco, M. A. (2006). Creativity: Theories and themes: Research, development, and practice. Burlington: Academic Press.

Wallas, G. (1926). The art of thought. New York: Harcourt.

-- Aaron Gilbee, Graduate Student