The Study of Creativity and Intelligence in Theory and Practice Kenny L. Hicks and Randall W. Engle Georgia Institute of Technology 1 Abstract Despite decades of scholarship devoted to its importance, the cognitive drivers of creative behaviors and products remain poorly understood. Although previous research has proposed a relationship between the convergent processes of creativity and higher order cognition, studies investigating the relationship between divergent thinking and fluid intelligence have revealed little to no relationship between the two. In this article, we review the noteworthy scholars and debates in the field of creativity and the various methodological approaches used to define the construct. We propose that previous failures to find a relationship between intelligence and creativity are due, in part, to researchers’ emphasis on the differences between the two constructs instead of focusing on their commonality. In this study, we view the creativity construct through the lens of problem-solving across spatial and verbal domains. Using a simple scoring procedure that rates verbal and spatial creative responses, we show some of the most robust relationships between measures of creativity and intelligence to date. Further, our results demonstrate that creativity, verbal fluency, and fluid intelligence share many of the same cognitive processes. Keywords: Creativity, Divergent Thinking, Convergent Thinking, Fluid Intelligence, Working Memory Capacity, Torrance Test of Creativity An Introduction to Creative Faculties 2 For well over a century, researchers have tried to understand the nature of creativity through individual differences in both the quality and quantity of creative ideas. H. L. Hargreaves was one of the first to conduct empirical research on the issue in his large-scale correlational study of creativity in 1927. The work was ahead of its time, and it received little attention. This was likely due to Hargreaves finding that creativity consisted of multiple factors, which contradicted the g theory put forward by his mentor, Charles Spearman (1927). Hargreaves was also the first researcher to combine both the experimental and correlational methods to study creativity across a wide range of intelligence and memory tasks. What is unique about this early work on creativity is that it is the first attempt to distinguish the quantity of ideas a subject can generate (fluency) and the quality of the ideas they could generate (originality). Although Hargreaves speculated that both intelligence and memory were important factors in the creative process, he could not commit to a clear theoretical account for two reasons. First, many of the tests he used demonstrated poor reliability. The second issue is that he could not distinguish between the number of ideas a subject could generate and the quality of those ideas. This result has been replicated many times and has led many researchers to conclude that verbal fluency and creativity are in fact the same ability (Simonton, 1985). In other words, subjects who generate more responses are more likely to generate higher quality responses. Unfortunately, the field of creativity hasn’t advanced much since Hargreaves’ work, and the cognitive mechanisms driving creative thought remain poorly understood. Researchers investigating the nature of intelligence have become a victim of their own success to some degree. The rise of better methodologies, paradigms, and theoretical accounts of the construct have led to widespread disagreements about its underlying nature. Although research interest in the field of creativity rivals that of intelligence, researchers have made little 3 progress toward understanding or measuring the construct. Unlike other areas of psychological research and practice, the study of creativity has fallen behind in both theoretical and applied advancements. This criticism is echoed in nearly every review of creativity research since the 1960s, across several branches of psychology including educational psychology (Jackson & Messick, 1965; Cronbach, 1968; Hocevar, 1979: 1981; Plucker, Qian, & Wang, 2011), organizational psychology (Mumford & Gustafson, 1988), cognitive psychology (Horn, 1976; Eysenck, 1994), and more recently in neuroscience (Dietrich, 2006). Human Abilities In the concluding remarks of Human Cognitive Abilities, John Carroll wrote that no factor has “scientific status unless it is restated to refer to the abilities that compose it” (1974). In other words, the most informative constructs are those that are linked to more simple cognitive processes. Understanding how subjects use and allocate cognitive resources during activities that require novelty will be an important part of any training or development program in creative problem-solving. The processes that give rise to creative thought and skill reveal what learning goals and potential transfer, if any, we can expect from these efforts (Cronbach & Snow, 1977; Snow & Lohman, 1984). Spearman’s discovery of g relied on observations of positive manifold, which is defined as the common variance among tests of mental ability. The emergent quality of g became a powerful predictor of individual differences in selection, but its underlying nature remained a theoretical black-box. To uncover the processes that govern it and other mental abilities of potential value such as creativity, early theorists in the field of intelligence developed the underlying mathematics and instruments known today as psychometrics (Pearson, 1908; Spearman, 1904; Thurstone, 1931). Spearman’s unitary theory might have stayed a monolith in 4 the world of intelligence if Thurstone had not proposed his own perspective on the multidimensional nature of intelligence. With this insight, he took Spearman’s perspective and transformed it into a new method referred to today as factor analysis (Thurstone, 1938a). Researchers could then ask new research questions and test new theories about mental abilities, both related to and distinct from intelligence. We base our current understanding of human abilities on these early advances in classical test theory. In response to these issues, we begin our paper with a historical review of creativity, highlighting the methodological and practical challenges that have come to define its measurement. We examine the key concepts, noteworthy scholars, and crucial debates that are most relevant to the study of creativity. Creativity research is represented by a wide range of disciplinary perspectives, theoretical orientations, and methodological practices. The validity and real-world relevance of this work depends on our ability to create and discover common ground. Creativity as Problem-Solving Numerous research papers have been devoted to the problem of determining whether creative thinking is any different from the more traditional concept of intelligence. When evaluating complex constructs such as creativity, cognitive and educational psychologists have noted the similarities between popular task paradigms used in creativity and problem-solving tasks. Several researchers have described creativity tests as an advanced type of problem-solving (Newell, Shaw, and Simon, 1958; Vincent, Decker & Mumford, 2002). This link is not surprising. Tests of creativity and problem-solving both require idea and hypothesis generation, use of heuristics, evaluative thinking and likely share many common cognitive processes. Before we discuss creativity in relation to problem-solving or any particular cognitive abilities such as working memory capacity and attention, it's important to first describe the structure and 5 defining characteristics of tasks used to study creativity. Tests of creativity can be categorized as ill-defined or well-defined. A divergent thinking task is an archetypal example of an ill-defined problem (see Figure 1A). Tasks like this are unstructured, usually only guided by a short prompt or instruction (Getzels & Csikszentmihaly, 1976). Subjects are given a problem and asked to generate multiple novel strategies to solve the problem. There is no single correct or even optimal strategy for solving the problem. Figure 1. A) Divergent thinking task (ill-defined) (Torrance, 1990). B) Remote Associates Test item (well-defined). Item from the Remote Associates Test (Mednick & Mednick, 1967). Some researchers measure creativity with well-defined tasks (Figure 1B). A popular example is The Remote Associates Test, a convergent thinking task (Mednick & Mednick, 1967). These tasks share many defining characteristics with traditional measures of reasoning. Both have a clearly defined goal and a single, correct solution. During a remote associates task, 6 subjects see three word cues (associates). They have to think of a word that ties the three words together. Unlike tasks that feature ill-defined problems, these tasks require a single, correct solution. Like the first group, intelligence tests developed by the American psychologist Lewis Terman and the quick-scoring mental ability tests that followed from his student Arthur Otis, most of the cognitive tests we have used in psychological research feature well-defined problems. Well-defined problems are objective, governed by a strict set of rules that dictate how it should be solved. Ease of scoring and compiling normative data from large-scale datasets made these tasks optimal for selection and development in military and in education after WWI. As an example, refer to a matrix reasoning problem from the Raven’s Progressive Matrices Test