James C. Kaufman, in
Creativity and the Performing Artist, 2017 Much of the core creativity research and theory is rooted in the arts, but writing and visual art have been more traditional subjects. Yet studies of acting, dancing, and other
performance-based arts have continued to grow, and it is my delight to introduce Creativity and the Performing Artist: Behind the Mask as the latest volume to the Explorations in Creativity Research series from Academic Press. Paula Thomson and Victoria S. Jacque have produced a comprehensive, meaningful work that is readable, grounded in the literature, and of great interest to scholars and performers alike. I hope that you will enjoy this book as much as I have!Foreword
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Theories of Creativity
A. Kozbelt, in Encyclopedia of Creativity (Second Edition), 2011
Conclusion
The variety of current creativity theories has plusses and minuses. On the plus side, there is a pluralistic array of perspectives available, which admirably attempt to understand many aspects of this complex phenomenon, which account for current data reasonably well, and which have the potential for a great deal of integration and cross-connection. On the minus side, many theories, generally speaking, have not progressed far beyond earlier speculative claims and have often failed to spark the identification of new phenomena and counterintuitive testable hypotheses. While it is too early to forecast the fate of theories of creativity, and the enterprise of studying creativity more generally, it seems likely that the two will rise or fall together. For any real conceptual progress to occur, existing theories must be continually constrained by more and better data and analyses, and generate new constructs for measurement and analysis in their turn.
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Implications of Domain Specificity for Creativity Theory*
John Baer, in Domain Specificity of Creativity, 2016
If large-scale, domain-general creativity theory is impossible, why is it so attractive? Some reasons for this have already been discussed, such as the lure of GUTs in other fields like physics8 and biology and the simple fact that life (and creativity research) would be so much easier if a single, grand unifying theory of creativity were possible. (It might also make creativity less interesting, but because such a theory is impossible, we will never know.)
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Intelligence (as Related to Creativity)
R.J. Sternberg, J.C. Kaufman, in Encyclopedia of Creativity (Second Edition), 2011
Systems Theories
In recent years, there has been an emphasis on creativity theories that incorporate factors that are interrelated. Some of these theories emphasize issues such as the environment or evolution and are less relevant here. Other theories emphasize a confluence of different elements and include intellectual and cognitive abilities in the equation. One such theory is Sternberg and Lubart's ‘investment’ theory of creativity, in which the key to being creative is to buy low and sell high in the world of ideas. In this model, a creative person is like a talented Wall Street investor. A successful creator will generate ideas that may be initially unpopular or underappreciated (as in buying stocks with low price-earnings ratios), yet will persist and convince others of the ideas’ merits. The creator will then know when to move on to pursue other ideas (as in selling high, when one divests oneself of stocks).
According to this model, six main elements contribute to creativity: intelligence, knowledge, thinking styles, personality, motivation, and the environment. Intelligence contributes using three elements drawn from Sternberg's triarchic theory (later expanded into the theory of successful intelligence).
The first element is synthetic ability, which is the ability to generate ideas that are novel, high in quality, and high in task appropriateness. Because creativity is viewed as an interaction between a person, a task, and an environment, what is novel, high in quality, or task appropriate may vary from one person, task, or environment to another. Central to this ability is being able to redefine problems. Creative people may take problems that other people see, or they themselves may previously have seen, in one way, and redefine the problems in a different way. This synthetic ability includes three knowledge-acquisition components. The first, selective encoding, involves distinguishing relevant from irrelevant information. Selective combination, the second, involves combining bits of relevant information in novel ways. Finally, selective comparison involves relating new information to old information in a novel way.
The second element, practical ability, is needed to communicate creative ideas to other people (i.e., ‘selling’ an idea). Good ideas do not always sell themselves – the creative person needs to devise strategies for and expend effort in selling those ideas.
The third component, analytical ability, is often measured by traditional intelligence tests. Yet this component is also related to creativity, as a successful creator must be able to judge the value of his or her own ideas and decide which ones to pursue. Such analytical ability can be used to evaluate the strengths and weaknesses of the idea and determine the best steps to improve upon the idea. People who are high in synthetic ability but low in analytical ability may need someone else to evaluate and judge their work for them. People who are able incisively to evaluate their own work may be said to be high in metacognition (which is related to planning, a key component of Luria's model).
There has been some empirical work on the role of metacognitive abilities in creativity. Some studies have found that people who tended to produce more original responses also were better at rating their most original responses to a divergent-thinking task. In one study, people were asked to pick their best responses to a similar divergent-thinking task, and then examined whether they were more likely to choose responses that outside raters considered creative. Research found that people were able to discern their more creative responses – and that people who were more open to experience were more likely to choose accurately.
A theory of giftedness that could be argued to be a Systems theory is Renzulli's Three-Ring Model, which proposes that giftedness is at the intersection among above-average intelligence (measured traditionally), creativity, and task commitment. The circles representing creativity and intelligence overlap. Renzulli distinguishes between two types of giftedness – schoolhouse (i.e., what would be measured by an ability or achievement test) and creative-production. Examples of his components of creativity include Guilford's divergent thinking components (fluency, flexibility, and originality), and being open to new experiences, curious, willing to take risks, and sensitive to aesthetic characteristics.
Another theory that views creativity as a mix of different abilities is Amabile's componential model of creativity. She argued that three variables were needed for creativity to occur: domain-relevant skills, creativity-relevant skills, and task motivation. Domain-relevant skills include knowledge, technical skills, and specialized talent (i.e., a creative mathematician should know basic algebra and geometry). Creativity-relevant skills are personal factors that are associated with creativity. These skills include tolerance for ambiguity, self-discipline, and risk-taking. Finally, Amabile singles out your motivation toward the task at hand. Intelligence would primarily occur at the domain-relevant skill level.
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Creativity and Innovation
Michael A. West, Claudia A. Sacramento, in Handbook of Organizational Creativity, 2012
The Importance of Context in Creativity and Innovation Theory
Climate is a contextual feature and therefore an understanding of the role of climate in creativity theory implies an understanding of the broader role attributed to the context in general. Yet, before discussing the role of context, we should start by clarifying what we mean by creativity and innovation. Innovation can be described as:
“the intentional introduction and application within a job, work team or organization of ideas, processes, products or procedures which are new to that job, work team or organization” (West & Farr, 1990, p. 9).
Innovation can be seen as encompassing two major stages, the development of ideas— creativity; followed by their implementation—the introduction of new and improved products, services, and ways of doing things at work. Although several definitions of creativity can be found in the recent organizational creativity literature, they are consensual in stressing that creativity implies novelty and usefulness (Amabile, 1988; George & Zhou, 2002; Pamela Tierney & Farmer, 2002).
In order to contextualize the importance of climate on organizational creativity and innovation it is useful to look at how this literature evolved. Organizational creativity research has its intellectual roots both in creativity research in general, which has been conducted primarily within psychology, and on macro-level approaches to the study of organizational innovation. In contrast with macro-level innovation research, which focused essentially on contextual factors but disregarded the individual (e.g., Aiken & Hage, 1971), psychology research placed less emphasis on the context and more importance on identifying the characteristics of the creative individual. For instance, the “person approach”, which represented one of the dominant schools of thought in the psychological study of creativity, conceptualized creativity as the constellation of personality and intellectual traits shown by individuals who, when given sufficient autonomy, spent significant amounts of time engaged in the creative process (Findlay & Lumsden, 1988). Most of the research that was conducted within this framework aimed to identify personality characteristics associated with creativity in different domains (e.g., Barron & Harrington, 1981; James & Asmus, 2000; MacKinnon, 1962).
The development of the social psychological approach to the study of creativity was to a great extent responsible for bringing together these two research streams, integrating the importance of both individual features and contextual characteristics (Amabile, 1983). Although these efforts had already been initiated (e.g., Baldridge & Burnham, 1975), the social–psychological approach brought a new impetus to this research agenda. Next, we briefly describe two models central to this approach, with reference to the role they attribute to the context.
Amabile’s Componential Model (1983) describes creativity as the product of the combination of three factors: domain relevant skills, which refer to factual knowledge and expertise in a certain domain; creativity-relevant skills, which refer to the strategies and cognitive styles that influence idea production; and intrinsic motivation, conceptualized as the individual’s genuine interest in the task. Amabile attributes special relevance to intrinsic motivation because this component can make the difference between what one can do (determined by domain relevant skills and creativity-relevant skills) and what one will in fact do. In other words, intrinsic motivation determines the extent to which domain relevant skills and creativity-relevant skills will be fully and appropriately applied towards successful creative performance. Amabile gives the environment a critical role in this model. The social world is given special relevance because it has the potential to influence any of the three components that are conducive to creativity, in particular intrinsic motivation. In summary, a core contribution of Amabile’s (1993) proposal is to have highlighted the role played by contextual factors such as organizational climate in influencing the individual features critical for creativity. We will refer back to this model later in this chapter when discussing organizational climate features.
The importance of context was further stressed by Woodman, Sawyer and Griffin (1993). In their multilevel, interactionist model of creativity, the authors suggest that creativity is a phenomenon that is influenced by both situational and dispositional factors. The authors propose that creativity is the product of a complex person–situation interaction influenced by events of the past as well as salient aspects of the current situation. They stress that:
“individual creativity is a function of antecedent conditions (e.g., past reinforcement history, biographical variables), cognitive style and ability (e.g., divergent thinking, ideational fluency), personality factors (e.g., self-esteem, locus of control), relevant knowledge, motivation, social influences (e.g., social facilitation, social rewards), and contextual influences (e.g., physical environment, task and time constraints)” (p. 294).
In addition, they argue that this interaction between person and situation is repeated at each level of analysis: group creativity is a function of individual creative inputs plus the interaction between the individuals involved in the composition of the group, group characteristics (e.g., size), group processes (e.g., conflict), and contextual influences (e.g., the larger organization, task characteristics). Finally, organizational creativity is also a function of the interaction between the creative outputs of its component groups and contextual influences (such as organizational climate and culture, reward systems, resources, or the external environment). As the componentional model previously suggested, the interactionist model also stresses the role played by the context, but it further adds the notion that the effects between person and situation are not simply additive but are instead of an interactive nature. This implies that in order to fully understand creativity, one has to consider the interplay between the person and the environment. This idea is the foundation for a rich stream of research that has strongly contributed to the understanding of organizational creativity and innovation. We will return to this notion of interaction between person and situation when discussing recent developments on the effect of team climate on creativity. Note that this emphasis on the role of context in the creativity literature runs in parallel with the trend observed in the general organizational behavior literature (Johns, 2006).
Next, we turn to the concept of climate.
Organizational Climate
Central to most, if not all models of organizational behavior, are perceptions of the work environment, referred to generally as “organizational climate” (Rousseau, 1988). Organizational climate has occupied a pivotal role in the organizational sciences dating from Lewin’s classic work on motivation in the 1950s (Lewin, 1951), and was formalized through the human relations movement of the 1960s (Argyris, 1958). Primarily understood as the intervening variable between the context of an organization and the responses and behavior of its members, the concept has inspired many descriptions and operationalizations. Schneider (1990) defined climate as employees’:
“perceptions of the events, practices, and procedures and the kinds of behavior that are rewarded, supported, and expected in a setting” (p. 384).
Climate refers to the perceptions of the work environment and the term can designate descriptions and perceptions at the individual, group, or organizational level of analysis. Individual perceptions of the work environment are usually termed psychological climate, and, when shared to a level sufficient for aggregation to the group or organizational level, are labelled group or organizational climate.
Individuals can describe the organizational environment both in an overall global sense, as well as in a more specific, targeted manner. In relation to the global organizational environment, James and his colleagues (James & James, 1989) describe four dimensions of global organizational climate, which have been identified across a number of different work contexts:
1.role stress and lack of harmony (including role ambiguity, conflict and overload, subunit conflict, lack of organizational identification, and lack of management concern and awareness),
2.job challenge and autonomy (as well as job importance),
3.leadership facilitation and support (including leader trust, support, goal facilitation and interaction facilitation, and psychological and hierarchical influence), and
4.work group cooperation, friendliness, and warmth (as well as responsibility for effectiveness; James & McIntyre, 1996).
James suggests that individuals develop a global or holistic perception of their work environment (e.g., James & Jones, 1974), which could be applied to any number of contexts and industries.
More recently, researchers have departed from a general conceptualization of climate and have turned their focus to specific types or facets of climate, such as climate for safety, climate for service and climate for initiative (Baer & Frese, 2003; Schneider & Reichers, 1983; Schneider, Wheeler, & Cox, 1992). Next we briefly outline a number of climate for creativity and innovation taxonomies that, in line with this trend, have been suggested in the literature.
Climate for Creativity and Innovation: Taxonomies
Based on different theoretical frameworks, several models of climate have been developed identifying a number of dimensions that can influence creativity and innovation (cf. Hunter, Bedell, & Mumford, 2007).
West and colleagues’ climate model is, in our awareness, the only model focusing on team level climate (Anderson & West, 1998; West, 1990; West & Anderson, 1996). Based on a theory of team innovation, the authors developed a four factor model including:
1.vision,
2.participative safety,
3.task orientation, and
4.support for innovation.
In contrast, Amabile and colleagues’ (1996) climate model, grounded in a theory of intrinsic motivation, focuses at the broader organizational climate. Based on qualitative and quantitative work, the authors identified the following eight dimensions:
1.work group support,
2.organizational encouragement,
3.supervisory encouragement,
4.challenging work,
5.freedom,
6.resources,
7.work load pressure, and
8.organizational impediments.
Focusing on a theory of psychological processes, Ekval and colleagues (Ekvall, 1996; Ekvall & Ryhammar, 1999; Ekvall & Tangebergandersson, 1986; Isaksen, Lauer, Ekvall, & Britz, 2000) proposed a 9 dimensional model integrating:
1.challenge and involvement,
2.freedom,
3.trust and openness,
4.idea time,
5.playfulness and humor,
6.conflict,
idea support,
8.debate, and
9.risk-taking.
We note that other models more strongly embedded in organizational management theory have also been developed (e.g., Abbey & Dickson, 1983; Tesluk, Farr, &. Klein, 1997).
Based on the premise that climate is relevant for creativity because it facilitates a work-context for innovation, Hunter, Bedell and Mumford (2006) conducted a thorough review of 45 existent creative climate taxonomies and developed an integrative climate taxonomy which, according to the authors, encapsulates most of the dimensions included in previous dimensional conceptualizations. The 14 dimensions are:
1.positive peer group,
2.positive supervisor relations,
3.resources,
4.challenge,
5.mission clarity,
6.autonomy,
7.positive interpersonal exchange,
8.intellectual stimulation,
9.top management support,
10.reward orientation,
11.flexibility and risk taking,
12.product emphasis,
13.participation, and
14.organizational integration.
Aligned with some of the taxonomies described above, several instruments have been developed to assess a climate for creativity. To name just a few, we highlight KEYS (Amabile, et al., 1996); the Team Climate for Innovation (TCI; Anderson & West, 1998; West & Farr, 1989); the Siegal Scale of Support for Innovation (SSSI; Siegel & Kaemmerer, 1978), and the Creative Climate Questionnaire (CCQ, Ekvall, 1996). We will refer in more detail to TCI and KEYS later in this chapter (for a comprehensive review see Mathisen & Einarsen, 2004).
West’s team climate model (1990) and Amabile and colleagues’ work environment model (1996) are arguably the most widely validated models of climate for creativity and innovation. Moreover, they complement each other in accounting for the more proximal team climate and the more distal organizational climate influences. Thus, our following discussions on team and organizational climates will be grounded on these two frameworks. After this introductory overview, we turn to a discussion of the aspects of team and organizational climate that influence creativity and innovation.
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Autonomy and control across cognition
Nathaniel Barr, ... Paul Seli, in Creativity and the Wandering Mind, 2020
Creativity
Creativity has long stood as an integral facet of what it means to be human and has served as an object of deep discussion, but, for most of our time pondering it as a species, it has remained mysterious, ephemeral, and even mystical. Even as psychology became well established as a science, the study of creativity remained largely untouched by empirical inquiry and conceptions of autonomy and control remained theoretically imprecise and ill-articulated. In J.P. Guilford's now famous 1950 APA Address, he lamented the “appalling neglect” of the concept of creativity. Guilford's address, and his conceptualization of divergent and convergent thinking, sparked a massive influx of research on creativity. Guilford identified only 186 papers directly focused on creativity in his assessment of the literature in the years from 1927 to 1950, but Arons's (1965) review found over 800 records in the mere decade following the address. Since this time, things have not slowed down, and the sheer volume of research on creativity continues to increase.
Speculating on the gross disregard of creativity up to that point, Guilford (1950) argued that many to that point had viewed genius and creativity as largely synonymous, with intelligence seen as being able to capture most of the meaningful variance in individual creative capacity. His work spawned a considerable and concerted effort to isolate aspects of creative potential unrelated to intelligence. A good example is Mednick's (1962) seminal Psychological Review paper, The associative basis of the creative process. In this work, Mednick argued that creativity could be predicted from associative hierarchies. His emphasis on the source of variance in creative potential was not on cognitive control and the ability to effectively access and combine information—core functions of general intelligence—but rather focused on the organization of semantic memory and the way that responses are autonomously generated in response to stimuli. Related is the serial-order effect: the finding that ideas generated in divergent-thinking sessions tend to get more creative over time (Christensen, Guilford, & Wilson, 1957). Most accounts of this finding emphasize the associative organization of information, with more proximal associates becoming active first, followed by more distal creative ideas later. This emphasis on the way that responses are autonomously generated is still apparent in modern creativity research and the way that experiments are structured. For example, in Slepian and Ambady (2012), participants were asked to terminate their attempt if they could not produce a solution to a Remote Associates Test (RAT; REF) problem within 5 seconds, and this was done to “ensure that answers were discovered by connecting remotely associated concepts rather than by brute-force searching (see Dorfman, Shames, & Kihlstrom, 1996; Slepian, Weisbuch, Rutchick, Newman, & Ambady, 2010)” (p. 4). This focus on spontaneous illumination is most obviously present in the rich literature on creative insight, which reveals the ways in which new and useful ideas arise autonomously in the mind (though there is discussion of the role of controlled and volitional thought in insight; see Kounios & Beeman, 2014; Chein & Weisberg, 2014).
Despite the well-developed body of research that has been amassed on autonomous processes in creativity, there remain threads of research that connect back to the notion that intelligence and executive functions, which include inhibition, interference control, working memory, and cognitive flexibility (see Diamond, 2013), are indeed important for creative thought. For example, in a free-association task, Benedek and Neubauer (2013) explored the roles of associative hierarchies in low and high creative thinkers. They found no support for the notion that the high creatives were accessing more remote associates earlier on and argued that “creativity … may not necessarily imply a special organization of associative memory, but it may rather rely on advanced executive abilities allowing for a highly effective access [to] and processing of memory content” (p. 287). Beaty and Silvia (2012) revisited the serial-order effect and found evidence in their experiments for the position that greater cognitive control is implicated in creative thinking: Whereas individuals with lower intelligence exhibited a typical serial-order effect, more intelligent individuals did not, which suggests that these participants were strategically accessing more creative ideas with executive control and management of resources, rather than simply allowing ideas to emerge. Observations of the importance of cognitive control in creative thinking are also apparent in research on creative analogical reasoning. Neuroscientific research has shown an increase in frontopolar cortex activation when individuals identify or generate more creative analogies (with higher creativity quantified by increased semantic distance between the constituent elements of an analogy; see Green, 2016 for a review; also see Kenett, 2018 for a review of quantitative measure of semantic distance in creativity research). Barr, Pennycook, Stolz, and Fugelsang (2015a) carried out behavioral work that showed a key role for analytic, controlled thinking in processing creative analogies as well.
Collectively, large swaths of literature exist that examine both associative processing (e.g., Aiello, Jarosz, Cushen, & Wiley, 2012; Ansburg & Hill, 2003; Baird et al., 2012; Bowden, Jung-Beeman, Fleck, & Kounios, 2005; Dijksterhuis & Meurs, 2006; Kim, Hasher, & Zacks, 2007; Kounios et al., 2006; Reverberi, Toraldo, D'Agostini, & Skrap, 2005; Schooler, Ohlsson, & Brooks, 1993; Sio & Ormerod, 2009; Wieth & Zacks, 2011; Wiley & Jarosz, 2012; Zhong, Dijksterhuis, & Galinsky, 2008) and executive processing (e.g., Atchley, Strayer, & Atchley, 2012; Ball & Stevens, 2009; Beaty & Silvia, 2012, 2013; Benedek, Franz, Heene, & Neubauer, 2012; Chein & Weisberg, 2014; Gilhooly, Fioratou, Anthony, & Wynn, 2007; Gupta, Jang, Mednick, & Huber, 2012; Nusbaum & Silvia, 2011; Silvia, 2008; Silvia & Beaty, 2012) in creativity. There has been significant debate surrounding the relative importance of the contributions of associative and executive processes in creative cognition, with arguments made both for associative theories of creativity and for controlled-attention theories of creativity (for reviews, see Barr, 2018 and Benedek & Jauk, 2018).
As valuable as such approaches have been in isolating processes involved in creative thinking, given the considerable bodies of empirical evidence supporting roles for both associative and executive processing, researchers are increasingly seeking a deeper understanding of the interaction between these modes of thought and, accordingly, are adopting more global approaches. For example, Allen and Thomas (2011) revisited modern conceptions of Wallas's famous stages of creativity and argued that associative and executive processes are active throughout all stages, with different stages differentially associated with each type of thinking process. Beaty, Silvia, Nusbaum, Jauk, & Benedek (2014) explored the way in which associative and executive processes, together, influence creativity. Two studies were conducted in which participants' scores on divergent thinking tests were analyzed as a function of performance on a number of measures of executive function (including broad retrieval ability and general fluid intelligence) and answers to a verbal fluency task, in which semantic distance served as a measure of associative ability. Multivariate structural equation models showed unique contributions of both the associative and executive measures to creativity, demonstrating that both types of processes are important in predicting the ability to generate novel ideas.
In other work, Beaty and colleagues have extended these behavioral findings to the neuroscientific realm, demonstrating the importance of the interaction between brain regions that underlie associative and executive processes (see Beaty, Benedek, Silvia, & Schacter, 2016, for a review). Looking at resting-state connectivity, Beaty et al. (2014) found that greater functional connectivity between the prefrontal cortex (which is linked to executive processing) and the default network (which is linked to associative processing) was associated with higher scores on tests of divergent thinking. In later work, Beaty, Benedek, Kaufman, and Silvia (2015) also employed temporal connectivity analysis to show interactions within these regions, whereas participants generated novel ideas, demonstrating that creative thought relies on “cooperation between brain networks linked to cognitive control and spontaneous thought, which may reflect focused internal attention and the top-down control of spontaneous cognition during creative idea production” (p. 1).
Another neural network identified as important for creativity is the salience network, which includes the dorsal anterior cingulate cortex and the anterior insula (Abraham, Rutter, Bantin, & Hermann, 2018; Beaty et al., 2015; Heinonen et al., 2016). These regions are implicated in the interplay between the prefrontal cortex, other regions of the central executive network, and the default network. The neuroscientific literature showcasing the relation among these networks provides a firm foundation from which to understand the structures and mechanisms in the brain responsible for such levels of processing, and the vacillation between diverse types of processing (see Chrysikou, 2018).
As the evidence surrounding the importance of interaction between associative and executive processing in creative thought continues to emerge, at both the behavioral and neural levels, many have articulated a need for dual-process theoretical frameworks that can more fully account for this interplay. For instance, Beaty et al. (2015) suggest that to “further reconcile the associative and executive theories, a dual-process model may be the best approach” and could “provide a promising approach to understanding the relative contributions of automatic and controlled processes in creative thought” (p. 1195). Wiley and Jarosz (2012) agree that creative problem-solving requires a mixture of “non-goal-directed processes and more controlled, attention-demanding processes” (p. 260) and call for “a dual-process model of problem solving that incorporates both analytic and nonanalytic processes” (p. 261).
In the article, The shifting sands of creative thinking: Connections to dual-process theory, Sowden, Pringle, and Gabora (2015) systematically review the multiple theories in creativity that can be conceptualized as dual-process in nature. Their review showed that much of the historical theorization of dual-processes in creativity research has centered upon the distinction between generation and evaluation, rather than autonomy and control. This constitutes a deviation from a majority of cognitive psychological research, though this focus is unsurprising given that creativity has been defined by the content of generated thought and the relatively clear demarcation between the functional purpose of generation and evaluation. One of the most famous conceptions in this tradition comes from Wallas' (1926) classic, The Art of Thought. Wallas outlined the stages that lead to a creative insight: preparation, incubation, illumination, and verification. This staged framework, while focused on how an idea arises unintentionally from consciousness, emphasized focused and controlled thought in the evaluation of the utility of the insight. Similar emphasis on generation versus evaluation is found in other prominent theories of creativity. Guilford (1950), for instance, defined divergent thinking as the generation of many alternatives and ideationally branching out from a single starting point, and convergent thinking as homing in on a singular solution and evaluation of fit. The Blind-Variation-and-Selective-Retention model of Campbell (1960), Simonton's (1999) Darwinian theory of creativity, Finke, Ward, and Smith's (1992) Genoplore model, and Howard-Jones’ (2002) dual-state model of creative thought all articulate the distinction between generating ideas and evaluating them, and the importance of this back and forth in creativity.
In addition to reviewing existing dual-process theories of creativity, Sowden et al. (2015) also deeply considered the connections between creativity theories that are dual-process, and in more general dual-process theories of cognition. They explain, in detail, the considerable deviation in conceptualizations mentioned above—that dual-process theories of cognition predominantly focus on distinctions of autonomy and control in dividing types of processing, whereas creativity researchers tend to focus on the difference between generative and evaluative processes, and divergent and convergent thinking. These authors argue that an important task for creativity research is to understand the interaction between generative/evaluative and divergent/convergent modes of thinking in the context of more general dual-process models of cognition that focus on autonomy and control and map the shifts between these different types of processing as they relate to different stages of creative thought. Given the emphasis on understanding the shifting of processing types in time, they identify chronometric approaches as having particular promise both in unraveling the way creative thinking unfolds at the cognitive and neural levels and in developing effective interventions to enhance creative thinking. Sowden et al. (2015) conclude by noting that a means by which to proceed is to integrate creativity research more fulsomely within the broader cognitive psychological literature on thinking:
the time is ripe to develop an integrated dual-process model of creativity that clearly specifies the nature of this interaction [between modes of thought] across different points in the creative process, and the mechanisms that underlie shifting between generative and evaluative thinking. An important part of this process will be to incorporate findings from more general dual-process theories of cognition. (p. 16)
To facilitate this vision, and to achieve the goals laid out at the outset of this chapter, we will next review the way that autonomy and control are conceptualized and empirically studied across different areas of cognitive research.
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The Effect of Mood On Creativity in the Innovative Process
Geir Kaufmann, in The International Handbook on Innovation, 2003
Inconsistent Evidence on the Positive Mood–Creativity Link
Even if we keep strictly within the specific task domain of creative problem-solving, however, several findings anomalous to the positive mood-enhance-creativity theory have been reported. Jausovec (1989), comparing the effects of positive, negative and neutral mood on analogical transfer in insight problems, reported a complex set of findings. In one task, a facilitating effect of positive mood on an analogical transfer task was obtained. In another task, positive mood was detrimental to performance, whereas in a third task, no significant differences between the different moods appeared. It is interesting to note that the task where positive mood was found to be detrimental is a typical insight problem (the Radiation Problem; Duncker, 1945), held in the classical literature to be a representative indicator of core creative processes in creative problem-solving (e.g. restructuring; cf. Wertheimer, 1958). Weisberg (1994) pointed to an important distinction between productivity and creativity. With reference to the evidence indicating a significant relationship between hypomania and creativity cited above, Weisberg conducted an interesting case study of Schumann's mood bipolarity. The results suggested that the relationship demonstrated between elevated positive mood and creativity may reflect increased productivity, in the sense of quantity of products, but it did not generalize to a higher quality of creativity. Vosburg (1998b) made similar observations. In her study, positive mood significantly enhanced ideational fluency, compared to negative mood, but no significant differences between positive and negative mood were obtained on scores of originality and usefulness of ideas.
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Domain Specificity: Introduction and Overview
John Baer, in Domain Specificity of Creativity, 2016
In the past quarter century the idea that creativity is domain general has been seriously challenged. To give a sense of the significance of this issue in the world of creativity research and theory, the Creativity Research Journal has published just one invited debate (in the form of a pair of Point-Counterpoint articles) in its history. The two articles that constituted that debate (Baer, 1998b; Plucker, 1998) addressed this crucial domain specificity/generality question, a hugely significant one for creativity research and theory. Even the author of the paper arguing for domain generality acknowledged that the tide had turned in favor of a domain-specific view:
Recent observers of the theoretical (Csikszentmihalyi, 1988) and empirical (Gardner, 1993; Runco, 1989; Sternberg & Lubart, 1995) creativity literature could reasonably assume that the debate is settled in favor of content specificity. In fact, Baer (1994a, 1994b, 1994c)1994a1994b1994c provided convincing evidence that creativity is not only content specific but is also task specific within content areas. (Plucker, 1998, p. 179)
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Domains of Creativity
J. Baer, in Encyclopedia of Creativity (Second Edition), 2011
Conclusions and Implications
If creativity is domain specific, it means that a single theory of creativity – such as the theory that divergent thinking is a basic component of all creative thinking – cannot account for the diversity of creativity across domains. Creativity theories must either become domain specific themselves or find some general approach to dealing with these domain-based differences. Similarly, domain specificity of creativity means that creativity testing as currently practiced is necessarily inadequate and of limited validity. And finally, creativity training programs cannot be assumed to increase creativity across all domains simply because they successfully promote creativity in one domain.
Baer has proposed a divergent thinking metatheory of creativity that, although encompassing all domains of creativity in a single conceptual scheme, nonetheless takes into account the domain specificity of creativity. According to this metatheory, divergent thinking is an important creative thinking skill, but the cognitive mechanisms underlying divergent thinking are different in each domain (or possibly even for each task within a given domain). Thus there are many different divergent thinking skills rather than a single divergent thinking skill. Divergent thinking as a general class of thinking skills is still a useful construct, however, both (a) because it makes this wide range of skills more coherent and easy to conceptualize and (b) because it makes it simpler to postulate and identify the appropriate domain-specific divergent thinking skills that will be important within any given domain or microdomain. Thus in terms of what is happening inside a creative thinker's head, divergent thinking skill may actually be many unrelated, domain specific cognitive skills; but in terms of how psychologists can understand these many diverse skills (viewing divergent thinking from the outside, as it were), divergent thinking is a coherent class of skills that bear a strong family resemblance.
Moving from the implications of domain specificity for creativity theory to its implications for creativity testing, a domain specific understanding of creativity provides a very direct challenge to existing notions of how to test creativity. Simply put, to the extent that creativity is domain specific, creativity testing becomes that much more difficult. If creativity is domain specific, what exactly is one to test? Creativity testers will necessarily have to determine in which domain(s) of creativity they are interested, because under a domain-specific theory of creativity, general creative thinking skill becomes an empty construct. Tests of creativity in specific content domains – which might use the consensual assessment technique to evaluate the creativity of products, or might instead find simpler (perhaps paper-and-pencil) techniques for assessing domain specific skills – would still be possible in principle, but they could be of only limited range and applicability. Major test developers may not be willing to support extensive test development efforts for tests of such limited potential use.
Creativity training, on the other hand, can accommodate domain specificity of creativity rather easily. Most creativity training programs already use a wide variety of tasks, spread across various content domains, in the exercises they use to improve divergent thinking and other creative thinking skills. Creativity training programs aimed at a particular domain can easily limit their training exercises to ones connected to that domain, while programs aimed at increasing creativity in general – the vast majority of programs – must be careful not to limit their training exercises to just one or a few content domains.
Creativity theory has only recently begun to accommodate research evidence suggesting that creativity is task specific, although the hierarchical approach discussed above is promising. General, domain-transcending theories – if true – would have far greater power than domain specific theories that account only for creativity in a limited content domain. For this reason, and because creativity theories have historically been one-size-fits-all theories, domain general theories of creativity continue to have great appeal.
It should be noted that the research evidence pointing toward domain specificity of creativity is fairly new, and, like the research that preceded it, this research may not tell the whole story. As noted above, self-report scales of creative behavior suggest more generality of creativity than do assessments of the creativity of actual creative products. It is quite possible that both domain specificity and generality are true, each in part and in its own way. More research will be needed to clarify the conditions under which generality or specificity of creativity is the more valid perspective. In the meantime, both views will continue to claim adherents among researchers and theorists.
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Foreword
In Animal Creativity and Innovation, 2015
Within the field of creativity research, psychologists tend to stick to the study of humans. Biologists or ethologists usually either focus on animal problem solving or else consider creativity to be an evolutionary adaptation. However, much of human creativity theory can be applied to animal behavior. Creativity and innovation found in the animal kingdom appear to follow similar rules, constraints, and models to those in humans. There has been one outstanding edited book on the topic—Animal Innovation by Simon Reader and Kevin Laland (Oxford University Press, 2003)—but it was, with some exceptions, focused on work by animal researchers. Our vision was for a dialog between those who study creativity in animals and those who study the same topic in humans. We sought a wide variety of contributors and commenters, both in terms of fields (we span psychology, biology, neuroscience, engineering, business, ecology, and education) and location (the contributors come from 12 countries). There has not been a synthesized collection and exchange of ideas between the two communities until now, however, despite the clear benefits to understanding the benefits of creativity in both an evolutionary and cognitive sense.
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