Creativity in gifted classroom-

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In Search of the Wild Things: The Choice, Voice, and Challenge (CVC) Model for Creative Instruction Perkins, Emma Gillespie;Carter, Mary C Art Education; Jan 2011; 64, 1; Education Database pg. 20

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COLUMN: RETHINKING TECHNOLOGY & CREATIVITY IN THE 21ST CENTURY

A Pragmatic but Hopeful Conception of Creativity: a Conversation with Dr. Barbara Kerr

Danah Henriksen1 & Punya Mishra1 & the Deep-Play Research Group

Published online: 23 January 2020 # Association for Educational Communications & Technology 2020

Well-behaved women seldom make history. ~ Laurel Thatcher Ulrich (though often mis-attributed to Eleanor Roosevelt, Marilyn Monroe or Kim Kardashian) If we really want education to be friendly to creative kids, to all kids—we need to allow kids to progress at their own rate in the domains where they excel or are interested, or get help where needed. ~ Dr. Barbara Kerr

Introduction

Creativity is a varied, rich and multifaceted construct, and understanding this richness requires diverse theoretical and research approaches. This article series explores creativity across the disciplines, from design or business to psychology, writing or the arts—through the perspectives of notable crea- tivity researchers. The diversity of our interview subjects has offered both unique nuances and distinctive views, and also common themes—providing a complex, detailed and emer- gent picture of creativity scholarship. Adding to the complex- ity and richness, we also consider the relationship of technol- ogy to creativity, specifically in educational contexts.

This article adds another perspective to this picture, focused on the work of Dr. Barbara Kerr. Dr. Kerr holds an endowed chair as Distinguished Professor of Counseling Psychology, and is co-director of the Center for Creativity and Entrepreneurship

in Education at the University of Kansas. She is an American Psychological Association Fellow, with her Ph.D. from the University of Missouri in counseling psychology. Dr. Kerr uti- lizes innovative counseling and therapy approaches to better understand the relationship of creativity to gender, privilege, and talent development. Her research has focused mainly on the development of talent, creativity, and optimal states. She has trained psychologists and counselors to be talent scouts who provide positive, strengths-based services. Dr. Kerr founded the Guidance Laboratory for Gifted and Talented at the University of Nebraska; she was Associate Director of the Belin-Blank National Center for Gifted and Talented at the University of Iowa; and was co-director of the National Science Foundation projects for talented at-risk girls at Arizona State University. Dr. Kerr is also author of Smart Girls in the Twenty-First Century and over one hundred articles, chap- ters, books and papers in the area of giftedness, talent, and cre- ativity. She currently directs the Counseling Laboratory for the Exploration of Optimal States (CLEOS) at the University of Kansas, a research-through-service program that identifies and guides creative adolescents.

Dr. Kerr’s work has explored creativity and giftedness through a diverse scholarly trajectory. In this interview, she discussed how she studies creativity in ways that offer a view of creative personalities and development, as well as the gen- der and creativity relationship, and structural influences on creativity. We also explored educational approaches to support creativity, and how creativity and technology intersect in ed- ucational futures.

Creativity in Personality and Professional Talent Development

Dr. Kerr’s interest in creativity stemmed from her early fasci- nation with creative work, through her own aspirations and creative dabbling. As she noted:

* Danah Henriksen [email protected]

Punya Mishra [email protected]

1 Arizona State University, Tempe, AZ, USA

TechTrends (2020) 64:195–201 https://doi.org/10.1007/s11528-020-00476-6

I can’t remember a time that I wasn’t interested in crea- tive people, since I wanted to be a writer when I was young. But I learned I was not the best creative writer in the world, since my all characters sounded exactly like me. I realized I may never be a great writer, artist, or musician—but I could spend my life around creative people, if I studied them and provided psychological counseling.

Studying creativity became a way to immerse herself in it across the disciplines to investigate, understand, and support it. She views therapy as both an art and a science, requiring openness and interpretation alongside analysis and knowledge of the human psyche. She has frequently provided psychother- apy to creative adolescents, which she says is, “The most challenging and exciting work that anybody can possibly do.”

Her prior experiences have developed insight into cre- ative personalities across different fields. For instance, for over 15 years she volunteered as a therapist at a writer’s workshop, and also served as a psychologist for archi- tects as the Frank Lloyd Wright school Taliesin West. She has worked with artists, musicians, engineers, and other creative professionals as a therapist. In providing psychotherapy she observed what research is now confirming—that creative personality is often domain- specific. Relatively few personality traits consistently correlate to creativity—with openness to experience be- ing the most reliable correlate of creative personality (Prabhu et al. 2008). So, despite the notion of a “creative type” of personality in popular culture, in reality, creative personalities differ across professions. For instance, she notes:

Writers tended to have more neurosis than other groups. They are more willing to talk about their psychological issues, perhaps because they’re narrators. Often people are drawn to a career in writing because they have such a strong need for autonomy and a tremendous capacity to empathize with other humans … Young creative writers, at 16 years old, already have high openness to experi- ence, incredibly high need for autonomy, pretty low conscientiousness—that is they’re not rule followers.

In contrast, Dr. Kerr found, via detailed research interviews with 30 of the most patented U.S. inventors, that, “The inven- tors were actually much more well-adjusted than writers or artists. There was one way in which they were similar to musicians. They were highly conscientious and detail-orient- ed, whereas the artists and writers were less so.”

Although creativity is often associated with the arts, it ex- ists in a range of human-centered fields of work. Creativity, Dr. Kerr argues, emerges differently in specific groups that she has studied. For instance, her work with indigenous leaders/

healers showed that they had a set of unique characteristics, as she stated, “They [indigenous leaders/healers] were more like artists than they were like scientists.” But they also demon- strated the common trait of openness to experience that all creative types demonstrate:

These creative personalities, they’re all open to experi- ence. All of them. But they have differing kinds of moods, different interpersonal skills, some being very introverted—that’s musicians for the most part—and some being very extroverted, such as the ceremonial leaders and spiritual leaders of indigenous people.

Openness to experience is a common correlate of creative personalities, but other variables differ by characteristics, re- quirements, and affordances of different professions. There is a transactional-developmental dynamic to this, because while people are drawn to a profession based on how it aligns with their own tendencies—the demands of that profession can ultimately change or reshape personality along the way. Dr. Kerr described this among creative writers:

Writers get involved in writing programs or workshops, and then enter into publication. That’s when other as- pects of the personality become shaped by the profes- sion. They become much more conscientious as they deal with rejection after rejection; and we see a reduc- tion in substance use over time. Most people mature and become less impulsive in growing older, but with writers the change is much more obvious.

Given her interest in formative aspects of creative personality, Dr. Kerr has also done significant work with creative youth. The key challenge with this group is often in having to give advice that is the opposite of what they typically receive:

In school they’re told to be good at everything, to be well rounded, have lots of friends, be popular and ath- letic. We almost tell them the opposite. We discuss the importance of prioritizing, giving 100% to activities that relate to their creative flow, to their passions. Giving 80% to things they absolutely must do, like get enough A’s to get into an institution that will propel their creative goals. Give 50% to things that are nice but not neces- sary, and give 0% to things that are not going to propel them and may obstruct them. Being well rounded can be a trap, especially for women. We tell them how to avoid those traps.

This gender related aspect of creative personality and profes- sional success leads into an area of research that Dr. Kerr is known for—in understanding creativity, gender and structural inequities.

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Creativity and Gender: Structural Inequalities and Implications

Dr. Kerr’s early career work in creativity focused on women and gender roles—covered in her book Smart Girls: A New Psychology of Girls, Women, and Giftedness. Her interest in gender and creativity began early, rooted in her own experience:

I graduated from a special Sputnik-era school for gifted kids. I hadn’t followed my peers after gradu- ation, until my tenth reunion. I realized that despite our extraordinary education—equal to the best pri- vate school in the country—the women had very traditional careers, if any. Half were homemakers, though they once had lofty career goals … girls at 11 years old who wanted to be cell pathologists or foreign ambassadors.

Since embarking on this initial focus, Dr. Kerr’s work has also branched out into other areas of creativity, but her interest in gender has always remained, as she noted, “I still have a strong concern for women because they are socialized to say yes to everybody, to be compliant and friendly. But to succeed creatively they need to learn to be disagreeable, to have thorns, to push back, to have boundaries.”

She described how, at the tenth reunion experience, one of her former classmates suggested that she find out, “Why we didn’t become the leaders of tomorrow.” This concern and the reflection that followed built the trajectory of her career for many years:

In a group of women with the best education, that had grown up at the heyday of feminism—what happened? For years, ideas have been pushed about internal bar- riers, like self-efficacy, imposter syndrome. But I began seeing the external barriers—the structural barriers to gifted women, preventing their full achievement potential.

Dr. Kerr learned that creative women in the arts, music, and writing, “Have fewer protections than most women, even in academe, which is really not a lot of protection.” She noticed that women in the arts face tremendous barriers of sexual harassment from their mentors and coaches, and flagrant dis- crimination against female creative writers or women film directors, reflecting, “The barriers are incredible. So, that’s where I’ve devoted a lot of energy, to understanding those barriers, and to preparing adolescent girls by focusing upon gender relations.”

Her research suggests the need to help women understand how to hold their career goals equal to their romantic goals, and to create career pathways that afford equitable treatment

of those goals. She described some of her earlier research, in which she and her colleagues examined gender relations among young gifted women, as follows:

We found that the degree to which women placed im- portance upon their romantic relationships, the degree to which they put time and energy into them, could predict their intent to persist professionally. In science majors for instance, it wasn’t self-efficacy that predicted persis- tence, it was how much they valued their romantic goals.

As women’s valuing of romantic relationships increased, professional persistence and goals decreased. Women tend to make greater career sacrifices toward their romantic relationships, creating barriers they are often unaware of. Making women aware of this trade-off has been a goal for Dr. Kerr, along with teaching them to have boundaries or stand firm in their aims. She does so through her scholar- ship, and her work at the Counseling Laboratory for the Exploration of Optimal States, which identifies and sup- ports creative youth. As she describes it:

By the time women are adolescents they need to understand structural barriers and ways to overcome those, to become social change agents. When young women come to us with a creative personality and significant creative accomplishments already … we tell those girls, “You need to pick and choose your fights, but being as sarcastic as you are and having the boundaries you have are going to help you. Just use that as talent wisely.”

In the case of intelligent and creative women who never re- ceived the support to develop boundaries or understand the barriers, they may have “had their wings clipped.” Thus, Dr. Kerr’s work is often connected to education, in supporting change through awareness. This has led her to understand and inform how education can support and nurture creativity broadly.

Supporting Creativity in Education

Dr. Kerr argues that despite the value of gifted education, it has faltered when it comes to supporting creative kids, commenting, “A third of our creative kids never even got into gifted education because their overall grade point average wasn’t good enough, since they were focused on specific things they liked.” She continued:

Creative kids get short shrift in education. If kids have conventionally high IQs and high verbal, high

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math, there’s plenty of agreement about what they need—general acceleration and enrichment. For cre- ative kids, what is lacking is the understanding of how much they long for domain knowledge and expertise.

In other words, it is impossible to actualize or exercise one’s creativity without having the knowledge needed to actually create something or develop a project. Dr. Kerr noted that creative kids, “just want to get going on their ideas and pro- jects and need the information to do that.” She described how education misses the boat on this:

One of the stupidest things that gifted education does for creative kids, is creativity exercises. They’re already creative, they don’t need creativity training. Instead, they may need to actually learn some forms. They may be extraordinarily verbally creative, so they could learn how to write a sonnet, to discipline that ability with knowledge. Maybe they need help writing a good criti- cal paragraph. They want domain knowledge and skills to enact their creativity.

When asked what the single most important thing that educa- tion could do for the creative development of all kids, whether identified as gifted or not, she was clear about the importance of acceleration by domain:

The most important thing is to get rid of grade levels by age. There’s no reason why all sixth graders need to be the same age. But we have these outdated notions that all kids need to be socialized in middle school, rather than continuing to challenge them academically. If we really want education to be friendly to creative kids, to all kids—we need to allow kids to progress at their own rate in the domains where they excel or are interested, or get help where needed.

She reiterated that being well-rounded is a trap, pointing out, “Many creative people don’t need a record of having partici- pated in every extracurricular activity and leadership activity. That goes against a lot of assumptions.” Instead of pushing the notion of well-roundedness, Dr. Kerr instead asserts the im- portance of offering diversity in learning—not locking kids into age groups:

Part of becoming open to experience involves being among people who are very different from you in many ways. But that doesn’t mean locking all 10-year-olds into fourth grade—that’s crazy. Creativity and learning thrive in diverse environments … where kids get to be around people from different places, with different

conceptual orientations, of different ages or from differ- ent nationalities or ethnicities.

Dr. Kerr emphasized diversity of experience as being critical not just to the development of creative kids, but also as benefitting the creative development of all students. She em- phasized how the best way to increase creativity is to increase experience. This means increasing exposure to a wide variety of people and environments:

If we look at the personality construct of openness to experience, which is reliably associated with creativity, there’s just a few things that build it—things like travel, learning other languages, and exposure to rich, stimulat- ing, diverse environments. As people learn to love learn- ing, they learn that new people and new experiences aren’t scary, they’re cool and fun.

This underlines the transdisciplinary perspective in her philos- ophy, since transdisciplinarity demands knowledge and expe- riences across disciplines in order to cross-pollinate creative thinking (Guyotte et al. 2014). Some of our previous columns in this series focused on transdisciplinary creativity, and learn- ing by criss-crossing the landscape of subject matters (Henriksen and Mishra 2014). Creativity is combinatorial, re- quiring both deep knowledge of a particular subject matter, as well as a breadth of experiences and knowledge across sub- jects to inspire openness to new ideas (Liao 2016). This is echoed in Dr. Kerr’s comment:

Musical training doesn’t just teach you music, it teaches you history, in playing pieces from other eras. It teaches you about the world religions, about culture … Musical training, language training, and arts training has been found to be very effective for people in technical and engineering fields.

This has curricular implications which align with existing re- search on integrating subject matter for creative education (Craft 2010). Another relevant point that she noted has impli- cations for teachers, in recognizing the utility of different stu- dent temperaments; even those that do not fit traditional ideals:

We shouldn’t strive for an “American” temperament. The temperament that most teachers love, is a child who’s extroverted, conscientious, industrious, agreeable and friendly. I like those kinds of students too, but we don’t need all students to be that type. Part of teacher creativity training is teaching tolerance of creative per- sonalities, being okay with kids not being friendly or extroverted, and cutting slack to the creative ones who may not be fully conscientious yet.

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Thus, her educational recommendations broadly involve ac- celeration by domain, and expanding diversity of experiences in learning. Part of expanding learners’ horizons involves con- sidering the opportunities afforded by new technologies, as tools to think with. On this front, she is excited and hopeful about the possibilities.

Creativity and Technology: An Optimistic Eye to the Future

When it comes to the relationship between technology, crea- tivity and learning, Dr. Kerr is optimistic and forward-looking. She characterizes the technology-creativity relationship as “overall a big plus,” specifically for the hunger that creative people have for domain knowledge:

For a creative person, the world is at their fingertips. Kids used to have to go to the library and beg for books off the top shelf from somebody older. Now they can get access to that information. Any of these new ways to access knowledge … it’s just so good for creativity.

She is also excited about new trends in technology that have potential to change how we think, learn and operate creatively. She pointed to the rise of artificial intelligence (AI) as one of the new frontier of creativity, knowledge and growth. AI is a relatively new field (though it is growing fast) with a shortage of people prepared to work in it. Despite this, she suggests that this is an area for significant creative workforce growth:

We have a generation of young people coming who are so comfortable with technology that artificial intelli- gence won’t be seen as a threat but as an exciting area … The kids who are linguistically talented can work with machine language. Kids who are artistically talent- ed or spatially/visually oriented now have all kinds of computer-assisted design.

Dr. Kerr provided an example of a creative technology project she is working on with a with engineering student Christopher Tacca at University of Kansas. She described a virtual reality (VR) enabled counseling environment, called Heila Valley, that they have developed:

This new virtual counseling space is for very isolated clients—people who would never set foot in a therapists office, but need some help. Think of the gamer sitting alone in her or his basement, who is comfortable with the online world, but not comfortable in a therapy space. They can enter the VR, choose their environment, their archetypal therapist, even the type of therapy that fits

their worldview. The counselor will have a dashboard showing the person in the VR and a microphone to speak in real time through the archetype.

This is a novel approach to counseling, providing mental health to people who may desperately need it but would never otherwise receive it. That said, Dr. Kerr is also sensitive to the fact that non-traditional approaches can be uncomfortable to traditional practitioners:

When we present it to regular psychologists, sometimes the response is, “Oh, I don’t know. That sounds too far removed from therapy.” I tell them, “Not for these peo- ple!” It’s enabled to receive a constant EEG read, be- cause in a VR space the therapist can’t read nonverbals. But with the person’s EEG they can read arousal level, and whatever spectrum they’re in to read their attention, engagement, and frustration.

This is just one example of Dr. Kerr’s broadly positive view of creative technological possibilities, which she described say- ing, “I am full on—let’s see what tech can do to make our lives and work interesting and better.” Of course, she is aware of concerns about new technologies, particularly around ethics, which is evolving behind rapid technology growth. But she believes that as technology develops, awareness of ethical needs and standards will come along too, despite some grow- ing pains:

I sympathize with people who say, “Do we really have any standards here?” No, we haven’t developed enough yet, but we will. That happens naturally as we see how things can be abused. For instance, this therapy VR I’m developing, we’re ensuring it complies with HIPAA standards and with the APA Code of Ethics on online therapy. Any technology can be used unethically, but any technology can be used ethically.

For concerns about other potential effects of new technologies—such as concerns about anxiety and depression linked to smart phones, Dr. Kerr advocates a more nuanced and informed approach—rather than the default mode of blaming technology. For instance, she is a critic of Jean Twenge’s (2013, 2020) studies that indicated links between technology- use and feelings of anxiety and depression. Dr. Kerr remarked:

[Twenge] has multiple variables and thousands of cases. In those data points, yes, the trend for anxiety, depres- sion, and even suicidality among college students is go- ing up. But of all the possible causation she says it’s the technology, social media, phones. My response is, “We have a generation that’s graduating into a world where

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the climate is collapsing, societies are collapsing, it’s impossible for people to survive and have a livable wage, and she thinks that the reason young people are anxious, is because of the phones?” That makes me crazy.

Dr. Kerr’s experiences and research with young people in her creativity development work do not demonstrate a pattern of technology causing mental health problems. In recent years, she and her student colleague, Max Birdnow, have worked with 12 focus groups of over 100 creative adolescents, in which she and her col- leagues ask them why they think their particular genera- tion or cohort is more anxious and depressed, and how they feel about it. Through focus group studies she finds that:

A major anxiety for many kids today is academic pres- sure, feeling like they may not do well enough on all the tests—as though that performance reflects who they are. The second cause they give is the world situation, they use the word collapse a lot, societal collapse, environ- mental collapse. Third is bullying, but it’s not always online. Fourth, being adolescents, is disputes with their parents. There are things you would expect them to be feeling. Their concerns about social media/phones, that’s only seventh or eighth, way down there on their list.

Notably, she and her colleagues first started to see anxiety taking a hard upward-spike with the first group of kids that had experienced the No Child Left Behind era of high-pressure testing. While causality is hard to prove—this finding does suggest that policymakers and stakeholders do not understand the anxiety-inducing con- sequences of living and learning in a high-stakes testing culture. A recent Psychology Today article (Gray 2019), aligned with Dr. Kerr’s concern—reflecting how both anxiety and hatred of school are fueled by frequent high-pressure testing, now appearing as early as kinder- garten. Gray (2019) noted that children are tested at youn- ger and younger ages, stripping the joy of learning and play from childhood.

Beyond this, Dr. Kerr’s ideas suggest that we also need to pay attention to how global and societal fears affect youth today. She points out that students can “see and they under- stand that things are not so good right now. They need help in understanding how creativity can translate into solutions to problems—a reframing of the negative into the possibilities they can offer.”

Conclusion

Dr. Kerr’s positioning of creativity, technology and edu- cation is hopeful and optimistic, but also acknowledges concerns about our unstable world. She notes that this uncertainty is why creativity is particularly important for young people and students today, both for solving the problems society faces and assuaging their existential fears. As she noted, “Times like these—whether the great plague or the great wars—stimulated enormous creativity. Human creativity is borne out of disastrous situations. Young people need to know that they’re living at a time when their creativity really matters.”

Her research trajectory, grounded in psychological exper- tise and empirical rigor, is built on a backdrop of hope for how creativity can make the world better. Her focus on creative personalities and groups has led to an understanding of how creativity emerges in different professions and people, and has sought to break down structural barriers and gender-related inequities around creativity.

Her work also suggests the need for a structural re- thinking of education. Our current paradigm does not sup- port creative development, in that most children are locked into age-groupings for learning, rather than being supported based on individual passions, interests, abilities or needs. Further, students’ creative development could be strengthened by a more transdisciplinary integration of school subjects, more recognition of different types of temperaments, and stronger connections to diverse real- world experiences.

Dr. Kerr provides a critical voice in education, speaking to the need to support and develop creative potential in our stu- dents. As we look ahead to the uncertainty of the future and complexity of our world, there may be no greater goal to aspire to.

Acknowledgments The Deep-Play Research group is a loose collective of faculty and graduate students at Arizona State University, California State University, and Michigan State University. Participants include: Danah Henriksen, Sarah Keenan-Lechel, Rohit Mehta, Punya Mishra, Carmen Richardson & Melissa Warr.

References

Craft, A. (2010). Creativity and education futures: Learning in a digital age. Trentham Books.

Gray, P. (2019). Kindergarten teachers are quitting, and here is why. Psychology Today. https://www.psychologytoday.com/us/blog/ freedom-learn/201912/kindergarten-teachers-are-quitting-and-here- is-why

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Guyotte, K. W., Sochacka, N. W., Costantino, T. E., Walther, J., & Kellam, N. N. (2014). STEAM as social practice: Cultivating crea- tivity in transdisciplinary spaces. Art Education, 67(6), 12–19.

Henriksen, D., & Mishra, P. (2014). Twisting knobs and connecting things: Rethinking technology & creativity in the 21st century. TechTrends, 58(1), 15.

Liao, C. (2016). From interdisciplinary to transdisciplinary: An arts- integrated approach to STEAM education. Art Education, 69(6), 44–49.

Prabhu, V., Sutton, C., & Sauser, W. (2008). Creativity and certain per- sonality traits: Understanding the mediating effect of intrinsic moti- vation. Creativity Research Journal, 20(1), 53–66.

Twenge, J. M. (2013). Does online social media lead to social connection or social disconnection? Journal of College and Character, 14(1), 11–20.

Twenge, J. M. (2020). Why increases in adolescent depression may be linked to the technological environment. Current Opinion in Psychology, 32, 89–94.

Publisher’s Note Springer Nature remains neutral with regard to jurisdic- tional claims in published maps and institutional affiliations.

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REVIEW ARTICLE

Intelligence and Creativity Are Pretty Similar After All

Paul J. Silvia

Published online: 20 February 2015 # Springer Science+Business Media New York 2015

Abstract This article reviews the history of thought on how intelligence and creativity, two individual differences important to teaching and learning, are connected. For decades, intelligence and creativity have been seen as essentially unrelated abilities. Recently, however, new theories, assessment methods, and statistical tools have caused a shift in the field’s consensus. New lines of work on creative thinking strategies, executive cognitive processes and abilities, and cognitive neuroscience have revealed that intelligence and creativity are much more closely linked than the field has thought. The deep connections between these concepts offer opportunities for a more fertile conception of both intelligence and creativity, one that emphasizes similarities between solving problems with right answers and thinking flexibly, critically, and playfully.

Keywords Creativity. Intelligence . Divergent thinking . Assessment . Executive control

Anyone who teaches encounters individual differences: students are so variable in so many ways. Understanding what these ways are, how they work, and how they can be assessed has been one of the major projects of educational theory and research during the past century. This article considers intelligence and creativity, two ways people differ that are deeply embedded in teaching and learning. Until recently, intelligence and creativity have been seen as essentially unrelated abilities, as distinct strengths that students bring to the classroom. This view is founded on some good evidence—including landmark studies and a high-quality meta-analysis—so it is not a mere myth. Recently, however, some new theories, assessment methods, and statistical tools have sparked interest in an alternative view: intelligence and creativity are probably much more alike than we have thought. The past decade has seen a reconsideration of past work, and the consensus is thus shifting. We will consider some of the new sources of evidence and some implications of viewing intelligence and creativity as similar cognitive strengths.

A Brief History

Intelligence and creativity have traveled on different tracks. For the most part, they are studied by different scholarly communities that seek to influence different audiences. At a few points,

Educ Psychol Rev (2015) 27:599–606 DOI 10.1007/s10648-015-9299-1

P. J. Silvia (*) Department of Psychology, University of North Carolina at Greensboro, P. O. Box 26170, Greensboro, NC 27402-6170, USA e-mail: [email protected]

however, these tracks have converged, and the most significant convergence by far is Guilford’s (1967) Structure of Intellect (SoI) model of intelligence. Guilford was interested in both creativity and intelligence, and his model of intelligence was unique in integrating them. His SoI model is largely of historical interest in modern intelligence research (Carroll 1993), but it continues to cast a long shadow over modern creativity research. Guilford set the stage for later work by casting some mental processes as convergent (processes that narrow thought and lead to correct answers) and others as divergent (processes that widen thought and lead to many responses). Since then, the convergent processes are what we see as prototypical markers of intelligence, and the divergent processes are what we see as markers of creativity.

The relationship between convergent and divergent processes was an obvious question implied by Guilford’s model, and it represents the modern start of research on the links between intelligence and creativity. He and his colleagues developed a wide range of tasks and generated an enormous amount of data (e.g., Guilford 1957, 1967; Wilson et al. 1953). Historically, the most influential aspect of Guilford’s work was (1) couching the problem in terms of convergent and divergent labels and (2) developing and popularizing tasks for assessing divergent thinking.

Other researchers soon started examining how intelligence and creativity were associated. Getzels and Jackson (1962), in an influential book, argued that the two concepts were distinct. They measured both intelligence and creativity in a sample of 132 middle-school and high school children, and they carved the sample into groups that were high in one trait but low in the other. This yielded a high IQ/low creativity group and a low IQ/high creativity group. In addition to its awkward emphasis on the diagonal elements of the four cells formed by intelligence and creativity, this study was criticized for the poor discriminant validity of the creativity tasks. When viewed as a multitrait/multimethod matrix, the study’s tasks show poor validity: the creativity tasks tended to correlate just as highly with the intelligence tasks as they did with each other. Nevertheless, the Getzels and Jackson book established the framing of the problem as Bintelligence versus creativity.^

Not long after, Wallach and Kogan (1965) published their touchstone work, a book that remains influential 50 years later. Motivated by similar questions, they assessed intelligence and creativity in a sample of 151 children. Their work is best remembered for the creativity assessment approach that they developed. Wallach and Kogan argued that creative responses were unique responses—responses that no one else in a sample gave. They had students complete divergent thinking tasks and then scored them for two things: fluency (the total number of responses) and uniqueness (the number of unique responses). People received one point for each response that they gave that no one else in the sample gave and zero points for each response given by anyone else. Guilford and his group had used similar systems, usually complex schemes that weighted each response by its prevalence or that constrained the number of responses (e.g., Wilson et al. 1953). Wallach and Kogan, however, greatly simplified how divergent thinking was measured: they whittled down Guilford’s many tasks and scoring systems into a small battery of tasks that was easy to administer and score. Wallach and Kogan found good validity for their tasks: the intelligence tasks correlated much more highly with each other than with the creativity tasks and vice versa. Overall, the correlation between intelligence and creativity was a meager r=0.09 (95 % confidence interval (CI) [−0.07, 0.25]).

It is easy to see why the work of Wallach and Kogan (1965) was so influential: it had a large sample of schoolchildren, clear findings, and some novel assessment tools that seemed to clarify and solve some of creativity’s more vexing aspects. The uniqueness scoring method turned out to be particularly popular. Because the scoring approach was straightforward and the uniqueness index could be scored objectively, researchers in the following decades primarily used the divergent thinking methods developed by Wallach and Kogan or a similar family of tasks from the Torrance Tests of Creative Thinking (TTCT; Torrance 2008).

600 Educ Psychol Rev (2015) 27:599–606

As researchers consistently observed small correlations between divergent thinking and intelligence, a consensus emerged. When Kim (2005) synthesized the large literature on creativity and intelligence using meta-analysis, she found a weighted average correlation of r=0.17 (95 % CI [0.16, 0.18]), which is modest at most. All the textbooks on creativity and its assessment from this period concluded that intelligence and creativity were largely independent cognitive abilities (e.g., Kaufman et al. 2008; Runco 2007; Sawyer 2006; Weisberg 2006).

A Contemporary Reevaluation

It seems like the story should end here. Nevertheless, several creativity researchers, at about the same time, began to suggest that the literature to date probably understated the case. Since Kim’s (2005) meta-analysis, the tide has shifted the other way: creativity researchers increas- ingly see creativity and intelligence as similar.

Statistical Advances

One simple reason to think that the relation between intelligence and creativity is larger comes from recent statistical models for studying cognitive abilities. Most studies have examined correlations between observed variables—and understandably so, for latent variable models have only recently become widespread. Latent variable models allow researchers to model a construct’s true score and error separately (Skrondal and Rabe-Hesketh 2004). As a result, they allow researchers to separate the variance due to an underlying trait (such as Bcreativity^) from variance due to task-specific and rater-specific factors. By distinguishing true trait variance from error, latent variable models give more accurate estimates of effect sizes. In most cases, the effects will be somewhat larger. One example comes from the classic study by Wallach and Kogan (1965). When the data are reanalyzed using structural equation models, the correlation between creativity and intelligence rises from r=0.09 to around r=0.20 (Silvia 2008b), thus illustrating how observed correlations can deflate relationships.

Assessment Advances

Uniqueness scoring became firmly entrenched. Between the Wallach and Kogan approach and the similar TTCT approach, most divergent thinking research from the 1960s to the present has used some form of it. But many researchers over the years have leveled serious criticisms at uniqueness scoring, and in hindsight, it is seriously flawed.

The first flaw is the confounding of fluency and uniqueness. As people generate more responses, their probability of having a unique response goes up. Researchers pointed out this problem long ago (e.g., Clark and Mirels 1970; Hocevar 1979a, b; Hocevar and Michael 1979). In even modest sample sizes, the correlation between fluency and uniqueness becomes very large. In the reanalysis of Wallach and Kogan’s data, the correlation was r=0.89 (Silvia 2008b). In the TTCT’s national norm samples (Torrance 2008), it is r=0.88. Clearly, there is little unique variance to be found in uniqueness scores—they are basically the same as fluency. A creativity task that assesses only the quantity of ideas, not their quality, seems impractical.

The second serious flaw is the confounding of uniqueness with sample size. People receive one point if their response was unique within their sample. As a result, the likelihood that any particular response is unique declines as the sample size increases. As a result, the sample’s

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mean uniqueness score will also decline as the sample size increases. People thus appear less creative when you assess more of them. Stated differently, the creativity task becomes Bharder^—it takes even higher levels of novelty to get a point—when the sample size is larger. Theoretically, a very large sample could have no unique responses. This flaw is fatal. There is something amiss about a test that performs more poorly as the sample size increases.

In recent years, researchers have revisited some tools from Guilford’s early work, most notably the value of subjective ratings. Guilford had developed many creativity tasks, such as coming up with clever titles for short stories, that asked raters to score the responses on dimensions like cleverness or remoteness, and he found evidence for the validity of such ratings (e.g., Wilson et al. 1953). This general approach was developed further by Amabile (1982) in her consensual assessment technique (CAT) for judging creative products. The CAT has been extensively applied and evaluated in creativity research (e.g., Kaufman et al. 2013).

Subjective ratings have turned out to be unusually useful for divergent thinking tasks (Benedek et al. 2013; Silvia et al. 2008, 2009). Researchers can have trained raters score each response (or some subset, like the best 2 or 3) on a rating scale. The raters’ scores can be averaged, used as indicators in a latent variable model to account for rater-specific variance, or scaled in Many-Facet Rasch models that estimate creativity scores in light of the difficulty of the tasks and raters (Primi 2014). Many studies show that subjective ratings resolve the problems of uniqueness scoring: (1) rated creativity correlates only minimally and usually negatively, with fluency, and (2) rated creativity is not so sample dependent (Benedek et al. 2013). And, as we will see later, their correlations with intelligence are much stronger.

The Executive Era

Since the 1960s, psychology became increasingly interested in executive processes. Huge literatures have developed around self-regulatory concepts in different areas of psychology, from motivation to social psychology to health behaviors to cognitive psychology. In partic- ular, cognitive psychology sowed the seeds of the new look at creativity and intelligence, with its sophisticated models of how executive abilities (e.g., working memory capacity, inhibition, and fluid intelligence) and executive processes (e.g., interference management and strategy use) affect reasoning and problem solving.

Several researchers began to suggest that divergent thinking tasks should involve abilities associated with intelligence. Gilhooly et al. (2007) examined people’s spontaneous strategies when confronted with a divergent thinking task. People were asked to come up with unusual uses for a common object and to Bthink aloud^ while doing so. The verbal protocols were coded and distilled into a core set of strategies. Many of the findings suggested a strong role for executive processes. First, and simply, people who came up with better responses were using abstract strategies, indicating that the ideation process was at least somewhat controlled. Second, the strategies that predicted better responses (e.g., mentally disassembling an object and using its parts) were more abstract and harder to deploy than strategies that did not (e.g., simply repeating the name of the object to oneself).

Other researchers conducted latent-variable studies of how different executive abilities predicted divergent thinking. This body of work has generally anchored itself in the Cattell- Horn-Carroll (CHC) approach to cognitive abilities (Carroll 1993; McGrew 2005), which distinguishes between a higher-level general intelligence (g), a middle level of cognitive abilities, such as fluid, crystallized, and visuospatial intelligences, and a lower level of narrow abilities (e.g., inductive reasoning as a facet of fluid intelligence). By differentiating intelli- gence into components, the CHC model offers a useful framework for thinking about how creativity relates to the many cognitive abilities studied in modern intelligence research.

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In our first studies, we focused on fluid intelligence, which captures a range of processes associated with reasoning and executive control (McGrew 2009). A latent fluid intelligence variable strongly predicted the creativity of response to unusual uses tasks (β=0.43; Silvia 2008a), scored using subjective ratings. These results were replicated elsewhere in a study that found large effects of fluid intelligence on idea originality (β=0.51; Benedek et al. 2012a). In a later analysis, we found that the effect of fluid intelligence on creativity was mediated by markers of Bexecutive switching,^ the ability to shift idea categories during the task (Nusbaum and Silvia 2011, study 1) and that people higher in fluid intelligence were better at using a good creativity strategy when given one (Nusbaum and Silvia 2011, study 2). Other studies have unpacked the executive abilities most strongly linked to creativity (Benedek et al. 2014a, b, c) and examined the likely nonlinear nature of the relationship (Jauk et al. 2013; Karwowski and Gralewski 2013).

In addition to fluid intelligence, research has explored other CHC abilities. Broad retrieval ability (Gr)—also known as long-term storage and retrieval and verbal fluency—primarily reflects the ability to retrieve knowledge from memory selectively and strategically. Several studies have shown large effects of broad retrieval ability on divergent thinking (e.g., Benedek et al. 2012a, b; Lee and Therriault 2013) and unpacked the unique contributions of its lower- level facets, such as ideational fluency (Silvia et al. 2013) and encoding ability (Avitia and Kaufman 2014). Broad retrieval ability has effects on divergent thinking that are distinct from the effects of fluid and crystallized intelligence (Avitia and Kaufman 2014; Benedek et al. 2012a, b), thus illustrating the value of a differentiated CHC approach.

Creative thought is much broader than divergent thinking, and recent research has explored how intelligence influences creative ideas on other tasks. Several studies have examined how people generate metaphors, which are a salient example of creativity in everyday language (Gibbs 1994). Some studies have asked people to generate creative metaphors to describe an experience—such as what it is like to sit in a boring class or eat disgusting food—and fluid intelligence strongly predicts the creativity of the metaphors (β=0.49; Silvia and Beaty 2012). When other CHC abilities like crystallized intelligence and broad retrieval ability are included, around half the variance in metaphor creativity can be accounted for (Beaty and Silvia 2013). Other studies have used a newly developed metaphor completion task (De Barros et al. 2010), which involves completing a metaphor stem (e.g., Camels are the _____ of the desert) with a creative entry. Fluid intelligence strongly predicts metaphor creativity for that task, too (β= 0.51; Primi 2014).

Like metaphor, humor is a common example of creativity in everyday life. Several researchers have considered whether intelligence is important to humor production, the ability to generate funny material when prompted (Earleywine 2010). Although this is a small area, several studies have found notable effects of fluid and crystallized intelligence on humor production (e.g., Greengross and Miller 2011; Howrigan and MacDonald 2008), which is measured by asking people to write captions for cartoons, complete jokes with funny endings, or draw silly pictures.

Finally, a flourishing cognitive neuroscience of creativity has supported the view that intelligence and creativity are strongly linked. This complex literature cannot be summarized here, but many EEG and fMRI studies have found strong support for a role of top-down executive processes in the generation of creative ideas. In general, these studies give people creativity tasks (usually divergent thinking, metaphor production, or musical improvisation) and then assess neurological markers of controlled, executive thought, such as the activation of specific regions known to be important in executive control and the activation of brain networks involved in top-down, controlled cognition (Beaty 2015; Beaty et al. 2014; Benedek and Beaty et al. 2014; Benedek et al. 2014a, b, c; Vartanian et al. 2014). Because the

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neuroscience of executive control is well understood, the cognitive neuroscience of creativity has been able to establish an important role for executive neurological systems when people perform creativity tasks.

Practical Implications

The modern look at intelligence and creativity sees them as closely linked: people who do better on prototypically Bintellectual^ tasks (e.g., fluid reasoning) also do much better on typically Bcreative^ tasks (e.g., divergent thinking). Thus, these seem to be similar—but certainly not identical—strengths. What are some implications of the field changing its mind about this issue?

One implication is for how we define and think about creativity. Many theorists have pointed out that viewing intelligence and creativity as distinct abilities did a disservice to both (Kaufman 2013). Carving out creativity yields a sterile view of intelligence that emphasizes how people get right answers over how they think flexibly, critically, and playfully. And carving out intelligence yields a view of creativity that seems capricious and uncontrolled instead of something that can be directed and nurtured. Talking about intelligence and creativity as noun-like things—instead of as families of processes and functions that the mind can do—obscures the bigger conceptual picture (Billig 2013). The mind can do a lot of things, and the processes that it uses for solving closed-ended problems are similar to those used for making, judging, and playing with ideas.

Another implication is for models of the creative process. Several classic theories of creative thought explain individual differences in terms of crystallized knowledge. Mednick (1962), for example, argued that creative people have flatter associative hierarchies (e.g., less tightly structured semantic networks). Likewise, Weisberg (2006) has argued that creativity is largely determined by how much people know. Research clearly shows that the amount (Weisberg 2006) and the organization (Kenett et al. 2014) of knowledge are important to creativity, but how people access, manage, and control their knowledge has been overlooked. The emerging body of work on fluid and executive abilities shows that creativity is not just a matter of what we know but how well we use our knowledge: how we access, manipulate, combine, and transform what we know in the service of creative goals. As a result, the renewed emphasis on intelligence is congenial to models that view creative thought in terms of problem solving, judgment, and decision making (e.g., Finke et al. 1992; Gilhooly et al. 2007; Sternberg and Lubart 1991).

A more practical implication concerns how and why we should assess creativity. Divergent thinking tests are widely used in educational contexts, often for assessments related to giftedness programs. Historically, adding creativity tests has been justified by creativity’s apparently small correlation with intelligence. As our understanding of intelligence and creativity shifts, this argument seems less compelling. There are, however, other and better reasons for using creativity assessments in educational contexts. Some evidence suggests that creativity assessments are less biased (Kaufman 2010), and flexible, productive thinking is a cardinal twenty-first century skill. As Kaufman (2013) argues, an expanded view of intelli- gence should include both sides of the convergent/divergent coin along with measures of key motivational factors, like interest and openness to experience.

At the same time, the field should take a new look at current commercial creativity tests and decide how comfortable it is with using them for high-stakes decisions, such as admitting a child into a gifted track. The most popular forms of these tests, such as the TTCT, are essentially fluency tests, and a view of creativity as mere idea quantity seems impoverished. On the bright side, an evolving sense of what both intelligence and creativity are like (Kaufman 2013) presents interesting opportunities for new models and measurement tools for assessing creative potential.

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References

Amabile, T. M. (1982). Social psychology of creativity: a consensual assessment technique. Journal of Personality and Social Psychology, 43, 997–1013.

Avitia, M. J., & Kaufman, J. C. (2014). Beyond g and c: the relationship of rated creativity to long-term storage and retrieval (Glr). Psychology of Aesthetics, Creativity, and the Arts, 8, 293–302.

Beaty, R. E. (2015). The neuroscience of musical improvisation. Neuroscience and Biobehavioral Reviews, 51, 108–117.

Beaty, R. E., & Silvia, P. J. (2013). Metaphorically speaking: cognitive abilities and the production of figurative language. Memory and Cognition, 41, 255–267.

Beaty, R. E., Benedek, M., Wilkins, R. W., Jauk, E., Fink, A., Silvia, P. J., Hodges, D. A., Koschutnig, K., & Neubauer, A. C. (2014). Creativity and the default network: a functional connectivity analysis of the creative brain at rest. Neuropsychologia, 64, 92–98.

Benedek, M., Franz, F., Heene, M., & Neubauer, A. C. (2012a). Differential effects of cognitive inhibition and intelligence on creativity. Personality and Individual Differences, 53, 480–485.

Benedek, M., Könen, T., & Neubauer, A. C. (2012b). Associative abilities underlying creativity. Psychology of Aesthetics, Creativity, and the Arts, 6, 273–281.

Benedek, M., Mühlmann, C., Jauk, E., & Neubauer, A. C. (2013). Assessment of divergent thinking by means of the subjective top-scoring method: effects of the number of top-ideas and time-on-task on reliability and validity. Psychology of Aesthetics, Creativity, and the Arts, 7, 341–349.

Benedek, M., Beaty, R. E., Jauk, E., Koschutnig, K., Fink, A., Silvia, P. J., & Neubauer, A. C. (2014a). Creating metaphors: the neural basis of figurative language production. NeuroImage, 90, 99–106.

Benedek, M., Jauk, E., Fink, A., Koschutnig, K., Reishofer, G., Ebner, F., & Neubauer, A. C. (2014b). To create or to recall? Neural mechanisms underlying the generation of creative new ideas. NeuroImage, 88, 125–133.

Benedek, M., Jauk, E., Sommer, M., Arendasy, M., & Neubauer, A. C. (2014c). Intelligence, creativity, and cognitive control: the common and differential involvement of executive functions in intelligence and creativity. Intelligence, 46, 73–83.

Billig, M. (2013). Learn to write badly: How to succeed in the social sciences. New York: Cambridge University Press.

Carroll, J. B. (1993). Human cognitive abilities: a survey of factor-analytic studies. New York: Cambridge University Press.

Clark, P. M., & Mirels, H. L. (1970). Fluency as a pervasive element in the measurement of creativity. Journal of Educational Measurement, 7, 83–86.

De Barros, D. P., Primi, R., Miguel, F. K., Almeida, L. S., & Oliveira, E. P. (2010). Metaphor creation: a measure of creativity or intelligence? European Journal of Education and Psychology, 3, 103–115.

Earleywine, M. (2010). Humor 101. New York: Springer Publishing. Finke, R. A., Ward, T. B., & Smith, S. M. (1992). Creative cognition: theory, research, and applications.

Cambridge: MIT Press. Getzels, J. W., & Jackson, P. W. (1962). Creativity and intelligence: explorations with gifted students. New York:

Wiley. Gibbs, R. W., Jr. (1994). The poetics of mind: figurative thought, language, and understanding. New York:

Cambridge University Press. Gilhooly, K. J., Fioratou, E. E., Anthony, S. H., & Wynn, V. V. (2007). Divergent thinking: strategies and

executive involvement in generating novel uses for familiar objects. British Journal of Psychology, 98, 611– 625.

Greengross, G., & Miller, G. (2011). Humor ability reveals intelligence, predicts mating success, and is higher in males. Intelligence, 39, 188–192.

Guilford, J. P. (1957). Creative abilities in the arts. Psychological Review, 64, 110–118. Guilford, J. P. (1967). The nature of human intelligence. New York: McGraw-Hill. Hocevar, D. (1979a). A comparison of statistical infrequency and subjective judgment as criteria in the

measurement of originality. Journal of Personality Assessment, 43, 297–299. Hocevar, D. (1979b). Ideational fluency as a confounding factor in the measurement of originality. Journal of

Educational Psychology, 71, 191–196. Hocevar, D., & Michael, W. B. (1979). The effects of scoring formulas on the discriminant validity of tests of

divergent thinking. Educational and Psychological Measurement, 39, 917–921. Howrigan, D. P., & MacDonald, K. B. (2008). Humor as a mental fitness indicator. Evolutionary Psychology, 6,

652–666. Jauk, E., Benedek, M., Dunst, B., & Neubauer, A. C. (2013). The relationship between intelligence and

creativity: new support for the threshold hypothesis by means of empirical breakpoint detection. Intelligence, 41, 212–221.

Educ Psychol Rev (2015) 27:599–606 605

Karwowski, M., & Gralewski, J. (2013). Threshold hypothesis: fact or artifact? Thinking Skills and Creativity, 8, 25–33.

Kaufman, J. C. (2010). Using creativity to reduce ethnic bias in college admissions. Review of General Psychology, 14, 189–203.

Kaufman, S. B. (2013). Ungifted: intelligence redefined. New York: Basic Books. Kaufman, J. C., Plucker, J. A., & Baer, J. (2008). Essentials of creativity assessment. Hoboken: Wiley. Kaufman, J. C., Baer, J., Cropley, D. H., Reiter-Palmon, R., & Sinnett, S. (2013). Furious activity vs.

understanding: how much expertise is needed to evaluate creative work? Psychology of Aesthetics, Creativity, and the Arts, 7, 332–340.

Kenett, Y. N., Anaki, D., & Faust, M. (2014). Investigating the structure of semantic networks in low and high creative persons. Frontiers in Human Neuroscience, 8(407), 1–16.

Kim, K. H. (2005). Can only intelligent people be creative? A meta-analysis. Journal of Secondary Gifted Education, 16, 57–66.

Lee, C. S., & Therriault, D. J. (2013). The cognitive underpinnings of creative thought: a latent variable analysis exploring the roles of intelligence and working memory in three creative thinking processes. Intelligence, 41, 306–320.

McGrew, K. S. (2005). The Cattell-Horn-Carroll theory of cognitive abilities. In D. P. Flanagan & P. L. Harrison (Eds.), Contemporary intellectual assessment: theories, tests, and issues (2nd ed., pp. 136–181). New York: Guilford.

McGrew, K. S. (2009). CHC theory and the human cognitive abilities project: standing on the shoulders of the giants of psychometric intelligence research. Intelligence, 37, 1–10.

Mednick, S. A. (1962). The associative basis of the creative process. Psychological Review, 69, 220–232. Nusbaum, E. C., & Silvia, P. J. (2011). Are intelligence and creativity really so different? Fluid intelligence,

executive processes, and strategy use in divergent thinking. Intelligence, 39, 36–45. Primi, R. (2014). Divergent productions of metaphors: combining many-facet Rasch measurement and cognitive

psychology in the assessment of creativity. Psychology of Aesthetics, Creativity, and the Arts, 8, 461–474. Runco, M. A. (2007). Creativity. Amsterdam: Elsevier. Sawyer, R. K. (2006). Explaining creativity: the science of human innovation. New York: Oxford University

Press. Silvia, P. J. (2008a). Another look at creativity and intelligence: exploring higher-order models and probable

confounds. Personality and Individual Differences, 44, 1012–1021. Silvia, P. J. (2008b). Creativity and intelligence revisited: a latent variable analysis of Wallach and Kogan (1965).

Creativity Research Journal, 20, 34–39. Silvia, P. J., & Beaty, R. E. (2012). Making creative metaphors: the importance of fluid intelligence for creative

thought. Intelligence, 40, 343–351. Silvia, P. J., Winterstein, B. P., Willse, J. T., Barona, C. M., Cram, J. T., Hess, K. I., Martinez, J. L., & Richard, C.

A. (2008). Assessing creativity with divergent thinking tasks: exploring the reliability and validity of new subjective scoring methods. Psychology of Aesthetics, Creativity, and the Arts, 2, 68–85.

Silvia, P. J., Martin, C., & Nusbaum, E. C. (2009). A snapshot of creativity: evaluating a quick and simple method for assessing divergent thinking. Thinking Skills and Creativity, 4, 79–85.

Silvia, P. J., Beaty, R. E., & Nusbaum, E. C. (2013). Verbal fluency and creativity: general and specific contributions of broad retrieval ability (Gr) factors to divergent thinking. Intelligence, 41, 328–340.

Skrondal, A., & Rabe-Hesketh, S. (2004). Generalized latent variable modeling: Multilevel, longitudinal, and structural equation models. Boca Raton: Chapman & Hall/CRC.

Sternberg, R. J., & Lubart, T. I. (1991). An investment theory of creativity and its development. Human Development, 34, 1–31.

Torrance, E. P. (2008). Torrance Tests of Creative Thinking: norms-technical manual, verbal forms A and B. Bensenville: Scholastic Testing Service.

Vartanian, O., Bouak, F., Caldwell, J. L., Cheung, B., Cupchik, G., Jobidon, M. E., Lam, Q., Nakashima, A., Paul, M., Peng, H., Silvia, P. J., & Smith, I. (2014). The effects of a single night of sleep deprivation on fluency and prefrontal cortex function during divergent thinking. Frontiers in Human Neuroscience, 8(214), 1–12.

Wallach, M. A., & Kogan, N. (1965). Modes of thinking in young children: a study of the creativity–intelligence distinction. New York: Holt, Rinehart, & Winston.

Weisberg, R. W. (2006). Creativity: understanding innovation in problem solving, science, invention, and the arts. Hoboken: Wiley.

Wilson, R. C., Guilford, J. P., & Christensen, P. R. (1953). The measurement of individual differences in originality. Psychological Bulletin, 50, 362–370.

606 Educ Psychol Rev (2015) 27:599–606

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