Creativity Training

Comparing research on creativity training with the one on increasing intelligence reveals several differences. However, the most apparent one is that the idea to increase creative cognition has no real opposition as it is the case with intelligence. Several meta-analyses showed that there is moderate to high evidence that it is possible to raise creativity (e.g., Torrance, 1972; Scot et al., 2004; Ma, 2006). Given the importance of creativity for society underlined in almost every research paper[1], it is surprising that we do not face a more intense promotion and an extended range of computerized creativity training programs, as it is the case with so-called brain training programs of intelligence. SharpBrains (2013; 2015) assessed the state of the digital brain training market in the intelligence domain (products for assessing training-induced improvements in brain function), reporting sales of $210 million in 2005, $600 million in 2009, and $1.3 billion in 2013; predicting a total of $6.15 billion in yearly sales by the year 2020 ($3.38 billion for training software). In contrast, computerized creativity training programs are often designed for research purposes only (e.g., Coppi, 2015; Fink et al., 2015). Thus we are faced with a paradox: creative training appears to work, creativity is of immense importance for society, but there is no broader interest/intention to boost it. Why? In our opinion the most likely reason is the prevailing view in folk and scientific psychology that creativity is just part of the intelligence construct. Yet another issue that hampers the development of creativity training programs is that albeit training increases the number of original and flexible uses for an umbrella, this has very little to do with Einstein’s relativity theory, Mozart’s Marriage of Figaro, Leonardo’s Mona Lisa, or Kafka’s The Trial.

Increasing creativity – behavioral level

Creativity training was most popular in the second half of the 20^th century. Research interest for the topic has declined since then and the focus has moved toward the neurobiological changes elicited by such training programs. One of the first reviews on the trainability of creativity in children was carried out by Torrance (1972). The review of 142 studies established that the Osborn–Parnes Creative Problem Solving (CPS) training program and its modifications were the most successful. Similar conclusions on the effectiveness of creativity training programs were also found in two more recent meta-analyses (Scot et al., 2004; Ma, 2006). Both authors also pointed out that approaches to encourage creativity are rather diverse.

For example, Scot et al. (2004) classified them into six categories: (1)  provisioning of effective incentives, (2) acquisition of requisite expertise, (3) effective structuring of group interactions, (4) optimization of climate, (5) identification of requisite career development experiences and (6) training to enhance creativity. It was further reported that training programs to enhance creativity were the most preferred methods by providers from organizations as well as educational institutions. Moreover, these training programs were predominantly shaped by theoretical frameworks for understanding the creative act adopted by scholars (e.g., cognition,  personality, motivation, or social interactions). The meta-analysis by Scot et al. (2004) included 70 studies. The overall effect size obtained was 0.68 (SD = 0.09; when corrected for outliers 0.64; SD = 0.07).  With respect to the criteria used to evaluate the training outcomes, the highest effect sizes were obtained for divergent thinking (0.75) and problem solving (0.84), whereas for performance and behavior criteria smaller, albeit still sizable effects were observed (0.35; 0.24). Furthermore, the highest effect sizes were obtained for originality, followed by fluency, flexibility and elaboration. In addition it was found that training effects were similar for older and younger individuals. There was also no difference with respect to the institution providing the program (educational versus organizational). The training was more beneficial for males, and for nongifted subjects. All in all: “…. the most clear-cut conclusion to emerge from this study is that creativity training is effective” (Scot et al., 2004; p. 381).

Even more pronounced effect sizes were reported in the meta-analysis by Ma (2006), with a grand mean effect size of 0.77 (SD = 0.74). In this study altogether 268 effect sizes from 34 studies were included. The training programs were divided into 10 categories with an additional category for composite techniques. The program categories were: (1) simple ideation program, (2) attitude training (3) synectics, (4) Idea checklist/SCAMPER (an acronym for substitute, combine, adapt, modify/magnify/minimize, put to other uses, eliminate, and reverse/rearrange), and (5) incubation. The programs  (6) brainstorming (7) forced relation, (8) catalog, (9) part improving, and (10) morphological synthesis were combined as “problem identifying” methods. The composite techniques included were: Computer-aided creativity training programs, Purdue Creative Thinking Program, New Directions in Creativity Program (based on Guilford’s SOI model); Khatena’s Training Method, and the Osborn–Parnes CPS program. The meta-analysis further revealed that the training effects were influenced by the moderating variables type of training program and age of participants. The highest effect sizes were observed for attitude training, simple ideation and New Directions in Creativity Program (effect sizes between 0.99 to 1.46). The lowest effect sizes were obtained for the Idea checklist/SCAMPER; incubation and the combined category problem identifying (effect sizes from 0.06 to 0.34). The effect sizes for the other programs ranged between 0.61 and 0.84. The results showed a trend that the older the age of participants, the larger the effect size (with the exception of college students). The moderating variables tests used to measure creativity, experimental design and duration of training were not significant.

A Web of Science search for meta-analyses of creative training found no more recent publications, which indicates that the interest for these kind of programs has declined. We found only specific research highlighting particular approaches and techniques.

Colzato et al. (2012), for instance, analyzed the influence meditation has on creativity. The authors compared the effects of Focused Attention meditation (FA) and Open Monitoring meditation (OM) on divergent and convergent creative thinking. During FA meditation, participants had to focus attention to particular parts of the body while during OM meditation, they had to open the mind to any occurring thought with a nonjudgmental attitude. Both meditation types had specific effects on creativity. OM meditation positively influenced performance on tasks of alternate uses that require weak top-down guidance during generation of new ideas. In contrast, FA meditation had no beneficial influence on the remote association test (RAT) that would require a focused control style of operating. The authors explained the FA effects in relation to improved mood observed after FA meditation that could have hampered RAT performance. In yet another study, Sahin (2014) analyzed the effectiveness of mentoring showing that this method is highly effective in teaching creative thinking skills to gifted and non-gifted students. Furthermore, Madore et al. (2015) showed that episodic-specificity induction can enhance divergent creative thinking. Compared were episodic inductions which fostered specific recall of events by imagery with recall of more general events without imagery. In the former approach participants generated more categories of alternative uses than after episodic induction without imagery. The authors inferred: “…that an episodic-specificity induction that increases the number of episodic details participants generate in imagining future events also boosts their performance on the AUT, a classic test of divergent thinking” (Madore et al., 2015; p.1466).

This brief review of papers on creativity training indicates that the topic is far from being in the mainstream of creativity research. There is a lack of elaborated general goals, recommendations or identified trends for future exploration.

Increasing creativity – neurobiological changes

Studies aiming to relate training-induced changes in creative performance with changes in brain function have only recently gained in popularity, thus there is not much to review. Like in the general research area on neurobiological underpinnings of creativity, the main lab that studies this topic is the group involving Andreas Fink and Mathias Benedek from the University of Graz. In one of their first studies, Fink et al. (2010) investigated whether creative cognition can be enhanced by idea sharing and whether the performance differences are reflected in brain activity determined with fMRI. Respondents were exposed to two training conditions and in one of them they were confronted with ideas (answers – alternative uses of everyday objects) of other participants. This approach was shown to be effective in group-based brainstorming. In the control condition the individuals were instructed to reflect on their own answers. The cognitive training was effective in improving the originality of answers. Furthermore, the performance improvement was also reflected in brain activity mainly in right-hemispheric temporo-parietal, medial frontal, and posterior cingulate cortices, bilaterally. The central finding was that creative idea generation was associated with deactivations in parieto-temporal brain regions.

In a second study by the same group (Jauk et al., 2015), the influence of a 3 week verbal creativity training program on creative performance and brain activity was investigated. Respondents were tested 3 times, and were randomly assigned into two groups. The first group received training between the 1^st and 2^nd testing, whereas the second group was trained between the 2^nd and 3^rd test sessions. The training was computer based (CreaTrain) and consisted of different verbal divergent thinking exercises requiring about 20 min of daily work. Increases in verbal creativity were only observed for the second group receiving training between the 2^nd and 3^rd testing. Contrary to behavioral results, which differed between groups,  functional patterns of brain activity during creative ideation were similar across both training groups. The main brain areas involved were the left inferior parietal cortex and the left middle temporal gyrus. Comparable results were also obtained  in a longitudinal training study by Sun et al., (2016) who used a similar training paradigm as the one adopted by Fink et al. (2010). In addition to the functional changes in brain activity, the training induced gray matter volume increases in the dorsal anterior cingulate cortex.

In summary, it seems that creative training works and shows also changes in brain activity and structure, albeit the latter conclusion must be taken with care given the limited number of studies it is based on. All authors agreed that creative training changed brain activation patterns in exactly those brain areas that had been associated with creativity in correlational studies. This is of course not surprising since creativity was shown to be related to almost every brain area – either activating or deactivating it, thereby limiting the conclusions that can be drawn regarding the influence of creative training on brain activity.

A question that remains is: to what extent are these creativity training programs similar to the criterion tests? For several of them we could say that the improvements point to near transfer effects, such as improvements in n-back performance after n-back training. What about far transfer effects? To exaggerate, do you become a poet or a novelist after verbal ideational training of the CreaTrain type? Perhaps the answer NO is one of the reasons why there is a lack of interest in this kind of research.

References

Colzato, L. S., Ozturk, A., & Hommel, B. (2012). Meditate to Create: The Impact of Focused-Attention and Open-Monitoring Training on Convergent and Divergent Thinking. Frontiers in Psychology, 3. https://doi.org/10.3389/fpsyg.2012.00116

Coppi, A. E. (2015). Fostering Creativity through Games and Digital Story Telling (pp. 17–21). IEEE. https://doi.org/10.1109/iTAG.2015.12

Fink, A., Benedek, M., Koschutnig, K., Pirker, E., Berger, E., Meister, S., … Weiss, E. M. (2015). Training of verbal creativity modulates brain activity in regions associated with language- and memory-related demands: Training of Verbal Creativity. Human Brain Mapping, 36(10), 4104–4115. https://doi.org/10.1002/hbm.22901

Fink, A., Grabner, R. H., Gebauer, D., Reishofer, G., Koschutnig, K., & Ebner, F. (2010). Enhancing creativity by means of cognitive stimulation: Evidence from an fMRI study. NeuroImage, 52(4), 1687–1695. https://doi.org/10.1016/j.neuroimage.2010.05.072

Ma, H.-H. (2006). A synthetic analysis of the effectiveness of single components and packages in creativity training programs. Creativity Research Journal, 18(4), 435–446.

Madore, K. P., Addis, D. R., & Schacter, D. L. (2015). Creativity and memory effects of an episodic-specificity induction on divergent thinking. Psychological Science, 956797615591863.

Şahin, F. (2014). The effectiveness of mentoring strategy for developing the creative potential of the gifted and non-gifted students. Thinking Skills and Creativity, 14, 47–55. https://doi.org/10.1016/j.tsc.2014.07.002

Scott, G., Leritz, L. E., & Mumford, M. D. (2004). The effectiveness of creativity training: A quantitative review. Creativity Research Journal, 16(4), 361–388.

SharpBrains. (2013). Web-based, mobile and biometrics-based technology to assess, monitor and enhance cognition and brain functioning: The digital brain health market, 2012–2020. San Francisco, CA: SharpBrains.

SharpBrains. (2015, January). The digital brain health market 2012–2020: Web-based, mobile and biometrics-based 184 technology to assess, monitor, and enhance cognition and brain functioning [Addendum]. San Francisco, CA: SharpBrains.

Sun, J., Chen, Q., Zhang, Q., Li, Y., Li, H., Wei, D., … Qiu, J. (2016). Training your brain to be more creative: brain functional and structural changes induced by divergent thinking training: The Neural Plasticity of Creativity. Human Brain Mapping, 37(10), 3375–3387. https://doi.org/10.1002/hbm.23246

Torrance, E. P. (1972). Can we teach children to think creatively? Journal of Creative Behavior, 6, 114–143.

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[1]Importance for entrepreneurial activities and long-term economic growth; linked to the development of new social institutions,“good” jobs, well-being and successful adaptation to the demands of daily life;  the evolution of civilization; creativity can help us understand the rapidly increasing complexity of the world around us, where it is estimated that human knowledge doubles every seven years, etc.