Seven Questions about Creativity and Creative Thinking

2. Divergent and convergent thinking: which tasks led to more creative ideas on the PISA test?

The literature broadly agrees that creative thinking involves both divergent-exploratory and convergent-integrative cognitive processes (Barbot, Besançon and Lubart, 2011[1]; Cropley, 2006[2]; Dygert and Jarosz, 2020[3]; Guilford, 1967[4]). Divergent thinking supports idea generation by enabling individuals to connect diverse pieces of information and adopt different points of view (Guilford, 1956[5]; Guilford, 1967[4]). Convergent thinking is the ability to apply logical reasoning to information and it is crucial for problem-finding, identifying and selecting good ideas, and supporting decision-making (Guilford, 1956[5]; Cropley, 2006[2]). This process has also been referred to as convergent-integrative thinking, where several disparate elements are brought together into a new, original synthesis (Barbot, Besançon and Lubart, 2011[1]). Some researchers have also sought to understand and explore the similarities between the dual cognitive processes involved in creative thinking and other dual-process models of cognition that differentiate between more freely associative and more structured or deliberate thinking modes (e.g. (Sowden, Pringle and Gabora, 2018[6]; Smith, Ward and Finke, 1995[7]; Beaty et al., 2016[8]). Generally, these dual divergent and convergent cognitive processes involved in creative work occur iteratively throughout the creative process, but their relative importance and effectiveness may vary depending on the domain or task at hand (Baer, 2016[9]; Barbot, Besançon and Lubart, 2011[1]; Botella and Lubart, 2015[10]), situational or dispositional factors (Nijstad et al., 2010[11]), or the stage of the creative process in which they occur (Howard-Jones, 2002[12]).

The PISA 2022 test identified and measured three distinct ideation processes that reflected these divergent-exploratory and convergent-integrative aspects of creative thinking, with each test task corresponding to a specific ideation process (OECD, 2023[13]). ‘Generate diverse ideas’ tasks elicited evidence of the divergent-exploratory aspects of creative thinking: these tasks presented students with a context and some stimulus material (e.g. an image, a problem or need, etc.), and asked students to come up with two or three ideas that were as different as possible from each other. ‘Generate creative ideas’ and ‘evaluate and improve ideas’ tasks similarly presented students with a context and stimulus material but asked them to come up with an original idea or improve someone else’s idea. While these latter task types also involve idea generation, they also involve the convergent-integrative aspects of creative thinking (understanding the problem, evaluating and selecting ideas, and/or producing an original synthesis).

The PISA 2022 results reported students’ success in the different types of task in the assessment (i.e. in generating diverse or original ideas), but the results could not provide information about the overall creative quality of students’ ideas resulting from these different ideation processes. Data from the PISA CT Rescoring project does allow us to examine this. Can we observe differences in the quality of creative outcomes following different ideation processes? What might any differences imply for supporting students to come up with creative ideas in different types of tasks?

2.1. Do divergent thinking tasks generate creative ideas?

Four of the seven tasks included in the PISA CT Rescoring project were classified as ‘generate diverse ideas’ tasks: Illustration Titles, Food Waste and The Exhibit (Tasks 2, 5 and 7) asked students to come up with three ideas for a given scenario that were as different as possible, whereas the Save the River task (Task 6) asked students to come up with just two different ideas (see Figures C, F, G and H in the Introduction section of this report for more information on the tasks included in the study). Although the task instructions did not explicitly instruct students to think of creative ideas per se in these tasks, did students generate them anyway as a result of engaging in divergent thinking?

Figure 2.1 shows the share of students that suggested none, one or multiple creative ideas in the four ‘generate diverse ideas’ tasks included in the PISA CT Rescoring study. “Creative ideas” in this chapter are defined as those that scored highly (within 1 point of the maximum score) for each idea criteria of appropriateness, originality and value (see Box 2.1). On average across country-language groups, just under half (48%) of all student responses in ‘generate diverse ideas’ tasks requiring three ideas included at least one creative idea, despite students not being explicitly instructed to be creative in their responses. Around 1 in 4 student responses to these divergent thinking tasks included at least two creative ideas, on average across country-language groups (Table B2.1).

Box 2.1. Which score data are used in this chapter?

The analyses in this chapter draw upon one type of rescored data from the PISA CT Rescoring project, the criteria scores. The Criteria-Based scoring method awarded each idea within a student response a score for appropriateness, originality and value (see Annex A2). A cumulative idea sum score was also produced by aggregating the scores across these three criteria for each idea.

This chapter focuses on examining the quality of students’ ideas in subsets of tasks (‘generate diverse ideas’ and ‘generate creative ideas’ tasks) that involve different ideation processes. The analyses conducted in this chapter identify a “creative idea” as an idea that scored at least 1 point for appropriateness (out of an available 2 score points) and at least 2 points for both originality and value respectively (out of an available 3 score points each).

We use criteria scores for the analyses in this chapter as these scores apply to each idea within a student response. In contrast, only one holistic creativity score is attributed per student response (i.e. considering all ideas together), and as such, these scores do not allow the quality of each idea within a response to be examined independently.

In general, and in around half of the country-language groups, students were less likely to propose creative ideas in the problem-solving tasks asking for different ideas (Tasks 5, 6 and 7) compared to the sole written expression divergent thinking task, Illustration Titles (Task 2) (Table B2.1). This difference may largely be due to the relative difficulty of the tasks in the different domains, with students more likely to achieve lower sum scores and individual criteria scores in the problem-solving tasks on average across country-language groups than in the creative expression tasks (Tables B2.2).

Across country-language groups, there is significant variation in the number of responses containing creative ideas in the ‘generate diverse ideas’ tasks (Figure 2.2). Students in Korea were by far the most successful, with nearly 9 in 10 student responses including at least one creative idea on average across the three tasks requiring three ideas (Tasks 2, 5 and 7). Well over 50% of student responses in Hong Kong (China), Italy, Saudi Arabia, Slovenia, Belgium (French community), Germany and France also contained at least one creative idea on average across these three tasks. Conversely, over 80% of responses in Colombia and Brazil, and nearly 90% of responses in Chile, did not include any creative ideas on average across the three ‘generate diverse ideas’ tasks requiring three ideas.

Figure 2.1. Nearly half of all student responses in ‘generate diverse ideas’ tasks contained at least one creative idea

Percentage of student responses with 0-3 creative ideas, on average across country-language groups, by task

Note: (*) As Task 6 – Save the River requires only two ideas, rather than three ideas, the Average task bar excludes data from Task 6. Average percentages for each task were computed by country-language group then averaged across country-language groups. ‘Creative ideas' are defined as those that scored at least 1 score point in appropriateness (out of a possible 2 score points) and that scored at least 2 score points in both originality and value (out of a possible 3 score points each).

Source: Table B2.1

These results suggest that even when students are not explicitly prompted to think of creative ideas, divergent thinking tasks nonetheless encourage creative idea generation. These findings also align with experimental studies focused on training creativity that have generally targeted divergent thinking processes and noted positive effects (see Box 2.2). It is notable that many students across many country-language group contexts in our study can successfully think of creative ideas in these tasks even though they only require a limited number of different ideas (in contrast to, for example, the “think-of-as-many-ideas-as-you-can” model that is typically used in other divergent thinking tasks). It may be that students engaged in some initial filtering of a longer list of ideas before submitting their responses to these PISA 2022 tasks, thus selecting only their ‘best’ ideas, but it suggests that even limited idea generation activities can support creative outcomes.

Figure 2.2. The share of student responses containing creative ideas varies across country-language groups

Percentage of student responses with 0-3 creative ideas, on average across ‘generate diverse ideas’ tasks (*), by country-language group

Note: (*) As Task 6 – Save the River requires only two ideas, rather than three ideas, the country-language group averages exclude data from Task 6. ‘Creative ideas' are defined as those that scored at least 1 score point in appropriateness (out of a possible 2 score points) and that scored at least 2 score points in both originality and value (out of a possible 3 score points each).

Source: Table B2.1

Box 2.2. Research spotlight: Strategies for teaching students to think creatively

Various creativity techniques have been developed to enhance creative thinking at different stages of the creative process, although most focus on facilitating idea generation (Vernon, Hocking and Tyler, 2016[14]). In general, techniques aiming to promote idea generation generally employ two types of methods: (1) a stimuli-oriented method (i.e. using input to achieve a shift in perspective and foster creative idea generation) and (2) a relationship-oriented method (i.e. focusing on free association or forced relationships as means to generate new ideas). For instance, studies have found a positive effect of showing novel examples (in contrast to common examples) as input stimuli, in particular to improve the originality of ideas generated during divergent thinking exercises (Agogué et al., 2014[15]; Yuan et al., 2021[16]), although others have highlighted that input stimuli should be aligned with individual needs and preferences in order to be effective (De Jonge, Rietzschel and Van Yperen, 2018[17]).

Relatively less research has focused on techniques to promote and improve convergent thinking processes. Some techniques, such as idea evaluation metrics or strengths and weaknesses analyses, have been used in prior creativity training programs but were found to have little effect on convergent thinking outcomes – likely because success in identifying and evaluating “good” ideas is intimately tied with domain knowledge, while creativity techniques tend to address creative thinking in a domain-general way (van Broekhoven et al., 2020[18]; Ritter et al., 2020[19]).

General creativity training interventions in higher education settings

Most recent studies examining the effectiveness of creativity training programs have been conducted in university settings, employing general cognitive-based techniques to promoting students’ creativity. Ritter et al. (2020[19]) conducted a year-long creativity training program involving university students in the Netherlands enrolled in the Business department, during which students learned how to apply the Six Step Cycle of Creativity (understanding the question, convergent thinking, divergent thinking, detached thinking, stop thinking, and sleeping) to a range of problems. The study found the intervention significantly improved students’ idea generation and flexibility in divergent thinking tasks, but not idea originality. Interestingly, although the course ran for an academic year, researchers observed significant effects after just 3 months of training, with no further improvement in students’ creative performance following further training. In a separate study, Ritter and Mostert (2017[20]) also found that even a brief 1.5 hour cognitive-based training improved outcomes on different creative thinking measures, particularly improving cognitive flexibility on divergent thinking tasks.

Similar undergraduate creativity and innovation training modules for students across disciplines have been developed by researchers at universities in the United Arab Emirates (UAE) and Germany, respectively. In the UAE study, the module introduced students to theoretical conceptualisations of creative thinking as well as to the practical application of a variety of techniques to solve real-world problems, and sessions primarily centred around group activities; after the training, students significantly improved in their idea originality, elaboration, and fluency (Vally et al., 2019[21]). In the German study, students attended eight 90-minute lectures to introduce participants to essential theories and models of creativity, before completing a 4-week practical component; results showed a positive effect of the training on creative performance, with the increase in performance remaining relatively stable over time (beyond the training period) (Meinel et al., 2018[22]).

School-based interventions aimed at improving students’ scientific creativity

Most studies looking at the effects of creativity interventions in school-age populations have focused on creativity in the sciences. For example, Sun, Wang and Wegerif (2020[23]) conducted an experimental study involving 105 high school students in China. Students in the experimental condition were trained in divergent thinking strategies, including association, decomposition and combination with adjustment, with examples of how to apply these strategies to real-world problems. The study found a significant difference in the post-test performance between the experimental and control groups, suggesting that the cognitive-based training was useful in improving students’ scientific creativity. The study found that all students (both those with “low” and “high” self-reported creative potential) benefitted from the training, but that students with greater scientific-domain knowledge before the training improved their scientific creativity even more than students with a low level of domain-knowledge.

Yang and colleagues (2016[24]) studied the effect of a well-designed, inquiry-based teaching classroom intervention over the course of a semester on students’ scientific creativity in an elementary school in Chinese Taipei. They found that the intervention group significantly outperformed students in the control group in the post-tests focused on science inquiry, convergent thinking and divergent thinking respectively. The study also explored effective teaching practices on creative cognitive processes. The main practices supporting divergent thinking were ‘facilitating associative thinking’ and ‘sharing impressive ideas’, while ‘encouraging evidence-based conclusions’ and ‘reviewing and commenting on group presentations’ were the teaching practices most supportive to developing convergent thinking.

Summary

Recent research has found that training programs or interventions can support improvements in creative outcomes, particularly students’ ideation skills in divergent thinking tasks. These findings align with those of an earlier review of the effectiveness of creativity training, which found that well-designed creativity training programs typically do induce gains in performance that generalise across different creativity criteria (e.g. fluency, flexibility, originality), settings, and target populations (Scott, Leritz and Mumford, 2004[25]). Factors contributing to the relative effectiveness of such training programs include focusing on developing cognitive skills and the heuristics involved in their practical application using realistic exercises.

The school-based interventions described above also highlight how domain knowledge facilitates successful creative thinking outcomes, and the importance of developing well-designed, contextualised approaches to teaching creative thinking in educational settings. It may also be that such interventions typically require students to be more active participants in self-directed learning activities, thus increasing their motivation and metacognitive skills, which in turn facilitates their capacity to engage successfully in creative thinking in these contexts (Hu et al., 2013[26]).

2.2. Which ideation process led to more creative outcomes?

The findings in the first section of this chapter raise a related question: in which type of task on the PISA test were students more successful in thinking of creative ideas? In the ‘generate creative ideas’ tasks, students were explicitly asked to think of a single, original idea in response to the task stimulus. Perhaps surprisingly, students were far less likely to come up with a creative idea on these tasks compared to the divergent thinking tasks – with only around 25% of student responses on average across country-language groups scoring highly in appropriateness, originality and value in these tasks (Figure 2.3). This means that, on average across the different tasks, there is a 20-percentage point gap in the relative share of students that provided at least one creative idea when instructed to focus on idea originality compared to generating diverse ideas of any quality (Figure 2.4).

Figure 2.3. Only one quarter of responses to ‘generate creative ideas’ tasks were creative

Percentage of student responses that included a creative idea, on average across country-language groups, by task

Note: Average percentages for each task were computed by country-language group then averaged across country-language groups. ‘Creative ideas' are defined as those that scored at least 1 score point in appropriateness (out of a possible 2 score points) and that scored at least 2 score points in both originality and value (out of a possible 3 score points each).

Source: Table B2.3

This trend is consistent across most country-language groups included in the PISA CT Rescoring study, although the relative shares of student responses with at least one creative idea on average across the two task types are similar in Brazil, Canada (English provinces) and Chile (Figure 2.4). Differences in the relative shares of responses that included at least one creative idea across the two task types are most pronounced in Hong Kong (China), Italy and Saudi Arabia, with a difference of over 30-percentage points in favour of creative outcomes in the ‘generate diverse ideas’ tasks.

Figure 2.4. Divergent thinking tasks consistently led to more student responses with creative ideas

Note: Average percentages for each task ideation process were computed first by country-language group on the pooled responses across relevant tasks, then averaged across country-language groups. All four GDI tasks are included in the GDI task average. ‘Creative ideas' are defined as those that scored at least 1 score point in appropriateness (out of a possible 2 score points) and that scored at least 2 score points in both originality and value (out of a possible 3 score points each). In all country-language groups except Chile and Canada (French provinces), which are shown in a lighter tone, differences are statistically significant.

Source: Table B2.4

While these differences are substantial, one should take into consideration that the task difficulty and constraints across task types were not the same and therefore may have influenced the findings in our study. Nonetheless, the mean criteria scores of ideas across the two task types can shed additional light on the potential sources of these differences in creative outcomes (Table B2.2). On average across country-language groups, ideas in both types of task are similarly appropriate. The average idea in ‘generate diverse ideas’ tasks tended to be slightly less original than those in ‘generate creative ideas’ tasks, though the difference is small (less than 0.1 score points). This aligns with previous research that has found idea flexibility (the focus of the PISA divergent thinking tasks) to be more strongly associated with originality than other aspects of divergent thinking, for example fluency (Nijstad et al., 2010[11]). It may be that instructing students to focus on idea flexibility inevitably brings forth original ideas as a byproduct, regardless of whether originality is an explicit task demand. The criteria that is most different across the two task types is value, with ideas scoring 0.15 score points higher in the ‘generate diverse ideas’ tasks than in the ‘generate creative ideas’ tasks. Perhaps directing students’ attention to originality leads them to largely ignore the value of valuable ideas in their idea generation process, or to search for original ideas at the expense of value. In other words, focusing students on originality too early during idea generation might limit the utility of their idea generation process and result in a less creative pool of ideas from which to further iterate.

These differences in creative success across the two task types may also point towards difficulties in convergent thinking, that is identifying, evaluating and selecting ideas to move forward. Research has found that individuals tend to have difficulties in recognising and selecting creative ideas, opting instead to choose more feasible and desirable ideas (Rietzschel, Nijstad and Stroebe, 2014[27]). In both types of PISA tasks, it’s reasonable to assume that students engage in divergent thinking (i.e. thinking of multiple possible ideas), with students additionally needing to apply convergent thinking (i.e. choosing their most original idea) in the ‘generate creative ideas’ task. It may be at this point, rather than the idea generation phase, that students encounter difficulties. The data show that while the mean originality score of students’ ideas in the ’generate creative ideas’ tasks was 1.2 score points, the mean originality score of their most creative idea in the ‘generate diverse ideas’ tasks was much higher at 1.7 score points (a difference of around 0.5 score points) (Table B2.2 and Table B2.5). Although the different task instructions may have differentially constrained the quality of ideas that students generated and thus were able to choose from, it may also be that students did not successfully choose their most creative idea in the ‘generate creative ideas’ tasks. Further examining the role of convergent thinking in the creative process, the factors influencing its success (e.g. domain-knowledge, affective states), and instructional strategies to promote it is an area worthy of focus in future research (van Broekhaven, 2025[28]).

2.3. Are last ideas always better in an idea generation process?

As described above, student responses to the PISA tasks tended to be slightly more creative on average in the ‘generate diverse ideas’ tasks (mean idea sum score of 3.7 points) compared to the ‘generate creative ideas’ tasks (mean idea sum score of 3.6 points) (Table B2.2). These score differences become much starker when averaging students’ ‘best’ ideas only in each task, with the mean ‘best idea’ sum scores in the ‘generate diverse ideas’ tasks totalling 5.4 score points on average across tasks (Table B2.2 and Table B2.5). Where do these ‘best ideas’ occur? Is it that students’ last ideas in an idea generation process tend to be of higher quality?

Some empirical studies have found that later responses tend to be more creative than earlier ones in divergent thinking tasks (Benedek and Neubauer, 2013[29]; Benedek et al., 2014[30]; Christensen, Guilford and Wilson, 1957[31]; Piers and Kirchner, 1971[32]), whereas others have shown mixed results depending on the study conditions (Camarda et al., 2018[33]). Other researchers have also suggested that this order effect is mediated by various factors including fluid intelligence (Beaty et al., 2014[34]; Beaty and Silvia, 2012[35]) and executive control mechanisms (Beaty et al., 2014[34]; Ezzat et al., 2017[36]; Zabelina and Robinson, 2010[37]; Beaty et al., 2016[8]; Hao et al., 2015[38]) that inhibit the relevant but unoriginal ideas that typically come to mind at the beginning of a divergent thinking task (Gilhooly et al., 2007[39]).

We examined this idea order effect on the three ‘generate diverse ideas’ tasks in the PISA CT Rescoring study that require students to think of three different ideas. Our results show that, unlike prior research, students’ first ideas tended to be their most creative idea and their last ideas least creative (Table 2.1). This general observation is also confirmed by looking at the frequency of students’ most creative idea per response idea position, with well over half (58%) submitted as students’ first idea on average across these three tasks (Table B2.7). This trend was also consistent across all country-language groups. Each of the individual criteria scores also tended to decrease as idea position increased, although idea originality remained relatively stable on average.

Table 2.1. First ideas in ‘generate diverse ideas’ tasks tended to be more creative

Mean idea sum and criteria scores by idea position in GDI tasks (*), on average across country-language groups

Response idea position	Appropriateness score	Originality score	Value score	Idea sum score
1	1.5	1.1	1.5	4.2
2	1.4	1.2	1.3	3.8
3	1.3	1.1	1.2	3.3

Note: (*) As Task 6 – Save the River requires only two ideas, rather than three ideas, the GDI task average excludes data from Task 6. Mean idea criteria scores for GDI tasks were computed first by country-language group on the pooled responses across relevant tasks, then averaged across country-language groups. Scores shown in the table are rounded to the nearest decimal point.

Source: Table B2.6

One reason for this may be that the PISA tasks focus on idea flexibility, specifically, rather than fluency or remoteness, which is often the focus of other divergent thinking tasks. Given the limited number of ideas required in the PISA tasks, it might be that students already engage in some executive control mechanisms to select only their best ideas as part of their response, opting to submit their best idea first. Recent research has found that the number of ideas provided in a task can influence the relationship between originality and serial order effect, with the ideas of participants with lower fluency being both more original and elaborate than those with higher fluency regardless of idea position (Gonthier and Besançon, 2024[40]). There is also a dependency between students’ ideas in the PISA tasks, given the instruction to provide ideas that are as different as possible to each other. Students may be able to think of creative ideas that are relatively similar, in which case they may choose to replace more creative ideas with more familiar yet different ones as the task progresses.

Key findings and implications

• Around 1 in 2 student responses to ‘generate diverse ideas’ tasks included at least one creative idea, on average. However, large differences were observed across country-language groups, with around 9 of every 10 student responses in Korea including at least one creative idea in these tasks compared to just 1 in 10 responses in Chile.

  • Idea generation activities that encourage students to come up with different ideas or solutions, even if limited in scope, can support creative idea generation in the context of everyday tasks.

• In general, a larger proportion of student ideas in the PISA ‘generate diverse ideas’ tasks (focused on idea flexibility) were considered creative than in the ‘generate creative ideas’ tasks (focused on idea originality). Only 1 in 4 responses to ‘generate creative ideas’ tasks included a creative idea (compared to around 1 in 2 in ‘generate diverse ideas’ tasks).

  • Constraining idea generation activities to original ideas only may serve to limit the quality of ideas that students are able to generate. Focusing on coming up with a few different ideas during the ideation phase may be a better strategy.

  • Students may also have difficulties in evaluating and selecting creative ideas (i.e. convergent thinking). Domain-relevant knowledge and skills support such decision-making processes by facilitating students’ understanding of what constitutes a “good” creative idea.

• Experimental studies focused on developing creativity have largely focused on training divergent thinking skills, with findings generally supporting that these skills can be trained and that they are associated with more creative outcomes (see Box 2.2).

  • Successful training programs tend to focus on developing cognitive skills and include activities related to their practical application in real-world contexts.

  • Effective school-based interventions have focused on contextualised approaches to creative thinking, weaving creative thinking techniques with the acquisition of domain-specific knowledge.

References

[15] Agogué, M. et al. (2014), “The impact of type of examples on originality: explaining fixation and stimulation effects”, Journal of Creative Behavior, Vol. 48/1, pp. 1-12, https://doi.org/10.1002/jocb.37.

[9] Barbot, B. (ed.) (2016), “Creativity doesn’t develop in a vacuum”, New Directions for Child and Adolescent Development, Vol. 151, pp. 9-20, https://doi.org/10.1002/cad.20151.

[1] Barbot, B., M. Besançon and T. Lubart (2011), “Assessing Creativity in the Classroom”, Open Education Journal, Vol. 4/1, pp. 58 - 66, https://doi.org/10.2174/1874920801104010058.

[8] Beaty, R. et al. (2016), “Creative Cognition and Brain Network Dynamics”, Trends in Cognitive Sciences, Vol. 20/2, pp. 87-95, https://doi.org/10.1016/J.TICS.2015.10.004.

[35] Beaty, R. and P. Silvia (2012), “Why do ideas get more creative across time? An executive interpretation of the serial order effect in divergent thinking tasks.”, Psychology of Aesthetics, Creativity, and the Arts, Vol. 6/4, pp. 309-319.

[34] Beaty, R. et al. (2014), “The roles of associative and executive processes in creative cognition”, Memory and Cognition, Vol. 42/7, pp. 1186-1197, https://doi.org/10.3758/S13421-014-0428-8.

[30] Benedek, M. et al. (2014), “To create or to recall? Neural mechanisms underlying the generation of creative new ideas”, NeuroImage, Vol. 88, pp. 125-133, https://doi.org/10.1016/J.NEUROIMAGE.2013.11.021.

[29] Benedek, M. and A. Neubauer (2013), “Revisiting Mednick’s model on creativity-related differences in associative hierarchies. Evidence for a common path to uncommon thought”, Journal of Creative Behavior, Vol. 47/4, pp. 273-289, https://doi.org/10.1002/JOCB.35.

[33] Camarda, A. et al. (2018), “Neural basis of functional fixedness during creative idea generation: An EEG study”, Neuropsychologia, Vol. 118, pp. 4-12, https://doi.org/10.1016/J.NEUROPSYCHOLOGIA.2018.03.009.

[31] Christensen, P., J. Guilford and R. Wilson (1957), “Relations of creative responses to working time and instructions”, Journal of Experimental Psychology, Vol. 53/2, pp. 82-88, https://doi.org/10.1037/H0045461.

[10] Corazza, G. and S. Agnoli (eds.) (2015), Creative processes: Art, design and science, Springer.

[2] Cropley, A. (2006), “In Praise of Convergent Thinking”, Creativity Research Journal, Vol. 18/3, pp. 391-404, https://doi.org/10.1207/s15326934crj1803_13.

[17] De Jonge, K., E. Rietzschel and N. Van Yperen (2018), “Stimulated by novelty? The role of psychological needs and perceived creativity”, Personality and Social Psychology Bulletin, Vol. 44/6, https://doi.org/10.1177/014616721775236.

[3] Dygert, S. and A. Jarosz (2020), “Individual differences in creative cognition”, Journal of Experimental Psychology: General, Vol. 149/7, pp. 1249-1274, https://doi.org/10.1037/xge0000713.

[36] Ezzat, H. et al. (2017), “How minimal executive feedback influences creative idea generation”, PLOS ONE, Vol. 12/6, p. e0180458, https://doi.org/10.1371/JOURNAL.PONE.0180458.

[39] Gilhooly, K. et al. (2007), “Divergent thinking: Strategies and executive involvement in generating novel uses for familiar objects”, British Journal of Psychology, Vol. 98/4, pp. 611-625, https://doi.org/10.1111/J.2044-8295.2007.TB00467.X.

[40] Gonthier, C. and M. Besançon (2024), “It is not always better to have more ideas: Serial order and the trade-off between fluency and elaboration in divergent thinking tasks”, Psychology of Aesthetics, Creativity, and the Arts, Vol. 18/4, pp. 480-492, https://doi.org/10.1037/aca0000485.

[4] Guilford, J. (1967), “Creativity: Yesterday, Today and Tomorrow”, The Journal of Creative Behavior, Vol. 1/1, pp. 3-14, https://doi.org/10.1002/j.2162-6057.1967.tb00002.x.

[5] Guilford, J. (1956), “The structure of intellect”, Psychological Bulletin, Vol. 53/4, pp. 267-293, https://doi.org/10.1037/H0040755.

[38] Hao, N. et al. (2015), “More mind wandering, fewer original ideas: Be not distracted during creative idea generation”, Acta Psychologica, Vol. 161, pp. 110-116, https://doi.org/10.1016/J.ACTPSY.2015.09.001.

[12] Howard-Jones, P. (2002), “A dual-state model of creative cognition for supporting strategies that foster creativity in the classroom”, International Journal of Technology and Design Education, Vol. 12/3, pp. 215-226, https://doi.org/10.1023/A:1020243429353.

[26] Hu, W. et al. (2013), “Increasing students’ scientific creativity: The “Learn to Think” intervention program”, The Journal of Creative Behavior, Vol. 47/1, pp. 3-21, https://doi.org/10.1002/jocb.20.

[22] Meinel, M. et al. (2018), “Explorin the effects of creativity training on creative performance and creative self-efficacy: Evidence from a longitudinal study”, Journal of Creative Behavior, Vol. 53/4, pp. 546-558, https://doi.org/10.1002/jocb.234.

[11] Nijstad, B. et al. (2010), “The dual pathway to creativity model: Creative ideation as a function of flexibility and persistence”, European Review of Social Psychology, Vol. 21/1, pp. 34-77, https://doi.org/10.1080/10463281003765323.

[13] OECD (2023), PISA 2022 Assessment and Analytical Framework, OECD Publishing, Paris, https://doi.org/10.1787/dfe0bf9c-en.

[32] Piers, E. and E. Kirchner (1971), “Productivity and uniqueness in continued word association as a function of subject creativity and stimulus properties”, Journal of Personality, Vol. 39/2, pp. 264-276, https://doi.org/10.1111/J.1467-6494.1971.TB00041.X.

[27] Rietzschel, E., B. Nijstad and W. Stroebe (2014), “Effects of problem scope and creativity instructions on idea generation and selection”, Creativity Research Journal, Vol. 26/2, pp. 185-191, https://doi.org/10.1080/10400419.2014.901084.

[19] Ritter, S. et al. (2020), “Fostering students’ creative thinking skills by means of a one-year creativity training program”, PLoS ONE, Vol. 15/3, https://doi.org/10.1371/journal.pone.0229773.

[20] Ritter, S. and N. Mostert (2017), “Enhancement of creative thinking skills using a cognitive-based creativity training”, Journal of Cognitive Enhancement, Vol. 1, pp. 243-253, https://doi.org/10.1007/s41465-016-0002-3.

[25] Scott, G., L. Leritz and M. Mumford (2004), “The effectiveness of creativity training: A quantitative review”, Creativity Research Journal, Vol. 16, pp. 361-388.

[7] Smith, S., T. Ward and R. Finke (eds.) (1995), The creative cognition approach, The MIT Press.

[6] Sowden, P., A. Pringle and L. Gabora (2018), “The shifting sands of creative thinking: Connections to dual-process theory”, in Gilhooly, K., L. Ball and L. Macchi (eds.), Insight and Creativity in Problem Solving, Routledge, https://doi.org/10.4324/9781315144061-3.

[23] Sun, M., M. Wang and R. Wegerif (2020), “Effects of divergent thinking training on students’ scientific creativity: The impact of individual creative potential and domain knowledge”, Thinking Skills and Creativity, Vol. 37, https://doi.org/10.1016/j.tsc.2020.100682.

[21] Vally, Z. et al. (2019), “Examining the effects of creativity training on creative production, creative self-efficacy, and neuro-executive functioning”, Creativity and Thinking Skills, Vol. 71, pp. 70-78, https://doi.org/10.1016/j.tsc.2018.11.003.

[28] van Broekhaven, K. (2025), “The evaluation and selection of creative ideas in educational settings: Current knowledge and future directions”, Creativity Research Journal, Vol. 37/2, pp. 307-131, https://doi.org/10.1080/10400419.2023.2253403.

[18] van Broekhoven, K. et al. (2020), “Fostering university students’ idea generation and idea evaluation skills with a cognitive-based creativity training”, Creativity: Theories - Research - Applications, Vol. 7/2, pp. 284-308, https://doi.org/10.2478/ctra-2020-0015.

[14] Vernon, D., I. Hocking and T. Tyler (2016), “An evidence-based review of creative problem solving tools: A practitioner’s resource”, Human Resource Development Review, Vol. 15/2, pp. 230-259, https://doi.org/10.1177/1534484316641512.

[24] Yang, K. et al. (2016), “Investigation of effective strategies for developing creativescience thinking”, International Journal of Science Education, Vol. 38/13, pp. 2133-2151, https://doi.org/10.1080/09500693.2016.1230685.

[16] Yuan, H. et al. (2021), “Examples facilitate divergent thinking: The effects of timing and quality”, Consciousness and cognition, Vol. 93, https://doi.org/10.1016/j.concog.2021.103169.

[37] Zabelina, D. and M. Robinson (2010), “Creativity as flexible cognitive control”, Psychology of Aesthetics, Creativity, and the Arts, Vol. 4/3, pp. 136-143, https://doi.org/10.1037/A0017379.