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What Is Creative Problem-Solving & Why Is It Important?

• 01 Feb 2022

One of the biggest hindrances to innovation is complacency—it can be more comfortable to do what you know than venture into the unknown. Business leaders can overcome this barrier by mobilizing creative team members and providing space to innovate.

There are several tools you can use to encourage creativity in the workplace. Creative problem-solving is one of them, which facilitates the development of innovative solutions to difficult problems.

Here’s an overview of creative problem-solving and why it’s important in business.

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What Is Creative Problem-Solving?

Research is necessary when solving a problem. But there are situations where a problem’s specific cause is difficult to pinpoint. This can occur when there’s not enough time to narrow down the problem’s source or there are differing opinions about its root cause.

In such cases, you can use creative problem-solving , which allows you to explore potential solutions regardless of whether a problem has been defined.

Creative problem-solving is less structured than other innovation processes and encourages exploring open-ended solutions. It also focuses on developing new perspectives and fostering creativity in the workplace . Its benefits include:

• Finding creative solutions to complex problems : User research can insufficiently illustrate a situation’s complexity. While other innovation processes rely on this information, creative problem-solving can yield solutions without it.
• Adapting to change : Business is constantly changing, and business leaders need to adapt. Creative problem-solving helps overcome unforeseen challenges and find solutions to unconventional problems.
• Fueling innovation and growth : In addition to solutions, creative problem-solving can spark innovative ideas that drive company growth. These ideas can lead to new product lines, services, or a modified operations structure that improves efficiency.

Creative problem-solving is traditionally based on the following key principles :

1. Balance Divergent and Convergent Thinking

Creative problem-solving uses two primary tools to find solutions: divergence and convergence. Divergence generates ideas in response to a problem, while convergence narrows them down to a shortlist. It balances these two practices and turns ideas into concrete solutions.

2. Reframe Problems as Questions

By framing problems as questions, you shift from focusing on obstacles to solutions. This provides the freedom to brainstorm potential ideas.

3. Defer Judgment of Ideas

When brainstorming, it can be natural to reject or accept ideas right away. Yet, immediate judgments interfere with the idea generation process. Even ideas that seem implausible can turn into outstanding innovations upon further exploration and development.

4. Focus on "Yes, And" Instead of "No, But"

Using negative words like "no" discourages creative thinking. Instead, use positive language to build and maintain an environment that fosters the development of creative and innovative ideas.

Creative Problem-Solving and Design Thinking

Whereas creative problem-solving facilitates developing innovative ideas through a less structured workflow, design thinking takes a far more organized approach.

Design thinking is a human-centered, solutions-based process that fosters the ideation and development of solutions. In the online course Design Thinking and Innovation , Harvard Business School Dean Srikant Datar leverages a four-phase framework to explain design thinking.

The four stages are:

• Clarify: The clarification stage allows you to empathize with the user and identify problems. Observations and insights are informed by thorough research. Findings are then reframed as problem statements or questions.
• Ideate: Ideation is the process of coming up with innovative ideas. The divergence of ideas involved with creative problem-solving is a major focus.
• Develop: In the development stage, ideas evolve into experiments and tests. Ideas converge and are explored through prototyping and open critique.
• Implement: Implementation involves continuing to test and experiment to refine the solution and encourage its adoption.

Creative problem-solving primarily operates in the ideate phase of design thinking but can be applied to others. This is because design thinking is an iterative process that moves between the stages as ideas are generated and pursued. This is normal and encouraged, as innovation requires exploring multiple ideas.

Creative Problem-Solving Tools

While there are many useful tools in the creative problem-solving process, here are three you should know:

Creating a Problem Story

One way to innovate is by creating a story about a problem to understand how it affects users and what solutions best fit their needs. Here are the steps you need to take to use this tool properly.

1. Identify a UDP

Create a problem story to identify the undesired phenomena (UDP). For example, consider a company that produces printers that overheat. In this case, the UDP is "our printers overheat."

2. Move Forward in Time

To move forward in time, ask: “Why is this a problem?” For example, minor damage could be one result of the machines overheating. In more extreme cases, printers may catch fire. Don't be afraid to create multiple problem stories if you think of more than one UDP.

3. Move Backward in Time

To move backward in time, ask: “What caused this UDP?” If you can't identify the root problem, think about what typically causes the UDP to occur. For the overheating printers, overuse could be a cause.

Following the three-step framework above helps illustrate a clear problem story:

• The printer is overused.
• The printer overheats.
• The printer breaks down.

You can extend the problem story in either direction if you think of additional cause-and-effect relationships.

4. Break the Chains

By this point, you’ll have multiple UDP storylines. Take two that are similar and focus on breaking the chains connecting them. This can be accomplished through inversion or neutralization.

• Inversion: Inversion changes the relationship between two UDPs so the cause is the same but the effect is the opposite. For example, if the UDP is "the more X happens, the more likely Y is to happen," inversion changes the equation to "the more X happens, the less likely Y is to happen." Using the printer example, inversion would consider: "What if the more a printer is used, the less likely it’s going to overheat?" Innovation requires an open mind. Just because a solution initially seems unlikely doesn't mean it can't be pursued further or spark additional ideas.
• Neutralization: Neutralization completely eliminates the cause-and-effect relationship between X and Y. This changes the above equation to "the more or less X happens has no effect on Y." In the case of the printers, neutralization would rephrase the relationship to "the more or less a printer is used has no effect on whether it overheats."

Even if creating a problem story doesn't provide a solution, it can offer useful context to users’ problems and additional ideas to be explored. Given that divergence is one of the fundamental practices of creative problem-solving, it’s a good idea to incorporate it into each tool you use.

Brainstorming

Brainstorming is a tool that can be highly effective when guided by the iterative qualities of the design thinking process. It involves openly discussing and debating ideas and topics in a group setting. This facilitates idea generation and exploration as different team members consider the same concept from multiple perspectives.

Hosting brainstorming sessions can result in problems, such as groupthink or social loafing. To combat this, leverage a three-step brainstorming method involving divergence and convergence :

• Have each group member come up with as many ideas as possible and write them down to ensure the brainstorming session is productive.
• Continue the divergence of ideas by collectively sharing and exploring each idea as a group. The goal is to create a setting where new ideas are inspired by open discussion.
• Begin the convergence of ideas by narrowing them down to a few explorable options. There’s no "right number of ideas." Don't be afraid to consider exploring all of them, as long as you have the resources to do so.

Alternate Worlds

The alternate worlds tool is an empathetic approach to creative problem-solving. It encourages you to consider how someone in another world would approach your situation.

For example, if you’re concerned that the printers you produce overheat and catch fire, consider how a different industry would approach the problem. How would an automotive expert solve it? How would a firefighter?

Be creative as you consider and research alternate worlds. The purpose is not to nail down a solution right away but to continue the ideation process through diverging and exploring ideas.

Continue Developing Your Skills

Whether you’re an entrepreneur, marketer, or business leader, learning the ropes of design thinking can be an effective way to build your skills and foster creativity and innovation in any setting.

If you're ready to develop your design thinking and creative problem-solving skills, explore Design Thinking and Innovation , one of our online entrepreneurship and innovation courses. If you aren't sure which course is the right fit, download our free course flowchart to determine which best aligns with your goals.

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Article • 10 min read

Creative Problem Solving

Finding innovative solutions to challenges.

By the Mind Tools Content Team

Imagine that you're vacuuming your house in a hurry because you've got friends coming over. Frustratingly, you're working hard but you're not getting very far. You kneel down, open up the vacuum cleaner, and pull out the bag. In a cloud of dust, you realize that it's full... again. Coughing, you empty it and wonder why vacuum cleaners with bags still exist!

James Dyson, inventor and founder of Dyson® vacuum cleaners, had exactly the same problem, and he used creative problem solving to find the answer. While many companies focused on developing a better vacuum cleaner filter, he realized that he had to think differently and find a more creative solution. So, he devised a revolutionary way to separate the dirt from the air, and invented the world's first bagless vacuum cleaner. [1]

Creative problem solving (CPS) is a way of solving problems or identifying opportunities when conventional thinking has failed. It encourages you to find fresh perspectives and come up with innovative solutions, so that you can formulate a plan to overcome obstacles and reach your goals.

In this article, we'll explore what CPS is, and we'll look at its key principles. We'll also provide a model that you can use to generate creative solutions.

About Creative Problem Solving

Alex Osborn, founder of the Creative Education Foundation, first developed creative problem solving in the 1940s, along with the term "brainstorming." And, together with Sid Parnes, he developed the Osborn-Parnes Creative Problem Solving Process. Despite its age, this model remains a valuable approach to problem solving. [2]

The early Osborn-Parnes model inspired a number of other tools. One of these is the 2011 CPS Learner's Model, also from the Creative Education Foundation, developed by Dr Gerard J. Puccio, Marie Mance, and co-workers. In this article, we'll use this modern four-step model to explore how you can use CPS to generate innovative, effective solutions.

Why Use Creative Problem Solving?

Dealing with obstacles and challenges is a regular part of working life, and overcoming them isn't always easy. To improve your products, services, communications, and interpersonal skills, and for you and your organization to excel, you need to encourage creative thinking and find innovative solutions that work.

CPS asks you to separate your "divergent" and "convergent" thinking as a way to do this. Divergent thinking is the process of generating lots of potential solutions and possibilities, otherwise known as brainstorming. And convergent thinking involves evaluating those options and choosing the most promising one. Often, we use a combination of the two to develop new ideas or solutions. However, using them simultaneously can result in unbalanced or biased decisions, and can stifle idea generation.

For more on divergent and convergent thinking, and for a useful diagram, see the book "Facilitator's Guide to Participatory Decision-Making." [3]

Core Principles of Creative Problem Solving

CPS has four core principles. Let's explore each one in more detail:

• Divergent and convergent thinking must be balanced. The key to creativity is learning how to identify and balance divergent and convergent thinking (done separately), and knowing when to practice each one.
• Ask problems as questions. When you rephrase problems and challenges as open-ended questions with multiple possibilities, it's easier to come up with solutions. Asking these types of questions generates lots of rich information, while asking closed questions tends to elicit short answers, such as confirmations or disagreements. Problem statements tend to generate limited responses, or none at all.
• Defer or suspend judgment. As Alex Osborn learned from his work on brainstorming, judging solutions early on tends to shut down idea generation. Instead, there's an appropriate and necessary time to judge ideas during the convergence stage.
• Focus on "Yes, and," rather than "No, but." Language matters when you're generating information and ideas. "Yes, and" encourages people to expand their thoughts, which is necessary during certain stages of CPS. Using the word "but" – preceded by "yes" or "no" – ends conversation, and often negates what's come before it.

How to Use the Tool

Let's explore how you can use each of the four steps of the CPS Learner's Model (shown in figure 1, below) to generate innovative ideas and solutions.

Figure 1 – CPS Learner's Model

Explore the Vision

Identify your goal, desire or challenge. This is a crucial first step because it's easy to assume, incorrectly, that you know what the problem is. However, you may have missed something or have failed to understand the issue fully, and defining your objective can provide clarity. Read our article, 5 Whys , for more on getting to the root of a problem quickly.

Gather Data

Once you've identified and understood the problem, you can collect information about it and develop a clear understanding of it. Make a note of details such as who and what is involved, all the relevant facts, and everyone's feelings and opinions.

Formulate Questions

When you've increased your awareness of the challenge or problem you've identified, ask questions that will generate solutions. Think about the obstacles you might face and the opportunities they could present.

Explore Ideas

Generate ideas that answer the challenge questions you identified in step 1. It can be tempting to consider solutions that you've tried before, as our minds tend to return to habitual thinking patterns that stop us from producing new ideas. However, this is a chance to use your creativity .

Brainstorming and Mind Maps are great ways to explore ideas during this divergent stage of CPS. And our articles, Encouraging Team Creativity , Problem Solving , Rolestorming , Hurson's Productive Thinking Model , and The Four-Step Innovation Process , can also help boost your creativity.

See our Brainstorming resources within our Creativity section for more on this.

Formulate Solutions

This is the convergent stage of CPS, where you begin to focus on evaluating all of your possible options and come up with solutions. Analyze whether potential solutions meet your needs and criteria, and decide whether you can implement them successfully. Next, consider how you can strengthen them and determine which ones are the best "fit." Our articles, Critical Thinking and ORAPAPA , are useful here.

4. Implement

Formulate a plan.

Once you've chosen the best solution, it's time to develop a plan of action. Start by identifying resources and actions that will allow you to implement your chosen solution. Next, communicate your plan and make sure that everyone involved understands and accepts it.

There have been many adaptations of CPS since its inception, because nobody owns the idea.

For example, Scott Isaksen and Donald Treffinger formed The Creative Problem Solving Group Inc . and the Center for Creative Learning , and their model has evolved over many versions. Blair Miller, Jonathan Vehar and Roger L. Firestien also created their own version, and Dr Gerard J. Puccio, Mary C. Murdock, and Marie Mance developed CPS: The Thinking Skills Model. [4] Tim Hurson created The Productive Thinking Model , and Paul Reali developed CPS: Competencies Model. [5]

Sid Parnes continued to adapt the CPS model by adding concepts such as imagery and visualization , and he founded the Creative Studies Project to teach CPS. For more information on the evolution and development of the CPS process, see Creative Problem Solving Version 6.1 by Donald J. Treffinger, Scott G. Isaksen, and K. Brian Dorval. [6]

Creative Problem Solving (CPS) Infographic

See our infographic on Creative Problem Solving .

Creative problem solving (CPS) is a way of using your creativity to develop new ideas and solutions to problems. The process is based on separating divergent and convergent thinking styles, so that you can focus your mind on creating at the first stage, and then evaluating at the second stage.

There have been many adaptations of the original Osborn-Parnes model, but they all involve a clear structure of identifying the problem, generating new ideas, evaluating the options, and then formulating a plan for successful implementation.

[1] Entrepreneur (2012). James Dyson on Using Failure to Drive Success [online]. Available here . [Accessed May 27, 2022.]

[2] Creative Education Foundation (2015). The CPS Process [online]. Available here . [Accessed May 26, 2022.]

[3] Kaner, S. et al. (2014). 'Facilitator′s Guide to Participatory Decision–Making,' San Francisco: Jossey-Bass.

[4] Puccio, G., Mance, M., and Murdock, M. (2011). 'Creative Leadership: Skils That Drive Change' (2nd Ed.), Thousand Oaks, CA: Sage.

[5] OmniSkills (2013). Creative Problem Solving [online]. Available here . [Accessed May 26, 2022].

[6] Treffinger, G., Isaksen, S., and Dorval, B. (2010). Creative Problem Solving (CPS Version 6.1). Center for Creative Learning, Inc. & Creative Problem Solving Group, Inc. Available here .

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Original research article, creative problem solving as overcoming a misunderstanding.

• Department of Psychology, University of Milano-Bicocca, Milan, Italy

Solving or attempting to solve problems is the typical and, hence, general function of thought. A theory of problem solving must first explain how the problem is constituted, and then how the solution happens, but also how it happens that it is not solved; it must explain the correct answer and with the same means the failure. The identification of the way in which the problem is formatted should help to understand how the solution of the problems happens, but even before that, the source of the difficulty. Sometimes the difficulty lies in the calculation, the number of operations to be performed, and the quantity of data to be processed and remembered. There are, however, other problems – the insight problems – in which the difficulty does not lie so much in the complexity of the calculations, but in one or more critical points that are susceptible to misinterpretation , incompatible with the solution. In our view, the way of thinking involved in insight problem solving is very close to the process involved in the understanding of an utterance, when a misunderstanding occurs. In this case, a more appropriate meaning has to be selected to resolve the misunderstanding (the “impasse”), the default interpretation (the “fixation”) has to be dropped in order to “restructure.” to grasp another meaning which appears more relevant to the context and the speaker’s intention (the “aim of the task”). In this article we support our view with experimental evidence, focusing on how a misunderstanding is formed. We have studied a paradigmatic insight problem, an apparent trivial arithmetical task, the Ties problem. We also reviewed other classical insight problems, reconsidering in particular one of the most intriguing one, which at first sight appears impossible to solve, the Study Window problem. By identifying the problem knots that alter the aim of the task, the reformulation technique has made it possible to eliminate misunderstanding, without changing the mathematical nature of the problem. With the experimental versions of the problems exposed we have obtained a significant increase in correct answers. Studying how an insight problem is formed, and not just how it is solved, may well become an important topic in education. We focus on undergraduate students’ strategies and their errors while solving problems, and the specific cognitive processes involved in misunderstanding, which are crucial to better exploit what could be beneficial to reach the solution and to teach how to improve the ability to solve problems.

Introduction

“A problem arises when a living creature has a goal but does not know how this goal is to be reached. Whenever one cannot go from the given situation to the desired situation simply by action, then there has to be recourse to thinking. (…) Such thinking has the task of devising some action which may mediate between the existing and the desired situations.” ( Duncker, 1945 , p. 1). We agree with Duncker’s general description of every situation we call a problem: the problem solving activity takes a central role in the general function of thought, if not even identifies with it.

So far, psychologists have been mainly interested in the solution and the solvers. But the formation of the problem remained in the shadows.

Let’s consider for example the two fundamental theoretical approaches to the study of problem solving. “What questions should a theory of problem solving answer? First, it should predict the performance of a problem solver handling specified tasks. It should explain how human problem solving takes place: what processes are used, and what mechanisms perform these processes.” ( Newell et al., 1958 , p. 151). In turn, authors of different orientations indicate as central in their research “How does the solution arise from the problem situation? In what ways is the solution of a problem attained?” ( Duncker, 1945 , p. 1) or that of what happens when you solve a problem, when you suddenly see the point ( Wertheimer, 1959 ). It is obvious, and it was inevitable, that the formation of the problem would remain in the shadows.

A theory of problem solving must first explain how the problem is constituted, and then how the solution happens, but also how it happens that it is not solved; it must explain the correct answer and with the same means the failure. The identification of the way in which the problem is constituted – the formation of the problem – and the awareness that this moment is decisive for everything that follows imply that failures are considered in a new way, the study of which should help to understand how the solution of the problems happens, but even before that, the source of the difficulty.

Sometimes the difficulty lies in the calculation, the number of operations to be performed, and the quantity of data to be processed and remembered. Take the well-known problems studied by Simon, Crypto-arithmetic task, for example, or the Cannibals and Missionaries problem ( Simon, 1979 ). The difficulty in these problems lies in the complexity of the calculation which characterizes them. But, the text and the request of the problem is univocally understood by the experimenter and by the participant in both the explicit ( said )and implicit ( implied ) parts. 1 As Simon says, “Subjects do not initially choose deliberately among problem representations, but almost always adopt the representation suggested by the verbal problem statement” ( Kaplan and Simon, 1990 , p. 376). The verbal problem statement determines a problem representation, implicit presuppositions of which are shared by both.

There are, however, other problems where the usual (generalized) interpretation of the text of the problem (and/or the associated figure) prevents and does not allow a solution to be found, so that we are soon faced with an impasse. We’ll call this kind of problems insight problems . “In these cases, where the complexity of the calculations does not play a relevant part in the difficulty of the problem, a misunderstanding would appear to be a more appropriate abstract model than the labyrinth” ( Mosconi, 2016 , p. 356). Insight problems do not arise from a fortuitous misunderstanding, but from a deliberate violation of Gricean conversational rules, since the implicit layer of the discourse (the implied ) is not shared both by experimenter and participant. Take for example the problem of how to remove a one-hundred dollar bill without causing a pyramid balanced atop the bill to topple: “A giant inverted steel pyramid is perfectly balanced on its point. Any movement of the pyramid will cause it to topple over. Underneath the pyramid is a $100 bill. How would you remove the bill without disturbing the pyramid?” ( Schooler et al., 1993 , p. 183). The solution is burn or tear the dollar bill but people assume that the 100 dollar bill must not be damaged, but contrary to his assumption, this is in fact the solution. Obviously this is not a trivial error of understanding between the two parties, but rather a misunderstanding due to social conventions, and dictated by conversational rules. It is the essential condition for the forming of the problem and the experimenter has played on the very fact that the condition was not explicitly stated (see also Bulbrook, 1932 ).

When insight problems are used in research, it could be said that the researcher sets a trap, more or less intentionally, inducing an interpretation that appears to be pertinent to the data and to the text; this interpretation is adopted more or less automatically because it has been validated by use but the default interpretation does not support understanding, and misunderstanding is inevitable; as a result, sooner or later we come up against an impasse. The theory of misunderstanding is supported by experimental evidence obtained by Mosconi in his research on insight problem solving ( Mosconi, 1990 ), and by Bagassi and Macchi on problem solving, decision making and probabilistic reasoning ( Bagassi and Macchi, 2006 , 2016 ; Macchi and Bagassi, 2012 , 2014 , 2015 , 2020 ; Macchi, 1995 , 2000 ; Mosconi and Macchi, 2001 ; Politzer and Macchi, 2000 ).

The implication of the focus on problem forming for education is remarkable: everything we say generates a communicative and therefore interpretative context, which is given by cultural and social assumptions, default interpretations, and attribution of intention to the speaker. Since the text of the problem is expressed in natural language, it is affected, it shares the characteristics of the language itself. Natural language is ambiguous in itself, differently from specialized languages (i.e., logical and statistical ones), which presuppose a univocal, unambiguous interpretation. The understanding of what a speaker means requires a disambiguation process centered on the intention attribution.

Restructuring as Reinterpreting

Traditionally, according to the Gestaltists, finding the solution to an insight problem is an example of “productive thought.” In addition to the reproductive activities of thought, there are processes which create, “produce” that which does not yet exist. It is characterized by a switch in direction which occurs together with the transformation of the problem or a change in our understanding of an essential relationship. The famous “aha!” experience of genuine insight accompanies this change in representation, or restructuring. As Wertheimer says: “… Solution becomes possible only when the central features of the problem are clearly recognized, and paths to a possible approach emerge. Irrelevant features must be stripped away, core features must become salient, and some representation must be developed that accurately reflects how various parts of the problem fit together; relevant relations among parts, and between parts and whole, must be understood, must make sense” ( Wertheimer, 1985 , p. 23).

The restructuring process circumscribed by the Gestaltists to the representation of the perceptual stimulus is actually a general feature of every human cognitive activity and, in particular, of communicative interaction, which allows the understanding, the attribution of meaning, thus extending to the solution of verbal insight problems. In this sense, restructuring becomes a process of reinterpretation.

We are able to get out of the impasse by neglecting the default interpretation and looking for another one that is more pertinent to the situation and which helps us grasp the meaning that matches both the context and the speaker’s intention; this requires continuous adjustments until all makes sense.

In our perspective, this interpretative function is a characteristic inherent to all reasoning processes and is an adaptive characteristic of the human cognitive system in general ( Levinson, 1995 , 2013 ; Macchi and Bagassi, 2019 ; Mercier and Sperber, 2011 ; Sperber and Wilson, 1986/1995 ; Tomasello, 2009 ). It guarantees cognitive economy when meanings and relations are familiar, permitting recognition in a “blink of an eye.” This same process becomes much more arduous when meanings and relations are unfamiliar, obliging us to face the novel. When this happens, we have to come to terms with the fact that the usual, default interpretation will not work, and this is a necessary condition for exploring other ways of interpreting the situation. A restless, conscious and unconscious search for other possible relations between the parts and the whole ensues until everything falls into place and nothing is left unexplained, with an interpretative heuristic-type process. Indeed, the solution restructuring – is a re -interpretation of the relationship between the data and the aim of the task, a search for the appropriate meaning carried out at a deeper level, not by automaticity. If this is true, then a disambiguant reformulation of the problem that eliminates the trap into which the subject has fallen, should produce restructuring and the way to the solution.

Insight Problem Solving as the Overcoming of a Misunderstanding: The Effect of Reformulation

In this article we support our view with experimental evidence, focusing on how a misunderstanding is formed, and how a pragmatic reformulation of the problem, more relevant to the aim of the task, allows the text of the problem to be interpreted in accordance with the solution.

We consider two paradigmatic insight problems, the intriguing Study Window problem, which at first sight appears impossible to solve, and an apparent trivial arithmetical task, the Ties problem ( Mosconi and D’Urso, 1974 ).

The Study Window problem

The study window measures 1 m in height and 1 m wide. The owner decides to enlarge it and calls in a workman. He instructs the man to double the area of the window without changing its shape and so that it still measures 1 m by 1 m. The workman carried out the commission. How did he do it?

This problem was investigated in a previous study ( Macchi and Bagassi, 2015 ). For all the participants the problem appeared impossible to solve, and nobody actually solved it. The explanation we gave for the difficulty was the following: “The information provided regarding the dimensions brings a square form to mind. The problem solver interprets the window to be a square 1 m high by 1 m wide, resting on one side. Furthermore, the problem states “without changing its shape,” intending geometric shape of the two windows (square, independently of the orientation of the window), while the problem solver interprets this as meaning the phenomenic shape of the two windows (two squares with the same orthogonal orientation)” ( Macchi and Bagassi, 2015 , p. 156). And this is where the difficulty of the problem lies, in the mental representation of the window and the concurrent interpretation of the text of the problem. Actually, spatial orientation is a decisive factor in the perception of forms. “Two identical shapes seen from different orientations take on a different phenomenic identity” ( Mach, 1914 ).

The solution is to be found in a square (geometric form) that “rests” on one of its angles, thus becoming a rhombus (phenomenic form). Now the dimensions given are those of the two diagonals of the represented rhombus (ABCD).

Figure 1. The study window problem solution.

The “inverted” version of the problem gave less trouble:

[…] The owner decides to make it smaller and calls in a workman. He instructs the man to halve the area of the window […].

Figure 2. The inverted version.

With this version, 30% of the participants solved the problem ( n = 30). They started from the representation of the orthogonal square (ABCD) and looked for the solution within the square, trying to respect the required height and width of the window, and inevitably changing the orientation of the internal square. This time the height and width are the diagonals, rather than the side (base and height) of the square.

Eventually, in another version (the “orientation” version) it was explicit that orientation was not a mandatory attribute of the shape, and this time 66% of the participants found the solution immediately ( n = 30). This confirms the hypothesis that an inappropriate representation of the relation between the orthogonal orientation of the square and its geometric shape is the origin of the misunderstanding .

The “orientation” version:

A study window measures 1 m in height and 1 m wide. The owner decides to make it smaller and calls in a workman. He instructs the man to halve the area of the window: the workman can change the orientation of the window, but not its shape and in such a way that it still measures one meter by one meter. The workman carries out the commission. How did he do it?

While with the Study window problem the subjects who do not arrive at the solution, and who are the totality, know they are wrong, with the problem we are now going to examine, the Ties problem, those who are wrong do not realize it at all and the solution they propose is experienced as the correct solution.

The Ties Problem ( Mosconi and D’Urso, 1974 )

Peter and John have the same number of ties.

Peter gives John five of his ties.

How many ties does John have now more than Peter?

We believe that the seemingly trivial problem is actually the result of the simultaneous activation and mutual interference of complex cognitive processes that prevent its solution.

The problem has been submitted to 50 undergraduate students of the Humanities Faculty of the University of Milano-Bicocca. The participants were tested individually and were randomly assigned to three groups: control version ( n = 50), experimental version 2 ( n = 20), and experimental version 3 ( n = 23). All groups were tested in Italian. Each participant was randomly assigned to one of the conditions and received a form containing only one version of the two assigned problems. There was no time limit. They were invited to think aloud and their spontaneous justifications were recorded and then transcribed.

The correct answer is obviously “ten,” but it must not be so obvious if it is given by only one third of the subjects (32%), while the remaining two thirds give the wrong answer “five,” which is so dominant.

If we consider the text of the problem from the point of view of the information explicitly transmitted ( said ), we have that it only theoretically provides the necessary information to reach the solution and precisely that: (a) the number of ties initially owned by P. and J. is equal, (b) P. gives J. five of his ties. However, the subjects are wrong. What emerges, however, from the spontaneous justifications given by the subjects who give the wrong answer is that they see only the increase of J. and not the consequent loss of P. by five ties. We report two typical justifications: “P. gives five of his to J., J. has five more ties than P., the five P. gave him” and also “They started from the same number of ties, so if P. gives J. five ties, J. should have five more than P.”

Slightly different from the previous ones is the following recurrent answer, in which the participants also consider the decrease of P. as well as the increase of J.: “I see five ties at stake, which are the ones that move,” or also “There are these five ties that go from one to the other, so one has five ties less and the other has five more,” reaching however the conclusion similar to the previous one that “J. has five ties more, because the other gave them to him.” 2

Almost always the participants who answer “five” use a numerical example to justify the answer given or to find a solution to the problem, after some unsuccessful attempts. It is paradoxical how many of these participants accept that the problem has two solutions, one “five ties” obtained by reasoning without considering a concrete number of initial ties, owned by P. and J., the other “ten ties” obtained by using a numerical example. So, for example, we read in the protocol of a participant who, after having answered “five more ties,” using a numerical example, finds “ten” of difference between the ties of P. and those of J.: “Well! I think the “five” is still more and more exact; for me this one has five more, period and that’s it.” “Making the concrete example: “ten” – he chases another subject on an abstract level. I would be more inclined to another formula, to five.”

About half of the subjects who give the answer “five,” in fact, at first refuse to answer because “we don’t know the initial number and therefore we can’t know how many ties J. has more than P.,” or at the most they answer: “J. has five ties more, P. five less, more we can’t know, because a data is missing.”

Even before this difficulty, so to speak, operational, the text of the problem is difficult because in it the quantity relative to the decrease of P. remains implicit (−5). The resulting misunderstanding is that if the quantity transferred is five ties, the resulting difference is only five ties: if the ties that P. gives to J. are five, how can J. have 10 ties more than P.?

So the difficulty of the problem lies in the discrepancy between the quantity transferred and the bidirectional effect that this quantity determines with its displacement. Resolving implies a restructuring of the sentence: “Peter gives John five of his ties (and therefore he loses five).” And this is precisely the reasoning carried out by those subjects who give the right answer “ten.”

We have therefore formulated a new version in which a pair of verbs should make explicit the loss of P.:

Peter loses five of his ties and John takes them.

However, the results obtained with this version, submitted to 20 other subjects, substantially confirm the results obtained with the original version: the correct answers are 17% (3/20) and the wrong ones 75% (15/20). From a Chi-square test (χ 2 = 2,088 p = 0.148) it results no significant difference between the two versions.

If we go to read the spontaneous justifications, we find that the subjects who give the answer “five” motivate it in a similar way to the subjects of the original version. So, for example: “P. loses five, J. gets them, so J. has five ties more than P.”

The decrease of P. is still not perceived, and the discrepancy between the lost amount of ties and the double effect that this quantity determines with its displacement persists.

Therefore, a new version has been realized in which the amount of ties lost by P. has nothing to do with J’s acquisition of five ties, the two amounts of ties are different and then they are perceived as decoupled, so as to neutralize the perceptual-conceptual factor underlying it.

Peter loses five of his ties and John buys five new ones.

It was submitted to 23 participants. Of them, 17 (74%) gave the answer “ten” and only 3 (13%) the answer “five.” There was a significant difference (χ 2 = 16,104 p = 0.000) between the results obtained using the present experimental version and the results from the control version. The participants who give the correct solution “ten” mostly motivate their answer as follows: “P. loses five and therefore J. has also those five that P. lost; he buys another five, there are ten,” declaring that he “added to the five that P. had lost the five that J. had bought.” The effectiveness of the experimental manipulation adopted is confirmed. 3

The satisfactory results obtained with this version cannot be attributed to the use of two different verbs, which proved to be ineffective (see version 2), but to the splitting, and consequent differentiation (J. has in addition five new ties), of the two quantities.

This time, the increase of J. and the decrease of P. are grasped as simultaneous and distinct and their combined effect is not identified with one or the other, but is equal to the sum of +5 and −5 in absolute terms.

The hypothesis regarding the effect of reformulation has also been confirmed in classical insight problems such as the Square and the Parallelogram ( Wertheimer, 1925 ), the Pigs in a Pen ( Schooler et al., 1993 ), the Bat & Ball ( Frederick, 2005 ) in recent studies ( Macchi and Bagassi, 2012 , 2015 ) which showed a dramatic increase in the number of solutions.

In their original version these problems are true brain teasers, and the majority of participants in these studies needed them to be reformulated in order to reach the solution. In Appendix B we present in detail the results obtained (see Table 1 ). Below we report, for each problem, the text of the original version in comparison with the reformulated experimental version.

Table 1. Percentages of correct solutions with reformulated experimental versions.

Square and Parallelogram Problem ( Wertheimer, 1925 )

Given that AB = a and AG = b, find the sum of the areas of square ABCD and parallelogram EBGD ( Figures 3 , 4 ).

Figure 3. The square and parallelogram problem.

Figure 4. Solution.

Experimental Version

Given that AB = a and AG = b , find the sum of the areas of the two partially overlapping figures .

Pigs in a Pen Problem ( Schooler et al., 1993 )

Nine pigs are kept in a square pen . Build two more square enclosures that would put each pig in a pen by itself ( Figures 5 , 6 ).

Figure 5. The pigs in a pen problem.

Figure 6. Solution.

Nine pigs are kept in a square pen. Build two more squares that would put each pig in a by itself .

Bat and Ball Problem ( Frederick, 2005 )

A bat and a ball cost $1.10 in total. The bat costs $ 1.00 more than the ball. How much does the ball cost? ___cents.

A bat and a ball cost $1.10 in total. The bat costs $ 1.00 more than the ball. Find the cost of the bat and of the ball .

Once the problem knots that alter the aim of the task have been identified, the reformulation technique can be a valid didactic tool, as it allows to reveal the misunderstanding and to eliminate it without changing the mathematical nature of the problem. The training to creativity would consist in this sense in training to have interpretative keys different from the usual, when the difficulty cannot be addressed through computational techniques.

Closing Thoughts

By identifying the misunderstanding in problem solving, the reformulation technique has made it possible to eliminate the problem knots, without changing the mathematical nature of the problem. With the experimental reformulated versions of paradigmatic problems, both apparent trivial tasks or brain teasers have obtained a significant increase in correct answers.

Studying how an insight problem is formed, and not just how it is solved, may well become an important topic in education. We focus on undergraduate students’ strategies and their errors while solving problems, and the specific cognitive processes involved in misunderstanding, which are crucial to better exploit what could be beneficial to reach the solution and to teach how to improve the ability to solve problems.

Without violating the need for the necessary rigor of a demonstration, for example, it is possible to organize the problem-demonstration discourse according to a different criterion, precisely by favoring the psychological needs of the subject to whom the explanation discourse is addressed, taking care to organize the explanation with regard to the way his mind works, to what can favor its comprehension and facilitate its memory.

On the other hand, one of the criteria traditionally followed by mathematicians in constructing, for example, demonstrations, or at least in explaining them, is to never make any statement that is not supported by the elements provided above. In essence, in the course of the demonstration nothing is anticipated, and indeed it happens frequently that the propositions directly relevant and relevant to the development of the reasoning (for example, the steps of a geometric demonstration) are preceded by digressions intended to introduce and deal with the elements that legitimize them. As a consequence of such an expositive formalism, the recipient of the speech (the student) often finds himself in the situation of being led to the final conclusion a bit like a blind man who, even though he knows the goal, does not see the way, but can only control step by step the road he is walking along and with difficulty becomes aware of the itinerary.

The text of every problem, if formulated in natural language, has a psychorhetoric dimension, in the sense that in every speech, that is in the production and reception of every speech, there are aspects related to the way the mind works – and therefore psychological and rhetorical – that are decisive for comprehensibility, expressive adequacy and communicative effectiveness. It is precisely to these aspects that we refer to when we talk about the psychorhetoric dimension. Rhetoric, from the point of view of the broadcaster, has studied discourse in relation to the recipient, and therefore to its acceptability, comprehensibility and effectiveness, so that we can say that rhetoric has studied discourse “psychologically.”

Adopting this perspective, the commonplace that the rhetorical dimension only concerns the common discourse, i.e., the discourse that concerns debatable issues, and not the scientific discourse (logical-mathematical-demonstrative), which would be exempt from it, is falling away. The matter dealt with, the truth of what is actually said, is not sufficient to guarantee comprehension.

Data Availability Statement

The datasets generated for this study are available on request to the corresponding author.

Ethics Statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

Author Contributions

LM and MB devised the project, developed the theory, carried out the experiment and wrote the manuscript. Both authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

• ^ The theoretical framework assumed here is Paul Grice’s theory of communication (1975) based on the existence in communication of the explicit layer ( said ) and of the implicit ( implied ), so that the recognition of the communicative intention of the speaker by the interlocutor is crucial for comprehension.
• ^ A participant who after having given the solution “five” corrects himself in “ten” explains the first answer as follows: “it is more immediate, in my opinion, to see the real five ties that are moved, because they are five things that are moved; then as a more immediate answer is ‘five,’ because it is something more real, less mathematical.”
• ^ The factor indicated is certainly the main responsible for the answer “five,” but not the only one (see the Appendix for a pragmatic analysis of the text).
• ^ Versions and results of the problems exposed are already published in Macchi e Bagassi 2012, 2014, 2015.

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Pragmatic analysis of the problematic loci of the Ties problem, which emerged from the spontaneous verbalizations of the participants:

- “the same number of ties”

This expression is understood as a neutral information, a kind of base or sliding plane on which the transfer of the five ties takes place and, in fact, these subjects motivate their answer “five” with: “there is this transfer of five ties from P. to J. ….”

- “5 more, 5 less”

We frequently resort to similar expressions in situations where, if I have five units more than another, the other has five less than me and the difference between us is five.

Consider, for example, the case of the years: say that J. is five years older than P. means to say that P. is five years younger than J. and that the difference in years between the two is five, not ten.

In comparisons, we evaluate the difference with something used as a term of reference, for example the age of P., which serves as a basis, the benchmark, precisely.

- “he gives”

The verb “to give” conveys the concept of the growth of the recipient, not the decrease of the giver, therefore, contributes to the crystallization of the “same number,” preventing to grasp the decrease of P.

Appendix B 4

Given that AB = a and AG = b, find the sum of the areas of square ABCD and parallelogram EBGD .

Typically, problem solvers find the problem difficult and fail to see that a is also the altitude of parallelogram EBGD. They tend to calculate its area with onerous and futile methods, while the solution can be reached with a smart method, consisting of restructuring the entire given shape into two partially overlapping triangles ABG and ECD. The sum of their areas is 2 x a b /2 = a b . Moreover, by shifting one of the triangles so that DE coincides with GB, the answer is “ a b ,” which is the area of the resultant rectangle. Referring to a square and a parallelogram fixes a favored interpretation of the perceptive stimuli, according to those principles of perceptive organization thoroughly studied by the Gestalt Theory. It firmly sets the calculation of the area on the sum of the two specific shapes dealt with in the text, while, the problem actually requires calculation of the area of the shape, however organized, as the sum of two triangles rectangles, or the area of only one rectangle, as well as the sum of square and parallelogram. Hence, the process of restructuring is quite difficult.

To test our hypotheses we formulated an experimental version:

In this formulation of the problem, the text does not impose constraints on the interpretation/organization of the figure, and the spontaneous, default interpretation is no longer fixed. Instead of asking for “the areas of square and parallelogram,” the problem asks for the areas of “the two partially overlapping figures.” We predicted that the experimental version would allow the subjects to see and consider the two triangles also.

Actually, we found that 80% of the participants (28 out of 35) gave a correct answer, and most of them (21 out of 28) gave the smart “two triangles” solution. In the control version, on the other hand, only 19% (9 out of 47) gave the correct response, and of these only two gave the “two triangles” solution.

The findings were replicated in the “Pigs in a pen” problem:

Nine pigs are kept in a square pen . Build two more square enclosures that would put each pig in a pen by itself.

The difficulty of this problem lies in the interpretation of the request, nine pigs each individually enclosed in a square pen, having only two more square enclosures. This interpretation is supported by the favored, orthogonal reference scheme, with which we represent the square. This privileged organization, according to our hypothesis, is fixed by the text which transmits the implicature that the pens in which the piglets are individually isolated must be square in shape too. The function of enclosure wrongfully implies the concept of a square. The task, on the contrary, only requires to pen each pig.

Once again, we created an experimental version by reformulating the problem, eliminating the word “enclosure” and the phrase “in a pen.” The implicit inference that the pen is necessarily square is not drawn.

The experimental version yielded 87% correct answers (20 out of 23), while the control version yielded only 38% correct answers (8 out of 25).

The formulation of the experimental versions was more relevant to the aim of the task, and allowed the perceptual stimuli to be interpreted in accordance with the solution.

The relevance of text and the re-interpretation of perceptual stimuli, goal oriented to the aim of the task, were worked out in unison in an interrelated interpretative “game.”

We further investigated the interpretative activity of thinking, by studying the “Bat and ball” problem, which is part of the CRT. Correct performance is usually considered to be evidence of reflective cognitive ability (correlated with high IQ scores), versus intuitive, erroneous answers to the problem ( Frederick, 2005 ).

Bat and Ball problem

A bat and a ball cost $1.10 in total. The bat costs $ 1.00 more than the ball. How much does the ball cost?___cents

Of course the answer which immediately comes to mind is 10 cents, which is incorrect as, in this case, the difference between $ 1.00 and 10 cents is only 90 cents, not $1.00 as the problem stipulates. The correct response is 5 cents.

Number physiognomics and the plausibility of the cost are traditionally considered responsible for this kind of error ( Frederick, 2005 ; Kahneman, 2003 ).

These factors aside, we argue that if the rhetoric structure of the text is analyzed, the question as formulated concerns only the ball, implying that the cost of the bat is already known. The question gives the key to the interpretation of what has been said in each problem and, generally speaking, in every discourse. Given data, therefore, is interpreted in the light of the question. Hence, “The bat costs $ 1.00 more than” becomes “The bat costs $ 1.00,” by leaving out “more than.”

According to our hypothesis, independently of the different cognitive styles, erroneous responses could be the effect of the rhetorical structure of the text, where the question is not adequate to the aim of the task. Consequently, we predicted that if the question were to be reformulated to become more relevant, the subjects would find it easier to grasp the correct response. In the light of our perspective, the cognitive abilities involved in the correct response were also reinterpreted. Consequently, we reformulated the text as follows in order to eliminate this misleading inference:

This time we predicted an increase in the number of correct answers. The difference in the percentages of correct solutions was significant: in the experimental version 90% of the participants gave a correct answer (28 out of 31), and only 10% (2 out of 20) answered correctly in the control condition.

The simple reformulation of the question, which expresses the real aim of the task (to find the cost of both items), does not favor the “short circuit” of considering the cost of the bat as already known (“$1,” by leaving out part of the phrase “more than”).

It still remains to be verified if those subjects who gave the correct response in the control version have a higher level of cognitive reflexive ability compared to the “intuitive” respondents. This has been the general interpretation given in the literature to the difference in performance.

We think it is a matter of a particular kind of reflexive ability, due to which the task is interpreted in the light of the context and not abstracting from it. The difficulty which the problem implicates does not so much involve a high level of abstract reasoning ability as high levels of pragmatic competence, which disambiguates the text. So much so that, intervening only on the pragmatic level, keeping numbers physiognomics and maintaining the plausible costs identical, the problem becomes a trivial arithmetical task.

Keywords : creative problem solving, insight, misunderstanding, pragmatics, language and thought

Citation: Bagassi M and Macchi L (2020) Creative Problem Solving as Overcoming a Misunderstanding. Front. Educ. 5:538202. doi: 10.3389/feduc.2020.538202

Received: 26 February 2020; Accepted: 29 October 2020; Published: 03 December 2020.

Reviewed by:

Copyright © 2020 Bagassi and Macchi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Laura Macchi, [email protected]

This article is part of the Research Topic

Psychology and Mathematics Education

Creativity and the Brain: How to Be a Creative Thinker

What do we know from research on brain activity involved in creative thought.

Posted April 30, 2024 | Reviewed by Michelle Quirk

• The book "The Creative Act" argues that creativity is a skill we can all use daily.
• Creativity is complex and involves multiple brain regions.
• Research shows that there are several ways to improve our creative thinking.

This post is part 2 of a series.

In my previous post, I wrote that, after being inspired by Rick Rubin’s book, The Creative Act: A Way of Being, I decided to find out what is going on in the human brain that results in creativity. It turned out to be a very complex and complicated subject. That is mainly because it is difficult to clearly define creativity, and there are many different kinds of creative processes, such as visual art, music, creative thinking , etc.

Coming from the field of cognitive processes, I decided that I would concentrate on research related to brain activity involved in creative thought processes. Most of the time, cognitive creativity involves testing the person’s divergent thinking (generating possible solutions to the problem) or convergent thinking (finding a single, correct solution to the problem).

The review of research papers indicated that creative thinking (convergent and divergent thinking) requires the coordination of multiple brain regions, mainly the executive control network (simply speaking involves planning, organizing, problem-solving, and decision-making ), default mode network (areas of the brain that are activated when we are letting our minds wander at rest), and salience network (a network that is involved in the awareness of the feelings associated with rewards). But, obviously, other parts of the brain are also involved, and this depends on the specific goal/outcome that we want to achieve.

I also promised my readers that I would try to find answers to the question of how to be a creative thinker. There are many suggestions on the internet, but let’s see what the research says.

You can learn how to meditate and practice it daily.

It may come as a surprise to many people, but the majority of the research papers in that area point to the daily practice of meditation as a way to improve creative thinking. It is not a surprise to me because I am a believer in meditation and do it daily. I also encourage all my patients to try to do it daily.

In a Chinese study (Ding, X. et al. 2014), 40 Chinese undergraduate students were assigned to three groups, a meditation group (30 minutes daily for 7 days), a relaxation training group, and a control group. Creativity performance was assessed by the Torrance Test of Creative Thinking (TTCT). The results indicated that the subjects in the meditation group improved their creativity performance on the divergent thinking tasks.

Research studies on meditation also indicate that it helps improve attention/ concentration skills and emotional regulation and reduces stress and anxiety , so it looks like a good daily habit to start.

You can read aloud and do arithmetic calculations.

In a Taiwan study (Lin, WL. et al. 2018), 50 junior high students were divided into a training group or a control group. The training group was reading aloud and performing arithmetic calculations for 20 sessions. The control group played the game Tetris (a puzzle video game). The results indicated that the participants in the training group outperformed the control group in thinking and creative abilities.

You can do neurofeedback.

Neurofeedback is a computer-guided, noninvasive brain-function training based on electroencephalography (EEG) feedback. Neurofeedback is also called neurotherapy, neurobiofeedback, or EEG biofeedback, and it helps control involuntary processes such as muscle tension and heart rate. Usually, the person is responding to a computer display of her/his own electrical activity of the brain, but it may also simply be a sound stimulation. The most important factor is that neurofeedback focuses on helping a person train himself/herself to regulate brain functions.

In an Italian study (Agnoli, S. et al. 2018), 80 female students from the University of Bologna got three neurofeedback training sessions. The researchers also measured the participants’ lifetime creative achievement by using the Creative Activity and Accomplishment Checklist. The results were measured with the divergent thinking tasks (producing original and effective ideas). The results indicated an increase in both originality and fluency. The increase was particularly evident in participants with an initial low creative achievement level.

This is good news for people who believe that they are not that creative. You may get better with neurofeedback training sessions. Artists and athletes do this nowadays to enhance their performance.

You can do overinclusive thinking training.

Overinclusive thinking can be described as increased generalization and/or considering concepts that most people consider unrelated to certain categories, which provides an increased number of options. In a Taiwan study (Chiu, F.C. 2015), the researcher examined the effect of overinclusive thinking on creativity. Four experiments were designed, and the subjects were undergraduate students who were randomly assigned to an overinclusive thinking training group or a control group. The training group did better on the overinclusive thinking that is related to creativity. The fluency and originality performance were higher than in the control group and the insight problem-solving was also better than in the control group.

So, if you would like to be a creative thinker, you can try some of the ideas described above. Good luck on the road to creativity!

Rick Rubin. The Creative Act: A Way of Being . Penguin Press, NY 2023.

Ding, X. et al. “Improving creativity performance by short-term meditation” Behavioral and Brain Functions. Vol. 10, 2014.

Lin, WL. et al. “ Improving junior high students’ thinking and creative abilities with an executive function training program” Thinking Skills and Creativity . Vol. 29, Sept. 2018.

Agnoli, S. et al. “Enhancing creative cognition with a rapid right-parietal neurofeedback procedure.” Neuropsychologia, Vol. 118, Part A Sept. 2018.

Chiu, F.C. “ Improving your creative potential without awareness: Overinclusive thinking training.” Thinking Skills and Creativity . Vol 15. March 2015.

Barbara Koltuska-Haskin, Ph.D., is a neuropsychologist in Albuquerque, New Mexico and the author of How My Brain Works.

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A Cognitive Trick for Solving Problems Creatively

• Theodore Scaltsas

Mental biases can actually help.

Many experts argue that creative thinking requires people to challenge their preconceptions and assumptions about the way the world works. One common claim, for example, is that the mental shortcuts we all rely on to solve problems get in the way of creative thinking. How can you innovate if your thinking is anchored in past experience?

• TS Theodore Scaltsas is a Chaired Professor in Classical Philosophy at the University of Edinburgh in Scotland.

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Enhancement of Creative Thinking Skills Using a Cognitive-Based Creativity Training

• Original Article
• Open access
• Published: 07 October 2016
• Volume 1 , pages 243–253, ( 2017 )

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• Simone M. Ritter 1 &
• Nel Mostert 2  

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Creative thinking skills can be considered one of the key competencies for the twenty-first century—they allow us to remain flexible and provide us with the capacity to deal with the opportunities and challenges that are part of our complex and fast-changing world. The increased focus on innovation combined with recent reports of decrements in creative performance brings attention to the need to develop creative thinking skills at both the educational and business levels. The main objective of the current project was to develop and scientifically test a brief, domain-unspecific creativity training. Undergraduate university students ( N  = 32) participated in the creativity training, which was a single session of 1.5 h and employed a cognitive approach (i.e., participants were shown how to apply creative thinking techniques in a systematic fashion). The effectiveness of the training was tested by means of a pre- and post-training comparison employing creativity measures that relied on divergent thinking, convergent thinking, and creative problem solving skills. To control for a possible instrumentation threat, two versions of each task were created and counterbalanced between the pre- and post-measure across participants. Following the creativity training, improvements were observed across a variety of creative performance measures. Importantly, the creativity level of the ideas generated during the divergent thinking task improved post-training. Moreover, the findings of the current study shed light on a possible underlying mechanism for these improvements in creativity, that is, cognitive flexibility. In addition to these divergent thinking skills, the training also improved convergent thinking and produced marginal improvements in creative problem solving skills. The current findings have important implications for educational and organizational settings, as they suggest that this brief creativity training (or one employing similar cognitive techniques) could be implemented to facilitate creative thinking skills.

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Introduction

Creative thinking can be considered one of the key competencies for the twenty-first century, and its effects are widespread. It allows us to fly to the moon, create art, develop computers, and cure illnesses. Creativity has not only been recognized in the sciences and the arts (Feist and Gorman 1998 ; MacKinnon 1962 ; Sternberg and Lubart 1996 ) but has also been shown to play an important role in everyday problem solving (Cropley 1990 ; Mumford et al. 1991 ; Runco 1994 ; Torrance 1971 ; Wallas 1926 ). The word creativity has its roots in the Latin term creō , which means “to create, to make,” and commonly refers to the ability to generate ideas or problem solutions that are original (i.e., novel) and useful (i.e., effective) (for example, Amabile 1983 ; Mumford 2003 ; Sternberg and Lubart 1999 ). In addition to its function of problem solving, creativity allows us to remain flexible. Cognitive flexibility provides us with the capacity to deal with the opportunities and changes that are part of our complex and fast-changing world (Cropley 1990 ; Reiter-Palmon et al. 1998 ). Due to its crucial role in innovation, the creation of new ideas and problem solutions has become a key concern for most organizations and businesses (Runco 2004 ), and some scholars refer to today’s economy as a creative economy (Florida 2002 ; Hawkins 2001 ). Supporting this trend, the US Council on Competitiveness has announced “innovation will be the single most important factor in determining […] success through the twenty-first century” (Wince-Smith 2006 ).

To meet the needs of the twenty-first century, academics, business leaders, and policy makers around the world have placed creativity high on their agenda. For example, 2009 was announced “the Year of Creativity and Innovation” to facilitate creative thinking skills among the entire population (European Commission 2008 ). Creativity is a skill that should be fostered in all disciplines and across all intellectual and social areas (UNESCO International Bureau of Education 2014 ). Initiatives to facilitate creativity are especially important since a creativity crisis has been identified, revealing significant decrements in creativity since the 1990s (Kim 2011 ; Kimbell 2000 ; Newton and Newton 2010 ). Both the heightened focus on creativity and innovation and the overall decline in creative performance bring attention to the need to develop creative thinking skills at both the educational and business levels. Creativity was long considered a topic not open to scientific research (Sternberg and Lubart 1999 ; Treffinger 2009 )—perhaps due to traditional beliefs that creativity has mystical origins—but in recent years, increasing insights have been gained into how creative ideas arise in the brain (e.g., see the review by Sawyer 2011 ). For example, it is now understood that creative thinking depends on fundamental cognitive processes, such as working memory, the ability to create new mental categories, and the ability to mentally manipulate objects (Ward et al. 1999 ). Creative thinking skills are thus inherent to normative cognitive functioning rather than an innate talent available to only a few genius minds. Importantly, research supports the idea that creative thinking can be trained (for a meta-analysis, see Scott et al. 2004a ).

Despite the urgent need for creativity, few curriculums devote much time or attention to developing creative thinking skills; in fact, the education system often discourages it (Edwards et al. 2006 ). This means that often, we are trained to consume knowledge but are not taught how to produce creative ideas and solutions. This is particularly problematic when graduates enter the workforce, as they have to be prepared for the needs of our creative economy (Florida 2002 ; Hawkins 2001 ). Similarly, those already established in work during adult life need to deal with twenty-first century problems but are not taught the creative thinking skills required to solve them. As such, people of all age groups could benefit from a training that enhances creative performance. Developing, evaluating, and implementing new content into the educational curriculum, such as creative thinking skills, take significant time. A valid alternative during this transition period might be to offer a short, well-developed, and scientifically tested creativity training—one that can be implemented easily in schools and business settings.

Previous creativity training approaches have been reported to differ across four main types of variables, including the cognitive processes targeted by the training, the techniques used in the training, the media used to deliver the training, and the types of exercises used during the training (for a more thorough discussion about these categories, see the meta-analysis of creativity training types by Scott et al. 2004b ). Of importance for the current study, the cluster analysis of creativity training techniques by Scott et al. ( 2004b ), revealed four broad themes: imagery training ( N  = 43, 27.6 %), idea production training ( N  = 83, 53.2 %), cognitive training ( N  = 17, 10.9 %), and thinking skills training ( N  = 13, 8.3 %). Thus, cognitive training approaches were found to be relatively uncommon. Although less common than idea production training, some cognitive training approaches (e.g., conceptual combination training) were found to have larger effects and higher success rates than did idea production training. These findings, plus the meta-analysis of training effectiveness by Scott et al. ( 2004a ), suggest that cognitive approaches will be effective, providing there is a focus on how to apply the technique (see Scott et al. 2004b ). One noted disadvantage of cognitive approaches, however, is that these techniques tend to be lengthy (see Scott et al. 2004b ). Thus, the length of cognitive training approaches could be a factor that limits the implementation of such creativity trainings in educational and business settings.

The aim of the current study was to develop and scientifically test a creativity training that anticipates these needs, and several requirements were specified for the training. First, it had to be domain unspecific ; that is, the training could be applied in various contexts irrespective of the trainee’s educational background. Second, the training had to employ a cognitive approach , as training programs that incorporate cognitive-oriented techniques have been shown to be effective (see Scott et al. 2004a ). Third, the training had to be brief (a single session, not exceeding 1.5 h) so that it could be implemented within an existing education program. Fourth, the current creativity training was developed by a scientist who holds a PhD in creativity and works as a creativity researcher, university teacher, and consultant and by a practitioner who has facilitated more than 900 creativity sessions with more than 14,000 participants worldwide. Thus, scientific insights and practical knowledge were combined when designing the training, which may strengthen the internal validity of the training (see Scott et al. 2004a ). Finally, the effectiveness of the training had to be scientifically tested by means of an extensive pre- and post-training assessment of participants’ creativity. We hypothesized that improvements in creative performance would be observed following the creativity training.

Materials and Methods

Participants.

A total of 32 (20 females) participants between the ages of 18 and 34 years old ( M  = 23.13, SD = 5.76) gave written informed consent to participate in the study, which was conducted according to the principles of the institutional review board (Ethics Committee Faculty of Social Sciences, Radboud University, the Netherlands) and the principles expressed in the Declarations of Helsinki. All the participants were Dutch and recruited for voluntary participation via the online research participation system (Sona) of Radboud University. The participants were from varied educational backgrounds, including MBO (EQ National Diploma or Vocational training; n  = 1), HAVO/VWO (EQ High School Diploma; n  = 2), HBO (EQ Applied Bachelor’s degree; n  = 2), and WO (EQ University Bachelor’s degree; n  = 27). Participants were given a choice of earning course credit (2.5 points) or €15 (approximately $16.70 USD) for their participation. Finally, the creativity training took place on March 30, 2015 at the laboratory of the Behavioural Science Institute, Radboud University, the Netherlands. Participants were subdivided across three training sessions (09:00–11:30, 10 participants; 11:45–14:15, 13 participants; 14:30–17:00, 9 participants). The same procedures were used during all sessions, which were conducted by the same experimenter and creativity trainer.

The overall effectiveness of the training was examined using a within-subjects design, with creative performance (pre, post) as the dependent variable. The techniques that were applied in the creativity training are described in the “ Training Techniques ” section, the measurement of creative performance is described in the “ Measures of Creative Performance ” section, and the procedure is described in the “ Procedure ” section.

Training Techniques

The training lasted 1.5 h. Based on the requirements outlined in the introduction, the following techniques were incorporated in the training: Silence , lines of evolution , random connections , and SCAMPER . Each of these techniques is described in detail below.

Technique 1: Silence

The participants were first provided with an explanation of the benefits of brainstorming individually and in silence. In particular, they were informed that brainstorming alone and in silence is beneficial for the creative process as it allows one to generate ideas without any restrictions, guidelines, or distractions. In addition, personal expertise and background knowledge can be used and individuals are not influenced by the ideas generated by other people. Moreover, during an individual brainstorming session, the creative thought process is not influenced by group processes (e.g., fear of criticism), idea loss due to turn-taking, and the dominance of certain group members (Nijstad and Stroebe 2006 ). If these group processes are at play at the beginning of a brainstorming session, the group may focus on a narrow range of idea directions—the ones mentioned by the participants who take the lead—and individual brainpower and expertise may be lost. After being introduced to the silent brainstorming technique, the participants generated ideas individually and in silence for 5 min.

Technique 2: Lines of Evolution

This technique relies on the findings of a Russian engineer, Genrikh Altshuller, who studied thousands of patents. He noticed that the evolution of breakthrough ideas—especially in the domain of technical innovation—follows universal principles. For example, a line of evolution could include changes in the form of an object using the following pattern: from solid, to powder or pieces, to liquid, to foam, to gel, to mechanics, to electronics, to spheres. A possible line of evolution for real-world inventions could be that what was once a chocolate bar can become mini chocolates or a chocolate drink, and what was once a solid $1 coin can become a virtual bit coin. This technique may facilitate the generation of creative ideas and solutions by examining how the current form of an idea or product can be changed into the next evolutionary form, that is, by “digging deeper.”

Technique 3: Random Connections

Creative ideas often come from making connections between seemingly unrelated concepts or objects. Accordingly, in some situations, creative thinking may not benefit from digging deeper, but instead from “digging elsewhere.” By digging elsewhere, one allows creative ideas to emerge from associative processes. The underlying approach of this technique is that one uses a random stimulus—for example, an object in the room or a picture in a newspaper—and tries to generate as many associations related to this stimulus as possible. Next, one can connect these associations to the problem that needs to be solved. To illustrate this process, imagine the following example: the problem at hand is “generate a new sun cream,” and the random object chosen is a “ballpoint pen.” Associations can be generated from the ballpoint pen, such as writing, color, and roller. By connecting these associations to the sun cream problem, one might generate the idea of colored sun cream (i.e., the sun cream is colored during application, which disappears once absorbed), a roll-on sun cream, or a roll-on sun cream containing colored sun cream. Thus, by facilitating the generation of random connections, this technique helps to create an environment that allows and encourages the generation of ideas that would very likely not emerge intentionally—a process which is called serendipitous creativity. The notion of serendipity is common throughout the history of creativity and scientific innovation, reportedly being involved in discoveries such as penicillin, the microwave, and the Post-it note.

Technique 4: Scamper

During the creative process, novel solutions may emerge when forced to think of possible changes to an existing idea or product. Hereby, a list of suggestions for possible changes can be helpful. A list with seven possible thinking techniques was provided using SCAMPER (Osborn 1953 ; Eberle 1971 ), and the participants could use any or all of the suggested approaches: substitute (remove some part of the accepted situation, thing, or concept and replace it with something else), combine (join, affiliate, or force together two or more elements of your subject matter and consider ways that such a combination might move you toward a solution), adapt (change some part of your problem so that it works where it did not before), modify (consider many of the attributes and change them if necessary; attributes can include size, shape, texture, color, attitude, position), purpose (put the product to some other use), eliminate (remove any or all elements of your subject, simplify it, or reduce it to its core functionality), reverse (change the direction or orientation; turn it upside-down, inside-out, or make it go backwards/against the direction it was intended to move or be used), and rearrange (modify the order of operations or any other hierarchy involved in the product). While applying these techniques, the participants have to remember the principle of force fitting; that is, if they cannot think of anything in response to the SCAMPER prompt they are using, they have to force a response (i.e., regardless of how ridiculous it seems) and then to think of ways to make any illogical responses work.

Measures of Creative Performance

Divergent thinking: the aut.

One of the creative skills to be developed by the current training program was divergent thinking, which is the capacity to generate multiple alternatives and solutions. There is a multitude of evidence suggesting that divergent thinking represents a distinct ability necessary for many forms of creative performance (Bachelor and Michael 1997 ; Mumford et al. 1998 ; Plucker and Renzulli 1999 ; Scott et al. 2004a ; Scratchley and Hakstian 2001 ; Sternberg and O’Hara 1999 ; Vincent et al. 2002 ). Divergent thinking tests can be considered the most widely used creativity test (Cropley 2000 ; Davis 2003 ), and they are applied in approximately 40 % of all creativity studies with college students and adults (Torrance and Presbury 1984 ). Divergent thinking can be assessed using open-ended tests, and several studies have documented its test-retest reliability (for example, see Yamamoto 1963a , 1963b ). Moreover, divergent thinking tests have been recommended as tests of effectiveness for creativity trainings (DeHaan 2011 ).

One of the most frequently used and well-validated divergent thinking test is the Alternative Uses task (AUT, Guilford 1967 ). During the AUT, the participants are asked to list as many different uses for a common object as possible and to make sure that the ideas they come up with are not too common and not completely impossible. The objects used in the current study were a brick and a newspaper and they were counterbalanced between the pre- and post-measure across the participants. The participants were given 3 min to perform the AUT and were instructed to list their ideas in the space provided. By coding the listed ideas, the participants’ creativity —the ability to generate ideas that are both novel and useful (for example, Amabile 1983 ; Mumford 2003 ; Sternberg and Lubart 1999 )—was examined. Moreover, the participant’s cognitive flexibility —the flexible switching among approaches—was assessed. Cognitive flexibility is characterized by global (as opposed to local) processing of information (for example, Ashby et al. 1999 ; Murray et al. 1990 ) and by the use of flat (as opposed to steep) associative hierarchies (for example, Mednick 1962 ). In other words, cognitive flexibility involves the ability to break cognitive patterns, to overcome functional fixedness, and to avoid a reliance on conventional ideas or solutions (Guilford 1967 ). Additionally, participant’s fluency —the total number of ideas generated by a participant—was measured. A more detailed description of the three measures is provided below.

Each idea was assigned a creativity score, ranging from not at all creative (=1) to very much creative (=5). Hereby, the two essential criteria of a creative idea—novelty and usefulness (for example, Amabile 1983 ; Mumford 2003 ; Sternberg and Lubart 1999 )—were taken into consideration. Two raters performed the creativity scoring. One rater assigned a creativity score to all of the ideas, and the other rater assigned creativity scores to 50 % of the ideas (50 % of the ideas generated for a brick and 50 % of those generated for a newspaper). The interrater reliability of the ratings was calculated using a two-way random intraclass correlation coefficient (ICC) analysis for consistency and can be considered substantial (ICC BothTasks  = 0.71, ICC Krant  = 0.65, ICC Baksteen  = 0.75). For each participant, across the ideas generated, a creativity sum score was calculated. The creativity sum score can be correlated with fluency (i.e., the total number of ideas generated by a participant). To control for the possibility that quantity confounds quality (e.g., that many less original and less useful ideas get a higher score than a few highly original and highly useful ideas) mean scores were calculated for each participant by dividing their creativity sum score by their fluency score.

Cognitive Flexibility

Cognitive flexibility can be quantified by the number of distinct idea categories used: each idea generated by a participant is assigned to a category from a predefined list of idea categories, and the total number of distinct idea categories is then calculated. For example, when asked to list possible uses for a brick, the ideas “build a house” and “build a bridge” would lead to a cognitive flexibility score of 1, as all ideas can be assigned to the category “building something.” On the other hand, the ideas build a house and “break a window” would lead to a score of 2, as the ideas can be assigned to two different idea categories (i.e., building something, and “destroying something”). For the flexibility scoring, a list of predefined idea categories was developed by two trained raters for each of the common objects (i.e., the brick and the newspaper). One of the raters assigned all of the ideas to the predefined idea categories, while the other rater did so for 50 % of the ideas (for 50 % of the ideas generated for a brick and for 50 % of those generated for a newspaper). The interrater reliability of the ratings was calculated using a two-way random ICC analysis for consistency and can be considered excellent (ICC BothTasks  = 0.97, ICC Krant  = 0.98, ICC Baksteen  = 0.95).

To calculate a participant’s fluency score, the number of complete and non-redundant ideas produced was counted.

Convergent Thinking: the RAT

Although important, divergent thinking is only one component of creative thinking. Many scholars emphasize the need for an additional cognitive ability, convergent thinking; that is, the cognitive process of deriving the single best, or most correct, answer to a problem or question (Fasko 2001 ; Guilford 1967 ; Nickerson 1999 ; Treffinger 1995 ). This component of creative thought was assessed using the Remote Associates Test (RAT), which was originally developed by Mednick ( 1962 ). In the RAT, the participants are presented with three-word combinations and are required to generate a fourth word that connects the three seemingly unrelated words (e.g., bar–dress–glass, fourth word: cocktail; cocktail bar, cocktail dress, cocktail glass). The structure of the RAT—finding a highly constrained, single solution—fits well with the concept of convergent thinking. As the English RAT version is rather difficult for non-native speakers of English (e.g., Estrada et al. 1994 ), in the current study, the Dutch version of the RAT (adapted from Chermahini et al. 2012 ) was used. The participants were presented with a list of ten three-word combinations. Two versions of the RAT were provided and counterbalanced between the pre- and post-measure across participants.

Creative Problem Solving

A creative activity that requires the interplay of divergent and convergent thinking is creative problem solving — the cognitive process of searching for a novel and inconspicuous solution to a problem. Creative problem solving can be blocked by fixations—a persistent impasse in problem solving in which unwarranted assumptions, typical thinking, or recent experiences block awareness of the solution. Two common forms are perceptual and functional fixations. The participants’ ability to overcome perceptual fixation was measured by a pattern perception task and the nine-dot-problem; the ability to overcome functional fixation was measured by insight tasks. Two different versions of the tasks were used and counterbalanced between the pre- and post-measure across participants.

In the pattern perception task, participants are presented with a picture consisting of various black patches on a white background and they have to indicate which pattern is presented in the picture. In the nine-dot-problem, nine dots are arranged in a square pattern. The task is to join the dots using four straight lines. Although there are no borders surrounding the task, people often feel constrained by the assumption that they must only draw within the square boundary formed by the dots. In fact, the task can only be solved if one draws outside of the square.

The insight tasks used in the current study were the two-string problem, the ball problem, the candle problem, and the switch problem. To solve these tasks, one has to use a displayed object in an unfamiliar manner (i.e., in the two-string and candle problems) or one has to complete the task in a manner which is different from prior experience or expectations (i.e., in the ball and switch problems). For example, in the two-string problem, participants are required to tie together two strings hanging from the ceiling. However, the strings are arranged so far apart that they cannot be reached at the same time. The solution requires the use of one of the objects available in the room so that one string can be set in motion as a pendulum. This swinging string can then be caught, while holding the other string, and thus can then be tied together.

Demographics

In addition to the various measures of creative performance, participants completed several demographic questions, determining the gender, age, nationality, and educational background of the participants.

Participants were welcomed individually at the BSI entrance. Once all of the participants who were scheduled for the training session had arrived, they were accompanied to the room in which the training was held. In the training room, the experimenter briefly introduced herself and the creativity trainer and informed the participants of how the 2.5-h session would be conducted.

During the first 20 min of the session, participants’ creative performance was measured (the pre-training, i.e., baseline measure) using several well-known creativity tasks (for information about the creativity tasks, see the “ Measures of creative performance ” section). Following the pre-training measure of creative performance, the participants received the creativity training for 1.5 h (for information about the training techniques, see the “ Training techniques ” section). The training itself started with a short word of welcome by the trainer as well as an explanation of the real-world problem that would be used for all brainstorming sessions during the training. The real-world problem required generating ideas for what the next generation sponge might look like (i.e., Hoe ziet de volgende generatie spons eruit? ). For each of the four techniques, the participants completed two procedures. First, the cognitive mechanism underlying the technique and how the technique can be applied were explained to them by the trainer. Second, the participants practiced and applied the technique to the real-world problem; first alone and then in a small group (the question whether brainstorming in groups has any benefit over-and-above brainstorming individually will be addressed in a separate paper). After the training, the post-measure of creative performance was administered. The post-measure lasted 20 min and employed equivalent versions of the tasks used in the creativity pre-measure (i.e., the versions did not differ in the types of questions nor in level of difficulty). To control for a possible instrumentation threat (i.e., the risk that an observed change from pre- to post-measure is due to the test that was used, rather than the training), two versions of each task were created and counterbalanced between the pre- and post-measure across participants. This meant that half of the participants performed one version as the pre-measure and the other version as the post-measure; the remaining half of the participants completed these versions in the reverse order. Finally, the participants ended the study by completing the demographic questions (for information about these questions, see the “ Demographics ” section). All questionnaires and training materials were provided on paper.

Impact of the Training on Creative Performance

The effectiveness of the training was scientifically tested by means of a pre- and post-test, employing creativity measures that relied on divergent thinking (the “ Divergent Thinking: the AUT ” section), convergent thinking (the “ Convergent Thinking: the RAT ” section), and creative problem solving skills (the “ Creative Problem Solving ” section).

An ANOVA was performed on the mean creativity rating of ideas generated during the AUT with training ( pre , post ) as the within-subjects variable and task order ( brick – newspaper , newspaper – brick ) as the between-subjects variable. The mean creativity level of ideas produced did not differ significantly across task order group ( F (1, 30) = 0.092, p  = .764), indicating that one group was not significantly more creative than the other, nor was a significant interaction effect found between task order and training ( F (1, 30) = 0.428, p  = .518). Importantly, a significant main effect for training was observed ( F (1, 30) = 5.709, p  = .023), suggesting that the mean creativity of the ideas generated following creativity training ( M  = 2.59, SD = 0.45) was significantly higher than that of the ideas generated prior to training ( M  = 2.36, SD = 0.41) (see Fig.  1 ).

Mean creativity of the ideas generated pre- and post-creativity training

Given that a significant improvement in creative performance was found following training, it is interesting to examine the possible mechanism for the observed change. Cognitive flexibility was examined as a possible mechanism, as the training employed a cognitive approach. That is, the increase in creativity after training could be partly explained by participants diversifying the categories of their given responses (Ritter et al. 2012 , 2014 ). As such, a 2 × 2 mixed ANOVA was performed on the number of distinct idea categories generated for the AUT ( cognitive flexibility ), with training (pre, post) as the within-subjects variable and task order (brick–newspaper, newspaper–brick) as the between-subjects variable. The analysis revealed that the cognitive flexibility of the participants in the different task order groups did not significantly differ ( F (1, 30) = 1.009, p  = .323), indicating that one group did not score higher on cognitive flexibility than the other. Importantly, a main effect of the training approached significance ( F (1, 30) = 3.788, p  = .061), suggesting that the mean number of idea categories generated on the AUT task could improve by approximately one distinct category from pre-training ( M  = 5.41, SD = 2.67) to post-training ( M  = 6.34, SD = 2.52), see Fig.  2 .

Cognitive flexibility pre- and post-creativity training

Finally, an interaction effect was found between training and task order ( F (1, 30) = 31.128, p  < .001) (see Fig.  2 ). Post hoc analyses revealed significant differences between the two tasks before and after training, such that the number of idea categories was higher for the newspaper task both prior to training ( p  < .001) and following training ( p  = .018). These results suggest that generating distinct ideas might be easier for the newspaper task overall, and this was confirmed by follow-up tests—the newspaper produced a larger number of distinct idea categories ( M  = 7.22, SD = 2.73) compared with the brick ( M  = 4.53, SD = 1.67; t (31) = 5.344, p  < .001). Importantly, follow up tests revealed that performance on the more difficult task (i.e., the brick) was significantly improved from pre-training ( M  = 3.75, SD = 1.18) to post-training ( M  = 7.06, SD = 2.74; t (30) = 2.970, p  = .006).

To examine whether the creativity training had any impact on divergent thinking, the participants’ number of correctly solved RAT word pairs prior to training were compared with that following creativity training. As no participants reported prior knowledge of the RAT word pairs used, all the participant responses were included in the analysis. Initially, a mixed ANOVA was performed to include an examination of task order. However, as no significant effects involving task order were found, a within-subjects t test was performed on the effect of creativity training on RAT scores (pre, post). The training appeared to have a significant impact on RAT task performance: on average, the participants solved approximately one more RAT word pair following creativity training ( M  = 4.73, SD = 2.32) compared with pre-training performance ( M  = 3.97, SD = 2.27; t (31) = 2.342, p  = .026) (see Fig.  3 ).

Performance on the RAT pre- and post-creativity training

To examine whether creativity training had any impact on creative problem solving skills, the problem solving performance scores prior to and following creativity training were calculated by adding the participants’ scores on the picture tasks, the dot problem task, and the two insight problems. Correct responses were excluded where participants reported prior knowledge of the task(s). Given the exclusion of scores for participants who reported prior knowledge of the tasks, mean problem solving scores were also calculated (i.e., an average score for the unknown tasks completed) and examined. As the overall findings did not differ for mean or sum scores, sum scores were retained in the analysis for improved ease of interpretation. A 2 × 2 mixed ANOVA was performed on the problem solving score with task order as the between-subjects variable. No significant main effect was found for task order ( F (1, 30) = 0.375, p  = .545), indicating that one group was not significantly better at solving the tasks than the other. Importantly, a main effect for training approached significance ( F (1, 30) = 3.695, p  = .064), such that performance on these tasks was higher following creativity training ( M  = 0.97, SD = 0.80) compared with performance prior to the training ( M  = 0.66, SD = 0.70).

In addition, the analyses revealed a significant interaction effect between training and task order ( F (1, 30) = 5.320, p  = .028). Post hoc tests indicated that prior to training, participants who completed the problem solving task set that included the ball and rope insight tasks performed significantly better than those who completed the set containing the candle and switch tasks ( p  = .041). Interestingly, no task order effect was observed post-training ( p  = .387). Moreover, participants who completed the set of problem solving tasks including the candle and switch insight tasks prior to training showed a significant improvement in task performance post-training ( p  = .006), while such a difference was not observed for the group who completed the problem solving tasks in the reverse order ( p  = .788). Taken together, these results suggest that the task set containing the candle and switch tasks were harder to solve than that containing the ball and rope problems and that the training increased performance for the more difficult tasks (Fig.  4 ).

Creative problem solving performance pre- and post-creativity training

Summary of Research Aims and Findings

Creativity has a crucial role in innovation, and the creation of new ideas and problem solutions has become a key concern for most organizations and businesses (Runco 2004 ). This goal is further supported by findings showing that creativity plays an important role in everyday problem solving (Cropley 1990 ; Mumford et al. 1991 ; Runco 1994 ; Torrance 1971 ; Wallas 1926 ) and in emotional health and well-being (Runco 2004 ; Simonton 2000 ). Given the importance of creativity and that creative thinking skills can be trained (Scott et al. 2004a ), the goal should be to train creative skills throughout the entire population. As such, there is a strong need for a well-developed, domain-unspecific creativity training that has been scientifically tested. In addition, such creativity training would be relatively easier to implement in educational and organizational settings if it was a single, brief session. Thus, the main objectives of the current research were to develop a brief creativity training that meets these requirements and to establish whether this training can enhance creative performance.

The findings of the current study demonstrate that a short training (i.e., a single training session of just 1.5 h), which develops cognitive skills necessary for creativity, can have an impact on creative performance. Following the creativity training session, improvements were observed across a variety of creative performance measures. Importantly, the creativity level of the ideas generated during the divergent thinking task improved post-training. In addition, the findings of the current study shed light on a possible underlying mechanism for these improvements in creativity, that is, cognitive flexibility. This is evidenced by a marginal improvement in the number of distinct idea categories generated post-training. Next to these divergent thinking skills, the training also improved convergent thinking, as improved performance on the RAT was observed post-training. Finally, the training provided marginal improvements in creative problem solving skills by reducing perceptual and functional fixations and mental blocks. Interestingly, it seems that the training benefitted the more difficult versions of some tasks, as demonstrated by the interaction effects for the AUT and the problem solving tasks.

The current findings provide support to the creative cognition model of creativity (for example, Ward et al. 1999 ), which states that individual differences in creativity can be explained by variations in the efficiency of cognitive processes underlying creativity (for example, Ward et al. 1999 ), and to the idea that creative thinking can be trained (Scott et al. 2004a ). Moreover, the current findings have important implications for educational and organizational settings. If the goal is to train creative skills among the entire population, effective creativity training programs need to be successfully implemented—this is particularly important if we want to meet the needs of the twenty-first century. The increases in creative performance reported here are impressive and promising since the training was only short (1.5 h), and the effects were demonstrated across a variety of well-validated measures.

Strengths and Contributions

Previous research has shown that creativity trainings with a focus on developing cognitive skills contribute to effectiveness (Scott et al. 2004a ). However, cognitive approaches tend to take longer to explain and implement and appear to be relatively less common (see Scott et al. 2004b ). The current training employed a cognitive approach, with the techniques used targeting multiple divergent, convergent, and problem-solving processes (i.e., not just idea generation) (see Scott et al. 2004a , b ). As such, the current creativity training makes a distinct contribution by employing a cognitive training approach in a brief, single-session, creativity training. Importantly, the exercises used during the creativity training differed from those used to evaluate the effectiveness of the training; that is, participants were not trained to the criterion (see Scott et al. 2004a ). Given that significant improvements were found following the current training employing a cognitive approach, this demonstrates a transfer of cognitive skills required for creative performance—and further supports the domain-unspecific nature of the training. In line with variables thought to strengthen training quality and efficacy (see Scott et al. 2004a ), the current creativity training did not include prizes, overt praise, or external motivation for creative performance.

Limitations and Suggestions for Future Research

While the current study provides evidence that the combined effects of various cognitive skills training methods work, there are some limitations of the study that should be addressed in future research. The current study included a within-subjects design with pre- and post-test creativity measures. Given the nature of the tasks included in the study, it is unlikely that the observed increase in creative performance on the post-measure was due to practice or learned effects (e.g., different objects were used in the AUT versions and different problems were presented in the insight task versions). Moreover, interaction effects were observed for some of the creativity measures (i.e., the training benefitted the more difficult task versions), suggesting that these effects would not be improved by practice alone. However, to eliminate any practice or learned effects on creative performance with certainty, a future study could employ a between-subjects design, or a mixed design, employing a control group. In future research, it could also be interesting to investigate whether the training is particularly effective for specific creativity domains. Importantly, the current study does not allow any conclusions to be made about the long-term effects of the training. In future research, a follow-up measure could be included to gain information about the maintained effects of creativity training.

The four techniques employed in the current study were carefully selected by the authors, and it was assumed that their combined effects would have a greater impact on creative performance. It remains unclear whether just one of the training methods would be necessary to obtain these observed effects or whether their combined effects were necessary to observe significant improvements in creative performance. Future research could answer this question by examining the impact of each of these techniques on creative performance in isolation. Such a test may, moreover, provide valuable information to further improve the form of the techniques applied during the training.

Finally, the western participant sample had a high education level and a relatively high proportion of females, which could limit the ecological validity of this study. On the other hand, findings of a meta-analysis by Scott et al. ( 2004a ) suggest that creativity training may be more effective in organizational than academic settings and may have greater effects on men than on women. Considering that this study relied on a population and setting for which the a priori chance of finding a training effect was not high, the ecological validity and generalizability of the current findings may be enhanced. However, it is still unknown what impact such training would have on eastern participants and on other age groups, for example, school-aged children and elderly people. Future research could include examining how this or a similar training can be adapted in eastern cultures and for other age groups.

Conclusions

Creative thinking can be considered one of the key competencies for the twenty-first century and is viewed as being essential for entrepreneurial activities and long-term economic growth (Amabile 1997 ; Wise 1992 ). If a goal is to train creative thinking skills, effective creativity training programs need to be developed and successfully implemented. The current study provided further evidence that creative potential is inherent to cognitive functioning and can be facilitated with training. Impressively, following a short (a single session lasting 1.5 h) domain-unspecific training, which develops cognitive skills necessary for creativity, improved creative performance on a variety of well-validated measures. These findings have important implications for educational and organizational settings, as they suggest that the present brief creativity training (or one employing similar cognitive techniques) could be implemented to facilitate creative thinking skills among the entire population.

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Acknowledgments

Financial support was provided by a Netherlands Organization for Scientific Research (NWO) Veni grant awarded to Simone M. Ritter (016.155.049. Veni 2014. Division Social Sciences).

We would like to thank Bernice Plant for her help with the data analysis and the writing of the paper.

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Ritter, S.M., Mostert, N. Enhancement of Creative Thinking Skills Using a Cognitive-Based Creativity Training. J Cogn Enhanc 1 , 243–253 (2017). https://doi.org/10.1007/s41465-016-0002-3

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Being lost in your thoughts can also help with problem solving and creativity. Image:  Unsplash/ bruce mars

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• Creativity and problem solving can happen when you let your mind wander, scientists in Germany have found.
• But smartphones mean we have mostly lost the habit of free thinking.
• Other studies have shown the phase just before falling asleep is highly creative, and that adapting to change forces us to think creatively.
• Creativity and problem solving are two of 10 key skills that will be needed in the world of work by 2025, according to the World Economic Forum.

Thinking about nothing in particular is more enjoyable than you’d imagine and can help in areas including creativity and problem solving, scientists have found.

At the University of Tübingen in southern Germany, psychologists studied more than 250 people who were “encouraged to engage in directionless contemplation or free-floating thinking ”, according to The Guardian newspaper.

The results, published in the Journal of Experimental Psychology, suggest humans find it hard to let their minds wander, but that this is an underused talent.

The wonders of a wandering mind

The psychologists found the benefits of free thinking include enhancing your imagination and making you feel better about yourself. Being lost in your thoughts can also help with problem solving and creativity, they said.

Participants in the study said they enjoyed letting their minds wander more than they had expected. But “some people simply found it hard to spend time with their own thoughts, especially if they tended towards negative thinking,” the Guardian reported.

Smartphones were concluded to be at least partly to blame - they are “distractions” that have “contributed to a loss of the habit of free thinking,” said the psychologists.

Take a nap to boost creativity

Other studies have shown the creative benefits of disengaging our brains. Researchers in France recently identified a point just before we fall asleep which is rich in creativity. Hypnagogia, or stage N1 was said to be used by the inventor Thomas Edison to plunder sleep-inspired ideas.

Scientists have found that creativity blends spontaneous and controlled thinking . This is the ability to “both spontaneously brainstorm ideas and deliberately evaluate them to determine whether they’ll actually work,” American neuroscientist Roger Beaty explains in an article for The Conversation.

Beaty makes the point that creativity isn’t just for geniuses. All of us use everyday creativity like drawing or making recipes, described by researchers as ‘little-c’ creativity. ‘Big-C’ creativity , on the other hand, tends to refer to creative breakthroughs in fields like science, technology, society and the arts.

Flexible thinking unlocks creativity

At the University of Cambridge in the UK, psychologists say “ cognitive flexibility ” is a crucial human skill in adapting to changing environments. COVID-19 essentially heralded a new era in flexible thinking – with most people, for example, having to cope with pandemic lockdowns. In the future, learning to use this flexible thinking will help us improve our resilience and wellbeing.

“Flexible thinking is key to creativity – in other words, the ability to think of new ideas, make novel connections between ideas, and make new inventions,” the Cambridge scientists say in an article for the World Economic Forum. “It also supports academic and work skills such as problem solving.”

Soft skills are key in the future world of work

In the Forum’s Future of Jobs Report 2020 , creativity and problem solving are two of 10 skills expected to be vital in the world of work by 2025.

“Core skills such as critical thinking, analysis and problem solving are consistently top of the reskilling and upskilling priorities for educators and businesses,” the report says.

Self-management skills like active learning, resilience, stress tolerance and flexibility are newly emerging skills on the list.

People skills like leadership and social influence are also vital, according to the report.

The World Economic Forum is working with Cabify, Deliveroo, Grab, MBO Partners, Postmates and Uber to improve working standards for the tens of millions of people who earn a living or top up their incomes through digital work/service platforms.

The chief executive officers from the six companies have signed The Charter of Principles for Good Platform Work , committing to ensure that platform workers receive fair conditions, treatment, benefits and training opportunities.

By collaborating with partners, the Forum is developing a comprehensive approach to provide clarity on platforms’ responsibilities to the workers who use their platforms, empower platform workers, promote their dignity and well-being, while supporting flexibility, innovation and the value offered by the platform economy to users and clients.

The Forum is looking for platform companies, regulatory bodies, workers’ organizations and independent experts globally who are committed to advancing working standards in the platform ecosystem, to collaborate on the next stage of the Promise of Platform Work initiative. Contact us to learn more.

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How to improve your creative skills for effective problem-solving

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What’s creative thinking?

Creative thinking versus critical thinking

Creative thinking skills

How to develop creative thinking skills

4 creative thinking examples to include on your resume

Sharpen your creativity

Creative thinking is the key to unlocking innovation and problem-solving excellence. 

In the whirlwind of everyday professional challenges, we’ve all encountered moments when fresh ideas feel elusive. If you’ve found yourself struggling to inspire your team or spinning out during a brainstorming session , it may be a sign you need to develop your creative skills. Plus, creative problem solving looks excellent on a resume .

As a leader or team member, your ability to think outside the box can ignite a spark of ingenuity that propels your team to new heights. Fan the flames of growth and learn how to improve your creative thinking (and highlight your new skills in your next job application).

What’s creative thinking? 

Creative thinking is the dynamic process of transforming your ideas into actions. The skillset equips you to think differently and approach challenges from innovative angles.

At its core, creative thinking empowers you to break free from the constraints of the status quo and dream up fresh, original ideas. It breathes life into your decisions, encouraging you to embrace your imaginative instincts. 

By daring to challenge traditional approaches, your creativity opens doors to uncharted innovations and groundbreaking solutions.

Creative thinking versus critical thinking 

Although creative and critical thinking are both used in problem-solving , the two skills are marked by key differences. 

Creative thinking is the catalyst for generating innovative ideas and crafting novel approaches to the challenges around them. With an open mind and a wild imagination, creative thinkers produce and explore unconventional solutions to the problems that stand in their way.

Critical thinking analyzes available information with an unbiased and rational approach. It involves questioning perceptions, ensuring that decisions are devoid of bias and reasoning remains grounded in sound judgment. 

Creative thinking skills 

When you look at creative thinking as a set of particular abilities, it becomes easier to develop and perfect. These creative skill examples can help you thrive inside and outside of the workplace:

1. Open-mindedness

When you’re open-minded, you can readily adapt to new information and look for fresh problem-solving approaches. You’re receptive to the opinions and ideas of others because you view them as constructive rather than criticizing . This openness also encourages you to freely share your creative ideas without fearing judgement.

2. Curiosity

You might find that you tap into creative potential the most when you’re challenging convention and posing new ways of thinking. Analyzing processes and asking yourself how you can improve them is an exciting way to make more efficient systems.

Whether you’re new to a job or have worked at the company for years, you may wonder why procedures are what they are — lean into this curiosity to develop new and better ways to work. 

3. Ability to brainstorm

There are numerous ways to solve a problem, and brainstorming helps to get them onto paper so you can weigh their pros and cons. This way of lateral thinking encourages you to view solutions as multifaceted rather than a single, straightforward answer.

4. Experimentation

Creative people experiment with various ways of solving a problem before deciding on the best way to take action. Emulate this mindset in your projects and tasks. For instance, if you work in web design, you might try several page layouts before deciding on a final visual identity for your client.

5. Networking

Speaking with people from different professional backgrounds is an excellent way to stimulate creative thinking and develop new perspectives. When you network with professionals with diverse skill sets and experiences, they might influence you to look at the world differently or suggest an innovative way to tackle a problem.

6. Observation

It’s important to know when to take the backseat and listen in. Observing how others tackle complex issues might inspire you to make changes within your team. Always keep an eye out for opportunities to learn from more experienced peers and innovative colleagues.

7. Organization

Although some individuals claim to thrive in clutter, keeping your work organized creates an environment where you can work freely without distraction. This involves keeping your workspace tidy, creating clear to-do lists, and using visual maps to express your plans and processes.

8. Communication

Proper communication empowers you to share valuable insight and ideas with your teammates. You need strong verbal and written skills to pitch and describe your thoughts and actively listen to others’ feedback and advice.

9. Analysis

Before you can dream up a creative approach to an obstacle, you must fully understand the problem at hand. Without proper analysis, your solution may contain flaws, or you could miss important details of your problem. Practice sifting through every detail of the issue and pinpointing the causes. 

10. Problem-solving

No matter your industry, problem-solving is always a valuable skill. Consider how to tackle a problem without asking the advice of others to see what creative solutions arise. This way, you can see what inventive ideas you can come up with before external opinions influence you.

Although some of your coworkers may seem to have a natural talent for creativity and creative thinking, it’s a skill anyone can develop and improve. Here are seven ways to advance your innovative problem-solving:

Reading is an effective way to exercise your mind, increase your vocabulary, and expose yourself to new ways of thinking. Whether your book is on a problem you’re facing at work or a new and exciting subject, reading is an excellent opportunity to learn. That’s right: simply cracking open a book can help you grow . 

Keep a notepad nearby and write down thoughts and ideas as they arise. Writing helps you to process information, and you can revisit your musing whenever you need to get your creative juices flowing. If you’ve never tried journaling before, it’s an excellent way to process your thoughts and feelings in a safe and private space. 

3. Exercise

Exercising improves your sleep and ability to cope with stress, making it easier to stay alert and contribute fresh ideas at work. 

4. Listen to music

Music can affect your mood and place you in the mindset to solve problems. If you’re struggling with creative writing or creating a visual piece of work, listening to music could push you toward expressing yourself more meaningfully. 

5. Ask for feedback

Collaboration and teamwork are key when developing creative solutions in the workplace. You can ask teammates or superiors for feedback on your ideas to gain insight into potential flaws in your reasoning and streamline your solutions.

6. Find a mentor or coach

Having an experienced person to bounce ideas off is a catalyst for creativity. A mentor or coach who’s dealt with similar obstacles can provide insight into what worked and what didn’t, saving you valuable brainstorming time. 

7. Change your approach

If you’ve been approaching your tasks the same way, adjusting your processes may bring a fresh perspective and stimulate change. Ask yourself why you tackle work from a similar angle each time and consider more creative ways to conduct your day-to-day operations.

4 creative thinking examples to include on your resume 

Employers want to add creative people to their teams because solving problems takes a lot of ingenuity. Use these four examples and bullet points for inspiration when listing creative thinking skills on your resume.

On a graphic designer’s resume:

• Collaborated on rebranding [company’s] visual identity and social media content strategy
• Developed unique and innovative branding material for [company A] , [company B] , and [company C]

On a copywriter’s resume:

• Revised [company’s] website and blog content to be more engaging, exciting, and SEO-focused
• Contributed original and innovative articles on [topic] to [publication A] and [publication B]

On a public relations specialist’s resume:

• Increased [company’s] brand awareness by planning [event] to launch [product]
• Collaborated with [brand] on [product’s] creative marketing strategy to reach a wider audience

On a teacher’s resume:

• Developed a novel approach to teaching [subject or class] to students with various learning styles and needs
• Introduced [extracurricular] , the first of its kind in [the school board] , to engage students in [activity]

Sharpen your creativity 

Critical and creative thinking broaden your perspective and allow you to devise unique solutions to everyday problems. You can develop your creative skills by changing your environment, learning from others, and adjusting your approach to work. 

Regardless of how you choose to spark creativity at work, don’t be afraid to step outside your comfort zone and confidently contribute your ideas. You never know — you might just come up with the next big company innovation.

Cultivate your creativity

Foster creativity and continuous learning with guidance from our certified Coaches.

Elizabeth Perry, ACC

Elizabeth Perry is a Coach Community Manager at BetterUp. She uses strategic engagement strategies to cultivate a learning community across a global network of Coaches through in-person and virtual experiences, technology-enabled platforms, and strategic coaching industry partnerships. With over 3 years of coaching experience and a certification in transformative leadership and life coaching from Sofia University, Elizabeth leverages transpersonal psychology expertise to help coaches and clients gain awareness of their behavioral and thought patterns, discover their purpose and passions, and elevate their potential. She is a lifelong student of psychology, personal growth, and human potential as well as an ICF-certified ACC transpersonal life and leadership Coach.

How to develop critical thinking skills

6 ways to leverage ai for hyper-personalized corporate learning, self directed learning is the key to new skills and knowledge, why asynchronous learning is the key to successful upskilling, the power of professional learning communities, why creativity isn't just for creatives and how to find it anywhere, can dreams help you solve problems 6 ways to try, experimentation brings innovation: create an experimental workplace, 8 creative solutions to your most challenging problems, similar articles, 10 problem-solving strategies to turn challenges on their head, thinking outside the box: 8 ways to become a creative problem solver, what is creative thinking and why does it matter, essential decision-making skills to guide your tough choices, what are professional skills, and which should you add to your resume, professional leadership skills to incorporate on your resume, stay connected with betterup, get our newsletter, event invites, plus product insights and research..

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• Open access
• Published: 11 January 2023

The effectiveness of collaborative problem solving in promoting students’ critical thinking: A meta-analysis based on empirical literature

• Enwei Xu   ORCID: orcid.org/0000-0001-6424-8169 1 ,
• Wei Wang 1 &
• Qingxia Wang 1  

Humanities and Social Sciences Communications volume  10 , Article number:  16 ( 2023 ) Cite this article

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• Science, technology and society

Collaborative problem-solving has been widely embraced in the classroom instruction of critical thinking, which is regarded as the core of curriculum reform based on key competencies in the field of education as well as a key competence for learners in the 21st century. However, the effectiveness of collaborative problem-solving in promoting students’ critical thinking remains uncertain. This current research presents the major findings of a meta-analysis of 36 pieces of the literature revealed in worldwide educational periodicals during the 21st century to identify the effectiveness of collaborative problem-solving in promoting students’ critical thinking and to determine, based on evidence, whether and to what extent collaborative problem solving can result in a rise or decrease in critical thinking. The findings show that (1) collaborative problem solving is an effective teaching approach to foster students’ critical thinking, with a significant overall effect size (ES = 0.82, z  = 12.78, P  < 0.01, 95% CI [0.69, 0.95]); (2) in respect to the dimensions of critical thinking, collaborative problem solving can significantly and successfully enhance students’ attitudinal tendencies (ES = 1.17, z  = 7.62, P  < 0.01, 95% CI[0.87, 1.47]); nevertheless, it falls short in terms of improving students’ cognitive skills, having only an upper-middle impact (ES = 0.70, z  = 11.55, P  < 0.01, 95% CI[0.58, 0.82]); and (3) the teaching type (chi 2  = 7.20, P  < 0.05), intervention duration (chi 2  = 12.18, P  < 0.01), subject area (chi 2  = 13.36, P  < 0.05), group size (chi 2  = 8.77, P  < 0.05), and learning scaffold (chi 2  = 9.03, P  < 0.01) all have an impact on critical thinking, and they can be viewed as important moderating factors that affect how critical thinking develops. On the basis of these results, recommendations are made for further study and instruction to better support students’ critical thinking in the context of collaborative problem-solving.

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Introduction.

Although critical thinking has a long history in research, the concept of critical thinking, which is regarded as an essential competence for learners in the 21st century, has recently attracted more attention from researchers and teaching practitioners (National Research Council, 2012 ). Critical thinking should be the core of curriculum reform based on key competencies in the field of education (Peng and Deng, 2017 ) because students with critical thinking can not only understand the meaning of knowledge but also effectively solve practical problems in real life even after knowledge is forgotten (Kek and Huijser, 2011 ). The definition of critical thinking is not universal (Ennis, 1989 ; Castle, 2009 ; Niu et al., 2013 ). In general, the definition of critical thinking is a self-aware and self-regulated thought process (Facione, 1990 ; Niu et al., 2013 ). It refers to the cognitive skills needed to interpret, analyze, synthesize, reason, and evaluate information as well as the attitudinal tendency to apply these abilities (Halpern, 2001 ). The view that critical thinking can be taught and learned through curriculum teaching has been widely supported by many researchers (e.g., Kuncel, 2011 ; Leng and Lu, 2020 ), leading to educators’ efforts to foster it among students. In the field of teaching practice, there are three types of courses for teaching critical thinking (Ennis, 1989 ). The first is an independent curriculum in which critical thinking is taught and cultivated without involving the knowledge of specific disciplines; the second is an integrated curriculum in which critical thinking is integrated into the teaching of other disciplines as a clear teaching goal; and the third is a mixed curriculum in which critical thinking is taught in parallel to the teaching of other disciplines for mixed teaching training. Furthermore, numerous measuring tools have been developed by researchers and educators to measure critical thinking in the context of teaching practice. These include standardized measurement tools, such as WGCTA, CCTST, CCTT, and CCTDI, which have been verified by repeated experiments and are considered effective and reliable by international scholars (Facione and Facione, 1992 ). In short, descriptions of critical thinking, including its two dimensions of attitudinal tendency and cognitive skills, different types of teaching courses, and standardized measurement tools provide a complex normative framework for understanding, teaching, and evaluating critical thinking.

Cultivating critical thinking in curriculum teaching can start with a problem, and one of the most popular critical thinking instructional approaches is problem-based learning (Liu et al., 2020 ). Duch et al. ( 2001 ) noted that problem-based learning in group collaboration is progressive active learning, which can improve students’ critical thinking and problem-solving skills. Collaborative problem-solving is the organic integration of collaborative learning and problem-based learning, which takes learners as the center of the learning process and uses problems with poor structure in real-world situations as the starting point for the learning process (Liang et al., 2017 ). Students learn the knowledge needed to solve problems in a collaborative group, reach a consensus on problems in the field, and form solutions through social cooperation methods, such as dialogue, interpretation, questioning, debate, negotiation, and reflection, thus promoting the development of learners’ domain knowledge and critical thinking (Cindy, 2004 ; Liang et al., 2017 ).

Collaborative problem-solving has been widely used in the teaching practice of critical thinking, and several studies have attempted to conduct a systematic review and meta-analysis of the empirical literature on critical thinking from various perspectives. However, little attention has been paid to the impact of collaborative problem-solving on critical thinking. Therefore, the best approach for developing and enhancing critical thinking throughout collaborative problem-solving is to examine how to implement critical thinking instruction; however, this issue is still unexplored, which means that many teachers are incapable of better instructing critical thinking (Leng and Lu, 2020 ; Niu et al., 2013 ). For example, Huber ( 2016 ) provided the meta-analysis findings of 71 publications on gaining critical thinking over various time frames in college with the aim of determining whether critical thinking was truly teachable. These authors found that learners significantly improve their critical thinking while in college and that critical thinking differs with factors such as teaching strategies, intervention duration, subject area, and teaching type. The usefulness of collaborative problem-solving in fostering students’ critical thinking, however, was not determined by this study, nor did it reveal whether there existed significant variations among the different elements. A meta-analysis of 31 pieces of educational literature was conducted by Liu et al. ( 2020 ) to assess the impact of problem-solving on college students’ critical thinking. These authors found that problem-solving could promote the development of critical thinking among college students and proposed establishing a reasonable group structure for problem-solving in a follow-up study to improve students’ critical thinking. Additionally, previous empirical studies have reached inconclusive and even contradictory conclusions about whether and to what extent collaborative problem-solving increases or decreases critical thinking levels. As an illustration, Yang et al. ( 2008 ) carried out an experiment on the integrated curriculum teaching of college students based on a web bulletin board with the goal of fostering participants’ critical thinking in the context of collaborative problem-solving. These authors’ research revealed that through sharing, debating, examining, and reflecting on various experiences and ideas, collaborative problem-solving can considerably enhance students’ critical thinking in real-life problem situations. In contrast, collaborative problem-solving had a positive impact on learners’ interaction and could improve learning interest and motivation but could not significantly improve students’ critical thinking when compared to traditional classroom teaching, according to research by Naber and Wyatt ( 2014 ) and Sendag and Odabasi ( 2009 ) on undergraduate and high school students, respectively.

The above studies show that there is inconsistency regarding the effectiveness of collaborative problem-solving in promoting students’ critical thinking. Therefore, it is essential to conduct a thorough and trustworthy review to detect and decide whether and to what degree collaborative problem-solving can result in a rise or decrease in critical thinking. Meta-analysis is a quantitative analysis approach that is utilized to examine quantitative data from various separate studies that are all focused on the same research topic. This approach characterizes the effectiveness of its impact by averaging the effect sizes of numerous qualitative studies in an effort to reduce the uncertainty brought on by independent research and produce more conclusive findings (Lipsey and Wilson, 2001 ).

This paper used a meta-analytic approach and carried out a meta-analysis to examine the effectiveness of collaborative problem-solving in promoting students’ critical thinking in order to make a contribution to both research and practice. The following research questions were addressed by this meta-analysis:

What is the overall effect size of collaborative problem-solving in promoting students’ critical thinking and its impact on the two dimensions of critical thinking (i.e., attitudinal tendency and cognitive skills)?

How are the disparities between the study conclusions impacted by various moderating variables if the impacts of various experimental designs in the included studies are heterogeneous?

This research followed the strict procedures (e.g., database searching, identification, screening, eligibility, merging, duplicate removal, and analysis of included studies) of Cooper’s ( 2010 ) proposed meta-analysis approach for examining quantitative data from various separate studies that are all focused on the same research topic. The relevant empirical research that appeared in worldwide educational periodicals within the 21st century was subjected to this meta-analysis using Rev-Man 5.4. The consistency of the data extracted separately by two researchers was tested using Cohen’s kappa coefficient, and a publication bias test and a heterogeneity test were run on the sample data to ascertain the quality of this meta-analysis.

Data sources and search strategies

There were three stages to the data collection process for this meta-analysis, as shown in Fig. 1 , which shows the number of articles included and eliminated during the selection process based on the statement and study eligibility criteria.

This flowchart shows the number of records identified, included and excluded in the article.

First, the databases used to systematically search for relevant articles were the journal papers of the Web of Science Core Collection and the Chinese Core source journal, as well as the Chinese Social Science Citation Index (CSSCI) source journal papers included in CNKI. These databases were selected because they are credible platforms that are sources of scholarly and peer-reviewed information with advanced search tools and contain literature relevant to the subject of our topic from reliable researchers and experts. The search string with the Boolean operator used in the Web of Science was “TS = (((“critical thinking” or “ct” and “pretest” or “posttest”) or (“critical thinking” or “ct” and “control group” or “quasi experiment” or “experiment”)) and (“collaboration” or “collaborative learning” or “CSCL”) and (“problem solving” or “problem-based learning” or “PBL”))”. The research area was “Education Educational Research”, and the search period was “January 1, 2000, to December 30, 2021”. A total of 412 papers were obtained. The search string with the Boolean operator used in the CNKI was “SU = (‘critical thinking’*‘collaboration’ + ‘critical thinking’*‘collaborative learning’ + ‘critical thinking’*‘CSCL’ + ‘critical thinking’*‘problem solving’ + ‘critical thinking’*‘problem-based learning’ + ‘critical thinking’*‘PBL’ + ‘critical thinking’*‘problem oriented’) AND FT = (‘experiment’ + ‘quasi experiment’ + ‘pretest’ + ‘posttest’ + ‘empirical study’)” (translated into Chinese when searching). A total of 56 studies were found throughout the search period of “January 2000 to December 2021”. From the databases, all duplicates and retractions were eliminated before exporting the references into Endnote, a program for managing bibliographic references. In all, 466 studies were found.

Second, the studies that matched the inclusion and exclusion criteria for the meta-analysis were chosen by two researchers after they had reviewed the abstracts and titles of the gathered articles, yielding a total of 126 studies.

Third, two researchers thoroughly reviewed each included article’s whole text in accordance with the inclusion and exclusion criteria. Meanwhile, a snowball search was performed using the references and citations of the included articles to ensure complete coverage of the articles. Ultimately, 36 articles were kept.

Two researchers worked together to carry out this entire process, and a consensus rate of almost 94.7% was reached after discussion and negotiation to clarify any emerging differences.

Eligibility criteria

Since not all the retrieved studies matched the criteria for this meta-analysis, eligibility criteria for both inclusion and exclusion were developed as follows:

The publication language of the included studies was limited to English and Chinese, and the full text could be obtained. Articles that did not meet the publication language and articles not published between 2000 and 2021 were excluded.

The research design of the included studies must be empirical and quantitative studies that can assess the effect of collaborative problem-solving on the development of critical thinking. Articles that could not identify the causal mechanisms by which collaborative problem-solving affects critical thinking, such as review articles and theoretical articles, were excluded.

The research method of the included studies must feature a randomized control experiment or a quasi-experiment, or a natural experiment, which have a higher degree of internal validity with strong experimental designs and can all plausibly provide evidence that critical thinking and collaborative problem-solving are causally related. Articles with non-experimental research methods, such as purely correlational or observational studies, were excluded.

The participants of the included studies were only students in school, including K-12 students and college students. Articles in which the participants were non-school students, such as social workers or adult learners, were excluded.

The research results of the included studies must mention definite signs that may be utilized to gauge critical thinking’s impact (e.g., sample size, mean value, or standard deviation). Articles that lacked specific measurement indicators for critical thinking and could not calculate the effect size were excluded.

Data coding design

In order to perform a meta-analysis, it is necessary to collect the most important information from the articles, codify that information’s properties, and convert descriptive data into quantitative data. Therefore, this study designed a data coding template (see Table 1 ). Ultimately, 16 coding fields were retained.

The designed data-coding template consisted of three pieces of information. Basic information about the papers was included in the descriptive information: the publishing year, author, serial number, and title of the paper.

The variable information for the experimental design had three variables: the independent variable (instruction method), the dependent variable (critical thinking), and the moderating variable (learning stage, teaching type, intervention duration, learning scaffold, group size, measuring tool, and subject area). Depending on the topic of this study, the intervention strategy, as the independent variable, was coded into collaborative and non-collaborative problem-solving. The dependent variable, critical thinking, was coded as a cognitive skill and an attitudinal tendency. And seven moderating variables were created by grouping and combining the experimental design variables discovered within the 36 studies (see Table 1 ), where learning stages were encoded as higher education, high school, middle school, and primary school or lower; teaching types were encoded as mixed courses, integrated courses, and independent courses; intervention durations were encoded as 0–1 weeks, 1–4 weeks, 4–12 weeks, and more than 12 weeks; group sizes were encoded as 2–3 persons, 4–6 persons, 7–10 persons, and more than 10 persons; learning scaffolds were encoded as teacher-supported learning scaffold, technique-supported learning scaffold, and resource-supported learning scaffold; measuring tools were encoded as standardized measurement tools (e.g., WGCTA, CCTT, CCTST, and CCTDI) and self-adapting measurement tools (e.g., modified or made by researchers); and subject areas were encoded according to the specific subjects used in the 36 included studies.

The data information contained three metrics for measuring critical thinking: sample size, average value, and standard deviation. It is vital to remember that studies with various experimental designs frequently adopt various formulas to determine the effect size. And this paper used Morris’ proposed standardized mean difference (SMD) calculation formula ( 2008 , p. 369; see Supplementary Table S3 ).

Procedure for extracting and coding data

According to the data coding template (see Table 1 ), the 36 papers’ information was retrieved by two researchers, who then entered them into Excel (see Supplementary Table S1 ). The results of each study were extracted separately in the data extraction procedure if an article contained numerous studies on critical thinking, or if a study assessed different critical thinking dimensions. For instance, Tiwari et al. ( 2010 ) used four time points, which were viewed as numerous different studies, to examine the outcomes of critical thinking, and Chen ( 2013 ) included the two outcome variables of attitudinal tendency and cognitive skills, which were regarded as two studies. After discussion and negotiation during data extraction, the two researchers’ consistency test coefficients were roughly 93.27%. Supplementary Table S2 details the key characteristics of the 36 included articles with 79 effect quantities, including descriptive information (e.g., the publishing year, author, serial number, and title of the paper), variable information (e.g., independent variables, dependent variables, and moderating variables), and data information (e.g., mean values, standard deviations, and sample size). Following that, testing for publication bias and heterogeneity was done on the sample data using the Rev-Man 5.4 software, and then the test results were used to conduct a meta-analysis.

Publication bias test

When the sample of studies included in a meta-analysis does not accurately reflect the general status of research on the relevant subject, publication bias is said to be exhibited in this research. The reliability and accuracy of the meta-analysis may be impacted by publication bias. Due to this, the meta-analysis needs to check the sample data for publication bias (Stewart et al., 2006 ). A popular method to check for publication bias is the funnel plot; and it is unlikely that there will be publishing bias when the data are equally dispersed on either side of the average effect size and targeted within the higher region. The data are equally dispersed within the higher portion of the efficient zone, consistent with the funnel plot connected with this analysis (see Fig. 2 ), indicating that publication bias is unlikely in this situation.

This funnel plot shows the result of publication bias of 79 effect quantities across 36 studies.

Heterogeneity test

To select the appropriate effect models for the meta-analysis, one might use the results of a heterogeneity test on the data effect sizes. In a meta-analysis, it is common practice to gauge the degree of data heterogeneity using the I 2 value, and I 2  ≥ 50% is typically understood to denote medium-high heterogeneity, which calls for the adoption of a random effect model; if not, a fixed effect model ought to be applied (Lipsey and Wilson, 2001 ). The findings of the heterogeneity test in this paper (see Table 2 ) revealed that I 2 was 86% and displayed significant heterogeneity ( P  < 0.01). To ensure accuracy and reliability, the overall effect size ought to be calculated utilizing the random effect model.

The analysis of the overall effect size

This meta-analysis utilized a random effect model to examine 79 effect quantities from 36 studies after eliminating heterogeneity. In accordance with Cohen’s criterion (Cohen, 1992 ), it is abundantly clear from the analysis results, which are shown in the forest plot of the overall effect (see Fig. 3 ), that the cumulative impact size of cooperative problem-solving is 0.82, which is statistically significant ( z  = 12.78, P  < 0.01, 95% CI [0.69, 0.95]), and can encourage learners to practice critical thinking.

This forest plot shows the analysis result of the overall effect size across 36 studies.

In addition, this study examined two distinct dimensions of critical thinking to better understand the precise contributions that collaborative problem-solving makes to the growth of critical thinking. The findings (see Table 3 ) indicate that collaborative problem-solving improves cognitive skills (ES = 0.70) and attitudinal tendency (ES = 1.17), with significant intergroup differences (chi 2  = 7.95, P  < 0.01). Although collaborative problem-solving improves both dimensions of critical thinking, it is essential to point out that the improvements in students’ attitudinal tendency are much more pronounced and have a significant comprehensive effect (ES = 1.17, z  = 7.62, P  < 0.01, 95% CI [0.87, 1.47]), whereas gains in learners’ cognitive skill are slightly improved and are just above average. (ES = 0.70, z  = 11.55, P  < 0.01, 95% CI [0.58, 0.82]).

The analysis of moderator effect size

The whole forest plot’s 79 effect quantities underwent a two-tailed test, which revealed significant heterogeneity ( I 2  = 86%, z  = 12.78, P  < 0.01), indicating differences between various effect sizes that may have been influenced by moderating factors other than sampling error. Therefore, exploring possible moderating factors that might produce considerable heterogeneity was done using subgroup analysis, such as the learning stage, learning scaffold, teaching type, group size, duration of the intervention, measuring tool, and the subject area included in the 36 experimental designs, in order to further explore the key factors that influence critical thinking. The findings (see Table 4 ) indicate that various moderating factors have advantageous effects on critical thinking. In this situation, the subject area (chi 2  = 13.36, P  < 0.05), group size (chi 2  = 8.77, P  < 0.05), intervention duration (chi 2  = 12.18, P  < 0.01), learning scaffold (chi 2  = 9.03, P  < 0.01), and teaching type (chi 2  = 7.20, P  < 0.05) are all significant moderators that can be applied to support the cultivation of critical thinking. However, since the learning stage and the measuring tools did not significantly differ among intergroup (chi 2  = 3.15, P  = 0.21 > 0.05, and chi 2  = 0.08, P  = 0.78 > 0.05), we are unable to explain why these two factors are crucial in supporting the cultivation of critical thinking in the context of collaborative problem-solving. These are the precise outcomes, as follows:

Various learning stages influenced critical thinking positively, without significant intergroup differences (chi 2  = 3.15, P  = 0.21 > 0.05). High school was first on the list of effect sizes (ES = 1.36, P  < 0.01), then higher education (ES = 0.78, P  < 0.01), and middle school (ES = 0.73, P  < 0.01). These results show that, despite the learning stage’s beneficial influence on cultivating learners’ critical thinking, we are unable to explain why it is essential for cultivating critical thinking in the context of collaborative problem-solving.

Different teaching types had varying degrees of positive impact on critical thinking, with significant intergroup differences (chi 2  = 7.20, P  < 0.05). The effect size was ranked as follows: mixed courses (ES = 1.34, P  < 0.01), integrated courses (ES = 0.81, P  < 0.01), and independent courses (ES = 0.27, P  < 0.01). These results indicate that the most effective approach to cultivate critical thinking utilizing collaborative problem solving is through the teaching type of mixed courses.

Various intervention durations significantly improved critical thinking, and there were significant intergroup differences (chi 2  = 12.18, P  < 0.01). The effect sizes related to this variable showed a tendency to increase with longer intervention durations. The improvement in critical thinking reached a significant level (ES = 0.85, P  < 0.01) after more than 12 weeks of training. These findings indicate that the intervention duration and critical thinking’s impact are positively correlated, with a longer intervention duration having a greater effect.

Different learning scaffolds influenced critical thinking positively, with significant intergroup differences (chi 2  = 9.03, P  < 0.01). The resource-supported learning scaffold (ES = 0.69, P  < 0.01) acquired a medium-to-higher level of impact, the technique-supported learning scaffold (ES = 0.63, P  < 0.01) also attained a medium-to-higher level of impact, and the teacher-supported learning scaffold (ES = 0.92, P  < 0.01) displayed a high level of significant impact. These results show that the learning scaffold with teacher support has the greatest impact on cultivating critical thinking.

Various group sizes influenced critical thinking positively, and the intergroup differences were statistically significant (chi 2  = 8.77, P  < 0.05). Critical thinking showed a general declining trend with increasing group size. The overall effect size of 2–3 people in this situation was the biggest (ES = 0.99, P  < 0.01), and when the group size was greater than 7 people, the improvement in critical thinking was at the lower-middle level (ES < 0.5, P  < 0.01). These results show that the impact on critical thinking is positively connected with group size, and as group size grows, so does the overall impact.

Various measuring tools influenced critical thinking positively, with significant intergroup differences (chi 2  = 0.08, P  = 0.78 > 0.05). In this situation, the self-adapting measurement tools obtained an upper-medium level of effect (ES = 0.78), whereas the complete effect size of the standardized measurement tools was the largest, achieving a significant level of effect (ES = 0.84, P  < 0.01). These results show that, despite the beneficial influence of the measuring tool on cultivating critical thinking, we are unable to explain why it is crucial in fostering the growth of critical thinking by utilizing the approach of collaborative problem-solving.

Different subject areas had a greater impact on critical thinking, and the intergroup differences were statistically significant (chi 2  = 13.36, P  < 0.05). Mathematics had the greatest overall impact, achieving a significant level of effect (ES = 1.68, P  < 0.01), followed by science (ES = 1.25, P  < 0.01) and medical science (ES = 0.87, P  < 0.01), both of which also achieved a significant level of effect. Programming technology was the least effective (ES = 0.39, P  < 0.01), only having a medium-low degree of effect compared to education (ES = 0.72, P  < 0.01) and other fields (such as language, art, and social sciences) (ES = 0.58, P  < 0.01). These results suggest that scientific fields (e.g., mathematics, science) may be the most effective subject areas for cultivating critical thinking utilizing the approach of collaborative problem-solving.

The effectiveness of collaborative problem solving with regard to teaching critical thinking

According to this meta-analysis, using collaborative problem-solving as an intervention strategy in critical thinking teaching has a considerable amount of impact on cultivating learners’ critical thinking as a whole and has a favorable promotional effect on the two dimensions of critical thinking. According to certain studies, collaborative problem solving, the most frequently used critical thinking teaching strategy in curriculum instruction can considerably enhance students’ critical thinking (e.g., Liang et al., 2017 ; Liu et al., 2020 ; Cindy, 2004 ). This meta-analysis provides convergent data support for the above research views. Thus, the findings of this meta-analysis not only effectively address the first research query regarding the overall effect of cultivating critical thinking and its impact on the two dimensions of critical thinking (i.e., attitudinal tendency and cognitive skills) utilizing the approach of collaborative problem-solving, but also enhance our confidence in cultivating critical thinking by using collaborative problem-solving intervention approach in the context of classroom teaching.

Furthermore, the associated improvements in attitudinal tendency are much stronger, but the corresponding improvements in cognitive skill are only marginally better. According to certain studies, cognitive skill differs from the attitudinal tendency in classroom instruction; the cultivation and development of the former as a key ability is a process of gradual accumulation, while the latter as an attitude is affected by the context of the teaching situation (e.g., a novel and exciting teaching approach, challenging and rewarding tasks) (Halpern, 2001 ; Wei and Hong, 2022 ). Collaborative problem-solving as a teaching approach is exciting and interesting, as well as rewarding and challenging; because it takes the learners as the focus and examines problems with poor structure in real situations, and it can inspire students to fully realize their potential for problem-solving, which will significantly improve their attitudinal tendency toward solving problems (Liu et al., 2020 ). Similar to how collaborative problem-solving influences attitudinal tendency, attitudinal tendency impacts cognitive skill when attempting to solve a problem (Liu et al., 2020 ; Zhang et al., 2022 ), and stronger attitudinal tendencies are associated with improved learning achievement and cognitive ability in students (Sison, 2008 ; Zhang et al., 2022 ). It can be seen that the two specific dimensions of critical thinking as well as critical thinking as a whole are affected by collaborative problem-solving, and this study illuminates the nuanced links between cognitive skills and attitudinal tendencies with regard to these two dimensions of critical thinking. To fully develop students’ capacity for critical thinking, future empirical research should pay closer attention to cognitive skills.

The moderating effects of collaborative problem solving with regard to teaching critical thinking

In order to further explore the key factors that influence critical thinking, exploring possible moderating effects that might produce considerable heterogeneity was done using subgroup analysis. The findings show that the moderating factors, such as the teaching type, learning stage, group size, learning scaffold, duration of the intervention, measuring tool, and the subject area included in the 36 experimental designs, could all support the cultivation of collaborative problem-solving in critical thinking. Among them, the effect size differences between the learning stage and measuring tool are not significant, which does not explain why these two factors are crucial in supporting the cultivation of critical thinking utilizing the approach of collaborative problem-solving.

In terms of the learning stage, various learning stages influenced critical thinking positively without significant intergroup differences, indicating that we are unable to explain why it is crucial in fostering the growth of critical thinking.

Although high education accounts for 70.89% of all empirical studies performed by researchers, high school may be the appropriate learning stage to foster students’ critical thinking by utilizing the approach of collaborative problem-solving since it has the largest overall effect size. This phenomenon may be related to student’s cognitive development, which needs to be further studied in follow-up research.

With regard to teaching type, mixed course teaching may be the best teaching method to cultivate students’ critical thinking. Relevant studies have shown that in the actual teaching process if students are trained in thinking methods alone, the methods they learn are isolated and divorced from subject knowledge, which is not conducive to their transfer of thinking methods; therefore, if students’ thinking is trained only in subject teaching without systematic method training, it is challenging to apply to real-world circumstances (Ruggiero, 2012 ; Hu and Liu, 2015 ). Teaching critical thinking as mixed course teaching in parallel to other subject teachings can achieve the best effect on learners’ critical thinking, and explicit critical thinking instruction is more effective than less explicit critical thinking instruction (Bensley and Spero, 2014 ).

In terms of the intervention duration, with longer intervention times, the overall effect size shows an upward tendency. Thus, the intervention duration and critical thinking’s impact are positively correlated. Critical thinking, as a key competency for students in the 21st century, is difficult to get a meaningful improvement in a brief intervention duration. Instead, it could be developed over a lengthy period of time through consistent teaching and the progressive accumulation of knowledge (Halpern, 2001 ; Hu and Liu, 2015 ). Therefore, future empirical studies ought to take these restrictions into account throughout a longer period of critical thinking instruction.

With regard to group size, a group size of 2–3 persons has the highest effect size, and the comprehensive effect size decreases with increasing group size in general. This outcome is in line with some research findings; as an example, a group composed of two to four members is most appropriate for collaborative learning (Schellens and Valcke, 2006 ). However, the meta-analysis results also indicate that once the group size exceeds 7 people, small groups cannot produce better interaction and performance than large groups. This may be because the learning scaffolds of technique support, resource support, and teacher support improve the frequency and effectiveness of interaction among group members, and a collaborative group with more members may increase the diversity of views, which is helpful to cultivate critical thinking utilizing the approach of collaborative problem-solving.

With regard to the learning scaffold, the three different kinds of learning scaffolds can all enhance critical thinking. Among them, the teacher-supported learning scaffold has the largest overall effect size, demonstrating the interdependence of effective learning scaffolds and collaborative problem-solving. This outcome is in line with some research findings; as an example, a successful strategy is to encourage learners to collaborate, come up with solutions, and develop critical thinking skills by using learning scaffolds (Reiser, 2004 ; Xu et al., 2022 ); learning scaffolds can lower task complexity and unpleasant feelings while also enticing students to engage in learning activities (Wood et al., 2006 ); learning scaffolds are designed to assist students in using learning approaches more successfully to adapt the collaborative problem-solving process, and the teacher-supported learning scaffolds have the greatest influence on critical thinking in this process because they are more targeted, informative, and timely (Xu et al., 2022 ).

With respect to the measuring tool, despite the fact that standardized measurement tools (such as the WGCTA, CCTT, and CCTST) have been acknowledged as trustworthy and effective by worldwide experts, only 54.43% of the research included in this meta-analysis adopted them for assessment, and the results indicated no intergroup differences. These results suggest that not all teaching circumstances are appropriate for measuring critical thinking using standardized measurement tools. “The measuring tools for measuring thinking ability have limits in assessing learners in educational situations and should be adapted appropriately to accurately assess the changes in learners’ critical thinking.”, according to Simpson and Courtney ( 2002 , p. 91). As a result, in order to more fully and precisely gauge how learners’ critical thinking has evolved, we must properly modify standardized measuring tools based on collaborative problem-solving learning contexts.

With regard to the subject area, the comprehensive effect size of science departments (e.g., mathematics, science, medical science) is larger than that of language arts and social sciences. Some recent international education reforms have noted that critical thinking is a basic part of scientific literacy. Students with scientific literacy can prove the rationality of their judgment according to accurate evidence and reasonable standards when they face challenges or poorly structured problems (Kyndt et al., 2013 ), which makes critical thinking crucial for developing scientific understanding and applying this understanding to practical problem solving for problems related to science, technology, and society (Yore et al., 2007 ).

Suggestions for critical thinking teaching

Other than those stated in the discussion above, the following suggestions are offered for critical thinking instruction utilizing the approach of collaborative problem-solving.

First, teachers should put a special emphasis on the two core elements, which are collaboration and problem-solving, to design real problems based on collaborative situations. This meta-analysis provides evidence to support the view that collaborative problem-solving has a strong synergistic effect on promoting students’ critical thinking. Asking questions about real situations and allowing learners to take part in critical discussions on real problems during class instruction are key ways to teach critical thinking rather than simply reading speculative articles without practice (Mulnix, 2012 ). Furthermore, the improvement of students’ critical thinking is realized through cognitive conflict with other learners in the problem situation (Yang et al., 2008 ). Consequently, it is essential for teachers to put a special emphasis on the two core elements, which are collaboration and problem-solving, and design real problems and encourage students to discuss, negotiate, and argue based on collaborative problem-solving situations.

Second, teachers should design and implement mixed courses to cultivate learners’ critical thinking, utilizing the approach of collaborative problem-solving. Critical thinking can be taught through curriculum instruction (Kuncel, 2011 ; Leng and Lu, 2020 ), with the goal of cultivating learners’ critical thinking for flexible transfer and application in real problem-solving situations. This meta-analysis shows that mixed course teaching has a highly substantial impact on the cultivation and promotion of learners’ critical thinking. Therefore, teachers should design and implement mixed course teaching with real collaborative problem-solving situations in combination with the knowledge content of specific disciplines in conventional teaching, teach methods and strategies of critical thinking based on poorly structured problems to help students master critical thinking, and provide practical activities in which students can interact with each other to develop knowledge construction and critical thinking utilizing the approach of collaborative problem-solving.

Third, teachers should be more trained in critical thinking, particularly preservice teachers, and they also should be conscious of the ways in which teachers’ support for learning scaffolds can promote critical thinking. The learning scaffold supported by teachers had the greatest impact on learners’ critical thinking, in addition to being more directive, targeted, and timely (Wood et al., 2006 ). Critical thinking can only be effectively taught when teachers recognize the significance of critical thinking for students’ growth and use the proper approaches while designing instructional activities (Forawi, 2016 ). Therefore, with the intention of enabling teachers to create learning scaffolds to cultivate learners’ critical thinking utilizing the approach of collaborative problem solving, it is essential to concentrate on the teacher-supported learning scaffolds and enhance the instruction for teaching critical thinking to teachers, especially preservice teachers.

Implications and limitations

There are certain limitations in this meta-analysis, but future research can correct them. First, the search languages were restricted to English and Chinese, so it is possible that pertinent studies that were written in other languages were overlooked, resulting in an inadequate number of articles for review. Second, these data provided by the included studies are partially missing, such as whether teachers were trained in the theory and practice of critical thinking, the average age and gender of learners, and the differences in critical thinking among learners of various ages and genders. Third, as is typical for review articles, more studies were released while this meta-analysis was being done; therefore, it had a time limit. With the development of relevant research, future studies focusing on these issues are highly relevant and needed.

Conclusions

The subject of the magnitude of collaborative problem-solving’s impact on fostering students’ critical thinking, which received scant attention from other studies, was successfully addressed by this study. The question of the effectiveness of collaborative problem-solving in promoting students’ critical thinking was addressed in this study, which addressed a topic that had gotten little attention in earlier research. The following conclusions can be made:

Regarding the results obtained, collaborative problem solving is an effective teaching approach to foster learners’ critical thinking, with a significant overall effect size (ES = 0.82, z  = 12.78, P  < 0.01, 95% CI [0.69, 0.95]). With respect to the dimensions of critical thinking, collaborative problem-solving can significantly and effectively improve students’ attitudinal tendency, and the comprehensive effect is significant (ES = 1.17, z  = 7.62, P  < 0.01, 95% CI [0.87, 1.47]); nevertheless, it falls short in terms of improving students’ cognitive skills, having only an upper-middle impact (ES = 0.70, z  = 11.55, P  < 0.01, 95% CI [0.58, 0.82]).

As demonstrated by both the results and the discussion, there are varying degrees of beneficial effects on students’ critical thinking from all seven moderating factors, which were found across 36 studies. In this context, the teaching type (chi 2  = 7.20, P  < 0.05), intervention duration (chi 2  = 12.18, P  < 0.01), subject area (chi 2  = 13.36, P  < 0.05), group size (chi 2  = 8.77, P  < 0.05), and learning scaffold (chi 2  = 9.03, P  < 0.01) all have a positive impact on critical thinking, and they can be viewed as important moderating factors that affect how critical thinking develops. Since the learning stage (chi 2  = 3.15, P  = 0.21 > 0.05) and measuring tools (chi 2  = 0.08, P  = 0.78 > 0.05) did not demonstrate any significant intergroup differences, we are unable to explain why these two factors are crucial in supporting the cultivation of critical thinking in the context of collaborative problem-solving.

Data availability

All data generated or analyzed during this study are included within the article and its supplementary information files, and the supplementary information files are available in the Dataverse repository: https://doi.org/10.7910/DVN/IPFJO6 .

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Acknowledgements

This research was supported by the graduate scientific research and innovation project of Xinjiang Uygur Autonomous Region named “Research on in-depth learning of high school information technology courses for the cultivation of computing thinking” (No. XJ2022G190) and the independent innovation fund project for doctoral students of the College of Educational Science of Xinjiang Normal University named “Research on project-based teaching of high school information technology courses from the perspective of discipline core literacy” (No. XJNUJKYA2003).

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Xu, E., Wang, W. & Wang, Q. The effectiveness of collaborative problem solving in promoting students’ critical thinking: A meta-analysis based on empirical literature. Humanit Soc Sci Commun 10 , 16 (2023). https://doi.org/10.1057/s41599-023-01508-1

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Engaging learners in the excitement of science, helping them discover the value of evidence-based reasoning and higher-order cognitive skills, and teaching them to become creative problem solvers have long been goals of science education reformers. But the means to achieve these goals, especially methods to promote creative thinking in scientific problem solving, have not become widely known or used. In this essay, I review the evidence that creativity is not a single hard-to-measure property. The creative process can be explained by reference to increasingly well-understood cognitive skills such as cognitive flexibility and inhibitory control that are widely distributed in the population. I explore the relationship between creativity and the higher-order cognitive skills, review assessment methods, and describe several instructional strategies for enhancing creative problem solving in the college classroom. Evidence suggests that instruction to support the development of creativity requires inquiry-based teaching that includes explicit strategies to promote cognitive flexibility. Students need to be repeatedly reminded and shown how to be creative, to integrate material across subject areas, to question their own assumptions, and to imagine other viewpoints and possibilities. Further research is required to determine whether college students' learning will be enhanced by these measures.

INTRODUCTION

Dr. Dunne paces in front of his section of first-year college students, today not as their Bio 110 teacher but in the role of facilitator in their monthly “invention session.” For this meeting, the topic is stem cell therapy in heart disease. Members of each team of four students have primed themselves on the topic by reading selected articles from accessible sources such as Science, Nature, and Scientific American, and searching the World Wide Web, triangulating for up-to-date, accurate, background information. Each team knows that their first goal is to define a set of problems or limitations to overcome within the topic and to begin to think of possible solutions. Dr. Dunne starts the conversation by reminding the group of the few ground rules: one speaker at a time, listen carefully and have respect for others' ideas, question your own and others' assumptions, focus on alternative paths or solutions, maintain an atmosphere of collaboration and mutual support. He then sparks the discussion by asking one of the teams to describe a problem in need of solution.

Science in the United States is widely credited as a major source of discovery and economic development. According to the 2005 TAP Report produced by a prominent group of corporate leaders, “To maintain our country's competitiveness in the twenty-first century, we must cultivate the skilled scientists and engineers needed to create tomorrow's innovations.” ( www.tap2015.org/about/TAP_report2.pdf ). A panel of scientists, engineers, educators, and policy makers convened by the National Research Council (NRC) concurred with this view, reporting that the vitality of the nation “is derived in large part from the productivity of well-trained people and the steady stream of scientific and technical innovations they produce” ( NRC, 2007 ).

For many decades, science education reformers have promoted the idea that learners should be engaged in the excitement of science; they should be helped to discover the value of evidence-based reasoning and higher-order cognitive skills, and be taught to become innovative problem solvers (for reviews, see DeHaan, 2005 ; Hake, 2005 ; Nelson, 2008 ; Perkins and Wieman, 2008 ). But the means to achieve these goals, especially methods to promote creative thinking in scientific problem solving, are not widely known or used. An invention session such as that led by the fictional Dr. Dunne, described above, may seem fanciful as a means of teaching students to think about science as something more than a body of facts and terms to memorize. In recent years, however, models for promoting creative problem solving were developed for classroom use, as detailed by Treffinger and Isaksen (2005) , and such techniques are often used in the real world of high technology. To promote imaginative thinking, the advertising executive Alex F. Osborn invented brainstorming ( Osborn, 1948 , 1979 ), a technique that has since been successful in stimulating inventiveness among engineers and scientists. Could such strategies be transferred to a class for college students? Could they serve as a supplement to a high-quality, scientific teaching curriculum that helps students learn the facts and conceptual frameworks of science and make progress along the novice–expert continuum? Could brainstorming or other instructional strategies that are specifically designed to promote creativity teach students to be more adaptive in their growing expertise, more innovative in their problem-solving abilities? To begin to answer those questions, we first need to understand what is meant by “creativity.”

What Is Creativity? Big-C versus Mini-C Creativity

How to define creativity is an age-old question. Justice Potter Stewart's famous dictum regarding obscenity “I know it when I see it” has also long been an accepted test of creativity. But this is not an adequate criterion for developing an instructional approach. A scientist colleague of mine recently noted that “Many of us [in the scientific community] rarely give the creative process a second thought, imagining one either ‘has it’ or doesn't.” We often think of inventiveness or creativity in scientific fields as the kind of gift associated with a Michelangelo or Einstein. This is what Kaufman and Beghetto (2008) call big-C creativity, borrowing the term that earlier workers applied to the talents of experts in various fields who were identified as particularly creative by their expert colleagues ( MacKinnon, 1978 ). In this sense, creativity is seen as the ability of individuals to generate new ideas that contribute substantially to an intellectual domain. Howard Gardner defined such a creative person as one who “regularly solves problems, fashions products, or defines new questions in a domain in a way that is initially considered novel but that ultimately comes to be accepted in a particular cultural setting” ( Gardner, 1993 , p. 35).

But there is another level of inventiveness termed by various authors as “little-c” ( Craft, 2000 ) or “mini-c” ( Kaufman and Beghetto, 2008 ) creativity that is widespread among all populations. This would be consistent with the workplace definition of creativity offered by Amabile and her coworkers: “coming up with fresh ideas for changing products, services and processes so as to better achieve the organization's goals” ( Amabile et al. , 2005 ). Mini-c creativity is based on what Craft calls “possibility thinking” ( Craft, 2000 , pp. 3–4), as experienced when a worker suddenly has the insight to visualize a new, improved way to accomplish a task; it is represented by the “aha” moment when a student first sees two previously disparate concepts or facts in a new relationship, an example of what Arthur Koestler identified as bisociation: “perceiving a situation or event in two habitually incompatible associative contexts” ( Koestler, 1964 , p. 95).

In this essay, I maintain that mini-c creativity is not a mysterious, innate endowment of rare individuals. Instead, I argue that creative thinking is a multicomponent process, mediated through social interactions, that can be explained by reference to increasingly well-understood mental abilities such as cognitive flexibility and cognitive control that are widely distributed in the population. Moreover, I explore some of the recent research evidence (though with no effort at a comprehensive literature review) showing that these mental abilities are teachable; like other higher-order cognitive skills (HOCS), they can be enhanced by explicit instruction.

Creativity Is a Multicomponent Process

Efforts to define creativity in psychological terms go back to J. P. Guilford ( Guilford, 1950 ) and E. P. Torrance ( Torrance, 1974 ), both of whom recognized that underlying the construct were other cognitive variables such as ideational fluency, originality of ideas, and sensitivity to missing elements. Many authors since then have extended the argument that a creative act is not a singular event but a process, an interplay among several interactive cognitive and affective elements. In this view, the creative act has two phases, a generative and an exploratory or evaluative phase ( Finke et al. , 1996 ). During the generative process, the creative mind pictures a set of novel mental models as potential solutions to a problem. In the exploratory phase, we evaluate the multiple options and select the best one. Early scholars of creativity, such as J. P. Guilford, characterized the two phases as divergent thinking and convergent thinking ( Guilford, 1950 ). Guilford defined divergent thinking as the ability to produce a broad range of associations to a given stimulus or to arrive at many solutions to a problem (for overviews of the field from different perspectives, see Amabile, 1996 ; Banaji et al. , 2006 ; Sawyer, 2006 ). In neurocognitive terms, divergent thinking is referred to as associative richness ( Gabora, 2002 ; Simonton, 2004 ), which is often measured experimentally by comparing the number of words that an individual generates from memory in response to stimulus words on a word association test. In contrast, convergent thinking refers to the capacity to quickly focus on the one best solution to a problem.

The idea that there are two stages to the creative process is consistent with results from cognition research indicating that there are two distinct modes of thought, associative and analytical ( Neisser, 1963 ; Sloman, 1996 ). In the associative mode, thinking is defocused, suggestive, and intuitive, revealing remote or subtle connections between items that may be correlated, or may not, and are usually not causally related ( Burton, 2008 ). In the analytical mode, thought is focused and evaluative, more conducive to analyzing relationships of cause and effect (for a review of other cognitive aspects of creativity, see Runco, 2004 ). Science educators associate the analytical mode with the upper levels (analysis, synthesis, and evaluation) of Bloom's taxonomy (e.g., Crowe et al. , 2008 ), or with “critical thinking,” the process that underlies the “purposeful, self-regulatory judgment that drives problem-solving and decision-making” ( Quitadamo et al. , 2008 , p. 328). These modes of thinking are under cognitive control through the executive functions of the brain. The core executive functions, which are thought to underlie all planning, problem solving, and reasoning, are defined ( Blair and Razza, 2007 ) as working memory control (mentally holding and retrieving information), cognitive flexibility (considering multiple ideas and seeing different perspectives), and inhibitory control (resisting several thoughts or actions to focus on one). Readers wishing to delve further into the neuroscience of the creative process can refer to the cerebrocerebellar theory of creativity ( Vandervert et al. , 2007 ) in which these mental activities are described neurophysiologically as arising through interactions among different parts of the brain.

The main point from all of these works is that creativity is not some single hard-to-measure property or act. There is ample evidence that the creative process requires both divergent and convergent thinking and that it can be explained by reference to increasingly well-understood underlying mental abilities ( Haring-Smith, 2006 ; Kim, 2006 ; Sawyer, 2006 ; Kaufman and Sternberg, 2007 ) and cognitive processes ( Simonton, 2004 ; Diamond et al. , 2007 ; Vandervert et al. , 2007 ).

Creativity Is Widely Distributed and Occurs in a Social Context

Although it is understandable to speak of an aha moment as a creative act by the person who experiences it, authorities in the field have long recognized (e.g., Simonton, 1975 ) that creative thinking is not so much an individual trait but rather a social phenomenon involving interactions among people within their specific group or cultural settings. “Creativity isn't just a property of individuals, it is also a property of social groups” ( Sawyer, 2006 , p. 305). Indeed, Osborn introduced his brainstorming method because he was convinced that group creativity is always superior to individual creativity. He drew evidence for this conclusion from activities that demand collaborative output, for example, the improvisations of a jazz ensemble. Although each musician is individually creative during a performance, the novelty and inventiveness of each performer's playing is clearly influenced, and often enhanced, by “social and interactional processes” among the musicians ( Sawyer, 2006 , p. 120). Recently, Brophy (2006) offered evidence that for problem solving, the situation may be more nuanced. He confirmed that groups of interacting individuals were better at solving complex, multipart problems than single individuals. However, when dealing with certain kinds of single-issue problems, individual problem solvers produced a greater number of solutions than interacting groups, and those solutions were judged to be more original and useful.

Consistent with the findings of Brophy (2006) , many scholars acknowledge that creative discoveries in the real world such as solving the problems of cutting-edge science—which are usually complex and multipart—are influenced or even stimulated by social interaction among experts. The common image of the lone scientist in the laboratory experiencing a flash of creative inspiration is probably a myth from earlier days. As a case in point, the science historian Mara Beller analyzed the social processes that underlay some of the major discoveries of early twentieth-century quantum physics. Close examination of successive drafts of publications by members of the Copenhagen group revealed a remarkable degree of influence and collaboration among 10 or more colleagues, although many of these papers were published under the name of a single author ( Beller, 1999 ). Sociologists Bruno Latour and Steve Woolgar's study ( Latour and Woolgar, 1986 ) of a neuroendocrinology laboratory at the Salk Institute for Biological Studies make the related point that social interactions among the participating scientists determined to a remarkable degree what discoveries were made and how they were interpreted. In the laboratory, researchers studied the chemical structure of substances released by the brain. By analysis of the Salk scientists' verbalizations of concepts, theories, formulas, and results of their investigations, Latour and Woolgar showed that the structures and interpretations that were agreed upon, that is, the discoveries announced by the laboratory, were mediated by social interactions and power relationships among members of the laboratory group. By studying the discovery process in other fields of the natural sciences, sociologists and anthropologists have provided more cases that further illustrate how social and cultural dimensions affect scientific insights (for a thoughtful review, see Knorr Cetina, 1995 ).

In sum, when an individual experiences an aha moment that feels like a singular creative act, it may rather have resulted from a multicomponent process, under the influence of group interactions and social context. The process that led up to what may be sensed as a sudden insight will probably have included at least three diverse, but testable elements: 1) divergent thinking, including ideational fluency or cognitive flexibility, which is the cognitive executive function that underlies the ability to visualize and accept many ideas related to a problem; 2) convergent thinking or the application of inhibitory control to focus and mentally evaluate ideas; and 3) analogical thinking, the ability to understand a novel idea in terms of one that is already familiar.

LITERATURE REVIEW

What do we know about how to teach creativity.

The possibility of teaching for creative problem solving gained credence in the 1960s with the studies of Jerome Bruner, who argued that children should be encouraged to “treat a task as a problem for which one invents an answer, rather than finding one out there in a book or on the blackboard” ( Bruner, 1965 , pp. 1013–1014). Since that time, educators and psychologists have devised programs of instruction designed to promote creativity and inventiveness in virtually every student population: pre–K, elementary, high school, and college, as well as in disadvantaged students, athletes, and students in a variety of specific disciplines (for review, see Scott et al. , 2004 ). Smith (1998) identified 172 instructional approaches that have been applied at one time or another to develop divergent thinking skills.

Some of the most convincing evidence that elements of creativity can be enhanced by instruction comes from work with young children. Bodrova and Leong (2001) developed the Tools of the Mind (Tools) curriculum to improve all of the three core mental executive functions involved in creative problem solving: cognitive flexibility, working memory, and inhibitory control. In a year-long randomized study of 5-yr-olds from low-income families in 21 preschool classrooms, half of the teachers applied the districts' balanced literacy curriculum (literacy), whereas the experimenters trained the other half to teach the same academic content by using the Tools curriculum ( Diamond et al. , 2007 ). At the end of the year, when the children were tested with a battery of neurocognitive tests including a test for cognitive flexibility ( Durston et al. , 2003 ; Davidson et al. , 2006 ), those exposed to the Tools curriculum outperformed the literacy children by as much as 25% ( Diamond et al. , 2007 ). Although the Tools curriculum and literacy program were similar in academic content and in many other ways, they differed primarily in that Tools teachers spent 80% of their time explicitly reminding the children to think of alternative ways to solve a problem and building their executive function skills.

Teaching older students to be innovative also demands instruction that explicitly promotes creativity but is rigorously content-rich as well. A large body of research on the differences between novice and expert cognition indicates that creative thinking requires at least a minimal level of expertise and fluency within a knowledge domain ( Bransford et al. , 2000 ; Crawford and Brophy, 2006 ). What distinguishes experts from novices, in addition to their deeper knowledge of the subject, is their recognition of patterns in information, their ability to see relationships among disparate facts and concepts, and their capacity for organizing content into conceptual frameworks or schemata ( Bransford et al. , 2000 ; Sawyer, 2005 ).

Such expertise is often lacking in the traditional classroom. For students attempting to grapple with new subject matter, many kinds of problems that are presented in high school or college courses or that arise in the real world can be solved merely by applying newly learned algorithms or procedural knowledge. With practice, problem solving of this kind can become routine and is often considered to represent mastery of a subject, producing what Sternberg refers to as “pseudoexperts” ( Sternberg, 2003 ). But beyond such routine use of content knowledge the instructor's goal must be to produce students who have gained the HOCS needed to apply, analyze, synthesize, and evaluate knowledge ( Crowe et al. , 2008 ). The aim is to produce students who know enough about a field to grasp meaningful patterns of information, who can readily retrieve relevant knowledge from memory, and who can apply such knowledge effectively to novel problems. This condition is referred to as adaptive expertise ( Hatano and Ouro, 2003 ; Schwartz et al. , 2005 ). Instead of applying already mastered procedures, adaptive experts are able to draw on their knowledge to invent or adapt strategies for solving unique or novel problems within a knowledge domain. They are also able, ideally, to transfer conceptual frameworks and schemata from one domain to another (e.g., Schwartz et al. , 2005 ). Such flexible, innovative application of knowledge is what results in inventive or creative solutions to problems ( Crawford and Brophy, 2006 ; Crawford, 2007 ).

Promoting Creative Problem Solving in the College Classroom

In most college courses, instructors teach science primarily through lectures and textbooks that are dominated by facts and algorithmic processing rather than by concepts, principles, and evidence-based ways of thinking. This is despite ample evidence that many students gain little new knowledge from traditional lectures ( Hrepic et al. , 2007 ). Moreover, it is well documented that these methods engender passive learning rather than active engagement, boredom instead of intellectual excitement, and linear thinking rather than cognitive flexibility (e.g., Halpern and Hakel, 2003 ; Nelson, 2008 ; Perkins and Wieman, 2008 ). Cognitive flexibility, as noted, is one of the three core mental executive functions involved in creative problem solving ( Ausubel, 1963 , 2000 ). The capacity to apply ideas creatively in new contexts, referred to as the ability to “transfer” knowledge (see Mestre, 2005 ), requires that learners have opportunities to actively develop their own representations of information to convert it to a usable form. Especially when a knowledge domain is complex and fraught with ill-structured information, as in a typical introductory college biology course, instruction that emphasizes active-learning strategies is demonstrably more effective than traditional linear teaching in reducing failure rates and in promoting learning and transfer (e.g., Freeman et al. , 2007 ). Furthermore, there is already some evidence that inclusion of creativity training as part of a college curriculum can have positive effects. Hunsaker (2005) has reviewed a number of such studies. He cites work by McGregor (2001) , for example, showing that various creativity training programs including brainstorming and creative problem solving increase student scores on tests of creative-thinking abilities.

Model creativity—students develop creativity when instructors model creative thinking and inventiveness.

Repeatedly encourage idea generation—students need to be reminded to generate their own ideas and solutions in an environment free of criticism.

Cross-fertilize ideas—where possible, avoid teaching in subject-area boxes: a math box, a social studies box, etc; students' creative ideas and insights often result from learning to integrate material across subject areas.

Build self-efficacy—all students have the capacity to create and to experience the joy of having new ideas, but they must be helped to believe in their own capacity to be creative.

Constantly question assumptions—make questioning a part of the daily classroom exchange; it is more important for students to learn what questions to ask and how to ask them than to learn the answers.

Imagine other viewpoints—students broaden their perspectives by learning to reflect upon ideas and concepts from different points of view.

How Is Creativity Related to Critical Thinking and the Higher-Order Cognitive Skills?

It is not uncommon to associate creativity and ingenuity with scientific reasoning ( Sawyer, 2005 ; 2006 ). When instructors apply scientific teaching strategies ( Handelsman et al. , 2004 ; DeHaan, 2005 ; Wood, 2009 ) by using instructional methods based on learning research, according to Ebert-May and Hodder ( 2008 ), “we see students actively engaged in the thinking, creativity, rigor, and experimentation we associate with the practice of science—in much the same way we see students learn in the field and in laboratories” (p. 2). Perkins and Wieman (2008) note that “To be successful innovators in science and engineering, students must develop a deep conceptual understanding of the underlying science ideas, an ability to apply these ideas and concepts broadly in different contexts, and a vision to see their relevance and usefulness in real-world applications … An innovator is able to perceive and realize potential connections and opportunities better than others” (pp. 181–182). The results of Scott et al. (2004) suggest that nontraditional courses in science that are based on constructivist principles and that use strategies of scientific teaching to promote the HOCS and enhance content mastery and dexterity in scientific thinking ( Handelsman et al. , 2007 ; Nelson, 2008 ) also should be effective in promoting creativity and cognitive flexibility if students are explicitly guided to learn these skills.

Creativity is an essential element of problem solving ( Mumford et al. , 1991 ; Runco, 2004 ) and of critical thinking ( Abrami et al. , 2008 ). As such, it is common to think of applications of creativity such as inventiveness and ingenuity among the HOCS as defined in Bloom's taxonomy ( Crowe et al. , 2008 ). Thus, it should come as no surprise that creativity, like other elements of the HOCS, can be taught most effectively through inquiry-based instruction, informed by constructivist theory ( Ausubel, 1963 , 2000 ; Duch et al. , 2001 ; Nelson, 2008 ). In a survey of 103 instructors who taught college courses that included creativity instruction, Bull et al. (1995) asked respondents to rate the importance of various course characteristics for enhancing student creativity. Items ranking high on the list were: providing a social climate in which students feels safe, an open classroom environment that promotes tolerance for ambiguity and independence, the use of humor, metaphorical thinking, and problem defining. Many of the responses emphasized the same strategies as those advanced to promote creative problem solving (e.g., Mumford et al. , 1991 ; McFadzean, 2002 ; Treffinger and Isaksen, 2005 ) and critical thinking ( Abrami et al. , 2008 ).

In a careful meta-analysis, Scott et al. (2004) examined 70 instructional interventions designed to enhance and measure creative performance. The results were striking. Courses that stressed techniques such as critical thinking, convergent thinking, and constraint identification produced the largest positive effect sizes. More open techniques that provided less guidance in strategic approaches had less impact on the instructional outcomes. A striking finding was the effectiveness of being explicit; approaches that clearly informed students about the nature of creativity and offered clear strategies for creative thinking were most effective. Approaches such as social modeling, cooperative learning, and case-based (project-based) techniques that required the application of newly acquired knowledge were found to be positively correlated to high effect sizes. The most clear-cut result to emerge from the Scott et al. (2004) study was simply to confirm that creativity instruction can be highly successful in enhancing divergent thinking, problem solving, and imaginative performance. Most importantly, of the various cognitive processes examined, those linked to the generation of new ideas such as problem finding, conceptual combination, and idea generation showed the greatest improvement. The success of creativity instruction, the authors concluded, can be attributed to “developing and providing guidance concerning the application of requisite cognitive capacities … [and] a set of heuristics or strategies for working with already available knowledge” (p. 382).

Many of the scientific teaching practices that have been shown by research to foster content mastery and HOCS, and that are coming more widely into use, also would be consistent with promoting creativity. Wood (2009) has recently reviewed examples of such practices and how to apply them. These include relatively small modifications of the traditional lecture to engender more active learning, such as the use of concept tests and peer instruction ( Mazur, 1996 ), Just-in-Time-Teaching techniques ( Novak et al. , 1999 ), and student response systems known as “clickers” ( Knight and Wood, 2005 ; Crossgrove and Curran, 2008 ), all designed to allow the instructor to frequently and effortlessly elicit and respond to student thinking. Other strategies can transform the lecture hall into a workshop or studio classroom ( Gaffney et al. , 2008 ) where the teaching curriculum may emphasize problem-based (also known as project-based or case-based) learning strategies ( Duch et al. , 2001 ; Ebert-May and Hodder, 2008 ) or “community-based inquiry” in which students engage in research that enhances their critical-thinking skills ( Quitadamo et al. , 2008 ).

Another important approach that could readily subserve explicit creativity instruction is the use of computer-based interactive simulations, or “sims” ( Perkins and Wieman, 2008 ) to facilitate inquiry learning and effective, easy self-assessment. An example in the biological sciences would be Neurons in Action ( http://neuronsinaction.com/home/main ). In such educational environments, students gain conceptual understanding of scientific ideas through interactive engagement with materials (real or virtual), with each other, and with instructors. Following the tenets of scientific teaching, students are encouraged to pose and answer their own questions, to make sense of the materials, and to construct their own understanding. The question I pose here is whether an additional focus—guiding students to meet these challenges in a context that explicitly promotes creativity—would enhance learning and advance students' progress toward adaptive expertise?

Assessment of Creativity

To teach creativity, there must be measurable indicators to judge how much students have gained from instruction. Educational programs intended to teach creativity became popular after the Torrance Tests of Creative Thinking (TTCT) was introduced in the 1960s ( Torrance, 1974 ). But it soon became apparent that there were major problems in devising tests for creativity, both because of the difficulty of defining the construct and because of the number and complexity of elements that underlie it. Tests of intelligence and other personality characteristics on creative individuals revealed a host of related traits such as verbal fluency, metaphorical thinking, flexible decision making, tolerance of ambiguity, willingness to take risks, autonomy, divergent thinking, self-confidence, problem finding, ideational fluency, and belief in oneself as being “creative” ( Barron and Harrington, 1981 ; Tardif and Sternberg, 1988 ; Runco and Nemiro, 1994 ; Snyder et al. , 2004 ). Many of these traits have been the focus of extensive research of recent decades, but, as noted above, creativity is not defined by any one trait; there is now reason to believe that it is the interplay among the cognitive and affective processes that underlie inventiveness and the ability to find novel solutions to a problem.

Although the early creativity researchers recognized that assessing divergent thinking as a measure of creativity required tests for other underlying capacities ( Guilford, 1950 ; Torrance, 1974 ), these workers and their colleagues nonetheless believed that a high score for divergent thinking alone would correlate with real creative output. Unfortunately, no such correlation was shown ( Barron and Harrington, 1981 ). Results produced by many of the instruments initially designed to measure various aspects of creative thinking proved to be highly dependent on the test itself. A review of several hundred early studies showed that an individual's creativity score could be affected by simple test variables, for example, how the verbal pretest instructions were worded ( Barron and Harrington, 1981 , pp. 442–443). Most scholars now agree that divergent thinking, as originally defined, was not an adequate measure of creativity. The process of creative thinking requires a complex combination of elements that include cognitive flexibility, memory control, inhibitory control, and analogical thinking, enabling the mind to free-range and analogize, as well as to focus and test.

More recently, numerous psychometric measures have been developed and empirically tested (see Plucker and Renzulli, 1999 ) that allow more reliable and valid assessment of specific aspects of creativity. For example, the creativity quotient devised by Snyder et al. (2004) tests the ability of individuals to link different ideas and different categories of ideas into a novel synthesis. The Wallach–Kogan creativity test ( Wallach and Kogan, 1965 ) explores the uniqueness of ideas associated with a stimulus. For a more complete list and discussion, see the Creativity Tests website ( www.indiana.edu/∼bobweb/Handout/cretv_6.html ).

The most widely used measure of creativity is the TTCT, which has been modified four times since its original version in 1966 to take into account subsequent research. The TTCT-Verbal and the TTCT-Figural are two versions ( Torrance, 1998 ; see http://ststesting.com/2005giftttct.html ). The TTCT-Verbal consists of five tasks; the “stimulus” for each task is a picture to which the test-taker responds briefly in writing. A sample task that can be viewed from the TTCT Demonstrator website asks, “Suppose that people could transport themselves from place to place with just a wink of the eye or a twitch of the nose. What might be some things that would happen as a result? You have 3 min.” ( www.indiana.edu/∼bobweb/Handout/d3.ttct.htm ).

In the TTCT-Figural, participants are asked to construct a picture from a stimulus in the form of a partial line drawing given on the test sheet (see example below; Figure 1 ). Specific instructions are to “Add lines to the incomplete figures below to make pictures out of them. Try to tell complete stories with your pictures. Give your pictures titles. You have 3 min.” In the introductory materials, test-takers are urged to “… think of a picture or object that no one else will think of. Try to make it tell as complete and as interesting a story as you can …” ( Torrance et al. , 2008 , p. 2).

Figure 1. Sample figural test item from the TTCT Demonstrator website ( www.indiana.edu/∼bobweb/Handout/d3.ttct.htm ).

How would an instructor in a biology course judge the creativity of students' responses to such an item? To assist in this task, the TTCT has scoring and norming guides ( Torrance, 1998 ; Torrance et al. , 2008 ) with numerous samples and responses representing different levels of creativity. The guides show sample evaluations based upon specific indicators such as fluency, originality, elaboration (or complexity), unusual visualization, extending or breaking boundaries, humor, and imagery. These examples are easy to use and provide a high degree of validity and generalizability to the tests. The TTCT has been more intensively researched and analyzed than any other creativity instrument, and the norming samples have longitudinal validations and high predictive validity over a wide age range. In addition to global creativity scores, the TTCT is designed to provide outcome measures in various domains and thematic areas to allow for more insightful analysis ( Kaufman and Baer, 2006 ). Kim (2006) has examined the characteristics of the TTCT, including norms, reliability, and validity, and concludes that the test is an accurate measure of creativity. When properly used, it has been shown to be fair in terms of gender, race, community status, and language background. According to Kim (2006) and other authorities in the field ( McIntyre et al. , 2003 ; Scott et al. , 2004 ), Torrance's research and the development of the TTCT have provided groundwork for the idea that creative levels can be measured and then increased through instruction and practice.

SCIENTIFIC TEACHING TO PROMOTE CREATIVITY

How could creativity instruction be integrated into scientific teaching.

Guidelines for designing specific course units that emphasize HOCS by using strategies of scientific teaching are now available from the current literature. As an example, Karen Cloud-Hansen and colleagues ( Cloud-Hansen et al. , 2008 ) describe a course titled, “Ciprofloxacin Resistance in Neisseria gonorrhoeae .” They developed this undergraduate seminar to introduce college freshmen to important concepts in biology within a real-world context and to increase their content knowledge and critical-thinking skills. The centerpiece of the unit is a case study in which teams of students are challenged to take the role of a director of a local public health clinic. One of the county commissioners overseeing the clinic is an epidemiologist who wants to know “how you plan to address the emergence of ciprofloxacin resistance in Neisseria gonorrhoeae ” (p. 304). State budget cuts limit availability of expensive antibiotics and some laboratory tests to patients. Student teams are challenged to 1) develop a plan to address the medical, economic, and political questions such a clinic director would face in dealing with ciprofloxacin-resistant N. gonorrhoeae ; 2) provide scientific data to support their conclusions; and 3) describe their clinic plan in a one- to two-page referenced written report.

Throughout the 3-wk unit, in accordance with the principles of problem-based instruction ( Duch et al. , 2001 ), course instructors encourage students to seek, interpret, and synthesize their own information to the extent possible. Students have access to a variety of instructional formats, and active-learning experiences are incorporated throughout the unit. These activities are interspersed among minilectures and give the students opportunities to apply new information to their existing base of knowledge. The active-learning activities emphasize the key concepts of the minilectures and directly confront common misconceptions about antibiotic resistance, gene expression, and evolution. Weekly classes include question/answer/discussion sessions to address student misconceptions and 20-min minilectures on such topics as antibiotic resistance, evolution, and the central dogma of molecular biology. Students gather information about antibiotic resistance in N. gonorrhoeae , epidemiology of gonorrhea, and treatment options for the disease, and each team is expected to formulate a plan to address ciprofloxacin resistance in N. gonorrhoeae .

In this project, the authors assessed student gains in terms of content knowledge regarding topics covered such as the role of evolution in antibiotic resistance, mechanisms of gene expression, and the role of oncogenes in human disease. They also measured HOCS as gains in problem solving, according to a rubric that assessed self-reported abilities to communicate ideas logically, solve difficult problems about microbiology, propose hypotheses, analyze data, and draw conclusions. Comparing the pre- and posttests, students reported significant learning of scientific content. Among the thinking skill categories, students demonstrated measurable gains in their ability to solve problems about microbiology but the unit seemed to have little impact on their more general perceived problem-solving skills ( Cloud-Hansen et al. , 2008 ).

What would such a class look like with the addition of explicit creativity-promoting approaches? Would the gains in problem-solving abilities have been greater if during the minilectures and other activities, students had been introduced explicitly to elements of creative thinking from the Sternberg and Williams (1998) list described above? Would the students have reported greater gains if their instructors had encouraged idea generation with weekly brainstorming sessions; if they had reminded students to cross-fertilize ideas by integrating material across subject areas; built self-efficacy by helping students believe in their own capacity to be creative; helped students question their own assumptions; and encouraged students to imagine other viewpoints and possibilities? Of most relevance, could the authors have been more explicit in assessing the originality of the student plans? In an experiment that required college students to develop plans of a different, but comparable, type, Osborn and Mumford (2006) created an originality rubric ( Figure 2 ) that could apply equally to assist instructors in judging student plans in any course. With such modifications, would student gains in problem-solving abilities or other HOCS have been greater? Would their plans have been measurably more imaginative?

Figure 2. Originality rubric (adapted from Osburn and Mumford, 2006 , p. 183).

Answers to these questions can only be obtained when a course like that described by Cloud-Hansen et al. (2008) is taught with explicit instruction in creativity of the type I described above. But, such answers could be based upon more than subjective impressions of the course instructors. For example, students could be pretested with items from the TTCT-Verbal or TTCT-Figural like those shown. If, during minilectures and at every contact with instructors, students were repeatedly reminded and shown how to be as creative as possible, to integrate material across subject areas, to question their own assumptions and imagine other viewpoints and possibilities, would their scores on TTCT posttest items improve? Would the plans they formulated to address ciprofloxacin resistance become more imaginative?

Recall that in their meta-analysis, Scott et al. (2004) found that explicitly informing students about the nature of creativity and offering strategies for creative thinking were the most effective components of instruction. From their careful examination of 70 experimental studies, they concluded that approaches such as social modeling, cooperative learning, and case-based (project-based) techniques that required the application of newly acquired knowledge were positively correlated with high effect sizes. The study was clear in confirming that explicit creativity instruction can be successful in enhancing divergent thinking and problem solving. Would the same strategies work for courses in ecology and environmental biology, as detailed by Ebert-May and Hodder (2008) , or for a unit elaborated by Knight and Wood (2005) that applies classroom response clickers?

Finally, I return to my opening question with the fictional Dr. Dunne. Could a weekly brainstorming “invention session” included in a course like those described here serve as the site where students are introduced to concepts and strategies of creative problem solving? As frequently applied in schools of engineering ( Paulus and Nijstad, 2003 ), brainstorming provides an opportunity for the instructor to pose a problem and to ask the students to suggest as many solutions as possible in a brief period, thus enhancing ideational fluency. Here, students can be encouraged explicitly to build on the ideas of others and to think flexibly. Would brainstorming enhance students' divergent thinking or creative abilities as measured by TTCT items or an originality rubric? Many studies have demonstrated that group interactions such as brainstorming, under the right conditions, can indeed enhance creativity ( Paulus and Nijstad, 2003 ; Scott et al. , 2004 ), but there is little information from an undergraduate science classroom setting. Intellectual Ventures, a firm founded by Nathan Myhrvold, the creator of Microsoft's Research Division, has gathered groups of engineers and scientists around a table for day-long sessions to brainstorm about a prearranged topic. Here, the method seems to work. Since it was founded in 2000, Intellectual Ventures has filed hundreds of patent applications in more than 30 technology areas, applying the “invention session” strategy ( Gladwell, 2008 ). Currently, the company ranks among the top 50 worldwide in number of patent applications filed annually. Whether such a technique could be applied successfully in a college science course will only be revealed by future research.

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• IMPORTANCE OF CREATIVITY IN ENTREPRENEURSHIP 1 January 2017
• Accessing the Finest Minds
• Science and Innovative Thinking for Technical and Organizational Development
• Learning High School Biology in a Social Context Creative Education, Vol. 08, No. 15
• Possibilities and limitations of integrating peer instruction into technical creativity education 6 September 2016 | Instructional Science, Vol. 44, No. 6
• Creative Cognitive Processes in Higher Education 20 November 2014 | The Journal of Creative Behavior, Vol. 50, No. 4
• An Evidence-Based Review of Creative Problem Solving Tools 6 April 2016 | Human Resource Development Review, Vol. 15, No. 2
• Case-based exams for learning and assessment: Experiences in an information systems course
• Case exams for assessing higher order learning: A comparative social media analytics usage exam
• Beyond belief: Structured techniques prove more effective than a placebo intervention in a problem construction task Thinking Skills and Creativity, Vol. 19
• A Belief System at the Core of Learning Science
• Student Research Work and Modeled Situations in Order to Bridge the Gap between Basic Science Concepts and Those from Preventive and Clinical Practice. Meaningful Learning and Informed beneficience Creative Education, Vol. 07, No. 07
• FOSTERING FIFTH GRADERS’ SCIENTIFIC CREATIVITY THROUGH PROBLEM-BASED LEARNING 25 October 2015 | Journal of Baltic Science Education, Vol. 14, No. 5
• Scaffolding for Creative Product Possibilities in a Design-Based STEM Activity 16 November 2014 | Research in Science Education, Vol. 45, No. 5
• Intuition and insight: two concepts that illuminate the tacit in science education 18 June 2015 | Studies in Science Education, Vol. 51, No. 2
• Arts and crafts as adjuncts to STEM education to foster creativity in gifted and talented students 28 March 2015 | Asia Pacific Education Review, Vol. 16, No. 2
• Initiatives Towards an Education for Creativity Procedia - Social and Behavioral Sciences, Vol. 180
• Brian A. Couch ,
• Tanya L. Brown ,
• Tyler J. Schelpat ,
• Mark J. Graham , and
• Jennifer K. Knight
• Michèle Shuster, Monitoring Editor
• Kim Quillin , and
• Stephen Thomas
• Mary Lee Ledbetter, Monitoring Editor
• The Design of IdeaWorks: Applying Social Learning Networks to Support Tertiary Education 21 July 2015
• Video Games and Malevolent Creativity
• Modelling a Laboratory for Ideas as a New Tool for Fostering Engineering Creativity Procedia Engineering, Vol. 100
• “Development of Thinking Skills” Course: Teaching TRIZ in Academic Setting Procedia Engineering, Vol. 131
• Leadership in the Future Experts’ Creativity Development with Scientific Research Activities 4 November 2014
• Developing Deaf Children's Conceptual Understanding and Scientific Argumentation Skills: A Literature Review 3 January 2014 | Deafness & Education International, Vol. 16, No. 3
• Leslie M. Stevens , and
• Sally G. Hoskins
• Nancy Pelaez, Monitoring Editor
• Cortex, Vol. 51
• A Sociotechnological Theory of Discursive Change and Entrepreneurial Capacity: Novelty and Networks SSRN Electronic Journal, Vol. 3
• GEOverse: An Undergraduate Research Journal: Research Dissemination Within and Beyond the Curriculum 1 August 2013
• Learning by Practice, High-Pressure Student Ateliers 2 August 2013
• Relating Inter-Individual Differences in Verbal Creative Thinking to Cerebral Structures: An Optimal Voxel-Based Morphometry Study 5 November 2013 | PLoS ONE, Vol. 8, No. 11
• 21st Century Biology: An Interdisciplinary Approach of Biology, Technology, Engineering and Mathematics Education Procedia - Social and Behavioral Sciences, Vol. 102
• Reclaiming creativity in the era of impact: exploring ideas about creative research in science and engineering Studies in Higher Education, Vol. 38, No. 9
• An Evaluation of Alternative Ways of Computing the Creativity Quotient in a Design School Sample Creativity Research Journal, Vol. 25, No. 3
• A.-M. Hoskinson ,
• M. D. Caballero , and
• J. K. Knight
• Eric Brewe, Monitoring Editor
• Understanding, attitude and environment International Journal for Researcher Development, Vol. 4, No. 1
• Promoting Student Creativity and Inventiveness in Science and Engineering
• Building creative thinking in the classroom: From research to practice International Journal of Educational Research, Vol. 62
• A Demonstration of a Mastery Goal Driven Learning Environment to Foster Creativity in Engineering Design SSRN Electronic Journal, Vol. 111
• The development of creative cognition across adolescence: distinct trajectories for insight and divergent thinking 8 October 2012 | Developmental Science, Vol. 16, No. 1
• A CROSS-NATIONAL STUDY OF PROSPECTIVE ELEMENTARY AND SCIENCE TEACHERS’ CREATIVITY STYLES 10 September 2012 | Journal of Baltic Science Education, Vol. 11, No. 3
• Evaluation of fostering students' creativity in preparing aided recalls for revision courses using electronic revision and recapitulation tools 2.0 Behaviour & Information Technology, Vol. 31, No. 8
• Scientific Creativity: The Missing Ingredient in Slovenian Science Education 15 April 2012 | European Journal of Educational Research, Vol. volume-1-2012, No. volume1-issue2.html
• Could the ‘evolution’ from biology to life sciences prevent ‘extinction’ of the subject field? 6 March 2012 | Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie, Vol. 31, No. 1
• Mobile innovations, executive functions, and educational developments in conflict zones: a case study from Palestine 1 October 2011 | Educational Technology Research and Development, Vol. 60, No. 1
• Informing Pedagogy Through the Brain-Targeted Teaching Model Journal of Microbiology & Biology Education, Vol. 13, No. 1
• Teaching Creative Science Thinking Science, Vol. 334, No. 6062
• Sally G. Hoskins ,
• David Lopatto , and
• Leslie M. Stevens
• Diane K. O'Dowd, Monitoring Editor
• Embedding Research-Based Learning Early in the Undergraduate Geography Curriculum Journal of Geography in Higher Education, Vol. 35, No. 3
• Jared L. Taylor ,
• Karen M. Smith ,
• Adrian P. van Stolk , and
• George B. Spiegelman
• Debra Tomanek, Monitoring Editor
• IFAC Proceedings Volumes, Vol. 43, No. 17
• Critical and Creative Thinking Activities for Engaged Learning in Graphics and Visualization Course
• Creativity Development through Inquiry-Based Learning in Biomedical Sciences

Submitted: 31 December 2008 Revised: 14 May 2009 Accepted: 28 May 2009

© 2009 by The American Society for Cell Biology

Articles on Creative thinking

Displaying all articles.

Human nature can steer people away from new things – and that can blind them to novel threats

Sam Hunter , University of Nebraska Omaha and Gina Scott Ligon , University of Nebraska Omaha

Lockdown schooling: research from around the world shows reasons to be hopeful

Nina Bergdahl , Stockholm University and Melissa Bond , University of South Australia

How businesses need to get creative if they want to survive coronavirus – and any other crisis in future

Julie Clare Roberts , Glasgow Caledonian University

How ‘gamification’ could revolutionise creative thinking in the workplace

Agnessa Spanellis , Heriot-Watt University

What creativity really is - and why schools need it

Liane Gabora , University of British Columbia

Schools will teach ‘soft skills’ from 2017, but assessing them presents a challenge

Bill Lucas , Victoria University

Why the best problem-solvers think with their hands, as well as their heads

Gaëlle Vallée-Tourangeau , Kingston University and Frédéric Vallée-Tourangeau , Kingston University

Help your children play out a story and watch them become more creative

Sandra Russ , Case Western Reserve University

Why make-believe play is an important part of childhood development

Tracy Gleason , Wellesley College

We can’t trust common sense but we can trust science

Peter Ellerton , The University of Queensland

Why politicians don’t want us to think, but opinions are okay

Related topics.

• Adaptability
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Top contributors

Senior Lecturer in Philosophy and Education; Curriculum Director, UQ Critical Thinking Project, The University of Queensland

Professor of Psychology, Wellesley College

International adviser, Mitchell Institute, Victoria University

Distinguished University Professor and Louis D. Beaumont University Professor, Case Western Reserve University

Professor of Behavioural Science, Kingston University

Professor of Psychology, Kingston University

Associate Professor of Psychology and Creative Studies, University of British Columbia

Assistant professor, business management, The University of Edinburgh

Senior Lecturer in Operations and Innovation Management, Glasgow Caledonian University

Director the National Counterterrorism Innovation, Technolology, and Education (NCITE) Center, University of Nebraska Omaha

Professor of Organizational Psychology, University of Nebraska Omaha

Research associate, Department of Computer and Systems Sciences, Stockholm University

Research Fellow, Adjunct Associate Professor, EPPI Reviewer Training & Support Officer, UCL

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