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Problem-Solving Strategies and Obstacles

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Sean is a fact-checker and researcher with experience in sociology, field research, and data analytics.

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From deciding what to eat for dinner to considering whether it's the right time to buy a house, problem-solving is a large part of our daily lives. Learn some of the problem-solving strategies that exist and how to use them in real life, along with ways to overcome obstacles that are making it harder to resolve the issues you face.

What Is Problem-Solving?

In cognitive psychology , the term 'problem-solving' refers to the mental process that people go through to discover, analyze, and solve problems.

A problem exists when there is a goal that we want to achieve but the process by which we will achieve it is not obvious to us. Put another way, there is something that we want to occur in our life, yet we are not immediately certain how to make it happen.

Maybe you want a better relationship with your spouse or another family member but you're not sure how to improve it. Or you want to start a business but are unsure what steps to take. Problem-solving helps you figure out how to achieve these desires.

The problem-solving process involves:

• Discovery of the problem
• Deciding to tackle the issue
• Seeking to understand the problem more fully
• Researching available options or solutions
• Taking action to resolve the issue

Before problem-solving can occur, it is important to first understand the exact nature of the problem itself. If your understanding of the issue is faulty, your attempts to resolve it will also be incorrect or flawed.

Problem-Solving Mental Processes

Several mental processes are at work during problem-solving. Among them are:

• Perceptually recognizing the problem
• Representing the problem in memory
• Considering relevant information that applies to the problem
• Identifying different aspects of the problem
• Labeling and describing the problem

Problem-Solving Strategies

There are many ways to go about solving a problem. Some of these strategies might be used on their own, or you may decide to employ multiple approaches when working to figure out and fix a problem.

An algorithm is a step-by-step procedure that, by following certain "rules" produces a solution. Algorithms are commonly used in mathematics to solve division or multiplication problems. But they can be used in other fields as well.

In psychology, algorithms can be used to help identify individuals with a greater risk of mental health issues. For instance, research suggests that certain algorithms might help us recognize children with an elevated risk of suicide or self-harm.

One benefit of algorithms is that they guarantee an accurate answer. However, they aren't always the best approach to problem-solving, in part because detecting patterns can be incredibly time-consuming.

There are also concerns when machine learning is involved—also known as artificial intelligence (AI)—such as whether they can accurately predict human behaviors.

Heuristics are shortcut strategies that people can use to solve a problem at hand. These "rule of thumb" approaches allow you to simplify complex problems, reducing the total number of possible solutions to a more manageable set.

If you find yourself sitting in a traffic jam, for example, you may quickly consider other routes, taking one to get moving once again. When shopping for a new car, you might think back to a prior experience when negotiating got you a lower price, then employ the same tactics.

While heuristics may be helpful when facing smaller issues, major decisions shouldn't necessarily be made using a shortcut approach. Heuristics also don't guarantee an effective solution, such as when trying to drive around a traffic jam only to find yourself on an equally crowded route.

Trial and Error

A trial-and-error approach to problem-solving involves trying a number of potential solutions to a particular issue, then ruling out those that do not work. If you're not sure whether to buy a shirt in blue or green, for instance, you may try on each before deciding which one to purchase.

This can be a good strategy to use if you have a limited number of solutions available. But if there are many different choices available, narrowing down the possible options using another problem-solving technique can be helpful before attempting trial and error.

In some cases, the solution to a problem can appear as a sudden insight. You are facing an issue in a relationship or your career when, out of nowhere, the solution appears in your mind and you know exactly what to do.

Insight can occur when the problem in front of you is similar to an issue that you've dealt with in the past. Although, you may not recognize what is occurring since the underlying mental processes that lead to insight often happen outside of conscious awareness .

Research indicates that insight is most likely to occur during times when you are alone—such as when going on a walk by yourself, when you're in the shower, or when lying in bed after waking up.

How to Apply Problem-Solving Strategies in Real Life

If you're facing a problem, you can implement one or more of these strategies to find a potential solution. Here's how to use them in real life:

• Create a flow chart . If you have time, you can take advantage of the algorithm approach to problem-solving by sitting down and making a flow chart of each potential solution, its consequences, and what happens next.
• Recall your past experiences . When a problem needs to be solved fairly quickly, heuristics may be a better approach. Think back to when you faced a similar issue, then use your knowledge and experience to choose the best option possible.
• Start trying potential solutions . If your options are limited, start trying them one by one to see which solution is best for achieving your desired goal. If a particular solution doesn't work, move on to the next.
• Take some time alone . Since insight is often achieved when you're alone, carve out time to be by yourself for a while. The answer to your problem may come to you, seemingly out of the blue, if you spend some time away from others.

Obstacles to Problem-Solving

Problem-solving is not a flawless process as there are a number of obstacles that can interfere with our ability to solve a problem quickly and efficiently. These obstacles include:

• Assumptions: When dealing with a problem, people can make assumptions about the constraints and obstacles that prevent certain solutions. Thus, they may not even try some potential options.
• Functional fixedness : This term refers to the tendency to view problems only in their customary manner. Functional fixedness prevents people from fully seeing all of the different options that might be available to find a solution.
• Irrelevant or misleading information: When trying to solve a problem, it's important to distinguish between information that is relevant to the issue and irrelevant data that can lead to faulty solutions. The more complex the problem, the easier it is to focus on misleading or irrelevant information.
• Mental set: A mental set is a tendency to only use solutions that have worked in the past rather than looking for alternative ideas. A mental set can work as a heuristic, making it a useful problem-solving tool. However, mental sets can also lead to inflexibility, making it more difficult to find effective solutions.

How to Improve Your Problem-Solving Skills

In the end, if your goal is to become a better problem-solver, it's helpful to remember that this is a process. Thus, if you want to improve your problem-solving skills, following these steps can help lead you to your solution:

• Recognize that a problem exists . If you are facing a problem, there are generally signs. For instance, if you have a mental illness , you may experience excessive fear or sadness, mood changes, and changes in sleeping or eating habits. Recognizing these signs can help you realize that an issue exists.
• Decide to solve the problem . Make a conscious decision to solve the issue at hand. Commit to yourself that you will go through the steps necessary to find a solution.
• Seek to fully understand the issue . Analyze the problem you face, looking at it from all sides. If your problem is relationship-related, for instance, ask yourself how the other person may be interpreting the issue. You might also consider how your actions might be contributing to the situation.
• Research potential options . Using the problem-solving strategies mentioned, research potential solutions. Make a list of options, then consider each one individually. What are some pros and cons of taking the available routes? What would you need to do to make them happen?
• Take action . Select the best solution possible and take action. Action is one of the steps required for change . So, go through the motions needed to resolve the issue.
• Try another option, if needed . If the solution you chose didn't work, don't give up. Either go through the problem-solving process again or simply try another option.

You can find a way to solve your problems as long as you keep working toward this goal—even if the best solution is simply to let go because no other good solution exists.

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By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

What Are Problem-Solving Skills? Definition and Examples

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Forage puts students first. Our blog articles are written independently by our editorial team. They have not been paid for or sponsored by our partners. See our full  editorial guidelines .

Why do employers hire employees? To help them solve problems. Whether you’re a financial analyst deciding where to invest your firm’s money, or a marketer trying to figure out which channel to direct your efforts, companies hire people to help them find solutions. Problem-solving is an essential and marketable soft skill in the workplace. 

So, how can you improve your problem-solving and show employers you have this valuable skill? In this guide, we’ll cover:

Problem-Solving Skills Definition

Why are problem-solving skills important, problem-solving skills examples, how to include problem-solving skills in a job application, how to improve problem-solving skills, problem-solving: the bottom line.

Problem-solving skills are the ability to identify problems, brainstorm and analyze answers, and implement the best solutions. An employee with good problem-solving skills is both a self-starter and a collaborative teammate; they are proactive in understanding the root of a problem and work with others to consider a wide range of solutions before deciding how to move forward. 

Examples of using problem-solving skills in the workplace include:

• Researching patterns to understand why revenue decreased last quarter
• Experimenting with a new marketing channel to increase website sign-ups
• Brainstorming content types to share with potential customers
• Testing calls to action to see which ones drive the most product sales
• Implementing a new workflow to automate a team process and increase productivity

Problem-solving skills are the most sought-after soft skill of 2022. In fact, 86% of employers look for problem-solving skills on student resumes, according to the National Association of Colleges and Employers Job Outlook 2022 survey . 

It’s unsurprising why employers are looking for this skill: companies will always need people to help them find solutions to their problems. Someone proactive and successful at problem-solving is valuable to any team.

“Employers are looking for employees who can make decisions independently, especially with the prevalence of remote/hybrid work and the need to communicate asynchronously,” Eric Mochnacz, senior HR consultant at Red Clover, says. “Employers want to see individuals who can make well-informed decisions that mitigate risk, and they can do so without suffering from analysis paralysis.”

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Problem-solving includes three main parts: identifying the problem, analyzing possible solutions, and deciding on the best course of action.

>>MORE: Discover the right career for you based on your skills with a career aptitude test .

Research is the first step of problem-solving because it helps you understand the context of a problem. Researching a problem enables you to learn why the problem is happening. For example, is revenue down because of a new sales tactic? Or because of seasonality? Is there a problem with who the sales team is reaching out to? 

Research broadens your scope to all possible reasons why the problem could be happening. Then once you figure it out, it helps you narrow your scope to start solving it. 

Analysis is the next step of problem-solving. Now that you’ve identified the problem, analytical skills help you look at what potential solutions there might be.

“The goal of analysis isn’t to solve a problem, actually — it’s to better understand it because that’s where the real solution will be found,” Gretchen Skalka, owner of Career Insights Consulting, says. “Looking at a problem through the lens of impartiality is the only way to get a true understanding of it from all angles.”

Decision-Making

Once you’ve figured out where the problem is coming from and what solutions are, it’s time to decide on the best way to go forth. Decision-making skills help you determine what resources are available, what a feasible action plan entails, and what solution is likely to lead to success.

On a Resume

Employers looking for problem-solving skills might include the word “problem-solving” or other synonyms like “ critical thinking ” or “analytical skills” in the job description.

“I would add ‘buzzwords’ you can find from the job descriptions or LinkedIn endorsements section to filter into your resume to comply with the ATS,” Matthew Warzel, CPRW resume writer, advises. Warzel recommends including these skills on your resume but warns to “leave the soft skills as adjectives in the summary section. That is the only place soft skills should be mentioned.”

On the other hand, you can list hard skills separately in a skills section on your resume .

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In a Cover Letter or an Interview

Explaining your problem-solving skills in an interview can seem daunting. You’re required to expand on your process — how you identified a problem, analyzed potential solutions, and made a choice. As long as you can explain your approach, it’s okay if that solution didn’t come from a professional work experience.

“Young professionals shortchange themselves by thinking only paid-for solutions matter to employers,” Skalka says. “People at the genesis of their careers don’t have a wealth of professional experience to pull from, but they do have relevant experience to share.”

Aaron Case, career counselor and CPRW at Resume Genius, agrees and encourages early professionals to share this skill. “If you don’t have any relevant work experience yet, you can still highlight your problem-solving skills in your cover letter,” he says. “Just showcase examples of problems you solved while completing your degree, working at internships, or volunteering. You can even pull examples from completely unrelated part-time jobs, as long as you make it clear how your problem-solving ability transfers to your new line of work.”

Learn How to Identify Problems

Problem-solving doesn’t just require finding solutions to problems that are already there. It’s also about being proactive when something isn’t working as you hoped it would. Practice questioning and getting curious about processes and activities in your everyday life. What could you improve? What would you do if you had more resources for this process? If you had fewer? Challenge yourself to challenge the world around you.

Think Digitally

“Employers in the modern workplace value digital problem-solving skills, like being able to find a technology solution to a traditional issue,” Case says. “For example, when I first started working as a marketing writer, my department didn’t have the budget to hire a professional voice actor for marketing video voiceovers. But I found a perfect solution to the problem with an AI voiceover service that cost a fraction of the price of an actor.”

Being comfortable with new technology — even ones you haven’t used before — is a valuable skill in an increasingly hybrid and remote world. Don’t be afraid to research new and innovative technologies to help automate processes or find a more efficient technological solution.

Collaborate

Problem-solving isn’t done in a silo, and it shouldn’t be. Use your collaboration skills to gather multiple perspectives, help eliminate bias, and listen to alternative solutions. Ask others where they think the problem is coming from and what solutions would help them with your workflow. From there, try to compromise on a solution that can benefit everyone.

If we’ve learned anything from the past few years, it’s that the world of work is constantly changing — which means it’s crucial to know how to adapt . Be comfortable narrowing down a solution, then changing your direction when a colleague provides a new piece of information. Challenge yourself to get out of your comfort zone, whether with your personal routine or trying a new system at work.

Put Yourself in the Middle of Tough Moments

Just like adapting requires you to challenge your routine and tradition, good problem-solving requires you to put yourself in challenging situations — especially ones where you don’t have relevant experience or expertise to find a solution. Because you won’t know how to tackle the problem, you’ll learn new problem-solving skills and how to navigate new challenges. Ask your manager or a peer if you can help them work on a complicated problem, and be proactive about asking them questions along the way.

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Step 1 of 3

Companies always need people to help them find solutions — especially proactive employees who have practical analytical skills and can collaborate to decide the best way to move forward. Whether or not you have experience solving problems in a professional workplace, illustrate your problem-solving skills by describing your research, analysis, and decision-making process — and make it clear that you’re the solution to the employer’s current problems. 

Looking to learn more workplace professional skills? Check out Two Sigma’s Professional Skills Development Virtual Experience Program .

Image Credit: Christina Morillo / Pexels 

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Piaget’s Preoperational Stage (Ages 2-7)

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

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Piaget’s preoperational stage is the second stage of his theory of cognitive development . It begins around age two and lasts until approximately age seven. During this stage, children can think symbolically and engage in make-believe play. However, their thinking is still egocentric and lacks logic. 

The child’s thinking during this stage is pre- (before) cognitive operations. This means the child cannot use logic, transform, combine, or separate ideas (Piaget, 1951, 1952).

The child’s development consists of building experiences about the world through adaptation and working towards the (concrete) stage when it can use logical thought.

During the end of this stage, children can mentally represent events and objects (the semiotic function), and engage in symbolic play.

Centration is the tendency to focus on only one aspect of a situation at one time. When a child can focus on more than one aspect of a situation, at the same time, they have the ability to decenter.

During this stage, children have difficulties thinking about more than one aspect of any situation at the same time; and they have trouble decentering in social situation just as they do in non-social contexts.

Egocentrism

Egocentrism refers to the child’s inability to see a situation from another person’s point of view. The egocentric child assumes that other people see, hear, and feel exactly the same as the child does.

In the developmental theory of Jean Piaget, this is a feature of the preoperational child. Childrens” thoughts and communications are typically egocentric (i.e., about themselves).

At the beginning of this stage, you often find children engaging in parallel play. That is to say, they often play in the same room as other children but they play next to others rather than with them.

Each child is absorbed in their own private world, and speech is egocentric. That is to say the main function of speech at this stage is to externalize the child’s thinking rather than to communicate with others.

As yet, the child has not grasped the social function of either language or rules.

Symbolic Representation

The early preoperational period (ages 2-3) is marked by a dramatic increase in children’s use of the symbolic function.

This is the ability to make one thing – a word or an object – stand for something other than itself. Language is perhaps the most obvious form of symbolism that young children display.

However, Piaget (1951) argues that language does not facilitate cognitive development, but merely reflects what the child already knows and contributes little to new knowledge. He believed cognitive development promotes language development, not vice versa.

Pretend (or symbolic) Play

Toddlers often pretend to be people they are not (e.g. superheroes, policeman), and may play these roles with props that symbolize real life objects. Children may also invent an imaginary playmate.

“In symbolic play, young children advance upon their cognitions about people, objects and actions and in this way construct increasingly sophisticated representations of the world” (Bornstein, 1996, p. 293).

As the pre-operational stage develops egocentrism declines and children begin to enjoy the participation of another child in their games and “lets pretend “ play becomes more important.

For this to work, there is going to be a need for some way of regulating each child’s relations with the other and out of this need we see the beginnings of an orientation to others in terms of rules.

This is the belief that inanimate objects (such as toys and teddy bears) have human feelings and intentions. By animism Piaget (1929) meant that for the pre-operational child the world of nature is alive, conscious and has a purpose.

Piaget has identified four stages of animism:

• Up to the ages 4 or 5 years, the child believes that almost everything is alive and has a purpose.
• During the second stage (5-7 years) only objects that move have a purpose.
• In the next stage (7-9 years), only objects that move spontaneously are thought to be alive.
• In the last stage (9-12 years), the child understands that only plants and animals are alive.

Artificialism

This is the belief that certain aspects of the environment are manufactured by people (e.g., clouds in the sky).

Irreversibility

This is the inability to reverse the direction of a sequence of events to their starting point.

The Three Mountains Task

Jean Piaget used the three mountains task (see picture below) to test whether children were egocentric. Egocentric children assume that other people will see the same view of the three mountains as they do.

According to Piaget, at age 7, thinking is no longer egocentric, as the child can see more than their own point of view.

Aim : Piaget and Inhelder (1956) wanted to find out at what age children decenter – i.e. become no longer egocentric.

Method : A child is shown a display of three mountains; the tallest mountain is covered with snow. On top of another are some trees, and on top of the third is a church. The child stands on one side of the display, and there is a doll on the other side of it.

The child was allowed to walk round the model, to look at it, then sit down at one side. A doll is then placed at various positions on the table.

The child is shown pictures of the scene from different viewpoints and asked to select the view that best matched what the doll can “see”.

The child is then shown 10 photographs of the mountains taken from different positions, and asked to indicate which showed the doll’s view.

Piaget assumed that if the child correctly picked out the card showing the doll’s view, s/he was not egocentric. Egocentrism would be shown by the child who picked out the card showing the view s/he saw.

Findings – Typically a four years old child reports what can be seen from her perspective and not what can be seen from the doll’s perspective.

Six years old were more aware of other viewpoints but still tended to choose the wrong one. This shows egocentrism as the child assumed that the doll “saw” the mountains as he did

Four year-olds almost always chose a picture that represented what they could see and showed no awareness that the doll’s view would be different from this.

Six year-olds frequently chose a picture different from their own view but rarely chose the correct picture for the doll’s point of view. Only seven- and eight-year-olds consistently chose the correct picture.

Conclusion – At age 7, thinking is no longer egocentric as the child can see more than their own point of view.

Evaluation – It has been suggested that Piaget’s tasks at this stage may have underestimated the child’s abilities due to a number of factors, including complicated language, unfamiliar materials, lack of context, and children misinterpreting the experimenter’s intention.

More recent studies have attempted to ask questions more clearly and to present situations to which children can relate more easily.

Critical Evaluation

Policeman doll study.

Martin Hughes (1975) argued that the three mountains task did not make sense to children and was made more difficult because the children had to match the doll’s view with a photograph.

Hughes devised a task which made sense to the child. He showed children a model comprising two intersecting walls, a “boy” doll and a “policeman” doll. He then placed the policeman doll in various positions and asked the child to hide the boy doll from the policeman.

Hughes did this to make sure that the child understood what was being asked of him, so if s/he made mistakes they were explained and the child tried again. Interestingly, very few mistakes were made.

The experiment then began. Hughes brought in a second policeman doll, and placed both dolls at the end of two walls, as shown in the illustration above.

The child was asked to hide the boy from both policemen, in other words he had to take account of two different points of view.

Hughes” sample comprised children between three and a half and five years of age, of whom 90 percent gave correct answers. Even when he devised a more complex situation, with more walls and a third policeman, 90 percent of four-year-olds were successful.

This shows that children have largely lost their egocentric thinking by four years of age, because they are able to take the view of another.

Hughes” experiment allowed them to demonstrate this because the task made sense to the child, whereas Piaget’s did not. Suggesting that differences in “meaning” children ascribe to situation might cause them to pass or fail task.

The ‘Turntable’ Task

In Borke’s (1975) test of egocentrism the child is given two identical models of a three-dimensional scene (several different scenes were used including different arrangements of toy people and animals and a mountain model similar to Piaget and Inhelder’s). One of the models is mounted on a turntable so it can easily be turned by the child.

After a practice session where the child is familiarized with the materials and the idea of looking at things from another person’s point of view, a doll is introduced (in Borke’s study it was the character Grover from ‘Sesame Street’, a programme the children were familiar with).

The Grover doll was placed so it was ‘looking’ at the model from a particular vantage point and the child was invited to turn the other model around until its view of the model matched what Grover would be able to see.

Borke (1975) found, using the ‘mountains’ model three-year-olds selected a correct view 42% of the time and four-year-olds selected the right view 67% of the time. With other displays, the three-years-olds accuracy increased to 80% and the four-year olds’ to 93%.

Limitations in the Child’s Thinking

Piaget focused most of the description of this stage on limitations in the child’s thinking, identifying a number of mental tasks which children seem unable to do.

These include the inability to decenter, conserve, understand seriation (the inability to understand that objects can be organized into a logical series or order) and to carry out inclusion tasks.

Children in the preoperational stage are able to focus on only one aspect or dimension of problems (i.e. centration). For example, suppose you arrange two rows of blocks in such a way that a row of 5 blocks is longer than a row of 7 blocks.

Preoperational children can generally count the blocks in each row and tell you the number contained in each. However, if you ask which row has more, they will likely say that it is the one that makes the longer line, because they cannot simultaneously focus on both the length and the number. This inability to decenter contributes to the preoperational child’s egocentrism.

Conservation is the understanding that something stays the same in quantity even though its appearance changes. To be more technical, conservation is the ability to understand that redistributing material does not affect its mass, number or volume.

The ability to solve this and other “conservation” problems signals the transition to the next stage .

So, what do these tasks tell us about the limitations of preoperational thought in general?

Piaget drew a number of related conclusions:

• Understanding of these situations is “perception bound”. The child is drawn by changes in the appearance of the materials to conclude that a change has occurred.
• Thinking is “centered” on one aspect of the situation. Children notice changes in the level of water or in the length of clay without noticing that other aspects of the situation have changed simultaneously.
• Thinking is focused on states rather than on transformations. Children fail to track what has happened to materials and simply make an intuitive judgment based on how they appear “now”.
• Thinking is “irreversible” in that the child cannot appreciate that a reverse transformation would return the material to its original state. Reversibility is a crucial aspect of the logical (operational) thought of later stages.

Frequently Asked Questions

Are there any specific educational strategies that can support children in the preoperational stage.

Here are some educational strategies for children in the preoperational stage (ages 2-7):

1) Use hands-on activities and materials; 2) Encourage pretend play for problem-solving; 3) Utilize visual aids like pictures and charts; 4) Break tasks into smaller steps; 5) Foster language development through conversations and storytelling.

These strategies make learning enjoyable and accessible, supporting cognitive growth during this stage.

How does the preoperational stage differ from the sensorimotor stage?

The preoperational stage and the sensorimotor stage are two distinct stages in Piaget’s theory of cognitive development.

In the sensorimotor stage, infants explore and learn about the world through their senses and motor actions. They develop object permanence and begin to coordinate their senses with their movements.

In contrast, the preoperational stage marks the advancement of symbolic thinking, language development, and pretend play. Children in this stage show egocentrism and struggle with logical reasoning.

Are there any cultural variations in the manifestation of the preoperational stage?

Yes, there are cultural variations in the manifestation of the preoperational stage. Cultural beliefs, values, and practices influence children’s experiences and interactions, which can impact their cognitive development .

For example, cultural differences in parenting styles, educational practices, and social expectations can shape the development of language, symbolic play, and social cognition during the preoperational stage.

Cultural variations may affect the emphasis placed on certain skills, the types of play activities encouraged, and the ways in which children are socialized, leading to differences in cognitive development across cultures.

What are the implications of the preoperational stage for social and emotional development?

During the preoperational stage, social and emotional development undergo significant changes. Children become increasingly aware of their own emotions and the emotions of others.

They begin to engage in cooperative play and develop friendships. However, egocentrism can affect their ability to take others’ perspectives and regulate their emotions effectively.

The emergence of language and symbolic play provides avenues for expressing emotions and understanding social roles.

Positive social interactions and nurturing relationships during this stage contribute to the development of social skills, empathy , and emotional self-regulation, laying the foundation for healthy social and emotional development in later stages.

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Complex cognition: the science of human reasoning, problem-solving, and decision-making

• Published: 23 March 2010
• Volume 11 , pages 99–102, ( 2010 )

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• Markus Knauff 1 &
• Ann G. Wolf 1  

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Climate change, globalization, policy of peace, and financial market crises—often we are faced with very complex problems. In order to tackle these complex problems, the responsible people should first come to mutual terms. An additional challenge is that typically the involved parties have different (often conflicting) interests and relate the problems to different emotions and wishes. These factors certainly do not ease the quest for a solution to these complex problems.

It is needless to say that the big problems of our time are not easy to solve. Less clear, however, is identifying the causes that led to these problems. Interest conflicts between social groups, the economic and social system or greed—one can think of many responsible factors for the large-scale problems we are currently confronted with.

The present “Special Corner: complex cognition” deals with questions in this regard that have often received little consideration. Under the headline “complex cognition”, we summarize mental activities such as thinking, reasoning, problem - solving, and decision - making that typically rely on the combination and interaction of more elementary processes such as perception, learning, memory, emotion, etc. (cf. Sternberg and Ben-Zeev 2001 ). However, even though complex cognition relies on these elementary functions, the scope of complex cognition research goes beyond the isolated analysis of such elementary mental processes. Two aspects are essential for “complex cognition”: The first aspect refers to the interaction of different mental activities such as perception, memory, learning, reasoning, emotion, etc. The second aspect takes the complexity of the situation into account an agent is confronted with. Based on these two aspects, the term “complex cognition” can be defined in the following way:

Complex psychological processes: We talk about “complex cognition”, when thinking, problem-solving, or decision-making falls back on other cognitive processes such as “perception”, “working memory”, “long-term memory”, “executive processes”, or when the cognitive processes are in close connection with other processes such as “emotion” and “motivation”. The complexity also results from an interaction from a multitude of processes that occur simultaneously or at different points in time and can be realized in different cognitive and/or neuronal structures.

Complex conditions: We also talk about “complex cognition” when the conditions are complex in which a person finds himself and in which conclusions need to be drawn, a problem needs to be solved, or decisions need to be made. The complexity of the conditions or constraints can have different causes. The situation structure itself can be difficult to “see”, or the action alternatives are difficult “to put into effect”. The conditions can themselves comprise of many different variables. These variables can exhibit a high level of interdependence and cross-connection, and it can, as time passes by, come to a change of the original conditions (e.g. Dörner and Wearing 1995 ; Osman 2010 ). It can also be the case that the problem is embedded in a larger social context and can be solved only under certain specifications (norms, data, legislations, culture, etc.) or that the problem can only be solved in interaction with other agents, be it other persons or technical systems.

When one summarizes these two aspects, this yields the following view of what should be understood as “complex cognition”.

As “complex cognition” we define all mental processes that are used by individuals for deriving new information out of given information, with the intention to solve problems, make decision, and plan actions. The crucial characteristic of “complex cognition” is that it takes place under complex conditions in which a multitude of cognitive processes interact with one another or with other noncognitive processes.

The “Special Corner: complex cognition” deals with complex cognition from many different perspectives. The typical questions of all contributions are: Does the design of the human mind enable the necessary thinking skills to solve the truly complex problems we are faced with? Where lay the boundaries of our thinking skills? How do people derive at conclusions? What makes a problem a complex problem? How can we improve our skills to effectively solve problems and make sound judgements?

It is for sure too much to expect that the Special Corner answers these questions. If it were that easy, we would not be still searching for an answer. It is, however, our intention with the current collection of articles to bring to focus such questions to a larger extent than has been done so far.

An important starting point is the fact that people’s skills to solve the most complex of all problems and to ponder about the most complex issues is often immense—humankind would not otherwise be there were she is now. Yet, on the other hand, it has become more clear in the past few years that often people drift away from what one would identify as “rational” (Kahneman 2003 ). People hardly ever adhere to that what the norms of logic, the probability calculus, or the mathematical decision theory state. For example, most people (and organizations) typically accept more losses for a potential high gain than would be the case if they were to take into account the rules of the probability theory. Similarly, they draw conclusions from received information in a way that is not according to the rules of logic. When people, for example, accept the rule “If it rains, then the street is wet”, they most often conclude that when the street is wet, it must have rained. That, however, is incorrect from a logical perspective: perhaps a cleaning car just drove by. In psychology, two main views are traditionally put forward to explain how such deviations from the normative guidelines occur. One scientific stream is interested in how deviations from the normative models can be explained (Evans 2005 ; Johnson-Laird 2008 ; Knauff 2007 ; Reason 1990 ). According to this line of research, deviations are caused by the limitations of the human cognitive system. The other psychological stream puts forward as the main criticism that the deviations can actually be regarded as mistakes (Gigerenzer 2008 ). The deviations accordingly have a high value, because they are adjusted to the information structure of the environment (Gigerenzer et al. 1999 ). They have probably developed during evolution, because they could ensure survival as for example the specifications of formal logic (Hertwig and Herzog 2009 ). We, the editors of the special corner, are very pleased that we can offer an impression of this debate with the contributions from Marewski, Gaissmaier, and Gigerenzer and the commentaries to this contribution from Evans and Over. Added to this is a reply from Marewski, Gaissmaier, and Gigerenzer to the commentary from Evans and Over.

Another topic in the area of complex cognition can be best illustrated by means of the climate protection. To be successful in this area, the responsible actors have to consider a multitude of ecological, biological, geological, political, and economical factors, the basic conditions are constantly at change, and the intervention methods are not clear. Because the necessary information is not readily available for the person dealing with the problem, the person is forced to obtain the relevant information from other sources. Furthermore, intervention in the complex variable structure of the climate can trigger processes whose impact was likely not intended. Finally, the system will not “wait” for intervention of the actors but will change itself over time. The special corner is also concerned with thinking and problem-solving in such complex situations. The article by Funke gives an overview of the current state of research on this topic from the viewpoint of the author, in which several research areas are covered that have internationally not received much acknowledgement (but see, for example, Osman 2010 ).

Although most contributions to the special corner come from the area of psychology, the contribution by Ragni and Löffler illustrates that computer science can provide a valuable addition to the understanding of complex cognition. Computer science plays an important role in complex cognition. In general, computer science, which is used to investigate computational processes central to all research approaches, can be placed in a “computational theory of cognition” framework. This is true especially for the development of computational theories of complex cognitive processes. In many of our modern knowledge domains, the application of simulations and modelling has become a major part of the methods inventory. Simulations help forecast the weather and climate change, help govern traffic flow and help comprehend physical processes. Although modelling in these areas is a vastly established method, it has been very little applied in the area of human thinking (but see e.g. Anderson 1990 ; Gray 2007 ). However, exactly in the area of complex cognition, the method of cognitive modelling offers empirical research an additional methodological access to the description and explanation of complex cognitive processes. While the validity of psychological theories can be tested with the use of empirical research, cognitive models, with their internal coherence, make possible to test consistency and completeness (e.g. Schmid 2008 ). They will also lead to new hypotheses that will in turn be possible to test experimentally. The contribution of Ragni and Löffler demonstrates with the help of an interesting example, finding the optimal route, the usefulness of simulation and modelling in psychology.

A further problem in the area of complex cognition is that many problems are solvable only under certain social conditions (norms, values, laws, culture) or only in interaction with other actors (cf. Beller 2008 ). The article on deontic reasoning by Beller is concerned with this topic. Deontic reasoning is thinking about whether actions are forbidden or allowed, obligatory or not obligatory. Beller proposes that social norms, imposing constraints on individual actions, constitute the fundamental concept for deontic thinking and that people reason from such norms flexibly according to deontic core principles. The review paper shows how knowing what in a certain situation is allowed or forbidden can influence how people derive at conclusions.

The article of Waldmann, Meder, von Sydow, and Hagmayer is concerned with the important topic of causal reasoning. More specifically, the authors explore the interaction between category and causal induction in causal model learning. The paper is a good example of how experimental work in psychology can combine different research traditions that typically work quite isolated. The paper goes beyond a divide and conquers approach and shows that causal knowledge plays an important role in learning, categorization, perception, decision-making, problem-solving, and text comprehension. In each of these fields, separate theories have been developed to investigate the role of causal knowledge. The first author of the paper is internationally well known for his work on the role of causality in other cognitive functions, in particular in categorization and learning (e.g. Lagnado et al. 2007 ; Waldmann et al. 1995 ). In a number of experimental studies, Waldmann and his colleagues have shown that people when learning about causal relations do not simply form associations between causes and effects but make use of abstract prior assumptions about the underlying causal structure and functional form (Waldmann 2007 ).

We, the guest editors, are very pleased that we have the opportunity with this Special corner to make accessible the topic “complex cognition” to the interdisciplinary readership of Cognitive Processing . We predict a bright future for this topic. The research topic possesses high research relevance in the area of basic research for a multitude of disciplines, for example psychology, computer science, and neuroscience. In addition, this area forms a good foundation for an interdisciplinary cooperation.

A further important reason for the positive development of the area is that the relevance of the area goes beyond fundamental research. In that way, the results of the area can for example also contribute to better understanding of the possibilities and borders of human thinking, problem-solving, and decisions in politics, corporations, and economy. In the long term, it might even lead to practical directions on how to avoid “mistakes” and help us better understand the global challenges of our time—Climate change, globalization, financial market crises, etc.

We thank all the authors for their insightful and inspiring contributions, a multitude of reviewers for their help, the editor-in-chief Marta Olivetti Belardinelli that she gave us the opportunity to address this topic, and the editorial manager, Thomas Hünefeldt, for his support for accomplishing the Special Corner. We wish the readers of the Special Corner lots of fun with reading the contributions!

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Knauff, M., Wolf, A.G. Complex cognition: the science of human reasoning, problem-solving, and decision-making. Cogn Process 11 , 99–102 (2010). https://doi.org/10.1007/s10339-010-0362-z

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Received : 10 March 2010

Accepted : 10 March 2010

Published : 23 March 2010

Issue Date : May 2010

DOI : https://doi.org/10.1007/s10339-010-0362-z

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