is critical thinking and reasoning the same

Logical Thinking vs Critical Thinking: Comparing and Breaking Down the Differences

Many people use the terms logical thinking and critical thinking interchangeably; however, there are subtle differences between the two. 

On the one hand, logical thinking is pretty straightforward. 

It’s a method of thinking that uses logic or analysis of information to evaluate a situation. 

Critical thinking, on the other hand, is a process that utilizes logical thinking but takes it a step further. 

To think critically is to question the face value, connect the dots, and seek the truth. 

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What Is Logical Thinking?

Logical thinking involves thinking in a disciplined manner. Everyday we come across situations where we need to determine what is going on and why. 

The process may be as simple as evaluating product information or as complex as embracing (or not) an opportunity that requires a significant life change. 

You probably don’t toss a coin in the air to make important life decisions. Instead, you analyze the facts and use reason to help you make good choices.

Let’s look at the example of a job opportunity in another state. 

It might sound like a fantastic career move, but applying a big of logical thinking before you take the leap can mean the difference between a positive outcome and one you’ll regret. 

• What will it cost you to move? 
• Is the cost of living higher in the new city than where you currently live? 
• What is the crime rate like?
• Is the city governed well?
• What about increased time commitment? Work load? 

Observing and analyzing all the facts and scenarios can help you come to a well reasoned conclusion—and that is logical thinking in a nutshell. 

What Is Critical Thinking?

Critical thinking is closely related to logical thinking. It involves the questioning of data, beliefs, and information to make a reasoned conclusion or decision. 

It’s the ability to take various ideas or pieces of information and make connections between them. 

Using the example above, if you were offered a great job opportunity in another city, you still consider all the same factors previously mentioned.

However, with critical thinking, you move beyond hard facts and ask things like:

• How do your kids feel about changing schools?
• Do the opportunities offered outweigh the disadvantages? 
• Why would the new job be better than what you have now?

Let me put it another way by posing another question:

Do you take whatever you’re presented with and assume that it is just so? Precisely as described and portrayed?

Likewise, that new career may look good on paper, but what about the invisible factors that go beyond the facts and figures in your contract?

Seeking truthful answers to those not-so-black-and-white questions is the definition of critical thinking. 

Logical Reasoning vs Critical Thinking: The Relationship Between the Two

As touched on earlier, logical reasoning involves assessing facts to arrive at a valid conclusion.

With no assumptions being made and emotions removed from the equation, the principles of logic can be used much like you would use a math formula to solve a problem. 

There’s a clear distinction between right and wrong. 

In theory, given the same situation with the exact same information, two different people would arrive at the same conclusion.

On the other hand, critical thinking involves questioning the answers and information you get. 

For instance, you might investigate if the person providing the information has a vested interest in a particular outcome and how that influences the information provided. 

You may also ask yourself if you’re missing information or how reliable your source is. 

There’s definitely a blurred line between logical reasoning and critical thinking, but the connection is this:

Logical thought processes involve critical thinking, and using critical thinking skills involves a bit of logic.

Is Questioning and Reasoning the Same Thing?

Reasoning involves the use of both deductive and inductive processes to reach a conclusion. 

“Deductive” is just a fancy word for following a fact (or idea, statement, and so on) to its logical conclusion. 

“Inductive” reasoning provides room for one’s own experiences and observations along the pathway to a conclusion. 

In short, to reason is to use logical thinking to evaluate and determine then explain your approach to a problem.

Questioning, on the other hand, is different than—though part of—reaching a reasoned conclusion. 

Questions help you dig up more information so you can reason effectively to determine the truth of a matter. 

So essentially, questioning is just one part of reasoning. They are not one in the same. 

How to Strengthen Your Critical Thinking Skills

When a situation calls for forming your own opinion or making a decision, it’s important to know how to think as opposed to being told what to think.  

I t’s all too easy to be swayed by popular opinion. 

That being the case, it’s important to pause amid the clamor and think both logically and critically to ensure you know exactly what you believe instead of simply following the crowd. 

Doing so also equips you to make choices based on your personal values, beliefs, and goals.

You can strengthen your critical thinking skills by thinking through situations, one step at a time. 

You’ll gain knowledge as you gain real-world experience, but that database of knowledge isn’t going to serve up a solution for every problem you face. 

That’s where the ability to think critically becomes so important. 

Practice asking questions while questioning assumptions. 

(Here’s a list of fun critical thinking questions that are more lighthearted if you need help getting started.)

Pay attention to the processes you use to analyze information and reach conclusions.

Take time to break down any barriers to critical thinking that may exist.

Today, we are spoon-fed so much information on social media and the internet that thinking sometimes seems irrelevant, but oh what a dangerous path that is. 

If you don’t already, begin questioning the things you read and hear. 

Do your own research. 

Question commonly accepted facts. 

Analyze the information you receive and from whose mouth you receive it from.

Of course, not every little situation requires an in-depth analysis or use of critical thinking skills. 

Family and friends won’t appreciate being questioned about everything they say or do. 

Still, judicial use of logical thinking and critical thinking skills can help you become more informed about what is true and what is not.

If you want to help your teen sharpen those skills, check out our award-winning curriculum, Philosophy Adventure .

will your children recognize truth?

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Critical Thinking and Decision-Making  - What is Critical Thinking?

Critical thinking and decision-making  -, what is critical thinking, critical thinking and decision-making what is critical thinking.

Critical Thinking and Decision-Making: What is Critical Thinking?

Lesson 1: what is critical thinking, what is critical thinking.

Critical thinking is a term that gets thrown around a lot. You've probably heard it used often throughout the years whether it was in school, at work, or in everyday conversation. But when you stop to think about it, what exactly is critical thinking and how do you do it ?

Watch the video below to learn more about critical thinking.

Simply put, critical thinking is the act of deliberately analyzing information so that you can make better judgements and decisions . It involves using things like logic, reasoning, and creativity, to draw conclusions and generally understand things better.

This may sound like a pretty broad definition, and that's because critical thinking is a broad skill that can be applied to so many different situations. You can use it to prepare for a job interview, manage your time better, make decisions about purchasing things, and so much more.

The process

As humans, we are constantly thinking . It's something we can't turn off. But not all of it is critical thinking. No one thinks critically 100% of the time... that would be pretty exhausting! Instead, it's an intentional process , something that we consciously use when we're presented with difficult problems or important decisions.

Improving your critical thinking

In order to become a better critical thinker, it's important to ask questions when you're presented with a problem or decision, before jumping to any conclusions. You can start with simple ones like What do I currently know? and How do I know this? These can help to give you a better idea of what you're working with and, in some cases, simplify more complex issues.  

Real-world applications

Let's take a look at how we can use critical thinking to evaluate online information . Say a friend of yours posts a news article on social media and you're drawn to its headline. If you were to use your everyday automatic thinking, you might accept it as fact and move on. But if you were thinking critically, you would first analyze the available information and ask some questions :

• What's the source of this article?
• Is the headline potentially misleading?
• What are my friend's general beliefs?
• Do their beliefs inform why they might have shared this?

After analyzing all of this information, you can draw a conclusion about whether or not you think the article is trustworthy.

Critical thinking has a wide range of real-world applications . It can help you to make better decisions, become more hireable, and generally better understand the world around you.

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What Are Critical Thinking Skills and Why Are They Important?

Learn what critical thinking skills are, why they’re important, and how to develop and apply them in your workplace and everyday life.

We often use critical thinking skills without even realizing it. When you make a decision, such as which cereal to eat for breakfast, you're using critical thinking to determine the best option for you that day.

Critical thinking is like a muscle that can be exercised and built over time. It is a skill that can help propel your career to new heights. You'll be able to solve workplace issues, use trial and error to troubleshoot ideas, and more.

We'll take you through what it is and some examples so you can begin your journey in mastering this skill.

What is critical thinking?

Critical thinking is the ability to interpret, evaluate, and analyze facts and information that are available, to form a judgment or decide if something is right or wrong.

More than just being curious about the world around you, critical thinkers make connections between logical ideas to see the bigger picture. Building your critical thinking skills means being able to advocate your ideas and opinions, present them in a logical fashion, and make decisions for improvement.

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Why is critical thinking important?

Critical thinking is useful in many areas of your life, including your career. It makes you a well-rounded individual, one who has looked at all of their options and possible solutions before making a choice.

According to the University of the People in California, having critical thinking skills is important because they are [ 1 ]:

Crucial for the economy

Essential for improving language and presentation skills

Very helpful in promoting creativity

Important for self-reflection

The basis of science and democracy 

Critical thinking skills are used every day in a myriad of ways and can be applied to situations such as a CEO approaching a group project or a nurse deciding in which order to treat their patients.

Examples of common critical thinking skills

Critical thinking skills differ from individual to individual and are utilized in various ways. Examples of common critical thinking skills include:

Identification of biases: Identifying biases means knowing there are certain people or things that may have an unfair prejudice or influence on the situation at hand. Pointing out these biases helps to remove them from contention when it comes to solving the problem and allows you to see things from a different perspective.

Research: Researching details and facts allows you to be prepared when presenting your information to people. You’ll know exactly what you’re talking about due to the time you’ve spent with the subject material, and you’ll be well-spoken and know what questions to ask to gain more knowledge. When researching, always use credible sources and factual information.

Open-mindedness: Being open-minded when having a conversation or participating in a group activity is crucial to success. Dismissing someone else’s ideas before you’ve heard them will inhibit you from progressing to a solution, and will often create animosity. If you truly want to solve a problem, you need to be willing to hear everyone’s opinions and ideas if you want them to hear yours.

Analysis: Analyzing your research will lead to you having a better understanding of the things you’ve heard and read. As a true critical thinker, you’ll want to seek out the truth and get to the source of issues. It’s important to avoid taking things at face value and always dig deeper.

Problem-solving: Problem-solving is perhaps the most important skill that critical thinkers can possess. The ability to solve issues and bounce back from conflict is what helps you succeed, be a leader, and effect change. One way to properly solve problems is to first recognize there’s a problem that needs solving. By determining the issue at hand, you can then analyze it and come up with several potential solutions.

How to develop critical thinking skills

You can develop critical thinking skills every day if you approach problems in a logical manner. Here are a few ways you can start your path to improvement:

1. Ask questions.

Be inquisitive about everything. Maintain a neutral perspective and develop a natural curiosity, so you can ask questions that develop your understanding of the situation or task at hand. The more details, facts, and information you have, the better informed you are to make decisions.

2. Practice active listening.

Utilize active listening techniques, which are founded in empathy, to really listen to what the other person is saying. Critical thinking, in part, is the cognitive process of reading the situation: the words coming out of their mouth, their body language, their reactions to your own words. Then, you might paraphrase to clarify what they're saying, so both of you agree you're on the same page.

3. Develop your logic and reasoning.

This is perhaps a more abstract task that requires practice and long-term development. However, think of a schoolteacher assessing the classroom to determine how to energize the lesson. There's options such as playing a game, watching a video, or challenging the students with a reward system. Using logic, you might decide that the reward system will take up too much time and is not an immediate fix. A video is not exactly relevant at this time. So, the teacher decides to play a simple word association game.

Scenarios like this happen every day, so next time, you can be more aware of what will work and what won't. Over time, developing your logic and reasoning will strengthen your critical thinking skills.

Learn tips and tricks on how to become a better critical thinker and problem solver through online courses from notable educational institutions on Coursera. Start with Introduction to Logic and Critical Thinking from Duke University or Mindware: Critical Thinking for the Information Age from the University of Michigan.

Article sources

University of the People, “ Why is Critical Thinking Important?: A Survival Guide , https://www.uopeople.edu/blog/why-is-critical-thinking-important/.” Accessed May 18, 2023.

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Coursera staff.

Editorial Team

Coursera’s editorial team is comprised of highly experienced professional editors, writers, and fact...

This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

Mind by Design

Critical thinking vs analytical thinking: The differences and similarities

The ability to think clearly and make informed decisions is paramount to life. This article delves deep into the realms of analytical thinking and critical thinking, shedding light on their differences and how they complement each other. By understanding these thinking styles, you’ll be better equipped to tackle complex problems, evaluate information, and make well-informed decisions. Let’s dive in!

Introduction to Analytical and Critical Thinking

Analytical and critical thinking are two skills essential for solving problems and making decisions in various aspects of life. While both involve the use of logic and reasoning, they differ in their approach and outcomes. Analytical thinking involves breaking down complex information into smaller parts, while critical thinking involves taking a holistic view and evaluating information from different angles. Analytical thinking involves the ability to dissect a problem or situation into its individual components and examining each part separately. It requires careful observation and the ability to identify patterns and relationships. This type of thinking is essential for tasks such as data analysis, problem-solving, and troubleshooting.

Critical thinking, on the other hand, involves the ability to assess information objectively, evaluate its credibility, and make logical judgments. It involves questioning assumptions, examining evidence, and considering different perspectives. Critical thinking is crucial for making informed decisions, weighing pros and cons, and avoiding biases and fallacies.

Both analytical and critical thinking complement each other and are necessary for effective problem-solving and decision-making. Analytical thinking provides a structured and systematic approach to understanding complex problems , while critical thinking helps evaluate different options and make sound judgments.

Developing analytical and critical thinking skills can greatly benefit individuals in various aspects of life. In academia, these skills are necessary for understanding and interpreting complex subjects, conducting research, and writing analytical essays. In the workplace, analytical and critical thinking skills are highly valued by employers as they enable employees to solve problems efficiently and make informed decisions. In daily life, these skills are essential for evaluating information, distinguishing between fact and opinion, and making rational choices.

There are various ways to improve analytical and critical thinking skills. Engaging in activities that require logical reasoning, such as puzzles, brain teasers, and mathematical problems, can help develop analytical thinking abilities. Reading diverse sources of information, questioning assumptions, and actively seeking different perspectives can enhance critical thinking skills . Additionally, engaging in debates, discussions, and problem-solving exercises can promote both analytical and critical thinking.

Analytical and critical thinking skills are essential for problem-solving and decision-making in various aspects of life. They involve breaking down complex information and evaluating it from different angles. Developing these skills can lead to more effective problem-solving, informed decision-making, and overall improved cognitive abilities. 

Traits of an Analytical Thinker

An analytical thinker is one who is adept at breaking down complex problems into smaller parts. This type of thinking is linear and involves analyzing cause and effect relationships. Analytical thinking uses logic and reasoning to come to a conclusion, often relying on data and facts. Some key traits of an analytical thinker include:

• The ability to dissect complex information into smaller pieces.
• A knack for recognizing patterns and relationships.
• A methodical approach to problem-solving.

What Does It Mean to Think Critically?

Critical thinking, on the other hand, is a type of higher-order thinking that requires a more holistic approach. Critical thinkers are often skeptical, questioning the validity of information before accepting it. They are adept at evaluating information from various sources and are not easily swayed by outside information. Key aspects of critical thinking include :

• The ability to form an opinion based on evidence.
• Considering multiple perspectives before making a decision.
• Recognizing biases and challenging one’s own assumptions.

Analytical Thinking vs Critical Thinking: The Major Differences

While both analytical and critical thinking are essential for solving problems, they differ in several key ways:

• Approach : Analytical thinking is more linear and focuses on breaking down complex information into smaller parts. Critical thinking, however, is holistic and looks at the bigger picture.
• Use of Information : Analytical thinkers rely heavily on facts and data, while critical thinkers use facts in conjunction with other pieces of information and perspectives.
• Outcome : Analytical thinking often leads to a single logical conclusion, whereas critical thinking might result in multiple potential solutions or outcomes.

The Processes: Analytical Thinking Process vs Critical Thinking Process

Both styles of thinking have distinct processes:

• Analytical Thinking Process : Starts with gathering data, followed by breaking down complex problems, analyzing the cause and effect relationships, and finally drawing a conclusion.
• Critical Thinking Process : Begins with gathering diverse pieces of information, evaluating their validity, considering various perspectives, and finally forming an opinion or decision.

Using Analytical and Critical Thinking in Real Life Scenarios

In real-life scenarios, these thinking styles can be applied in various ways. For instance, when faced with a business decision, an analytical thinker might focus on the numbers and statistics, while a critical thinker might consider the potential impact on employees, company culture, and external stakeholders.

Analytical thinking can be particularly useful when analyzing financial data and making data-driven decisions. For example, a business owner might use analytical thinking to analyze the company’s financial statements and determine the profitability and financial health of the business. They might examine key financial ratios, such as return on investment or gross profit margin, to assess the efficiency and effectiveness of various business operations.

On the other hand, critical thinking can be applied when evaluating different options and considering the potential consequences of each option. For example, when considering a potential business expansion, a critical thinker may explore the potential impact on existing employees, the company’s culture, and the external stakeholders. They may assess the potential risks and benefits of the expansion, considering factors such as increased competition, resource allocation, and market demand.

Analytical and critical thinking can also be applied in personal decision-making. For example, when considering a major life decision such as buying a house or changing careers, analytical thinking can help weigh the financial implications, such as the monthly mortgage payments or future earning potential. Critical thinking can help evaluate the potential impact on personal goals, values, and overall satisfaction.

In everyday life, analytical thinking can be useful when evaluating product options or making purchasing decisions. For example, comparing different phone models based on features, specifications, and customer reviews can help individuals make an informed choice. Critical thinking can be applied when assessing the potential consequences of a decision, such as considering the long-term environmental impact of a product or the ethical practices of a particular company.

Both analytical and critical thinking are valuable skills in problem-solving. They can help individuals identify the root causes of a problem, analyze potential solutions, and evaluate their effectiveness. Whether it’s troubleshooting a technical issue, resolving a conflict, or devising strategies to improve personal or professional performance, these thinking styles can be instrumental in finding effective solutions. 

Analytical and Critical Thinking in Problem-Solving

Problem-solving requires a combination of both analytical and critical thinking. Analytical thinking helps break the problem into manageable parts, while critical thinking helps in evaluating potential solutions and considering their implications.

The Importance of Combining Both Thinking Styles

While both styles are powerful on their own, combining analytical and critical thinking skills can lead to more robust solutions. This combination allows for a thorough analysis of a problem while also considering the broader implications and potential consequences of a decision.

Mistakes to Avoid: Misconceptions about Analytical and Critical Thinking

Many assume that analytical thinking and critical thinking are one and the same, but this is a misconception. It’s important to recognize their distinct differences and strengths. Another common mistake is over-relying on one style and neglecting the other, leading to potential oversights in decision-making.

Key Takeaways: The Future of Analytical and Critical Thinking

In summary, here are the most important things to remember:

• Distinct yet Complementary : While analytical and critical thinking have distinct processes and outcomes, they are complementary and can be used together for more effective decision-making.
• Real-world Applications : Both styles are essential in various aspects of life, from business decisions to personal choices.
• Continuous Learning : As the world becomes more complex, honing both analytical and critical thinking skills will be crucial for success.

Embrace both styles of thinking and watch as your decision-making skills, problem-solving abilities, and overall understanding of complex situations improve dramatically.

Q: What is the difference between critical thinking and analytical thinking?

A: Critical thinking and analytical thinking are similar thinking skills, but there are some differences between the two. Critical thinking involves gathering information, evaluating and interpreting it, and then making a judgment or decision based on that information. Analytical thinking, on the other hand, focuses more on breaking down complex problems into smaller components, analyzing the relationships between these components, and coming up with solutions based on this analysis. So while both skills involve a logical and systematic approach to thinking, critical thinking is more focused on making judgments and decisions, whereas analytical thinking is more focused on problem-solving and analysis.

Q: How do I use critical thinking in everyday life?

A: Critical thinking is a valuable skill that can be applied in various aspects of everyday life. To use critical thinking, you need to approach situations and problems with an open and questioning mind. This involves challenging your own assumptions and beliefs, gathering and evaluating information from different sources, considering alternative perspectives, and making informed decisions based on evidence and logical reasoning. By using critical thinking, you can enhance your problem-solving skills, improve your decision-making abilities , and think more creatively and independently.

Q: How do I use analytical thinking in my professional life?

A: Analytical thinking is an important skill in many professional fields. To use analytical thinking, you need to be able to break down complex problems or tasks into smaller parts, analyze the relationships between these parts, and come up with logical and well-reasoned solutions. This involves gathering and evaluating relevant data, identifying patterns or trends, and using logical reasoning to draw conclusions. By using analytical thinking, you can improve your problem-solving and decision-making abilities, demonstrate a logical and organized approach to your work, and effectively communicate your analysis and solutions to others.

Q: Can critical thinking and analytical thinking be used together?

A: Yes, critical thinking and analytical thinking are complementary skills that can be used together. Both skills involve a systematic and logical approach to thinking, and they can reinforce each other in problem-solving and decision-making processes. Critical thinking provides the framework for evaluating and interpreting information, while analytical thinking provides the tools for breaking down complex problems and finding solutions. By using both skills together, you can enhance your ability to think critically and analytically, make more informed decisions, and solve problems more effectively.

Q: What are the differences between analytical reasoning and critical thinking?

A: Analytical reasoning and critical thinking are related skills that involve a logical and systematic approach to thinking. However, there are some differences between the two. Analytical reasoning is more focused on the process of breaking down complex problems or arguments, identifying logical relationships between different elements, and drawing conclusions based on this analysis. Critical thinking, on the other hand, is a broader skill that involves evaluating and interpreting information, questioning assumptions and biases, and making judgments or decisions based on evidence and logical reasoning. While analytical reasoning is an important part of critical thinking, critical thinking encompasses a wider range of cognitive processes and skills.

Q: How can I develop and improve my analytical thinking skills?

A: To develop and improve your analytical thinking skills, you can engage in activities that stimulate your logical and problem-solving abilities. This may involve practicing with puzzles and brainteasers, analyzing case studies or real-life scenarios, participating in debates or discussions, learning and applying different analytical frameworks or models, and seeking feedback on your analytical thinking from others. Additionally, you can also cultivate your analytical thinking skills by staying curious, asking thoughtful questions, and continuously seeking new knowledge and perspectives. With practice and perseverance, you can enhance your analytical thinking abilities and become a more effective problem solver and decision maker.

Q: How can I become a critical thinker?

A: Becoming a critical thinker requires a conscious effort to develop and refine your thinking skills. Here are some steps you can take to become a critical thinker : 1. Cultivate intellectual humility and open-mindedness: Be willing to consider alternative viewpoints and challenge your own assumptions and beliefs. 2. Develop strong analytical and reasoning skills: Learn to gather and evaluate evidence, identify logical fallacies, and draw logical and well-supported conclusions. 3. Practice active listening and effective communication: Listen attentively to others’ perspectives, ask thoughtful questions, and communicate your own ideas clearly and persuasively. 4. Seek out diverse sources of information: Expose yourself to different perspectives and viewpoints to broaden your understanding and avoid bias. 5. Reflect and evaluate your own thinking: Regularly reflect on your own thinking processes, identify any biases or logical gaps, and work on improving your critical thinking skills.

Q: What role does critical thinking play in problem-solving?

A: Critical thinking is a fundamental skill in problem-solving. It helps you approach problems with a logical and systematic mindset, evaluate potential solutions, and make informed decisions. Critical thinking allows you to gather and analyze relevant information, identify patterns or trends, consider different perspectives or alternatives, weigh the pros and cons, and choose the most effective solution. By using critical thinking in problem-solving, you can enhance your ability to find creative and innovative solutions, overcome obstacles, and make well-informed decisions that are based on sound reasoning and evidence.

Q: Why is critical thinking important?

A: Critical thinking is important because it enables you to think independently, make informed decisions, solve problems effectively, and evaluate information and arguments critically. In a rapidly changing and complex world, critical thinking allows you to navigate through information overload, identify biases or misinformation, and make sense of a wide range of conflicting information. It also helps you develop a deep understanding of concepts and ideas, construct well-reasoned arguments, and communicate your thoughts effectively. In both personal and professional contexts, critical thinking is a valuable skill that empowers you to be a more effective and successful individual.

Q: How does analytical thinking contribute to problem-solving?

A: Analytical thinking is a key component of problem-solving. It involves breaking down complex problems into smaller components, analyzing the relationships between these components, and identifying patterns or trends. Analytical thinking helps you understand the underlying causes of problems, explore different possible solutions, and evaluate their feasibility and effectiveness. By using analytical thinking, you can approach problems in a structured and systematic way, make well-informed decisions, and find creative and innovative solutions. Analytical thinking provides a solid foundation for problem-solving, enabling you to effectively address challenges and find solutions in various domains.

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7 Module 7: Thinking, Reasoning, and Problem-Solving

This module is about how a solid working knowledge of psychological principles can help you to think more effectively, so you can succeed in school and life. You might be inclined to believe that—because you have been thinking for as long as you can remember, because you are able to figure out the solution to many problems, because you feel capable of using logic to argue a point, because you can evaluate whether the things you read and hear make sense—you do not need any special training in thinking. But this, of course, is one of the key barriers to helping people think better. If you do not believe that there is anything wrong, why try to fix it?

The human brain is indeed a remarkable thinking machine, capable of amazing, complex, creative, logical thoughts. Why, then, are we telling you that you need to learn how to think? Mainly because one major lesson from cognitive psychology is that these capabilities of the human brain are relatively infrequently realized. Many psychologists believe that people are essentially “cognitive misers.” It is not that we are lazy, but that we have a tendency to expend the least amount of mental effort necessary. Although you may not realize it, it actually takes a great deal of energy to think. Careful, deliberative reasoning and critical thinking are very difficult. Because we seem to be successful without going to the trouble of using these skills well, it feels unnecessary to develop them. As you shall see, however, there are many pitfalls in the cognitive processes described in this module. When people do not devote extra effort to learning and improving reasoning, problem solving, and critical thinking skills, they make many errors.

As is true for memory, if you develop the cognitive skills presented in this module, you will be more successful in school. It is important that you realize, however, that these skills will help you far beyond school, even more so than a good memory will. Although it is somewhat useful to have a good memory, ten years from now no potential employer will care how many questions you got right on multiple choice exams during college. All of them will, however, recognize whether you are a logical, analytical, critical thinker. With these thinking skills, you will be an effective, persuasive communicator and an excellent problem solver.

The module begins by describing different kinds of thought and knowledge, especially conceptual knowledge and critical thinking. An understanding of these differences will be valuable as you progress through school and encounter different assignments that require you to tap into different kinds of knowledge. The second section covers deductive and inductive reasoning, which are processes we use to construct and evaluate strong arguments. They are essential skills to have whenever you are trying to persuade someone (including yourself) of some point, or to respond to someone’s efforts to persuade you. The module ends with a section about problem solving. A solid understanding of the key processes involved in problem solving will help you to handle many daily challenges.

7.1. Different kinds of thought

7.2. Reasoning and Judgment

7.3. Problem Solving

READING WITH PURPOSE

Remember and understand.

By reading and studying Module 7, you should be able to remember and describe:

• Concepts and inferences (7.1)
• Procedural knowledge (7.1)
• Metacognition (7.1)
• Characteristics of critical thinking:  skepticism; identify biases, distortions, omissions, and assumptions; reasoning and problem solving skills  (7.1)
• Reasoning:  deductive reasoning, deductively valid argument, inductive reasoning, inductively strong argument, availability heuristic, representativeness heuristic  (7.2)
• Fixation:  functional fixedness, mental set  (7.3)
• Algorithms, heuristics, and the role of confirmation bias (7.3)
• Effective problem solving sequence (7.3)

By reading and thinking about how the concepts in Module 6 apply to real life, you should be able to:

• Identify which type of knowledge a piece of information is (7.1)
• Recognize examples of deductive and inductive reasoning (7.2)
• Recognize judgments that have probably been influenced by the availability heuristic (7.2)
• Recognize examples of problem solving heuristics and algorithms (7.3)

Analyze, Evaluate, and Create

By reading and thinking about Module 6, participating in classroom activities, and completing out-of-class assignments, you should be able to:

• Use the principles of critical thinking to evaluate information (7.1)
• Explain whether examples of reasoning arguments are deductively valid or inductively strong (7.2)
• Outline how you could try to solve a problem from your life using the effective problem solving sequence (7.3)

7.1. Different kinds of thought and knowledge

• Take a few minutes to write down everything that you know about dogs.
• Do you believe that:
• Psychic ability exists?
• Hypnosis is an altered state of consciousness?
• Magnet therapy is effective for relieving pain?
• Aerobic exercise is an effective treatment for depression?
• UFO’s from outer space have visited earth?

On what do you base your belief or disbelief for the questions above?

Of course, we all know what is meant by the words  think  and  knowledge . You probably also realize that they are not unitary concepts; there are different kinds of thought and knowledge. In this section, let us look at some of these differences. If you are familiar with these different kinds of thought and pay attention to them in your classes, it will help you to focus on the right goals, learn more effectively, and succeed in school. Different assignments and requirements in school call on you to use different kinds of knowledge or thought, so it will be very helpful for you to learn to recognize them (Anderson, et al. 2001).

Factual and conceptual knowledge

Module 5 introduced the idea of declarative memory, which is composed of facts and episodes. If you have ever played a trivia game or watched Jeopardy on TV, you realize that the human brain is able to hold an extraordinary number of facts. Likewise, you realize that each of us has an enormous store of episodes, essentially facts about events that happened in our own lives. It may be difficult to keep that in mind when we are struggling to retrieve one of those facts while taking an exam, however. Part of the problem is that, in contradiction to the advice from Module 5, many students continue to try to memorize course material as a series of unrelated facts (picture a history student simply trying to memorize history as a set of unrelated dates without any coherent story tying them together). Facts in the real world are not random and unorganized, however. It is the way that they are organized that constitutes a second key kind of knowledge, conceptual.

Concepts are nothing more than our mental representations of categories of things in the world. For example, think about dogs. When you do this, you might remember specific facts about dogs, such as they have fur and they bark. You may also recall dogs that you have encountered and picture them in your mind. All of this information (and more) makes up your concept of dog. You can have concepts of simple categories (e.g., triangle), complex categories (e.g., small dogs that sleep all day, eat out of the garbage, and bark at leaves), kinds of people (e.g., psychology professors), events (e.g., birthday parties), and abstract ideas (e.g., justice). Gregory Murphy (2002) refers to concepts as the “glue that holds our mental life together” (p. 1). Very simply, summarizing the world by using concepts is one of the most important cognitive tasks that we do. Our conceptual knowledge  is  our knowledge about the world. Individual concepts are related to each other to form a rich interconnected network of knowledge. For example, think about how the following concepts might be related to each other: dog, pet, play, Frisbee, chew toy, shoe. Or, of more obvious use to you now, how these concepts are related: working memory, long-term memory, declarative memory, procedural memory, and rehearsal? Because our minds have a natural tendency to organize information conceptually, when students try to remember course material as isolated facts, they are working against their strengths.

One last important point about concepts is that they allow you to instantly know a great deal of information about something. For example, if someone hands you a small red object and says, “here is an apple,” they do not have to tell you, “it is something you can eat.” You already know that you can eat it because it is true by virtue of the fact that the object is an apple; this is called drawing an  inference , assuming that something is true on the basis of your previous knowledge (for example, of category membership or of how the world works) or logical reasoning.

Procedural knowledge

Physical skills, such as tying your shoes, doing a cartwheel, and driving a car (or doing all three at the same time, but don’t try this at home) are certainly a kind of knowledge. They are procedural knowledge, the same idea as procedural memory that you saw in Module 5. Mental skills, such as reading, debating, and planning a psychology experiment, are procedural knowledge, as well. In short, procedural knowledge is the knowledge how to do something (Cohen & Eichenbaum, 1993).

Metacognitive knowledge

Floyd used to think that he had a great memory. Now, he has a better memory. Why? Because he finally realized that his memory was not as great as he once thought it was. Because Floyd eventually learned that he often forgets where he put things, he finally developed the habit of putting things in the same place. (Unfortunately, he did not learn this lesson before losing at least 5 watches and a wedding ring.) Because he finally realized that he often forgets to do things, he finally started using the To Do list app on his phone. And so on. Floyd’s insights about the real limitations of his memory have allowed him to remember things that he used to forget.

All of us have knowledge about the way our own minds work. You may know that you have a good memory for people’s names and a poor memory for math formulas. Someone else might realize that they have difficulty remembering to do things, like stopping at the store on the way home. Others still know that they tend to overlook details. This knowledge about our own thinking is actually quite important; it is called metacognitive knowledge, or  metacognition . Like other kinds of thinking skills, it is subject to error. For example, in unpublished research, one of the authors surveyed about 120 General Psychology students on the first day of the term. Among other questions, the students were asked them to predict their grade in the class and report their current Grade Point Average. Two-thirds of the students predicted that their grade in the course would be higher than their GPA. (The reality is that at our college, students tend to earn lower grades in psychology than their overall GPA.) Another example: Students routinely report that they thought they had done well on an exam, only to discover, to their dismay, that they were wrong (more on that important problem in a moment). Both errors reveal a breakdown in metacognition.

The Dunning-Kruger Effect

In general, most college students probably do not study enough. For example, using data from the National Survey of Student Engagement, Fosnacht, McCormack, and Lerma (2018) reported that first-year students at 4-year colleges in the U.S. averaged less than 14 hours per week preparing for classes. The typical suggestion is that you should spend two hours outside of class for every hour in class, or 24 – 30 hours per week for a full-time student. Clearly, students in general are nowhere near that recommended mark. Many observers, including some faculty, believe that this shortfall is a result of students being too busy or lazy. Now, it may be true that many students are too busy, with work and family obligations, for example. Others, are not particularly motivated in school, and therefore might correctly be labeled lazy. A third possible explanation, however, is that some students might not think they need to spend this much time. And this is a matter of metacognition. Consider the scenario that we mentioned above, students thinking they had done well on an exam only to discover that they did not. Justin Kruger and David Dunning examined scenarios very much like this in 1999. Kruger and Dunning gave research participants tests measuring humor, logic, and grammar. Then, they asked the participants to assess their own abilities and test performance in these areas. They found that participants in general tended to overestimate their abilities, already a problem with metacognition. Importantly, the participants who scored the lowest overestimated their abilities the most. Specifically, students who scored in the bottom quarter (averaging in the 12th percentile) thought they had scored in the 62nd percentile. This has become known as the  Dunning-Kruger effect . Many individual faculty members have replicated these results with their own student on their course exams, including the authors of this book. Think about it. Some students who just took an exam and performed poorly believe that they did well before seeing their score. It seems very likely that these are the very same students who stopped studying the night before because they thought they were “done.” Quite simply, it is not just that they did not know the material. They did not know that they did not know the material. That is poor metacognition.

In order to develop good metacognitive skills, you should continually monitor your thinking and seek frequent feedback on the accuracy of your thinking (Medina, Castleberry, & Persky 2017). For example, in classes get in the habit of predicting your exam grades. As soon as possible after taking an exam, try to find out which questions you missed and try to figure out why. If you do this soon enough, you may be able to recall the way it felt when you originally answered the question. Did you feel confident that you had answered the question correctly? Then you have just discovered an opportunity to improve your metacognition. Be on the lookout for that feeling and respond with caution.

concept :  a mental representation of a category of things in the world

Dunning-Kruger effect : individuals who are less competent tend to overestimate their abilities more than individuals who are more competent do

inference : an assumption about the truth of something that is not stated. Inferences come from our prior knowledge and experience, and from logical reasoning

metacognition :  knowledge about one’s own cognitive processes; thinking about your thinking

Critical thinking

One particular kind of knowledge or thinking skill that is related to metacognition is  critical thinking (Chew, 2020). You may have noticed that critical thinking is an objective in many college courses, and thus it could be a legitimate topic to cover in nearly any college course. It is particularly appropriate in psychology, however. As the science of (behavior and) mental processes, psychology is obviously well suited to be the discipline through which you should be introduced to this important way of thinking.

More importantly, there is a particular need to use critical thinking in psychology. We are all, in a way, experts in human behavior and mental processes, having engaged in them literally since birth. Thus, perhaps more than in any other class, students typically approach psychology with very clear ideas and opinions about its subject matter. That is, students already “know” a lot about psychology. The problem is, “it ain’t so much the things we don’t know that get us into trouble. It’s the things we know that just ain’t so” (Ward, quoted in Gilovich 1991). Indeed, many of students’ preconceptions about psychology are just plain wrong. Randolph Smith (2002) wrote a book about critical thinking in psychology called  Challenging Your Preconceptions,  highlighting this fact. On the other hand, many of students’ preconceptions about psychology are just plain right! But wait, how do you know which of your preconceptions are right and which are wrong? And when you come across a research finding or theory in this class that contradicts your preconceptions, what will you do? Will you stick to your original idea, discounting the information from the class? Will you immediately change your mind? Critical thinking can help us sort through this confusing mess.

But what is critical thinking? The goal of critical thinking is simple to state (but extraordinarily difficult to achieve): it is to be right, to draw the correct conclusions, to believe in things that are true and to disbelieve things that are false. We will provide two definitions of critical thinking (or, if you like, one large definition with two distinct parts). First, a more conceptual one: Critical thinking is thinking like a scientist in your everyday life (Schmaltz, Jansen, & Wenckowski, 2017).  Our second definition is more operational; it is simply a list of skills that are essential to be a critical thinker. Critical thinking entails solid reasoning and problem solving skills; skepticism; and an ability to identify biases, distortions, omissions, and assumptions. Excellent deductive and inductive reasoning, and problem solving skills contribute to critical thinking. So, you can consider the subject matter of sections 7.2 and 7.3 to be part of critical thinking. Because we will be devoting considerable time to these concepts in the rest of the module, let us begin with a discussion about the other aspects of critical thinking.

Let’s address that first part of the definition. Scientists form hypotheses, or predictions about some possible future observations. Then, they collect data, or information (think of this as making those future observations). They do their best to make unbiased observations using reliable techniques that have been verified by others. Then, and only then, they draw a conclusion about what those observations mean. Oh, and do not forget the most important part. “Conclusion” is probably not the most appropriate word because this conclusion is only tentative. A scientist is always prepared that someone else might come along and produce new observations that would require a new conclusion be drawn. Wow! If you like to be right, you could do a lot worse than using a process like this.

A Critical Thinker’s Toolkit 

Now for the second part of the definition. Good critical thinkers (and scientists) rely on a variety of tools to evaluate information. Perhaps the most recognizable tool for critical thinking is  skepticism (and this term provides the clearest link to the thinking like a scientist definition, as you are about to see). Some people intend it as an insult when they call someone a skeptic. But if someone calls you a skeptic, if they are using the term correctly, you should consider it a great compliment. Simply put, skepticism is a way of thinking in which you refrain from drawing a conclusion or changing your mind until good evidence has been provided. People from Missouri should recognize this principle, as Missouri is known as the Show-Me State. As a skeptic, you are not inclined to believe something just because someone said so, because someone else believes it, or because it sounds reasonable. You must be persuaded by high quality evidence.

Of course, if that evidence is produced, you have a responsibility as a skeptic to change your belief. Failure to change a belief in the face of good evidence is not skepticism; skepticism has open mindedness at its core. M. Neil Browne and Stuart Keeley (2018) use the term weak sense critical thinking to describe critical thinking behaviors that are used only to strengthen a prior belief. Strong sense critical thinking, on the other hand, has as its goal reaching the best conclusion. Sometimes that means strengthening your prior belief, but sometimes it means changing your belief to accommodate the better evidence.

Many times, a failure to think critically or weak sense critical thinking is related to a  bias , an inclination, tendency, leaning, or prejudice. Everybody has biases, but many people are unaware of them. Awareness of your own biases gives you the opportunity to control or counteract them. Unfortunately, however, many people are happy to let their biases creep into their attempts to persuade others; indeed, it is a key part of their persuasive strategy. To see how these biases influence messages, just look at the different descriptions and explanations of the same events given by people of different ages or income brackets, or conservative versus liberal commentators, or by commentators from different parts of the world. Of course, to be successful, these people who are consciously using their biases must disguise them. Even undisguised biases can be difficult to identify, so disguised ones can be nearly impossible.

Here are some common sources of biases:

• Personal values and beliefs.  Some people believe that human beings are basically driven to seek power and that they are typically in competition with one another over scarce resources. These beliefs are similar to the world-view that political scientists call “realism.” Other people believe that human beings prefer to cooperate and that, given the chance, they will do so. These beliefs are similar to the world-view known as “idealism.” For many people, these deeply held beliefs can influence, or bias, their interpretations of such wide ranging situations as the behavior of nations and their leaders or the behavior of the driver in the car ahead of you. For example, if your worldview is that people are typically in competition and someone cuts you off on the highway, you may assume that the driver did it purposely to get ahead of you. Other types of beliefs about the way the world is or the way the world should be, for example, political beliefs, can similarly become a significant source of bias.
• Racism, sexism, ageism and other forms of prejudice and bigotry.  These are, sadly, a common source of bias in many people. They are essentially a special kind of “belief about the way the world is.” These beliefs—for example, that women do not make effective leaders—lead people to ignore contradictory evidence (examples of effective women leaders, or research that disputes the belief) and to interpret ambiguous evidence in a way consistent with the belief.
• Self-interest.  When particular people benefit from things turning out a certain way, they can sometimes be very susceptible to letting that interest bias them. For example, a company that will earn a profit if they sell their product may have a bias in the way that they give information about their product. A union that will benefit if its members get a generous contract might have a bias in the way it presents information about salaries at competing organizations. (Note that our inclusion of examples describing both companies and unions is an explicit attempt to control for our own personal biases). Home buyers are often dismayed to discover that they purchased their dream house from someone whose self-interest led them to lie about flooding problems in the basement or back yard. This principle, the biasing power of self-interest, is likely what led to the famous phrase  Caveat Emptor  (let the buyer beware) .  

Knowing that these types of biases exist will help you evaluate evidence more critically. Do not forget, though, that people are not always keen to let you discover the sources of biases in their arguments. For example, companies or political organizations can sometimes disguise their support of a research study by contracting with a university professor, who comes complete with a seemingly unbiased institutional affiliation, to conduct the study.

People’s biases, conscious or unconscious, can lead them to make omissions, distortions, and assumptions that undermine our ability to correctly evaluate evidence. It is essential that you look for these elements. Always ask, what is missing, what is not as it appears, and what is being assumed here? For example, consider this (fictional) chart from an ad reporting customer satisfaction at 4 local health clubs.

Clearly, from the results of the chart, one would be tempted to give Club C a try, as customer satisfaction is much higher than for the other 3 clubs.

There are so many distortions and omissions in this chart, however, that it is actually quite meaningless. First, how was satisfaction measured? Do the bars represent responses to a survey? If so, how were the questions asked? Most importantly, where is the missing scale for the chart? Although the differences look quite large, are they really?

Well, here is the same chart, with a different scale, this time labeled:

Club C is not so impressive any more, is it? In fact, all of the health clubs have customer satisfaction ratings (whatever that means) between 85% and 88%. In the first chart, the entire scale of the graph included only the percentages between 83 and 89. This “judicious” choice of scale—some would call it a distortion—and omission of that scale from the chart make the tiny differences among the clubs seem important, however.

Also, in order to be a critical thinker, you need to learn to pay attention to the assumptions that underlie a message. Let us briefly illustrate the role of assumptions by touching on some people’s beliefs about the criminal justice system in the US. Some believe that a major problem with our judicial system is that many criminals go free because of legal technicalities. Others believe that a major problem is that many innocent people are convicted of crimes. The simple fact is, both types of errors occur. A person’s conclusion about which flaw in our judicial system is the greater tragedy is based on an assumption about which of these is the more serious error (letting the guilty go free or convicting the innocent). This type of assumption is called a value assumption (Browne and Keeley, 2018). It reflects the differences in values that people develop, differences that may lead us to disregard valid evidence that does not fit in with our particular values.

Oh, by the way, some students probably noticed this, but the seven tips for evaluating information that we shared in Module 1 are related to this. Actually, they are part of this section. The tips are, to a very large degree, set of ideas you can use to help you identify biases, distortions, omissions, and assumptions. If you do not remember this section, we strongly recommend you take a few minutes to review it.

skepticism :  a way of thinking in which you refrain from drawing a conclusion or changing your mind until good evidence has been provided

bias : an inclination, tendency, leaning, or prejudice

• Which of your beliefs (or disbeliefs) from the Activate exercise for this section were derived from a process of critical thinking? If some of your beliefs were not based on critical thinking, are you willing to reassess these beliefs? If the answer is no, why do you think that is? If the answer is yes, what concrete steps will you take?

7.2 Reasoning and Judgment

• What percentage of kidnappings are committed by strangers?
• Which area of the house is riskiest: kitchen, bathroom, or stairs?
• What is the most common cancer in the US?
• What percentage of workplace homicides are committed by co-workers?

An essential set of procedural thinking skills is  reasoning , the ability to generate and evaluate solid conclusions from a set of statements or evidence. You should note that these conclusions (when they are generated instead of being evaluated) are one key type of inference that we described in Section 7.1. There are two main types of reasoning, deductive and inductive.

Deductive reasoning

Suppose your teacher tells you that if you get an A on the final exam in a course, you will get an A for the whole course. Then, you get an A on the final exam. What will your final course grade be? Most people can see instantly that you can conclude with certainty that you will get an A for the course. This is a type of reasoning called  deductive reasoning , which is defined as reasoning in which a conclusion is guaranteed to be true as long as the statements leading to it are true. The three statements can be listed as an  argument , with two beginning statements and a conclusion:

Statement 1: If you get an A on the final exam, you will get an A for the course

Statement 2: You get an A on the final exam

Conclusion: You will get an A for the course

This particular arrangement, in which true beginning statements lead to a guaranteed true conclusion, is known as a  deductively valid argument . Although deductive reasoning is often the subject of abstract, brain-teasing, puzzle-like word problems, it is actually an extremely important type of everyday reasoning. It is just hard to recognize sometimes. For example, imagine that you are looking for your car keys and you realize that they are either in the kitchen drawer or in your book bag. After looking in the kitchen drawer, you instantly know that they must be in your book bag. That conclusion results from a simple deductive reasoning argument. In addition, solid deductive reasoning skills are necessary for you to succeed in the sciences, philosophy, math, computer programming, and any endeavor involving the use of logic to persuade others to your point of view or to evaluate others’ arguments.

Cognitive psychologists, and before them philosophers, have been quite interested in deductive reasoning, not so much for its practical applications, but for the insights it can offer them about the ways that human beings think. One of the early ideas to emerge from the examination of deductive reasoning is that people learn (or develop) mental versions of rules that allow them to solve these types of reasoning problems (Braine, 1978; Braine, Reiser, & Rumain, 1984). The best way to see this point of view is to realize that there are different possible rules, and some of them are very simple. For example, consider this rule of logic:

therefore q

Logical rules are often presented abstractly, as letters, in order to imply that they can be used in very many specific situations. Here is a concrete version of the of the same rule:

I’ll either have pizza or a hamburger for dinner tonight (p or q)

I won’t have pizza (not p)

Therefore, I’ll have a hamburger (therefore q)

This kind of reasoning seems so natural, so easy, that it is quite plausible that we would use a version of this rule in our daily lives. At least, it seems more plausible than some of the alternative possibilities—for example, that we need to have experience with the specific situation (pizza or hamburger, in this case) in order to solve this type of problem easily. So perhaps there is a form of natural logic (Rips, 1990) that contains very simple versions of logical rules. When we are faced with a reasoning problem that maps onto one of these rules, we use the rule.

But be very careful; things are not always as easy as they seem. Even these simple rules are not so simple. For example, consider the following rule. Many people fail to realize that this rule is just as valid as the pizza or hamburger rule above.

if p, then q

therefore, not p

Concrete version:

If I eat dinner, then I will have dessert

I did not have dessert

Therefore, I did not eat dinner

The simple fact is, it can be very difficult for people to apply rules of deductive logic correctly; as a result, they make many errors when trying to do so. Is this a deductively valid argument or not?

Students who like school study a lot

Students who study a lot get good grades

Jane does not like school

Therefore, Jane does not get good grades

Many people are surprised to discover that this is not a logically valid argument; the conclusion is not guaranteed to be true from the beginning statements. Although the first statement says that students who like school study a lot, it does NOT say that students who do not like school do not study a lot. In other words, it may very well be possible to study a lot without liking school. Even people who sometimes get problems like this right might not be using the rules of deductive reasoning. Instead, they might just be making judgments for examples they know, in this case, remembering instances of people who get good grades despite not liking school.

Making deductive reasoning even more difficult is the fact that there are two important properties that an argument may have. One, it can be valid or invalid (meaning that the conclusion does or does not follow logically from the statements leading up to it). Two, an argument (or more correctly, its conclusion) can be true or false. Here is an example of an argument that is logically valid, but has a false conclusion (at least we think it is false).

Either you are eleven feet tall or the Grand Canyon was created by a spaceship crashing into the earth.

You are not eleven feet tall

Therefore the Grand Canyon was created by a spaceship crashing into the earth

This argument has the exact same form as the pizza or hamburger argument above, making it is deductively valid. The conclusion is so false, however, that it is absurd (of course, the reason the conclusion is false is that the first statement is false). When people are judging arguments, they tend to not observe the difference between deductive validity and the empirical truth of statements or conclusions. If the elements of an argument happen to be true, people are likely to judge the argument logically valid; if the elements are false, they will very likely judge it invalid (Markovits & Bouffard-Bouchard, 1992; Moshman & Franks, 1986). Thus, it seems a stretch to say that people are using these logical rules to judge the validity of arguments. Many psychologists believe that most people actually have very limited deductive reasoning skills (Johnson-Laird, 1999). They argue that when faced with a problem for which deductive logic is required, people resort to some simpler technique, such as matching terms that appear in the statements and the conclusion (Evans, 1982). This might not seem like a problem, but what if reasoners believe that the elements are true and they happen to be wrong; they will would believe that they are using a form of reasoning that guarantees they are correct and yet be wrong.

deductive reasoning :  a type of reasoning in which the conclusion is guaranteed to be true any time the statements leading up to it are true

argument :  a set of statements in which the beginning statements lead to a conclusion

deductively valid argument :  an argument for which true beginning statements guarantee that the conclusion is true

Inductive reasoning and judgment

Every day, you make many judgments about the likelihood of one thing or another. Whether you realize it or not, you are practicing  inductive reasoning   on a daily basis. In inductive reasoning arguments, a conclusion is likely whenever the statements preceding it are true. The first thing to notice about inductive reasoning is that, by definition, you can never be sure about your conclusion; you can only estimate how likely the conclusion is. Inductive reasoning may lead you to focus on Memory Encoding and Recoding when you study for the exam, but it is possible the instructor will ask more questions about Memory Retrieval instead. Unlike deductive reasoning, the conclusions you reach through inductive reasoning are only probable, not certain. That is why scientists consider inductive reasoning weaker than deductive reasoning. But imagine how hard it would be for us to function if we could not act unless we were certain about the outcome.

Inductive reasoning can be represented as logical arguments consisting of statements and a conclusion, just as deductive reasoning can be. In an inductive argument, you are given some statements and a conclusion (or you are given some statements and must draw a conclusion). An argument is  inductively strong   if the conclusion would be very probable whenever the statements are true. So, for example, here is an inductively strong argument:

• Statement #1: The forecaster on Channel 2 said it is going to rain today.
• Statement #2: The forecaster on Channel 5 said it is going to rain today.
• Statement #3: It is very cloudy and humid.
• Statement #4: You just heard thunder.
• Conclusion (or judgment): It is going to rain today.

Think of the statements as evidence, on the basis of which you will draw a conclusion. So, based on the evidence presented in the four statements, it is very likely that it will rain today. Will it definitely rain today? Certainly not. We can all think of times that the weather forecaster was wrong.

A true story: Some years ago psychology student was watching a baseball playoff game between the St. Louis Cardinals and the Los Angeles Dodgers. A graphic on the screen had just informed the audience that the Cardinal at bat, (Hall of Fame shortstop) Ozzie Smith, a switch hitter batting left-handed for this plate appearance, had never, in nearly 3000 career at-bats, hit a home run left-handed. The student, who had just learned about inductive reasoning in his psychology class, turned to his companion (a Cardinals fan) and smugly said, “It is an inductively strong argument that Ozzie Smith will not hit a home run.” He turned back to face the television just in time to watch the ball sail over the right field fence for a home run. Although the student felt foolish at the time, he was not wrong. It was an inductively strong argument; 3000 at-bats is an awful lot of evidence suggesting that the Wizard of Ozz (as he was known) would not be hitting one out of the park (think of each at-bat without a home run as a statement in an inductive argument). Sadly (for the die-hard Cubs fan and Cardinals-hating student), despite the strength of the argument, the conclusion was wrong.

Given the possibility that we might draw an incorrect conclusion even with an inductively strong argument, we really want to be sure that we do, in fact, make inductively strong arguments. If we judge something probable, it had better be probable. If we judge something nearly impossible, it had better not happen. Think of inductive reasoning, then, as making reasonably accurate judgments of the probability of some conclusion given a set of evidence.

We base many decisions in our lives on inductive reasoning. For example:

Statement #1: Psychology is not my best subject

Statement #2: My psychology instructor has a reputation for giving difficult exams

Statement #3: My first psychology exam was much harder than I expected

Judgment: The next exam will probably be very difficult.

Decision: I will study tonight instead of watching Netflix.

Some other examples of judgments that people commonly make in a school context include judgments of the likelihood that:

• A particular class will be interesting/useful/difficult
• You will be able to finish writing a paper by next week if you go out tonight
• Your laptop’s battery will last through the next trip to the library
• You will not miss anything important if you skip class tomorrow
• Your instructor will not notice if you skip class tomorrow
• You will be able to find a book that you will need for a paper
• There will be an essay question about Memory Encoding on the next exam

Tversky and Kahneman (1983) recognized that there are two general ways that we might make these judgments; they termed them extensional (i.e., following the laws of probability) and intuitive (i.e., using shortcuts or heuristics, see below). We will use a similar distinction between Type 1 and Type 2 thinking, as described by Keith Stanovich and his colleagues (Evans and Stanovich, 2013; Stanovich and West, 2000). Type 1 thinking is fast, automatic, effortful, and emotional. In fact, it is hardly fair to call it reasoning at all, as judgments just seem to pop into one’s head. Type 2 thinking , on the other hand, is slow, effortful, and logical. So obviously, it is more likely to lead to a correct judgment, or an optimal decision. The problem is, we tend to over-rely on Type 1. Now, we are not saying that Type 2 is the right way to go for every decision or judgment we make. It seems a bit much, for example, to engage in a step-by-step logical reasoning procedure to decide whether we will have chicken or fish for dinner tonight.

Many bad decisions in some very important contexts, however, can be traced back to poor judgments of the likelihood of certain risks or outcomes that result from the use of Type 1 when a more logical reasoning process would have been more appropriate. For example:

Statement #1: It is late at night.

Statement #2: Albert has been drinking beer for the past five hours at a party.

Statement #3: Albert is not exactly sure where he is or how far away home is.

Judgment: Albert will have no difficulty walking home.

Decision: He walks home alone.

As you can see in this example, the three statements backing up the judgment do not really support it. In other words, this argument is not inductively strong because it is based on judgments that ignore the laws of probability. What are the chances that someone facing these conditions will be able to walk home alone easily? And one need not be drunk to make poor decisions based on judgments that just pop into our heads.

The truth is that many of our probability judgments do not come very close to what the laws of probability say they should be. Think about it. In order for us to reason in accordance with these laws, we would need to know the laws of probability, which would allow us to calculate the relationship between particular pieces of evidence and the probability of some outcome (i.e., how much likelihood should change given a piece of evidence), and we would have to do these heavy math calculations in our heads. After all, that is what Type 2 requires. Needless to say, even if we were motivated, we often do not even know how to apply Type 2 reasoning in many cases.

So what do we do when we don’t have the knowledge, skills, or time required to make the correct mathematical judgment? Do we hold off and wait until we can get better evidence? Do we read up on probability and fire up our calculator app so we can compute the correct probability? Of course not. We rely on Type 1 thinking. We “wing it.” That is, we come up with a likelihood estimate using some means at our disposal. Psychologists use the term heuristic to describe the type of “winging it” we are talking about. A  heuristic   is a shortcut strategy that we use to make some judgment or solve some problem (see Section 7.3). Heuristics are easy and quick, think of them as the basic procedures that are characteristic of Type 1.  They can absolutely lead to reasonably good judgments and decisions in some situations (like choosing between chicken and fish for dinner). They are, however, far from foolproof. There are, in fact, quite a lot of situations in which heuristics can lead us to make incorrect judgments, and in many cases the decisions based on those judgments can have serious consequences.

Let us return to the activity that begins this section. You were asked to judge the likelihood (or frequency) of certain events and risks. You were free to come up with your own evidence (or statements) to make these judgments. This is where a heuristic crops up. As a judgment shortcut, we tend to generate specific examples of those very events to help us decide their likelihood or frequency. For example, if we are asked to judge how common, frequent, or likely a particular type of cancer is, many of our statements would be examples of specific cancer cases:

Statement #1: Andy Kaufman (comedian) had lung cancer.

Statement #2: Colin Powell (US Secretary of State) had prostate cancer.

Statement #3: Bob Marley (musician) had skin and brain cancer

Statement #4: Sandra Day O’Connor (Supreme Court Justice) had breast cancer.

Statement #5: Fred Rogers (children’s entertainer) had stomach cancer.

Statement #6: Robin Roberts (news anchor) had breast cancer.

Statement #7: Bette Davis (actress) had breast cancer.

Judgment: Breast cancer is the most common type.

Your own experience or memory may also tell you that breast cancer is the most common type. But it is not (although it is common). Actually, skin cancer is the most common type in the US. We make the same types of misjudgments all the time because we do not generate the examples or evidence according to their actual frequencies or probabilities. Instead, we have a tendency (or bias) to search for the examples in memory; if they are easy to retrieve, we assume that they are common. To rephrase this in the language of the heuristic, events seem more likely to the extent that they are available to memory. This bias has been termed the  availability heuristic   (Kahneman and Tversky, 1974).

The fact that we use the availability heuristic does not automatically mean that our judgment is wrong. The reason we use heuristics in the first place is that they work fairly well in many cases (and, of course that they are easy to use). So, the easiest examples to think of sometimes are the most common ones. Is it more likely that a member of the U.S. Senate is a man or a woman? Most people have a much easier time generating examples of male senators. And as it turns out, the U.S. Senate has many more men than women (74 to 26 in 2020). In this case, then, the availability heuristic would lead you to make the correct judgment; it is far more likely that a senator would be a man.

In many other cases, however, the availability heuristic will lead us astray. This is because events can be memorable for many reasons other than their frequency. Section 5.2, Encoding Meaning, suggested that one good way to encode the meaning of some information is to form a mental image of it. Thus, information that has been pictured mentally will be more available to memory. Indeed, an event that is vivid and easily pictured will trick many people into supposing that type of event is more common than it actually is. Repetition of information will also make it more memorable. So, if the same event is described to you in a magazine, on the evening news, on a podcast that you listen to, and in your Facebook feed; it will be very available to memory. Again, the availability heuristic will cause you to misperceive the frequency of these types of events.

Most interestingly, information that is unusual is more memorable. Suppose we give you the following list of words to remember: box, flower, letter, platypus, oven, boat, newspaper, purse, drum, car. Very likely, the easiest word to remember would be platypus, the unusual one. The same thing occurs with memories of events. An event may be available to memory because it is unusual, yet the availability heuristic leads us to judge that the event is common. Did you catch that? In these cases, the availability heuristic makes us think the exact opposite of the true frequency. We end up thinking something is common because it is unusual (and therefore memorable). Yikes.

The misapplication of the availability heuristic sometimes has unfortunate results. For example, if you went to K-12 school in the US over the past 10 years, it is extremely likely that you have participated in lockdown and active shooter drills. Of course, everyone is trying to prevent the tragedy of another school shooting. And believe us, we are not trying to minimize how terrible the tragedy is. But the truth of the matter is, school shootings are extremely rare. Because the federal government does not keep a database of school shootings, the Washington Post has maintained their own running tally. Between 1999 and January 2020 (the date of the most recent school shooting with a death in the US at of the time this paragraph was written), the Post reported a total of 254 people died in school shootings in the US. Not 254 per year, 254 total. That is an average of 12 per year. Of course, that is 254 people who should not have died (particularly because many were children), but in a country with approximately 60,000,000 students and teachers, this is a very small risk.

But many students and teachers are terrified that they will be victims of school shootings because of the availability heuristic. It is so easy to think of examples (they are very available to memory) that people believe the event is very common. It is not. And there is a downside to this. We happen to believe that there is an enormous gun violence problem in the United States. According the the Centers for Disease Control and Prevention, there were 39,773 firearm deaths in the US in 2017. Fifteen of those deaths were in school shootings, according to the Post. 60% of those deaths were suicides. When people pay attention to the school shooting risk (low), they often fail to notice the much larger risk.

And examples like this are by no means unique. The authors of this book have been teaching psychology since the 1990’s. We have been able to make the exact same arguments about the misapplication of the availability heuristics and keep them current by simply swapping out for the “fear of the day.” In the 1990’s it was children being kidnapped by strangers (it was known as “stranger danger”) despite the facts that kidnappings accounted for only 2% of the violent crimes committed against children, and only 24% of kidnappings are committed by strangers (US Department of Justice, 2007). This fear overlapped with the fear of terrorism that gripped the country after the 2001 terrorist attacks on the World Trade Center and US Pentagon and still plagues the population of the US somewhat in 2020. After a well-publicized, sensational act of violence, people are extremely likely to increase their estimates of the chances that they, too, will be victims of terror. Think about the reality, however. In October of 2001, a terrorist mailed anthrax spores to members of the US government and a number of media companies. A total of five people died as a result of this attack. The nation was nearly paralyzed by the fear of dying from the attack; in reality the probability of an individual person dying was 0.00000002.

The availability heuristic can lead you to make incorrect judgments in a school setting as well. For example, suppose you are trying to decide if you should take a class from a particular math professor. You might try to make a judgment of how good a teacher she is by recalling instances of friends and acquaintances making comments about her teaching skill. You may have some examples that suggest that she is a poor teacher very available to memory, so on the basis of the availability heuristic you judge her a poor teacher and decide to take the class from someone else. What if, however, the instances you recalled were all from the same person, and this person happens to be a very colorful storyteller? The subsequent ease of remembering the instances might not indicate that the professor is a poor teacher after all.

Although the availability heuristic is obviously important, it is not the only judgment heuristic we use. Amos Tversky and Daniel Kahneman examined the role of heuristics in inductive reasoning in a long series of studies. Kahneman received a Nobel Prize in Economics for this research in 2002, and Tversky would have certainly received one as well if he had not died of melanoma at age 59 in 1996 (Nobel Prizes are not awarded posthumously). Kahneman and Tversky demonstrated repeatedly that people do not reason in ways that are consistent with the laws of probability. They identified several heuristic strategies that people use instead to make judgments about likelihood. The importance of this work for economics (and the reason that Kahneman was awarded the Nobel Prize) is that earlier economic theories had assumed that people do make judgments rationally, that is, in agreement with the laws of probability.

Another common heuristic that people use for making judgments is the  representativeness heuristic (Kahneman & Tversky 1973). Suppose we describe a person to you. He is quiet and shy, has an unassuming personality, and likes to work with numbers. Is this person more likely to be an accountant or an attorney? If you said accountant, you were probably using the representativeness heuristic. Our imaginary person is judged likely to be an accountant because he resembles, or is representative of the concept of, an accountant. When research participants are asked to make judgments such as these, the only thing that seems to matter is the representativeness of the description. For example, if told that the person described is in a room that contains 70 attorneys and 30 accountants, participants will still assume that he is an accountant.

inductive reasoning :  a type of reasoning in which we make judgments about likelihood from sets of evidence

inductively strong argument :  an inductive argument in which the beginning statements lead to a conclusion that is probably true

heuristic :  a shortcut strategy that we use to make judgments and solve problems. Although they are easy to use, they do not guarantee correct judgments and solutions

availability heuristic :  judging the frequency or likelihood of some event type according to how easily examples of the event can be called to mind (i.e., how available they are to memory)

representativeness heuristic:   judging the likelihood that something is a member of a category on the basis of how much it resembles a typical category member (i.e., how representative it is of the category)

Type 1 thinking : fast, automatic, and emotional thinking.

Type 2 thinking : slow, effortful, and logical thinking.

• What percentage of workplace homicides are co-worker violence?

Many people get these questions wrong. The answers are 10%; stairs; skin; 6%. How close were your answers? Explain how the availability heuristic might have led you to make the incorrect judgments.

• Can you think of some other judgments that you have made (or beliefs that you have) that might have been influenced by the availability heuristic?

7.3 Problem Solving

• Please take a few minutes to list a number of problems that you are facing right now.
• Now write about a problem that you recently solved.
• What is your definition of a problem?

Mary has a problem. Her daughter, ordinarily quite eager to please, appears to delight in being the last person to do anything. Whether getting ready for school, going to piano lessons or karate class, or even going out with her friends, she seems unwilling or unable to get ready on time. Other people have different kinds of problems. For example, many students work at jobs, have numerous family commitments, and are facing a course schedule full of difficult exams, assignments, papers, and speeches. How can they find enough time to devote to their studies and still fulfill their other obligations? Speaking of students and their problems: Show that a ball thrown vertically upward with initial velocity v0 takes twice as much time to return as to reach the highest point (from Spiegel, 1981).

These are three very different situations, but we have called them all problems. What makes them all the same, despite the differences? A psychologist might define a  problem   as a situation with an initial state, a goal state, and a set of possible intermediate states. Somewhat more meaningfully, we might consider a problem a situation in which you are in here one state (e.g., daughter is always late), you want to be there in another state (e.g., daughter is not always late), and with no obvious way to get from here to there. Defined this way, each of the three situations we outlined can now be seen as an example of the same general concept, a problem. At this point, you might begin to wonder what is not a problem, given such a general definition. It seems that nearly every non-routine task we engage in could qualify as a problem. As long as you realize that problems are not necessarily bad (it can be quite fun and satisfying to rise to the challenge and solve a problem), this may be a useful way to think about it.

Can we identify a set of problem-solving skills that would apply to these very different kinds of situations? That task, in a nutshell, is a major goal of this section. Let us try to begin to make sense of the wide variety of ways that problems can be solved with an important observation: the process of solving problems can be divided into two key parts. First, people have to notice, comprehend, and represent the problem properly in their minds (called  problem representation ). Second, they have to apply some kind of solution strategy to the problem. Psychologists have studied both of these key parts of the process in detail.

When you first think about the problem-solving process, you might guess that most of our difficulties would occur because we are failing in the second step, the application of strategies. Although this can be a significant difficulty much of the time, the more important source of difficulty is probably problem representation. In short, we often fail to solve a problem because we are looking at it, or thinking about it, the wrong way.

problem :  a situation in which we are in an initial state, have a desired goal state, and there is a number of possible intermediate states (i.e., there is no obvious way to get from the initial to the goal state)

problem representation :  noticing, comprehending and forming a mental conception of a problem

Defining and Mentally Representing Problems in Order to Solve Them

So, the main obstacle to solving a problem is that we do not clearly understand exactly what the problem is. Recall the problem with Mary’s daughter always being late. One way to represent, or to think about, this problem is that she is being defiant. She refuses to get ready in time. This type of representation or definition suggests a particular type of solution. Another way to think about the problem, however, is to consider the possibility that she is simply being sidetracked by interesting diversions. This different conception of what the problem is (i.e., different representation) suggests a very different solution strategy. For example, if Mary defines the problem as defiance, she may be tempted to solve the problem using some kind of coercive tactics, that is, to assert her authority as her mother and force her to listen. On the other hand, if Mary defines the problem as distraction, she may try to solve it by simply removing the distracting objects.

As you might guess, when a problem is represented one way, the solution may seem very difficult, or even impossible. Seen another way, the solution might be very easy. For example, consider the following problem (from Nasar, 1998):

Two bicyclists start 20 miles apart and head toward each other, each going at a steady rate of 10 miles per hour. At the same time, a fly that travels at a steady 15 miles per hour starts from the front wheel of the southbound bicycle and flies to the front wheel of the northbound one, then turns around and flies to the front wheel of the southbound one again, and continues in this manner until he is crushed between the two front wheels. Question: what total distance did the fly cover?

Please take a few minutes to try to solve this problem.

Most people represent this problem as a question about a fly because, well, that is how the question is asked. The solution, using this representation, is to figure out how far the fly travels on the first leg of its journey, then add this total to how far it travels on the second leg of its journey (when it turns around and returns to the first bicycle), then continue to add the smaller distance from each leg of the journey until you converge on the correct answer. You would have to be quite skilled at math to solve this problem, and you would probably need some time and pencil and paper to do it.

If you consider a different representation, however, you can solve this problem in your head. Instead of thinking about it as a question about a fly, think about it as a question about the bicycles. They are 20 miles apart, and each is traveling 10 miles per hour. How long will it take for the bicycles to reach each other? Right, one hour. The fly is traveling 15 miles per hour; therefore, it will travel a total of 15 miles back and forth in the hour before the bicycles meet. Represented one way (as a problem about a fly), the problem is quite difficult. Represented another way (as a problem about two bicycles), it is easy. Changing your representation of a problem is sometimes the best—sometimes the only—way to solve it.

Unfortunately, however, changing a problem’s representation is not the easiest thing in the world to do. Often, problem solvers get stuck looking at a problem one way. This is called  fixation . Most people who represent the preceding problem as a problem about a fly probably do not pause to reconsider, and consequently change, their representation. A parent who thinks her daughter is being defiant is unlikely to consider the possibility that her behavior is far less purposeful.

Problem-solving fixation was examined by a group of German psychologists called Gestalt psychologists during the 1930’s and 1940’s. Karl Dunker, for example, discovered an important type of failure to take a different perspective called  functional fixedness . Imagine being a participant in one of his experiments. You are asked to figure out how to mount two candles on a door and are given an assortment of odds and ends, including a small empty cardboard box and some thumbtacks. Perhaps you have already figured out a solution: tack the box to the door so it forms a platform, then put the candles on top of the box. Most people are able to arrive at this solution. Imagine a slight variation of the procedure, however. What if, instead of being empty, the box had matches in it? Most people given this version of the problem do not arrive at the solution given above. Why? Because it seems to people that when the box contains matches, it already has a function; it is a matchbox. People are unlikely to consider a new function for an object that already has a function. This is functional fixedness.

Mental set is a type of fixation in which the problem solver gets stuck using the same solution strategy that has been successful in the past, even though the solution may no longer be useful. It is commonly seen when students do math problems for homework. Often, several problems in a row require the reapplication of the same solution strategy. Then, without warning, the next problem in the set requires a new strategy. Many students attempt to apply the formerly successful strategy on the new problem and therefore cannot come up with a correct answer.

The thing to remember is that you cannot solve a problem unless you correctly identify what it is to begin with (initial state) and what you want the end result to be (goal state). That may mean looking at the problem from a different angle and representing it in a new way. The correct representation does not guarantee a successful solution, but it certainly puts you on the right track.

A bit more optimistically, the Gestalt psychologists discovered what may be considered the opposite of fixation, namely  insight . Sometimes the solution to a problem just seems to pop into your head. Wolfgang Kohler examined insight by posing many different problems to chimpanzees, principally problems pertaining to their acquisition of out-of-reach food. In one version, a banana was placed outside of a chimpanzee’s cage and a short stick inside the cage. The stick was too short to retrieve the banana, but was long enough to retrieve a longer stick also located outside of the cage. This second stick was long enough to retrieve the banana. After trying, and failing, to reach the banana with the shorter stick, the chimpanzee would try a couple of random-seeming attempts, react with some apparent frustration or anger, then suddenly rush to the longer stick, the correct solution fully realized at this point. This sudden appearance of the solution, observed many times with many different problems, was termed insight by Kohler.

Lest you think it pertains to chimpanzees only, Karl Dunker demonstrated that children also solve problems through insight in the 1930s. More importantly, you have probably experienced insight yourself. Think back to a time when you were trying to solve a difficult problem. After struggling for a while, you gave up. Hours later, the solution just popped into your head, perhaps when you were taking a walk, eating dinner, or lying in bed.

fixation :  when a problem solver gets stuck looking at a problem a particular way and cannot change his or her representation of it (or his or her intended solution strategy)

functional fixedness :  a specific type of fixation in which a problem solver cannot think of a new use for an object that already has a function

mental set :  a specific type of fixation in which a problem solver gets stuck using the same solution strategy that has been successful in the past

insight :  a sudden realization of a solution to a problem

Solving Problems by Trial and Error

Correctly identifying the problem and your goal for a solution is a good start, but recall the psychologist’s definition of a problem: it includes a set of possible intermediate states. Viewed this way, a problem can be solved satisfactorily only if one can find a path through some of these intermediate states to the goal. Imagine a fairly routine problem, finding a new route to school when your ordinary route is blocked (by road construction, for example). At each intersection, you may turn left, turn right, or go straight. A satisfactory solution to the problem (of getting to school) is a sequence of selections at each intersection that allows you to wind up at school.

If you had all the time in the world to get to school, you might try choosing intermediate states randomly. At one corner you turn left, the next you go straight, then you go left again, then right, then right, then straight. Unfortunately, trial and error will not necessarily get you where you want to go, and even if it does, it is not the fastest way to get there. For example, when a friend of ours was in college, he got lost on the way to a concert and attempted to find the venue by choosing streets to turn onto randomly (this was long before the use of GPS). Amazingly enough, the strategy worked, although he did end up missing two out of the three bands who played that night.

Trial and error is not all bad, however. B.F. Skinner, a prominent behaviorist psychologist, suggested that people often behave randomly in order to see what effect the behavior has on the environment and what subsequent effect this environmental change has on them. This seems particularly true for the very young person. Picture a child filling a household’s fish tank with toilet paper, for example. To a child trying to develop a repertoire of creative problem-solving strategies, an odd and random behavior might be just the ticket. Eventually, the exasperated parent hopes, the child will discover that many of these random behaviors do not successfully solve problems; in fact, in many cases they create problems. Thus, one would expect a decrease in this random behavior as a child matures. You should realize, however, that the opposite extreme is equally counterproductive. If the children become too rigid, never trying something unexpected and new, their problem solving skills can become too limited.

Effective problem solving seems to call for a happy medium that strikes a balance between using well-founded old strategies and trying new ground and territory. The individual who recognizes a situation in which an old problem-solving strategy would work best, and who can also recognize a situation in which a new untested strategy is necessary is halfway to success.

Solving Problems with Algorithms and Heuristics

For many problems there is a possible strategy available that will guarantee a correct solution. For example, think about math problems. Math lessons often consist of step-by-step procedures that can be used to solve the problems. If you apply the strategy without error, you are guaranteed to arrive at the correct solution to the problem. This approach is called using an  algorithm , a term that denotes the step-by-step procedure that guarantees a correct solution. Because algorithms are sometimes available and come with a guarantee, you might think that most people use them frequently. Unfortunately, however, they do not. As the experience of many students who have struggled through math classes can attest, algorithms can be extremely difficult to use, even when the problem solver knows which algorithm is supposed to work in solving the problem. In problems outside of math class, we often do not even know if an algorithm is available. It is probably fair to say, then, that algorithms are rarely used when people try to solve problems.

Because algorithms are so difficult to use, people often pass up the opportunity to guarantee a correct solution in favor of a strategy that is much easier to use and yields a reasonable chance of coming up with a correct solution. These strategies are called  problem solving heuristics . Similar to what you saw in section 6.2 with reasoning heuristics, a problem solving heuristic is a shortcut strategy that people use when trying to solve problems. It usually works pretty well, but does not guarantee a correct solution to the problem. For example, one problem solving heuristic might be “always move toward the goal” (so when trying to get to school when your regular route is blocked, you would always turn in the direction you think the school is). A heuristic that people might use when doing math homework is “use the same solution strategy that you just used for the previous problem.”

By the way, we hope these last two paragraphs feel familiar to you. They seem to parallel a distinction that you recently learned. Indeed, algorithms and problem-solving heuristics are another example of the distinction between Type 1 thinking and Type 2 thinking.

Although it is probably not worth describing a large number of specific heuristics, two observations about heuristics are worth mentioning. First, heuristics can be very general or they can be very specific, pertaining to a particular type of problem only. For example, “always move toward the goal” is a general strategy that you can apply to countless problem situations. On the other hand, “when you are lost without a functioning gps, pick the most expensive car you can see and follow it” is specific to the problem of being lost. Second, all heuristics are not equally useful. One heuristic that many students know is “when in doubt, choose c for a question on a multiple-choice exam.” This is a dreadful strategy because many instructors intentionally randomize the order of answer choices. Another test-taking heuristic, somewhat more useful, is “look for the answer to one question somewhere else on the exam.”

You really should pay attention to the application of heuristics to test taking. Imagine that while reviewing your answers for a multiple-choice exam before turning it in, you come across a question for which you originally thought the answer was c. Upon reflection, you now think that the answer might be b. Should you change the answer to b, or should you stick with your first impression? Most people will apply the heuristic strategy to “stick with your first impression.” What they do not realize, of course, is that this is a very poor strategy (Lilienfeld et al, 2009). Most of the errors on exams come on questions that were answered wrong originally and were not changed (so they remain wrong). There are many fewer errors where we change a correct answer to an incorrect answer. And, of course, sometimes we change an incorrect answer to a correct answer. In fact, research has shown that it is more common to change a wrong answer to a right answer than vice versa (Bruno, 2001).

The belief in this poor test-taking strategy (stick with your first impression) is based on the  confirmation bias   (Nickerson, 1998; Wason, 1960). You first saw the confirmation bias in Module 1, but because it is so important, we will repeat the information here. People have a bias, or tendency, to notice information that confirms what they already believe. Somebody at one time told you to stick with your first impression, so when you look at the results of an exam you have taken, you will tend to notice the cases that are consistent with that belief. That is, you will notice the cases in which you originally had an answer correct and changed it to the wrong answer. You tend not to notice the other two important (and more common) cases, changing an answer from wrong to right, and leaving a wrong answer unchanged.

Because heuristics by definition do not guarantee a correct solution to a problem, mistakes are bound to occur when we employ them. A poor choice of a specific heuristic will lead to an even higher likelihood of making an error.

algorithm :  a step-by-step procedure that guarantees a correct solution to a problem

problem solving heuristic :  a shortcut strategy that we use to solve problems. Although they are easy to use, they do not guarantee correct judgments and solutions

confirmation bias :  people’s tendency to notice information that confirms what they already believe

An Effective Problem-Solving Sequence

You may be left with a big question: If algorithms are hard to use and heuristics often don’t work, how am I supposed to solve problems? Robert Sternberg (1996), as part of his theory of what makes people successfully intelligent (Module 8) described a problem-solving sequence that has been shown to work rather well:

• Identify the existence of a problem.  In school, problem identification is often easy; problems that you encounter in math classes, for example, are conveniently labeled as problems for you. Outside of school, however, realizing that you have a problem is a key difficulty that you must get past in order to begin solving it. You must be very sensitive to the symptoms that indicate a problem.
• Define the problem.  Suppose you realize that you have been having many headaches recently. Very likely, you would identify this as a problem. If you define the problem as “headaches,” the solution would probably be to take aspirin or ibuprofen or some other anti-inflammatory medication. If the headaches keep returning, however, you have not really solved the problem—likely because you have mistaken a symptom for the problem itself. Instead, you must find the root cause of the headaches. Stress might be the real problem. For you to successfully solve many problems it may be necessary for you to overcome your fixations and represent the problems differently. One specific strategy that you might find useful is to try to define the problem from someone else’s perspective. How would your parents, spouse, significant other, doctor, etc. define the problem? Somewhere in these different perspectives may lurk the key definition that will allow you to find an easier and permanent solution.
• Formulate strategy.  Now it is time to begin planning exactly how the problem will be solved. Is there an algorithm or heuristic available for you to use? Remember, heuristics by their very nature guarantee that occasionally you will not be able to solve the problem. One point to keep in mind is that you should look for long-range solutions, which are more likely to address the root cause of a problem than short-range solutions.
• Represent and organize information.  Similar to the way that the problem itself can be defined, or represented in multiple ways, information within the problem is open to different interpretations. Suppose you are studying for a big exam. You have chapters from a textbook and from a supplemental reader, along with lecture notes that all need to be studied. How should you (represent and) organize these materials? Should you separate them by type of material (text versus reader versus lecture notes), or should you separate them by topic? To solve problems effectively, you must learn to find the most useful representation and organization of information.
• Allocate resources.  This is perhaps the simplest principle of the problem solving sequence, but it is extremely difficult for many people. First, you must decide whether time, money, skills, effort, goodwill, or some other resource would help to solve the problem Then, you must make the hard choice of deciding which resources to use, realizing that you cannot devote maximum resources to every problem. Very often, the solution to problem is simply to change how resources are allocated (for example, spending more time studying in order to improve grades).
• Monitor and evaluate solutions.  Pay attention to the solution strategy while you are applying it. If it is not working, you may be able to select another strategy. Another fact you should realize about problem solving is that it never does end. Solving one problem frequently brings up new ones. Good monitoring and evaluation of your problem solutions can help you to anticipate and get a jump on solving the inevitable new problems that will arise.

Please note that this as  an  effective problem-solving sequence, not  the  effective problem solving sequence. Just as you can become fixated and end up representing the problem incorrectly or trying an inefficient solution, you can become stuck applying the problem-solving sequence in an inflexible way. Clearly there are problem situations that can be solved without using these skills in this order.

Additionally, many real-world problems may require that you go back and redefine a problem several times as the situation changes (Sternberg et al. 2000). For example, consider the problem with Mary’s daughter one last time. At first, Mary did represent the problem as one of defiance. When her early strategy of pleading and threatening punishment was unsuccessful, Mary began to observe her daughter more carefully. She noticed that, indeed, her daughter’s attention would be drawn by an irresistible distraction or book. Fresh with a re-representation of the problem, she began a new solution strategy. She began to remind her daughter every few minutes to stay on task and remind her that if she is ready before it is time to leave, she may return to the book or other distracting object at that time. Fortunately, this strategy was successful, so Mary did not have to go back and redefine the problem again.

Pick one or two of the problems that you listed when you first started studying this section and try to work out the steps of Sternberg’s problem solving sequence for each one.

a mental representation of a category of things in the world

an assumption about the truth of something that is not stated. Inferences come from our prior knowledge and experience, and from logical reasoning

knowledge about one’s own cognitive processes; thinking about your thinking

individuals who are less competent tend to overestimate their abilities more than individuals who are more competent do

Thinking like a scientist in your everyday life for the purpose of drawing correct conclusions. It entails skepticism; an ability to identify biases, distortions, omissions, and assumptions; and excellent deductive and inductive reasoning, and problem solving skills.

a way of thinking in which you refrain from drawing a conclusion or changing your mind until good evidence has been provided

an inclination, tendency, leaning, or prejudice

a type of reasoning in which the conclusion is guaranteed to be true any time the statements leading up to it are true

a set of statements in which the beginning statements lead to a conclusion

an argument for which true beginning statements guarantee that the conclusion is true

a type of reasoning in which we make judgments about likelihood from sets of evidence

an inductive argument in which the beginning statements lead to a conclusion that is probably true

fast, automatic, and emotional thinking

slow, effortful, and logical thinking

a shortcut strategy that we use to make judgments and solve problems. Although they are easy to use, they do not guarantee correct judgments and solutions

udging the frequency or likelihood of some event type according to how easily examples of the event can be called to mind (i.e., how available they are to memory)

judging the likelihood that something is a member of a category on the basis of how much it resembles a typical category member (i.e., how representative it is of the category)

a situation in which we are in an initial state, have a desired goal state, and there is a number of possible intermediate states (i.e., there is no obvious way to get from the initial to the goal state)

noticing, comprehending and forming a mental conception of a problem

when a problem solver gets stuck looking at a problem a particular way and cannot change his or her representation of it (or his or her intended solution strategy)

a specific type of fixation in which a problem solver cannot think of a new use for an object that already has a function

a specific type of fixation in which a problem solver gets stuck using the same solution strategy that has been successful in the past

a sudden realization of a solution to a problem

a step-by-step procedure that guarantees a correct solution to a problem

The tendency to notice and pay attention to information that confirms your prior beliefs and to ignore information that disconfirms them.

a shortcut strategy that we use to solve problems. Although they are easy to use, they do not guarantee correct judgments and solutions

Introduction to Psychology Copyright © 2020 by Ken Gray; Elizabeth Arnott-Hill; and Or'Shaundra Benson is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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The Peak Performance Center

The pursuit of performance excellence, critical thinking.

Critical thinking refers to the process of actively analyzing, assessing, synthesizing, evaluating and reflecting on information gathered from observation, experience, or communication. It is thinking in a clear, logical, reasoned, and reflective manner to solve problems or make decisions. Basically, critical thinking is taking a hard look at something to understand what it really means.

Critical Thinkers

Critical thinkers do not simply accept all ideas, theories, and conclusions as facts. They have a mindset of questioning ideas and conclusions. They make reasoned judgments that are logical and well thought out by assessing the evidence that supports a specific theory or conclusion.

When presented with a new piece of new information, critical thinkers may ask questions such as;

“What information supports that?”

“How was this information obtained?”

“Who obtained the information?”

“How do we know the information is valid?”

“Why is it that way?”

“What makes it do that?”

“How do we know that?”

“Are there other possibilities?”

Combination of Analytical and Creative Thinking

Many people perceive critical thinking just as analytical thinking. However, critical thinking incorporates both analytical thinking and creative thinking. Critical thinking does involve breaking down information into parts and analyzing the parts in a logical, step-by-step manner. However, it also involves challenging consensus to formulate new creative ideas and generate innovative solutions. It is critical thinking that helps to evaluate and improve your creative ideas.

Elements of Critical Thinking

Critical thinking involves:

• Gathering relevant information
• Evaluating information
• Asking questions
• Assessing bias or unsubstantiated assumptions
• Making inferences from the information and filling in gaps
• Using abstract ideas to interpret information
• Formulating ideas
• Weighing opinions
• Reaching well-reasoned conclusions
• Considering alternative possibilities
• Testing conclusions
• Verifying if evidence/argument support the conclusions

Developing Critical Thinking Skills

Critical thinking is considered a higher order thinking skills, such as analysis, synthesis, deduction, inference, reason, and evaluation. In order to demonstrate critical thinking, you would need to develop skills in;

Interpreting : understanding the significance or meaning of information

Analyzing : breaking information down into its parts

Connecting : making connections between related items or pieces of information.

Integrating : connecting and combining information to better understand the relationship between the information.

Evaluating : judging the value, credibility, or strength of something

Reasoning : creating an argument through logical steps

Deducing : forming a logical opinion about something based on the information or evidence that is available

Inferring : figuring something out through reasoning based on assumptions and ideas

Generating : producing new information, ideas, products, or ways of viewing things.

Blooms Taxonomy

Bloom’s Taxonomy Revised

Mind Mapping

Chunking Information

Brainstorming

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• Working with sources
• What Is Critical Thinking? | Definition & Examples

What Is Critical Thinking? | Definition & Examples

Published on May 30, 2022 by Eoghan Ryan . Revised on May 31, 2023.

Critical thinking is the ability to effectively analyze information and form a judgment .

To think critically, you must be aware of your own biases and assumptions when encountering information, and apply consistent standards when evaluating sources .

Critical thinking skills help you to:

• Identify credible sources
• Evaluate and respond to arguments
• Assess alternative viewpoints
• Test hypotheses against relevant criteria

Table of contents

Why is critical thinking important, critical thinking examples, how to think critically, other interesting articles, frequently asked questions about critical thinking.

Critical thinking is important for making judgments about sources of information and forming your own arguments. It emphasizes a rational, objective, and self-aware approach that can help you to identify credible sources and strengthen your conclusions.

Critical thinking is important in all disciplines and throughout all stages of the research process . The types of evidence used in the sciences and in the humanities may differ, but critical thinking skills are relevant to both.

In academic writing , critical thinking can help you to determine whether a source:

• Is free from research bias
• Provides evidence to support its research findings
• Considers alternative viewpoints

Outside of academia, critical thinking goes hand in hand with information literacy to help you form opinions rationally and engage independently and critically with popular media.

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Critical thinking can help you to identify reliable sources of information that you can cite in your research paper . It can also guide your own research methods and inform your own arguments.

Outside of academia, critical thinking can help you to be aware of both your own and others’ biases and assumptions.

Academic examples

However, when you compare the findings of the study with other current research, you determine that the results seem improbable. You analyze the paper again, consulting the sources it cites.

You notice that the research was funded by the pharmaceutical company that created the treatment. Because of this, you view its results skeptically and determine that more independent research is necessary to confirm or refute them. Example: Poor critical thinking in an academic context You’re researching a paper on the impact wireless technology has had on developing countries that previously did not have large-scale communications infrastructure. You read an article that seems to confirm your hypothesis: the impact is mainly positive. Rather than evaluating the research methodology, you accept the findings uncritically.

Nonacademic examples

However, you decide to compare this review article with consumer reviews on a different site. You find that these reviews are not as positive. Some customers have had problems installing the alarm, and some have noted that it activates for no apparent reason.

You revisit the original review article. You notice that the words “sponsored content” appear in small print under the article title. Based on this, you conclude that the review is advertising and is therefore not an unbiased source. Example: Poor critical thinking in a nonacademic context You support a candidate in an upcoming election. You visit an online news site affiliated with their political party and read an article that criticizes their opponent. The article claims that the opponent is inexperienced in politics. You accept this without evidence, because it fits your preconceptions about the opponent.

There is no single way to think critically. How you engage with information will depend on the type of source you’re using and the information you need.

However, you can engage with sources in a systematic and critical way by asking certain questions when you encounter information. Like the CRAAP test , these questions focus on the currency , relevance , authority , accuracy , and purpose of a source of information.

When encountering information, ask:

• Who is the author? Are they an expert in their field?
• What do they say? Is their argument clear? Can you summarize it?
• When did they say this? Is the source current?
• Where is the information published? Is it an academic article? Is it peer-reviewed ?
• Why did the author publish it? What is their motivation?
• How do they make their argument? Is it backed up by evidence? Does it rely on opinion, speculation, or appeals to emotion ? Do they address alternative arguments?

Critical thinking also involves being aware of your own biases, not only those of others. When you make an argument or draw your own conclusions, you can ask similar questions about your own writing:

• Am I only considering evidence that supports my preconceptions?
• Is my argument expressed clearly and backed up with credible sources?
• Would I be convinced by this argument coming from someone else?

If you want to know more about ChatGPT, AI tools , citation , and plagiarism , make sure to check out some of our other articles with explanations and examples.

• ChatGPT vs human editor
• ChatGPT citations
• Is ChatGPT trustworthy?
• Using ChatGPT for your studies
• What is ChatGPT?
• Chicago style
• Paraphrasing

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Critical thinking refers to the ability to evaluate information and to be aware of biases or assumptions, including your own.

Like information literacy , it involves evaluating arguments, identifying and solving problems in an objective and systematic way, and clearly communicating your ideas.

Critical thinking skills include the ability to:

You can assess information and arguments critically by asking certain questions about the source. You can use the CRAAP test , focusing on the currency , relevance , authority , accuracy , and purpose of a source of information.

Ask questions such as:

• Who is the author? Are they an expert?
• How do they make their argument? Is it backed up by evidence?

A credible source should pass the CRAAP test  and follow these guidelines:

• The information should be up to date and current.
• The author and publication should be a trusted authority on the subject you are researching.
• The sources the author cited should be easy to find, clear, and unbiased.
• For a web source, the URL and layout should signify that it is trustworthy.

Information literacy refers to a broad range of skills, including the ability to find, evaluate, and use sources of information effectively.

Being information literate means that you:

• Know how to find credible sources
• Use relevant sources to inform your research
• Understand what constitutes plagiarism
• Know how to cite your sources correctly

Confirmation bias is the tendency to search, interpret, and recall information in a way that aligns with our pre-existing values, opinions, or beliefs. It refers to the ability to recollect information best when it amplifies what we already believe. Relatedly, we tend to forget information that contradicts our opinions.

Although selective recall is a component of confirmation bias, it should not be confused with recall bias.

On the other hand, recall bias refers to the differences in the ability between study participants to recall past events when self-reporting is used. This difference in accuracy or completeness of recollection is not related to beliefs or opinions. Rather, recall bias relates to other factors, such as the length of the recall period, age, and the characteristics of the disease under investigation.

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Critical Thinking Versus Clinical Reasoning Versus Clinical Judgment

Differential diagnosis.

Victor-Chmil, Joyce MS, RN-BC, MHA

Author Affiliation: Director, Clinical Nursing Simulation Center. School of Nursing, Wilkes University, Wilkes-Barre, Pennsylvania.

The author declares no conflict of interest.

Correspondence: Ms Victor-Chmil, Wilkes University School of Nursing, 84 West South St, Wilkes-Barre, PA 18766 ( [email protected] ).

Concepts of critical thinking, clinical reasoning, and clinical judgment are often used interchangeably. However, they are not one and the same, and understanding subtle difference among them is important. Following a review of the literature for definitions and uses of the terms, the author provides a summary focused on similarities and differences in the processes of critical thinking, clinical reasoning, and clinical judgment and notes suggested methods of measuring each.

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Critical thinking and problem-solving, jump to: , what is critical thinking, characteristics of critical thinking, why teach critical thinking.

• Teaching Strategies to Help Promote Critical Thinking Skills

References and Resources

When examining the vast literature on critical thinking, various definitions of critical thinking emerge. Here are some samples:

• "Critical thinking is the intellectually disciplined process of actively and skillfully conceptualizing, applying, analyzing, synthesizing, and/or evaluating information gathered from, or generated by, observation, experience, reflection, reasoning, or communication, as a guide to belief and action" (Scriven, 1996).
• "Most formal definitions characterize critical thinking as the intentional application of rational, higher order thinking skills, such as analysis, synthesis, problem recognition and problem solving, inference, and evaluation" (Angelo, 1995, p. 6).
• "Critical thinking is thinking that assesses itself" (Center for Critical Thinking, 1996b).
• "Critical thinking is the ability to think about one's thinking in such a way as 1. To recognize its strengths and weaknesses and, as a result, 2. To recast the thinking in improved form" (Center for Critical Thinking, 1996c).

Perhaps the simplest definition is offered by Beyer (1995) : "Critical thinking... means making reasoned judgments" (p. 8). Basically, Beyer sees critical thinking as using criteria to judge the quality of something, from cooking to a conclusion of a research paper. In essence, critical thinking is a disciplined manner of thought that a person uses to assess the validity of something (statements, news stories, arguments, research, etc.).

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Wade (1995) identifies eight characteristics of critical thinking. Critical thinking involves asking questions, defining a problem, examining evidence, analyzing assumptions and biases, avoiding emotional reasoning, avoiding oversimplification, considering other interpretations, and tolerating ambiguity. Dealing with ambiguity is also seen by Strohm & Baukus (1995) as an essential part of critical thinking, "Ambiguity and doubt serve a critical-thinking function and are a necessary and even a productive part of the process" (p. 56).

Another characteristic of critical thinking identified by many sources is metacognition. Metacognition is thinking about one's own thinking. More specifically, "metacognition is being aware of one's thinking as one performs specific tasks and then using this awareness to control what one is doing" (Jones & Ratcliff, 1993, p. 10 ).

In the book, Critical Thinking, Beyer elaborately explains what he sees as essential aspects of critical thinking. These are:

• Dispositions: Critical thinkers are skeptical, open-minded, value fair-mindedness, respect evidence and reasoning, respect clarity and precision, look at different points of view, and will change positions when reason leads them to do so.
• Criteria: To think critically, must apply criteria. Need to have conditions that must be met for something to be judged as believable. Although the argument can be made that each subject area has different criteria, some standards apply to all subjects. "... an assertion must... be based on relevant, accurate facts; based on credible sources; precise; unbiased; free from logical fallacies; logically consistent; and strongly reasoned" (p. 12).
• Argument: Is a statement or proposition with supporting evidence. Critical thinking involves identifying, evaluating, and constructing arguments.
• Reasoning: The ability to infer a conclusion from one or multiple premises. To do so requires examining logical relationships among statements or data.
• Point of View: The way one views the world, which shapes one's construction of meaning. In a search for understanding, critical thinkers view phenomena from many different points of view.
• Procedures for Applying Criteria: Other types of thinking use a general procedure. Critical thinking makes use of many procedures. These procedures include asking questions, making judgments, and identifying assumptions.

Oliver & Utermohlen (1995) see students as too often being passive receptors of information. Through technology, the amount of information available today is massive. This information explosion is likely to continue in the future. Students need a guide to weed through the information and not just passively accept it. Students need to "develop and effectively apply critical thinking skills to their academic studies, to the complex problems that they will face, and to the critical choices they will be forced to make as a result of the information explosion and other rapid technological changes" (Oliver & Utermohlen, p. 1 ).

As mentioned in the section, Characteristics of Critical Thinking , critical thinking involves questioning. It is important to teach students how to ask good questions, to think critically, in order to continue the advancement of the very fields we are teaching. "Every field stays alive only to the extent that fresh questions are generated and taken seriously" (Center for Critical Thinking, 1996a ).

Beyer sees the teaching of critical thinking as important to the very state of our nation. He argues that to live successfully in a democracy, people must be able to think critically in order to make sound decisions about personal and civic affairs. If students learn to think critically, then they can use good thinking as the guide by which they live their lives.

Teaching Strategies to Help Promote Critical Thinking

The 1995, Volume 22, issue 1, of the journal, Teaching of Psychology , is devoted to the teaching critical thinking. Most of the strategies included in this section come from the various articles that compose this issue.

• CATS (Classroom Assessment Techniques): Angelo stresses the use of ongoing classroom assessment as a way to monitor and facilitate students' critical thinking. An example of a CAT is to ask students to write a "Minute Paper" responding to questions such as "What was the most important thing you learned in today's class? What question related to this session remains uppermost in your mind?" The teacher selects some of the papers and prepares responses for the next class meeting.
• Cooperative Learning Strategies: Cooper (1995) argues that putting students in group learning situations is the best way to foster critical thinking. "In properly structured cooperative learning environments, students perform more of the active, critical thinking with continuous support and feedback from other students and the teacher" (p. 8).
• Case Study /Discussion Method: McDade (1995) describes this method as the teacher presenting a case (or story) to the class without a conclusion. Using prepared questions, the teacher then leads students through a discussion, allowing students to construct a conclusion for the case.
• Using Questions: King (1995) identifies ways of using questions in the classroom:
• Reciprocal Peer Questioning: Following lecture, the teacher displays a list of question stems (such as, "What are the strengths and weaknesses of...). Students must write questions about the lecture material. In small groups, the students ask each other the questions. Then, the whole class discusses some of the questions from each small group.
• Reader's Questions: Require students to write questions on assigned reading and turn them in at the beginning of class. Select a few of the questions as the impetus for class discussion.
• Conference Style Learning: The teacher does not "teach" the class in the sense of lecturing. The teacher is a facilitator of a conference. Students must thoroughly read all required material before class. Assigned readings should be in the zone of proximal development. That is, readings should be able to be understood by students, but also challenging. The class consists of the students asking questions of each other and discussing these questions. The teacher does not remain passive, but rather, helps "direct and mold discussions by posing strategic questions and helping students build on each others' ideas" (Underwood & Wald, 1995, p. 18 ).
• Use Writing Assignments: Wade sees the use of writing as fundamental to developing critical thinking skills. "With written assignments, an instructor can encourage the development of dialectic reasoning by requiring students to argue both [or more] sides of an issue" (p. 24).
• Written dialogues: Give students written dialogues to analyze. In small groups, students must identify the different viewpoints of each participant in the dialogue. Must look for biases, presence or exclusion of important evidence, alternative interpretations, misstatement of facts, and errors in reasoning. Each group must decide which view is the most reasonable. After coming to a conclusion, each group acts out their dialogue and explains their analysis of it.
• Spontaneous Group Dialogue: One group of students are assigned roles to play in a discussion (such as leader, information giver, opinion seeker, and disagreer). Four observer groups are formed with the functions of determining what roles are being played by whom, identifying biases and errors in thinking, evaluating reasoning skills, and examining ethical implications of the content.
• Ambiguity: Strohm & Baukus advocate producing much ambiguity in the classroom. Don't give students clear cut material. Give them conflicting information that they must think their way through.
• Angelo, T. A. (1995). Beginning the dialogue: Thoughts on promoting critical thinking: Classroom assessment for critical thinking. Teaching of Psychology, 22(1), 6-7.
• Beyer, B. K. (1995). Critical thinking. Bloomington, IN: Phi Delta Kappa Educational Foundation.
• Center for Critical Thinking (1996a). The role of questions in thinking, teaching, and learning. [On-line]. Available HTTP: http://www.criticalthinking.org/University/univlibrary/library.nclk
• Center for Critical Thinking (1996b). Structures for student self-assessment. [On-line]. Available HTTP: http://www.criticalthinking.org/University/univclass/trc.nclk
• Center for Critical Thinking (1996c). Three definitions of critical thinking [On-line]. Available HTTP: http://www.criticalthinking.org/University/univlibrary/library.nclk
• Cooper, J. L. (1995). Cooperative learning and critical thinking. Teaching of Psychology, 22(1), 7-8.
• Jones, E. A. & Ratcliff, G. (1993). Critical thinking skills for college students. National Center on Postsecondary Teaching, Learning, and Assessment, University Park, PA. (Eric Document Reproduction Services No. ED 358 772)
• King, A. (1995). Designing the instructional process to enhance critical thinking across the curriculum: Inquiring minds really do want to know: Using questioning to teach critical thinking. Teaching of Psychology, 22 (1) , 13-17.
• McDade, S. A. (1995). Case study pedagogy to advance critical thinking. Teaching Psychology, 22(1), 9-10.
• Oliver, H. & Utermohlen, R. (1995). An innovative teaching strategy: Using critical thinking to give students a guide to the future.(Eric Document Reproduction Services No. 389 702)
• Robertson, J. F. & Rane-Szostak, D. (1996). Using dialogues to develop critical thinking skills: A practical approach. Journal of Adolescent & Adult Literacy, 39(7), 552-556.
• Scriven, M. & Paul, R. (1996). Defining critical thinking: A draft statement for the National Council for Excellence in Critical Thinking. [On-line]. Available HTTP: http://www.criticalthinking.org/University/univlibrary/library.nclk
• Strohm, S. M., & Baukus, R. A. (1995). Strategies for fostering critical thinking skills. Journalism and Mass Communication Educator, 50 (1), 55-62.
• Underwood, M. K., & Wald, R. L. (1995). Conference-style learning: A method for fostering critical thinking with heart. Teaching Psychology, 22(1), 17-21.
• Wade, C. (1995). Using writing to develop and assess critical thinking. Teaching of Psychology, 22(1), 24-28.

Other Reading

• Bean, J. C. (1996). Engaging ideas: The professor's guide to integrating writing, critical thinking, & active learning in the classroom. Jossey-Bass.
• Bernstein, D. A. (1995). A negotiation model for teaching critical thinking. Teaching of Psychology, 22(1), 22-24.
• Carlson, E. R. (1995). Evaluating the credibility of sources. A missing link in the teaching of critical thinking. Teaching of Psychology, 22(1), 39-41.
• Facione, P. A., Sanchez, C. A., Facione, N. C., & Gainen, J. (1995). The disposition toward critical thinking. The Journal of General Education, 44(1), 1-25.
• Halpern, D. F., & Nummedal, S. G. (1995). Closing thoughts about helping students improve how they think. Teaching of Psychology, 22(1), 82-83.
• Isbell, D. (1995). Teaching writing and research as inseparable: A faculty-librarian teaching team. Reference Services Review, 23(4), 51-62.
• Jones, J. M. & Safrit, R. D. (1994). Developing critical thinking skills in adult learners through innovative distance learning. Paper presented at the International Conference on the practice of adult education and social development. Jinan, China. (Eric Document Reproduction Services No. ED 373 159)
• Sanchez, M. A. (1995). Using critical-thinking principles as a guide to college-level instruction. Teaching of Psychology, 22(1), 72-74.
• Spicer, K. L. & Hanks, W. E. (1995). Multiple measures of critical thinking skills and predisposition in assessment of critical thinking. Paper presented at the annual meeting of the Speech Communication Association, San Antonio, TX. (Eric Document Reproduction Services No. ED 391 185)
• Terenzini, P. T., Springer, L., Pascarella, E. T., & Nora, A. (1995). Influences affecting the development of students' critical thinking skills. Research in Higher Education, 36(1), 23-39.

On the Internet

• Carr, K. S. (1990). How can we teach critical thinking. Eric Digest. [On-line]. Available HTTP: http://ericps.ed.uiuc.edu/eece/pubs/digests/1990/carr90.html
• The Center for Critical Thinking (1996). Home Page. Available HTTP: http://www.criticalthinking.org/University/
• Ennis, Bob (No date). Critical thinking. [On-line], April 4, 1997. Available HTTP: http://www.cof.orst.edu/cof/teach/for442/ct.htm
• Montclair State University (1995). Curriculum resource center. Critical thinking resources: An annotated bibliography. [On-line]. Available HTTP: http://www.montclair.edu/Pages/CRC/Bibliographies/CriticalThinking.html
• No author, No date. Critical Thinking is ... [On-line], April 4, 1997. Available HTTP: http://library.usask.ca/ustudy/critical/
• Sheridan, Marcia (No date). Internet education topics hotlink page. [On-line], April 4, 1997. Available HTTP: http://sun1.iusb.edu/~msherida/topics/critical.html

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A Brief History of the Idea of Critical Thinking

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13 Easy Steps To Improve Your Critical Thinking Skills

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With the sheer volume of information that we’re bombarded with on a daily basis – and with the pervasiveness of fake news and social media bubbles – the ability to look at evidence, evaluate the trustworthiness of a source, and think critically is becoming more important than ever. This is why, for me, critical thinking is one of the most vital skills to cultivate for future success.

Critical thinking isn’t about being constantly negative or critical of everything. It’s about objectivity and having an open, inquisitive mind. To think critically is to analyze issues based on hard evidence (as opposed to personal opinions, biases, etc.) in order to build a thorough understanding of what’s really going on. And from this place of thorough understanding, you can make better decisions and solve problems more effectively.

To put it another way, critical thinking means arriving at your own carefully considered conclusions instead of taking information at face value. Here are 13 ways you can cultivate this precious skill:

1. Always vet new information with a cautious eye. Whether it’s an article someone has shared online or data that’s related to your job, always vet the information you're presented with. Good questions to ask here include, "Is this information complete and up to date?” “What evidence is being presented to support the argument?” and “Whose voice is missing here?”

2. Look at where the information has come from. Is the source trustworthy? What is their motivation for presenting this information? For example, are they trying to sell you something or get you to take a certain action (like vote for them)?

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3. Consider more than one point of view. Everyone has their own opinions and motivations – even highly intelligent people making reasonable-sounding arguments have personal opinions and biases that shape their thinking. So, when someone presents you with information, consider whether there are other sides to the story.

4. Practice active listening. Listen carefully to what others are telling you, and try to build a clear picture of their perspective. Empathy is a really useful skill here since putting yourself in another person's shoes can help you understand where they're coming from and what they might want. Try to listen without judgment – remember, critical thinking is about keeping an open mind.

5. Gather additional information where needed. Whenever you identify gaps in the information or data, do your own research to fill those gaps. The next few steps will help you do this objectively…

6. Ask lots of open-ended questions. Curiosity is a key trait of critical thinkers, so channel your inner child and ask lots of "who," "what," and "why" questions.

7. Find your own reputable sources of information, such as established news sites, nonprofit organizations, and education institutes. Try to avoid anonymous sources or sources with an ax to grind or a product to sell. Also, be sure to check when the information was published. An older source may be unintentionally offering up wrong information just because events have moved on since it was published; corroborate the info with a more recent source.

8. Try not to get your news from social media. And if you do see something on social media that grabs your interest, check the accuracy of the story (via reputable sources of information, as above) before you share it.

9. Learn to spot fake news. It's not always easy to spot false or misleading content, but a good rule of thumb is to look at the language, emotion, and tone of the piece. Is it using emotionally charged language, for instance, and trying to get you to feel a certain way? Also, look at the sources of facts, figures, images, and quotes. A legit news story will clearly state its sources.

10. Learn to spot biased information. Like fake news, biased information may seek to appeal more to your emotions than logic and/or present a limited view of the topic. So ask yourself, “Is there more to this topic than what’s being presented here?” Do your own reading around the topic to establish the full picture.

11. Question your own biases, too. Everyone has biases, and there’s no point pretending otherwise. The trick is to think objectively about your likes and dislikes, preferences, and beliefs, and consider how these might affect your thinking.

12. Form your own opinions. Remember, critical thinking is about thinking independently. So once you’ve assessed all the information, form your own conclusions about it.

13. Continue to work on your critical thinking skills. I recommend looking at online learning platforms such as Udemy and Coursera for courses on general critical thinking skills, as well as courses on specific subjects like cognitive biases.

Read more about critical thinking and other essential skills in my new book, Future Skills: The 20 Skills & Competencies Everyone Needs To Succeed In A Digital World . Written for anyone who wants to surf the wave of digital transformation – rather than be drowned by it – the book explores why these vital future skills matter and how to develop them.

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The good, bad and ugly of AI for news

Art Min demonstrates TrueMedia's AI-powered tool for detecting AI 'deepfakes.' Photo: RNZ Mediawatch

The New Zealand Herald copped criticism for using AI to create editorials recently, but it still wants journalists to keep using it to make their work better and more efficient. The chair of the ABC has also urged staff there to embrace AI for news. Mediawatch hears how AI has been deployed for news elsewhere in the Asia Pacific - and how AI-created fake content is threatening to undermine the news.              

In June, Dr Michelle Dickinson - aka Nanogirl - put artificial intelligence application Chat GPT 4.0 to the task by asking it how many times the letter ‘r’ occurs in ‘strawberry.’ 

Even after the unimpressed Dr Dickinson identified all three, ChatGPT still insisted she was wrong. 

“What I love is how confident it sounds. And I'm sure that if this is a more complex problem, I might actually doubt myself,” she said. 

After the Herald’s AI-infused editorials came to light last month , its current editor told journalists they should look for new ways to use AI for greater efficiency. 

The day before, the ABC puts its AI policy out in the open - including for journalism - in a live public forum called Futurecast . 

Angela Stengel, ABC’s Head of Digital Content & Innovation (L) and Kim Williams, chair of the ABC speaking at Futurecast 2024. Photo: screenshot from livestream

“Bury yourself in the technology and apply the technology - and understand the way in which it can be applied,” the ABC's chair Kim Williams said loftily. 

“In a simple application in journalism . . . you can use the technology to create a masterpiece of reductive presentation of all of the essential elements in a piece of information that people want to know about, but they don't want to spend an hour reading,” he said. 

Hear Mediawatch report on these issues in this week's show here 

“Before the end of the current year, checking will be done by AI  . . . by a separate set of programs, of material that is actually originated by AI,” said Williams - also a veteran of commercial media, entertainment and news companies - about the news agency Reuters.  

“Pretty scary when you think about it,” he added as an afterthought. 

Asked if AI was “a friend or a foe” for Australia's media, the chief technology officer of NewsCorp, Julian Delaney, told Futurecast that disclosing the use of AI was vital for public trust. 

“That, in a strange way, provides an incredible opportunity for a publisher to shine with trusted content that is of value. There might be a time where a news site is stamped: ‘No AI.’ Or their news site might say: “Completely done by AI.” I don't know  . . . but I do think it's a friend,” he said.  

Where is all this heading? 

Newsrooms in New Zealand are already using AI to cut stories down to size and change the grammar and the vocabulary.  

Elsewhere in the Asia Pacific, some newsrooms are already using AI in ways no one is here - yet. 

Some are also using it to fight back against the fake stuff undermining news and journalism. 

“My Hong Kong newsroom bans generative AI internally. We bar AI training bots from scraping us because I worry about hallucinations, plagiarism and its lack of attribution,” Tom Grundy from the independent online outlet Hong Kong Free Press said at The Future of Facts , a recent international media conference in the Philippines attended by several New Zealand journalists, including Mediawatch,  with the assistance of the NZ Asia Foundation .   

“There's no remuneration for gobbling up our archive, and it can't recognise bad-faith content and propaganda. Mostly, I worry about accuracy - and not the big, obvious, stupid stuff but small, nuanced errors that will get echoed through multiple generations of AI unnoticed.

“Is it not advisable for newsrooms to hold out on using AI  . . . .given the risk people may mistrust AI and return to and value news that remained human-powered?” he asked. 

Good question. 

But former Google News Lab boss Irene Jay Liu said it's a bit late for that, because the online tech everyone uses is AI-powered as well. 

“If you are still allowing indexing for Google . . . you are allowing Google to use your content for their generative AI.

"AI overviews - formerly known as ‘search generative experience’ - is at the top in search. You cannot block it unless you block indexing and every newsroom should know this,” she said. 

Charlie Beckett is the director of the JournalismAI project at the London School of Economics, which helps newsrooms around the world adopt AI safely. But to what end? 

“We're going through a big election year and I'm seeing some brilliant uses of generative AI to monitor what politicians are saying  . . . during that election process. I see this as a way to free up resources so that you can do more ‘human’ journalism that's going to stand out in a world where a lot of routine content will be created by AI,” he said. 

“Above all, it's (about) getting out there and reporting in the real world, because too many journalists are glued to their screens and social media, and they don't get out and witness things for themselves. And those are the things that AI can't do.” 

The Conversation is a free service founded by universities to bring the wisdom of academics to a wider audience online. 

Its head of audience insights Khalil Cassamilly, based in Mauritius, uses AI to rejig The Conversation’s content, saying readers have found it hard-to-reach in the past. 

“Lots of people find a lot of value in reading fairly long articles, but increasingly other people are finding value in getting the same information in different formats.” 

“That could be Smart Brevity where we give people the information very quickly with different types of video and audio. Really, the AI is just there to create that based on the journalism that we'd already produced,” he told Mediawatch .

He cited Indonesia’s election in June. 

“One of the things we kept hearing from younger audiences in Indonesia was the news coverage was not really targeted at them. (They) want more context so by us using AI to repurpose journalism via formats that would appeal to that younger audience, they actually got the information.” 

“The output from the AI is fact-checked and goes through the same editorial process. We have full control.”

Cassamilly even provocatively told the conference news media aren't always good enough at supplying high-quality information and AI can amplify that. 

“As an industry, we can do much, much better. I think we've done some really bad stuff, to be perfectly frank, in the way, for example, we cover elections.

"It's not a surprise when we talk to people outside of the industry, that more often than not they have a negative view of journalists. That's quite sad, but it's definitely coming from some point of truth somewhere,” he said. 

“The difference between the news organisations and every other content producer out there is the burden on us is much higher. We should do better. We should do it more.”

Rappler logo Photo: supplied

Like The Conversation , the leading online-only news outlet in the Philippines - Rappler - uses AI to reformat and summarise for younger people. 

Rappler’s reporting of the excesses of the former government of Rodrigo Duterte made it - and its now famous founder Maria Ressa - targets of sanctions, threats and harassment. 

Ressa won the Nobel Peace Prize in 2021 for standing up to this and Rappler used technology to expose the harassment and to fight back. 

AI is at the heart of its Politics Knowledge Graph mapping connections in Philippine society and politics, and thousands of candidates for the Philippines elections in 2022. 

“We used the data that we've collected over the years, and we used AI to help us generate around 50,000 profiles,” Rappler's head of data and innovation told Mediawatch .  

“We didn't have the capacity to write all the profiles for all 50,000 with our manpower.”

Can he be sure there are not important errors in them?

“We didn't just use ChatGPT to generate profiles for everyone and then serve it up directly to the audience. We used its capacity to analyse large sets of data. It hallucinates when, for example, you make it follow a template and there are missing fields. That's where it makes things up.

“A significant amount of time was spent on human reviews . . . and spot checks to make sure it's following the templates that you've set up. And of course it is disclosed to the audience that we use ChatGPT and there’s feedback mechanism so they can contact us if they do spot anything wrong,” Don Kevin Hapal told Mediawatch . 

Irene Jay Liu, Regional Director, Asia & the Pacific at the International Fund for Public Interest Media (L) and Don Kevin Hapal, Head of Data and Innovation at Rappler. Photo: RNZ Mediawatch

“We don't use AI to replace what (journalists) are really good at doing. We're just using AI for the things that we wouldn't have done or wouldn't have been able to do - or that our people didn't want to do. That's the low-hanging fruit,” he said. 

“They like to be able to see their news within the platforms that they use - watching newscasts on TikTok, on Facebook. They have a particular preference for short-form content, but that's a very, very boring task to ask journalists to do - and we didn't want to make them feel like we're trying to turn them into influencers or content creators.” 

“There's a lot of pressure for newsrooms to use AI just for the sake of it. I don't think that's a good starting point. I think they should do their own audience research and take a look at whether or not a specific AI tool could provide a solution,” said Don Kevin Hapal. 

The bad stuff by bad people 

Whereas Rappler has adopted AI early and heavily in the Philippines, so have the makers of malicious and misleading stuff. 

To show just how simple it is, AI expert Art Min made deep-fake images of his own fellow panellists at the East West Center conference within seconds.

Fake content like that looks convincing enough to be watched and shared within seconds, he said. 

Impulsive people might act on what they've seen long before any critical thinking or debunking takes place. 

Think of the angry rioters in the UK recently, shouting slogans and online hashtags based on false claims from influencers who knew the claims were fake. 

Or a fake video of Kamala Harris which Elon Musk circulated to his 200 million followers on his own platform.

Min’s Seattle-based TrueMedia.org uses the same AI technology to find and flag fake images. 

In his address to the Future of Facts conference in Manila, the secretary of foreign affairs for the Philippines, Enrique Manalo, cited “myriad attempts at misinformation and the peddling of false narratives” inflaming the Philippines’ territorial dispute with China.  

The two nations’ vessels have clashed in the West Philippine Sea - aka the South China Sea - recently, raising fears that this could boil over into armed conflict. 

That was not helped by a faked recording that went viral recently, purporting to be the Philippines President Marcos telling his personnel to fight back.

Journalists have been deep-faked there, too. 

Well-known Philippines TV news broadcaster Ruth Cabal raised the alarm earlier this year when she and her newscast were impersonated in an AI-driven scam.

“That's when you realise how serious it could be, and that you're helpless. People should trust us with information, but people who are not really tech-savvy or not informed about AI are more vulnerable,” she told Mediawatch .

Media in the lead? 

Dominic Ligot, CEO of CyrroLytics and and member of the international expert panel on AI safety. Photo:

“Journalists . . . should certainly be on top of it. We should be the ones shredding the use of it as much as we can, but cognisant of the flaws and limitations of these tools,”  Dominic Ligot, CEO of Manila-based data company CirroLytix told Mediawatch . 

“They are not databases. They're only meant to write human-looking sentences and are trained on relatively outdated information. It should never really be used as a source of truth,” said Ligot, who was also on the international panel of experts formed for last year's AI Safety Summit held at Bletchley Park in the UK. 

He told the East West Center media conference far too few people were working on the safety of AI.

“Cars had no seat belts for decades, and [they] were seen as an unnecessary cost. Volvo's innovation dropped fatalities  . . . and eventually became mandatory. There could be a similar move on AI very soon. Those things need to be highlighted and journalists are the best placed to put them up. People will realise we need to find a way of imposing some seat belts on these tools.

“When you combine that with social media . . . the algorithms were designed to segment populations as a marketing tool. That's a problem social media hasn't cracked - and now you have an automated way of producing all of that information." 

“The public has been led by OpenAI and other companies to use it like Google search . . . like the ultimate information-gathering tool. We need to balance that - and journalists should report how these tools don't seem to work,” he said. 

“I'm not saying the technology won't improve. I think eventually it has to, but the way they just work today isn't what we think is possible." 

If a newsroom’s editor knows ChatGPT can't spell ‘strawberry’ and refuses to use it at all, is that a mistake? 

“Don't use it as a source of information or facts. But you can certainly use it to format the article, to check grammar or rephrase the article. You can ask the chatbot to check whether your article can be misunderstood. You do get an interesting insights. AI is perfectly suited for that,” Ligot told Mediawatch . 

“But astute politicians know how to take advantage of a kind of ‘digitally brainwashed’ culture. That's something journalists should be looking at and also hold technology companies to account.” 

“Other parties will be too busy talking about one thing or the other. Journalism is all about giving that balanced view,” he told Mediawatch . 

Earlier this month  Reuters reported OpenAI is working on a new approach to “advanced reasoning capabilities”. 

The code name for this previously top secret program, according to Reuters’ source? Strawberry.

Mediawatch attended the East West Center's 2024 ‘The Future of Facts' conference in Manila with the assistance of the NZ Asia Foundation.  

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To the conspiracy-minded alternative health practitioner, everything was great until the Flexner Report was published. Humanity was crushing diseases with herbal remedies and natural potions until 1910 when the “medical-industrial complex” came together and  “criminalized natural therapies.”  We are now afflicted by Rockefeller medicine, where ill citizens are hooked on expensive drugs that never heal them and the truth about the benefits of herbs is being hidden by paid-off politicians and academics.

This alleged fall from paradise can all be blamed on the original sin of that darn Flexner Report.

I would wager that most of the people hurling insults at this century-old book have never actually read it; I did, because I wanted to know what the fuss was all about.

The Flexner Report was commissioned because the state of medical education in the United States and Canada was dire. A young educator was hired to visit all of North America’s medical colleges and report back, which led to much-needed changes and some unfortunate consequences.

And, yes, he did have some harsh words for what he called “the unconscionable quacks.”

A medical degree  and  a free trip to Europe!

There is a reason why leeches and purging agents are now rarely used in medicine: the discipline has evolved over the millennia, and Abraham Flexner found himself at the beginning of a new and exciting era.

Medicine in the Western tradition began with Hippocrates and Galen. It began with dogma. “Facts,” Flexner wrote in his report, “had no chance if pitted against the word of the master.” Those who despise modern medicine will claim it has remained dogmatic to this day; but while practitioners can be set in their ways and new findings can linger before they are adopted, we are far from the pontifical medicine of old.

With the rapid development of anatomy in the 1500s, medicine moved from dogma to empiricism. This meant that instead of doctors simply parroting what they had been taught by the rock stars of their field, they would learn from their own experience. They would observe and they would treat accordingly. This approach was more welcoming to discovery, but it was still hard for doctors of that era to properly disentangle diseases that superficially looked the same.

What propelled the discipline forward was science. We came to realize that the human body obeys the laws of biology: it grows, reproduces itself, and dies in predictable ways, and by understanding this underlying biology, the doctor would be better able to prevent and treat disease. Scientific research fed clinical practice, and the medical student, no longer limited to watching, would  do  as well.

Like medicine, medical training itself had changed over the centuries. It started as a system of apprenticeship, where a trainee became indentured at a young age to a doctor and ran his errands. Eventually, he would get to learn the secrets of his master’s trade. In Europe, the teaching of medicine would move to the lecture halls, which were host to anatomy demonstrations, and many American students would cross the Atlantic to benefit from this enrichment in Paris or Edinburgh. It wouldn’t take long before American doctors saw a way to sprout a similar system stateside and reap its financial benefits.

They were called proprietary schools. They were privately owned, with their teachers splitting the profits among themselves. They could rent a cheap hall, get some inexpensive benches, and recruit students who didn’t even have a high school diploma. “A school that began in October,” Flexner wrote, “would graduate a class the next spring.” Their facilities were poorly stocked, with barely-existing laboratories. The money that didn’t end up in the founders’ pockets was used to make all sorts of wild promises in the advertising material. One of these medical colleges swore it would gift its graduates a trip to Europe!

Following this explosion in questionable proprietary medical schools in the mid-1800s, change was thankfully afoot, but something major was needed around which this change could crystallize.

Quality over quantity

The Flexner Report’s actual title is  Medical Education in the United States and Canada: A Report to the Carnegie Foundation for the Advancement of Teaching.  It was commissioned by industrialist Andrew Carnegie’s policy and research foundation. Much has been made of the report’s ties to Carnegie and to Rockefeller, whose own foundation alongside eight others would pour a lot of money to implement the solutions proposed in the Flexner Report. Flexner’s brother, Simon, was also a friend of John D. Rockefeller, Jr, and he directed the Rockefeller Institute for Medical Research for more than three decades. Seen through our modern lens, this friendly alliance between medical education and capitalistic interest can trigger a fair amount of skepticism, if not outright conspiracy theories. It was in the wealthy elite’s interest to downplay the impact of social disparities on health and to promote the simpler idea that the human body was a machine whose broken parts could be mended by the right science-informed technician. But as we’ll see, the report itself did not stick to this narrow viewpoint.

Abraham Flexner, whom the Carnegie Foundation recruited for this massive work, was not a doctor; he was a teacher. Born in Louisville, Kentucky, Flexner studied Greek, Latin and philosophy as an undergrad at Johns Hopkins, and this university made a profound mark on him. It would become the template for Flexner’s medical education revolution.

After teaching high school, Flexner opened his own private preparatory school, which served as a laboratory for his educational convictions. After receiving a Master’s degree in philosophy from Harvard, exploring Europe, and writing a book on American education, he was recruited by the head of the Carnegie Foundation. His mission: to tour the 150 medical schools in the United States and Canada and report back in writing on what their problems were and how to solve them. Already, the deceptive marketing of many of these schools and their deficient scientific education was known; Flexner was to document it. His report was scathing.

Flexner wrote of the dissection rooms where cadavers were as dry as tanned leather. He denounced the medical colleges claiming to have access to a hospital for their students when that was not the case. Many schools did not have full-time faculty and lacked proper laboratories. At the North Carolina Medical College, in Charlotte, Flexner was told that asking about laboratories was futile: their students were “all thumbs,” better suited to be farmers.

His year-and-a-half survey of North America resulted in a three-tiered list of medical colleges.

Sixteen were in tier one, requiring at least two years of college for admission and doing their best to meet the standard set by the Johns Hopkins Medical School. Fifty were salvageable and required of their student applicants a high school diploma. The rest, mostly found in the south of the United States, was a complete loss, in his opinion. “For the law, if enforced, would stamp them out.” (In case my colleagues are curious, he admired McGill’s own medical school, calling it “excellent” and being impressed by its anatomical and pathological museums, as well as its library. Its medical budget at the time was a mere $77,000.)

Flexner’s short-term solution to the proliferation of inadequate, for-profit medical schools was to shut them down and fund the ones that had stricter standards and that were affiliated with a university. He recommended quality over quantity, with fewer but better equipped schools graduating fewer physicians that were better trained. His influential book-length report was used to justify an influx of $154 million in the medical education system over the course of nearly two decades.

While prioritizing quality is commendable, the consequences of the Flexner Report were not all positive. Almost all women’s and historically Black medical colleges  shut down in its wake , and women were nearly eliminated from the physician workforce until the 1970s. Medical schools were consolidated in large urban centres and required more money and education to get in, which meant that middle- and upper-class white men had an easier time becoming physicians. And closing a bad medical college in the American South might have been smart in the short term, but if it was not replaced by a better school, it simply created an educational desert.

But if the Flexner Report was focused on improving  medical  education, why are so many homeopaths and naturopaths mad about it?

Made-up minds

In chapter 10 of his report, Flexner goes for the jugular of what he calls the “medical sects.” Those were competing philosophies of medicine, like homeopathy, osteopathy, and eclectic medicine (a plant-based approach). Flexner correctly observes that unlike the doctor who wants facts and not dogma, “the sectarian […] begins with his mind made up.” He denounces the contradiction in many of the best sectarian colleges, where students underwent two years of chemistry, biology, and physics, before entering clinical training and suddenly being introduced to a pseudoscientific principle that contradicted what they had just learned.

Flexner was not single-handedly responsible for shutting these colleges down. In the ten years before the publication of his report, the 22 homeopathic colleges in the U.S. were trimmed down to 15. Much like the scientific revolution changing medicine, the Flexner Report did not begin the transformation but simply galvanized it.

Yet, Flexner, perceived as the hatchet man that tore down much of the medical education infrastructure, has become a lightning rod for misconceptions and bad arguments. He is sometimes accused of having denigrated the value of public health, which is simply false. In his report he writes of bad environmental conditions that breed disease, such as a contaminated water and food supply. The good doctor’s role, he writes on page 68, “is equally to heal the sick and to protect the well. The public health laboratory belongs, then, under the wing of the medical school.” To make the point even clearer, Flexner notes that “the physician’s function is fast becoming social and preventive, rather than individual and curative.”

And while a hyperfocus on science as the answer to medical problems can lead to inhumane treatment (and certainly had a role to play in eugenics and unconscionable medical experiments like Tuskegee’s), Flexner understood the importance of care. His ideal doctor required “insight and sympathy” in order to heal. That priority may have gotten lost in the implementation of his plan, but it is present in the report, black on white.

When the sectarians he condemns criticize his report, they often claim that he transformed medicine from a holistic view of the entire body into a myopic practice that only focused on broken body parts. This is a convenient argument for them. As scientific research nourished clinical practice, our body of medical knowledge grew, forcing doctors to specialize. But there is no real growth in so-called alternative medicine. There is no  need  to specialize when you believe there is only one true cause to all diseases. Whether it’s an alleged chiropractic subluxation or a blockage of the supposed life force called qi, it’s just an obstruction. All these practitioners need to do is find the source of the blockage and declog the pipe, much like a plumber. As Flexner pointed out, though, this is not science but dogma masquerading as knowledge.

As for the loss of holism in medicine, it still exists in family medicine, and especially in group practices, where integrating knowledge from specialties is commonplace. But given the incredible amount of knowledge generated in scientific medicine, it is absurd to expect every doctor to know everything.

The Flexner Report of 1910 was an imperfect catalyst that helped move medicine into its science-informed era. It would take many more decades, though, before the randomized controlled clinical trial was adopted as a gold standard for determining the worth of a treatment or preventative. The report also exacerbated inequalities in access to medical education in an attempt to reward the most rigorous institutions. Nonetheless, it argued that the best place for medical education was not in a privately owned and poorly regulated makeshift school but in a university, where foundational research could provide new solutions to the healer.

The kind of quackery that Flexner decried has not really gone away, despite what he predicted, and its practices certainly have not been criminalized.  Osteopathy  raised its standards in the United States and became, for all intents and purposes, equivalent to medicine. Homeopathic colleges are rare but  their hyperdiluted concoctions  are still widely available. Some dubious professions, like naturopaths, have acquired an unearned legitimacy in some states and provinces, and the concept of integrative medicine—of adding junk practices to actual medicine to get some sort of best of both worlds—has unfortunately made  massive strides in academia .

The battle against medical sectarianism has not been won. There is a lot of work left to do.

Take-home message: - The Flexner Report, published in 1910, crystallized a revolution in North America toward teaching a type of medicine that was strongly influenced by scientific discoveries - The claim that Flexner downplayed the importance of public health and preventive medicine in his report because he was working for the Carnegie Foundation is simply false - The claim that medicine stopped treating the whole person after the Flexner Report came out but that natural healers still do is false: family medicine is holistic; medical specialties exist because of our increased knowledge; and natural healing practices have no need to specialize since they often believe there is one true cause to every disease, which is wrong

@CrackedScience

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Amygdala fMRI—A Critical Appraisal of the Extant Literature

Tim varkevisser.

1 University Medical Center, Utrecht, The Netherlands

2 Brain Research and Innovation Center, Ministry of Defence, Utrecht, The Netherlands

3 Utrecht University, Utrecht, The Netherlands

Elbert Geuze

Jack van honk.

4 University of Cape Town, Cape Town, South Africa

Even before the advent of fMRI, the amygdala occupied a central space in the affective neurosciences. Yet this amygdala-centred view on emotion processing gained even wider acceptance after the inception of fMRI in the early 1990s, a landmark that triggered a goldrush of fMRI studies targeting the amygdala in vivo. Initially, this amygdala fMRI research was mostly confined to task-activation studies measuring the magnitude of the amygdala’s response to emotional stimuli. Later, interest began to shift more towards the study of the amygdala’s resting-state functional connectivity and task-based psychophysiological interactions. Later still, the test-retest reliability of amygdala fMRI came under closer scrutiny, while at the same time, amygdala-based real-time fMRI neurofeedback gained widespread popularity. Each of these major subdomains of amygdala fMRI research has left its marks on the field of affective neuroscience at large. The purpose of this review is to provide a critical assessment of this literature. By integrating the insights garnered by these research branches, we aim to answer the question: What part (if any) can amygdala fMRI still play within the current landscape of affective neuroscience? Our findings show that serious questions can be raised with regard to both the reliability and validity of amygdala fMRI. These conclusions force us to cast doubt on the continued viability of amygdala fMRI as a core pilar of the affective neurosciences.

Introduction

Now more than 20 years ago, Merboldt et al. 1 published a brief commentary titled: “Functional MRI of the Human Amygdala?.” At the time, Merboldt and his colleagues wrote this commentary to draw attention to the (then often overlooked) presence of magnetic susceptibility artifacts occurring in the amygdala due to the proximity of bone and air-filled cavities (ie, sinuses). Although these artifacts are less of a concern now that we scan at (much) higher field strengths, the question itself is now relevant as it was back then—albeit for somewhat different reasons. The purpose of this review is to provide an overview of the contributions amygdala functional magnetic resonance imaging (fMRI) has made over the years to the affective neurosciences at large, in order to critically assess its enduring role as a research tool in the current scientific landscape

Academic interest in the amygdala as an emotion processing region originally arose due to observations of hypo-emotional behavior in rhesus monkeys after (bilateral) ablation (part of the “Klüver-Bucy syndrome”). 2 - 4 A more explicit proposal for the amygdala’s role in emotion processing would not follow, however, until the structure came to be closely associated with Pavlovian fear conditioning in animal models (eg, see Maren & Fanselow 5 for a review). From this perspective, the amygdala (particularly its basolateral subdivision) is seen as the locus at which stimulus-reward/punishment associations are forged within the brain, thus linking noxious unconditioned stimuli (eg, an electric shock) on the 1 hand, to otherwise innocuous conditioned stimuli (eg, a tone) on the other hand. The autonomic response to this conditioned fear is then mediated indirectly by the (centromedial) amygdala via descending pathways projecting to lower brain regions such as the periaqueductal gray, while the activity of the amygdala itself can be modulated by regulatory prefrontal regions such as the medial prefrontal cortex (MPFC). 6 , 7 While not always explicitly addressed anymore in the literature, this fear conditioning framework has in fact shaped much of our way of thinking about the amygdala’s role in emotion processing.

With the advent of fMRI in the early 1990s, the study of amygdala and emotion was no longer confined to animal models, as the early work on Pavlovian fear conditioning often was, but could also be extended to human populations. Initially, this burgeoning field was mostly limited to studies that utilized some form of emotion provocation to measure the magnitude of the amygdala’s blood-oxygen-level-dependent (BOLD) response to in-scanner stimuli (see section “Amygdala Activation fMRI”; Figure 1 , top-left panel). From the mid-to-late 2000s onwards, however, scientific interest began to shift more and more towards the study of the brain’s (and by extension, the amygdala’s) functional- and effective connectivity architecture (see sections “Amygdala PPI fMRI” and “Amygdala RSFC fMRI”; Figure 1 , top-right and middle-left panels, respectively). In the 2010s, a general trend towards more reproducible science saw some research-groups more closely examining the test-retest reliability of amygdala fMRI (see section “Amygdala Test-Retest Reliability fMRI”; Figure 1 , middle-right panel). At around the same time, advances in the field of real-time fMRI neurofeedback enabled researchers to target the human amygdala in vivo (see section “Amygdala Real-Time fMRI Neurofeedback”; Figure 1 , lower panel). We end this review by integrating the main insights garnered by these subbranches of research, after which we aim to answer the question: What part (if any) can amygdala fMRI still play within the current landscape of the affective neurosciences (see section “Integration”)?

Number of publications per year for each of the amygdala fMRI subtopics discussed in the main body of the text. For the top-left panel (amygdala activation fMRI), a combination of the following search-terms was used: “amygdala” AND “fMRI” AND (“activity” OR “activation”). For the top-right panel (amygdala PPI fMRI), the following search-terms were used: “amygdala” AND “fMRI” AND (“PPI” OR “psychophysiological interaction” OR “psycho-physiological interaction”). For the middle-left panel (amygdala RSFC fMRI), the following search-terms were used: “amygdala” AND “fMRI” AND (“resting-state” OR “resting state”) AND “functional connectivity”. For the middle-right panel (amygdala test-retest reliability fMRI), the following search-terms were used: “Amygdala” AND “fMRI” AND (“test-retest reliability” OR “intraclass correlation coefficient” OR “ICC”). Finally, for the lower panel (amygdala rt-fMRI neurofeedback), the following search-terms were used: “amygdala” AND “fMRI” AND (“neurofeedback” OR “real-time fMRI”). All searches were conducted on PubMed based on keyword matches in the title/abstract field.

Amygdala Activation fMRI

Functional MRI first appeared in the early 1990s. 8 - 11 The first 2 studies to specifically target the amygdala via fMRI, Breiter et al. 12 successfully elicited an amygdala response by using stimuli based on human facial expressions (ie, fearful or happy), whereas Irwin et al. 13 utilized pictures taken from the International Affective Picture System (IAPS) to the same avail. Interestingly, these 2 tasks have remained the 2 gold standards for emotion provocation/amygdala fMRI to this very day.

Following in the footsteps of Breiter et al. 12 and Irwin et al., 13 multiple studies were published that similarly examined the amygdala’s role in emotion processing using task fMRI (see Figure 1 , top-left panel; see Costafreda et al. 14 and Sergerie et al. 15 for meta-analyses). In most of these studies, either (a variant of) the facial expression task described by Breiter et al. 12 was used (eg, 16 - 22 ), or an emotional pictures (ie, IAPS-based) task like the 1 detailed in Irwin et al. 13 (eg, 23 - 27 )—although (written) emotional words (eg, 28 - 30 ), and tasks based on Pavlovian fear conditioning (eg, 31 - 34 ) were also quite common. In 1 landmark study, Hariri et al. 35 directly compared the efficacy of stimuli based on facial expressions (ie, fearful or angry) or (negative) IAPS pictures, and found that while both types of stimuli were indeed able to induce a significant increase in amygdala (re)activity relative to baseline, facial expressions were significantly better at doing so than IAPS pictures were; it should be mentioned, however, that subsequent studies have been unable to replicate this finding. 36 , 37 While the amygdala was initially hypothesized to play a distinct role in the processing of facial emotion (fear, anger, happiness, disgust, etc.; eg, 16 , 18 , 38 ), fMRI researchers later began to consider the amygdala more as a region involved in the detection of salience in general (eg, 39 - 42 ). This altered viewpoint fitted well with observations of relatively high magnitudes of amygdala activation when using either scrambled pictures, a fixation cross, or a blank screen, instead of non-expressive faces, as a neutral baseline for contrast discriminability. 15 , 40 , 42 When viewed in this light, the amygdala responds to all stimuli that signal some form of personal relevance or threat, including emotional stimuli, be they of the facial variety or otherwise.

Given the above, it is perhaps not surprising that the amygdala has (also) garnered much attention by researchers interested in face processing. In fact, some authors have advocated that the amygdala should be seen as a core component of a larger network involved in processing faces (eg, see Mende-Siedlecki et al. 43 ). Consequently, much effort has been spent over the years in trying to uncover the optimal task and stimulus parameters to adequately activate the amygdala using facial expressions. A number of consistent findings have emerged from this research: (1) the amygdala responds more strongly to the presentation of dynamic (ie, rather than static) expressions of affect; 44 - 46 (2) the amygdala response is higher when the faces are looking directly toward (versus away from) the observer; 21 , 47 , 48 and (3) paying overt attention to facial expressions seems to augment the amygdala’s response, 17 , 20 —although non-consciously perceived faces are apparently still able to elicit a significant increase in amygdala activity relative to baseline. 18 , 49 , 50 More recently, Kätsyri et al. 51 observed that the amygdala’s response to facial stimuli may also be higher when participants are exposed to real versus computer-generated faces, although Moser et al. 52 were unable to record a similar effect previously. Overall, this body of literature seems to indicate that the amygdala response is strongest when participants are paying overt attention to facial stimuli that are presented to them in as much of a naturalistic and personally relevant (ie, salient) manner as possible.

An early systematic review of the amygdala fMRI literature by Baas et al. 53 was the first to point towards a possible lateralization effect of the amygdala’s reactivity to emotion stimuli, with more of the included studies reporting activation in the left than in the right amygdala—regardless of the stimulus type, task instructions, habituation rate, or complexity of the in-scanner task that was used. Sergerie et al. 15 later replicated this finding in a quantitative meta-analysis of the emotion processing fMRI literature; however, these authors were unable to record a significant difference in the magnitude of left versus right amygdala activation. In another meta-analysis, Costafreda et al. 14 recorded a left lateralization effect for the processing of (static) emotional expressions only when the stimuli contained language elements, at the same time recording right lateralization only when the stimuli were masked to prevent consciously perceiving the facial expressions. Importantly, no other indications of lateralization were observed in that study. In a voxel-based meta-analysis of facial expression task fMRI studies, Fusar-Poli et al. 54 were similarly unable to record significant lateralization of the amygdala’s task reactivity. Finally, in a meta-analysis of the dynamic facial expression task fMRI literature, Zinchenko et al. 46 recorded significant activation within the left amygdala but not the right amygdala. Together, these findings paint a somewhat unclear picture of the possible lateralization of amygdala activation.

The amygdala has frequently been linked to alterations in BOLD-reactivity in individuals suffering from some form of psychopathology. Indeed, the list of psychiatric disorders to which task fMRI studies have now been able to link the amygdala is long and includes (but is not limited to) disorders such as social anxiety disorder (SAD; eg, 55 , 56 ; see Etkin & Wager 57 for a meta-analysis), schizophrenia (eg, 58 - 60 ; see Anticevic et al. 61 for a meta-analysis), posttraumatic stress disorder (PTSD; eg, 62 - 65 ; see Hayes et al. 66 for a meta-analysis), borderline personality disorder (BPD; eg, 67 , 68 ; see Ruocco et al. 69 for a meta-analysis), major depressive disorder (MDD; eg, 70 - 72 ; see Groenewold et al. 73 for a meta-analysis), bipolar disorder (eg, 74 , 75 ; see Chen et al. 76 for a meta-analysis), intermittent explosive disorder (IED) 77 , 78 —and even Turner syndrome 79 and Alzheimer’s disease 80 . (We note that the meta-analyses of Etkin & Wager, 57 Anticevic et al., 61 and Hayes et al. 66 also include Positron Emission Tomography [PET] studies; however, a full list of the included studies is presented in each meta-analysis in table-form, along with the imaging methodology that was employed in each incorporated study [ie, fMRI or PET].) Overall, this body of research suggests that hyperreactivity of the amygdala may be present in individuals suffering from disorders such as SAD, PTSD, BPD, bipolar disorder, or IED, whereas hypo activation has often been recorded in schizophrenia; MDD has been linked both to hypoactivation in response to positive emotional stimuli, and hyper reactivity to emotional stimuli with negative valence. Together, these findings have led many researchers to posit that altered amygdala reactivity might be able to serve as a biomarker of emotion regulation pathology.

It should be mentioned that while the above body of literature may seem consistent in its reporting of amygdala reactivity in response to emotion provocation, there are, in fact, many examples of studies that failed to record such an effect (eg, 81 - 85 ). What is more, there are also many examples in which no significant difference in amygdala reactivity could be recorded when patients with a psychiatric disorder were compared to those without (eg, 86 - 90 ). This indicates that activation of the amygdala via emotion provocation fMRI may not be as robust a phenomenon as often assumed in the literature. It is also important to point out that only 3 of the 66 research articles cited in this section had a sample size of N ⩾ 30 (median N = 12; IQR = 10-15 participants). Such small sample sizes may increase the risk of false positive findings and inflate effect sizes, especially when considering that the shadow of publication bias looms large over the overarching field of functional neuroimaging. 91

Amygdala Connectivity fMRI

In the early years of fMRI, most studies focusing on the amygdala only examined the region’s magnitude of BOLD-reactivity in task-based settings. From the mid-2000s and onwards, however, fMRI researchers became increasingly interested in (also) examining the connectivity patterns of the amygdala, following a broader trend taking place in neuroscience at the time. These studies can be (roughly) subdivided into the following 2 categories: (1) psychophysiological interaction (PPI) studies that have examined task-dependent effective connectivity during active task periods, and (2) functional connectivity studies examining task-free (ie, intrinsic) fluctuations of the BOLD-signal at rest (ie, resting-state functional connectivity [RSFC]). An overview of the insights garnered by these 2 research areas is provided in the following 2 subsections.

Amygdala PPI fMRI

PPI is a measure of effective connectivity designed to ascertain instances of communication between brain regions that only take place under specific task demands, as maintaining these connections might otherwise prove costly in terms of energy consumption. In PPI analysis, linear regression is used to test for an interaction between a physiological variable (ie, the time-series of a seed region) on the 1 hand, and a psychological variable (ie, the experimental task) on the other hand. If significant, the brain region expressing the interaction is said to exhibit context-dependent effective connectivity with the seed ROI. 92

PPI analysis was developed by Karl Friston and co-workers in the mid-to-late 1990s. 93 , 94 Although the first PPI studies focusing on the amygdala date from the early 2000s, most of the work conducted in this field was actually published in the 2010s (see Figure 1 , top-right panel). As before, the majority of these studies employed either a facial expression task (eg, 43 , 95 - 99 ), or an emotional pictures task based on IAPS-photographs depicting non-facial objects or scenes (eg, 100 - 104 ). In many of these studies, amygdala PPI was examined while participants were performing some form of emotion regulation training (eg, 100 , 104 , 105 ; see Berboth & Morawetz 106 for a meta-analysis). Furthermore, some of these studies were conducted in patients with (versus without) a psychiatric disorder—examples of which include schizophrenia 107 , 108 (although see Fakra et al. 109 ), MDD, 110 bipolar disorder, 111 , 112 PTSD 113 , 114 (although see Van Rooij et al. 88 ), IED 77 , 78 (although see Heesink et al. 90 ), BPD, 115 and generalized anxiety disorder (GAD). 116 , 117 Still others report on the relationship between amygdala PPI and personality constructs such as trait neuroticism, 118 aggression, 77 and psychopathy. 119 Whatever the exact research aims, however, most of these studies converge on the same target regions exhibiting significant PPI with the amygdala during task performance. These regions include the early visual cortex (ie, Brodmann areas 17-19), fusiform gyrus—including the fusiform face area (FFA)—the anterior cingulate cortex (ACC) and insula; the 2 main constituents of the salience network, 120 the inferior frontal gyrus (IFG), orbitofrontal cortex (OFC), and dorsolateral prefrontal gyrus (DLPFC)—the last of which is considered to be a main constituent of the central executive network. 121 Other regions of the brain with which PPI research has often associated the amygdala include the MPFC (both its ventral and dorsal aspects) and the ventrolateral prefrontal cortex (VLPFC), as indicated by meta-analyses of the amygdala PPI literature by Smith et al., 122 Di et al., 123 and Berboth et al. 106 . Importantly, the results of these PPI studies are (largely) consistent with the patterns of task-based effective connectivity of a landmark study using structural equation modelling by Stein et al. 124 . (Note: 1 complicating factor in reviewing this literature is that authors tend to differ in their operational definitions of anatomical or functional brain regions. For instance, [part of] what is labelled as the ACC in 1 study, may instead be labelled as the MPFC or the OFC by others. This overlap should be kept in mind when reading both the sections on amygdala PPI and RSFC.)

Taken together, this body of research seems to support the notion that the activity of the amygdala is gated by executive control regions in the prefrontal cortex. Diminished coupling between these prefrontal regions and the amygdala might lead to the development of mental health issues, particularly those marked by emotion dysregulation problems. The amygdala’s PPI with the primary nodes of the salience network (ACC and insula) further support the region’s role in salience detection. Its effective connectivity with the fusiform gyrus is likely to reflect the amygdala’s role in facial processing.

Amygdala RSFC fMRI

Almost since the inception of fMRI, researchers were aware that spontaneous low-frequency fluctuations (<0.1 Hz) occur in BOLD-weighted data. 125 While initially (dis)regarded as noise, it was not until Biswal et al. 126 observed significant correlations between the resting-state signals of the left and right sensorimotor cortices that fMRI researchers truly began to take notice of these fluctuations, and realized that they are, in fact, of neuronal origins. Even then, however, “the neuroscience community, with few exceptions, was remarkably slow to take note of this important result,” as Snyder & Raichle 127 phrased it. Eventually, however, resting-state functional connectivity (RSFC)—also known as task-free, intrinsic, or spontaneous functional connectivity—began to gain a foothold in fMRI research.

Biswal’s seed-based approach remains a very common way to assess RSFC today. The first RSFC studies to use this method to target the amygdala were published in the late 2000s/early 2010s (see Figure 1 , middle-left panel). In a study that would become a major landmark in the literature, Roy et al. 128 characterized the patterns of amygdala-based RSFC in a (large) sample of healthy volunteers (N = 65), showing that the amygdala exhibits (1) positive RSFC with the hippocampus, parahippocampal gyrus, and superior temporal gyrus, as well as with medial prefrontal regions such as the ACC and (medial) OFC, a finding that is largely consistent with the amygdala’s purported role in associative learning; (2) positive RSFC with the insula (and ACC)—which again points towards its role in salience detection; (3) negative RSFC with (dorso)lateral regions of the prefrontal cortex, including the middle and superior frontal gyri, which is in line with a top-down (executive) control model on emotion regulation; and (4) negative RSFC with the precuneus/posterior cingulate cortex (PCC)—two main components of the “task-negative”, or default mode network. Following in the footsteps of Roy et al., 128 many others subsequently sought to chart the landscape of amygdala-based RSFC in populations suffering from psychiatric disorders, such as GAD (eg, 129 ), SAD (eg, 130 , 131 ), PTSD (eg, 132 - 134 ; see Koch et al. 135 for a systematic review), MDD (eg, 136 , 137 ; see Tang et al. 138 for a meta-analysis), bipolar disorder (eg, 139 , 140 ; see Vargas et al. 141 for a systematic review), and to a lesser extent, schizophrenia. 142 - 144 In our own work, we conducted amygdala-based RSFC analysis in war veterans with versus without a IED, recording group differences only when applying a rather lenient threshold of significance. 145 Intriguingly, even though (task) activation studies on BPD were quite common in the heyday of emotion provocation fMRI, relatively little research has focused on the amygdala-based RSFC of this Axis II disorder. Possibly, the high degree of psychiatric comorbidity common in this population has prevented researchers from conducting RSFC fMRI research in BPD patients (eg, see Table 1 in Shafie et al. 146 ). Nevertheless, taken as a whole, this body of literature tends to show that the strength of many of the functional connections reported by Roy et al. 128 may be disrupted in psychiatric disorders marked by emotion regulation problems.

In 2001, Raichle and colleagues 147 at Washington University proposed the existence of a network of (primarily) midline brain structures that activates when not engaged by a specific task, based on observations in PET-data. A few years later, Greicius et al. 148 used Biswal’s seed-based approach to demonstrate that the BOLD-signals of these same brain regions are highly intercorrelated during rest. It is now clear that this default mode network (or DMN)—which mainly comprises the (dorsal) MPFC and PCC/precuneus—can routinely be extracted from resting-state fMRI data by using independent component analysis (ICA). 149 , 150 The discovery of the DMN would mark the first of many large-scale connectivity networks to be uncovered (through ICA) over the years. Other well-known examples include the central executive network (CEN), a constellation of brain regions centering around the DLPFC and dorsal posterior parietal regions, 121 and the salience network (SN), which is anchored around the anterior insula and dorsal ACC. 120 Importantly, rather than (sub)serving any 1 function in particular, the activity and/or connectivity dynamics of these large-scale networks are purported to support a broad range of psychological faculties, operating in a much more domain-general fashion than often assumed by traditional views on brain functioning, which tend to focus on functional segregation (rather than integration). 151 For instance, the DMN has often been linked to functions that vary from remembering personal memories, to moral cognition and reasoning, and imagining the future, while the SN is associated with the detection of personally-relevant stimuli, be they internally or externally generated, of the emotional, cognitive, or social variety (or otherwise). 120 , 151 The interaction (switching) between these networks is thought to give rise to complex phenomena such as emotion and cognition. Importantly, the amygdala is often considered to be a part of the SN, 120 , 152 which on the 1 hand, fits well with its hypothesized role in salience detection, but on the other hand, somewhat trivializes the region’s importance, as when viewed from this angle, the amygdala is only a very small and non-central component of a much larger apparatus. It cannot be denied, however, that this (network-based) perspective does far more to consider the complex nature of brain functioning than do traditional small-scale circuit models on emotion processing. It also provides a viable explanation as to why much of the brain’s energy consumption actually takes place during the resting-state. 153

Amygdala Test-Retest Reliability fMRI

In the 2010s, researchers became increasingly interested in (re)evaluating the test-retest reliability of (amygdala) fMRI (see Figure 1 , middle-right panel), perhaps prompted by the reproducibility crisis that was slowly making its way over from the psychological sciences. 91 This is not to say that earlier work had not already explored the retest reliability of amygdala fMRI to some extent. For instance, Johnstone et al. 154 recorded mostly poor test-retest reliability for task-evoked amygdala responses to neutral or fearful faces measured over 3 (scan) sessions separated by several weeks (most intraclass correlation coefficients [ICC’s] <.4), indicating low replicability at the subject-level—although ICC’s tended to be somewhat higher when averaging across runs within scan sessions (ICC’s in the range of 0.4-0.63). (In the fMRI literature, ICC’s are generally categorized as follows: poor <0.4, fair 0.4-0.59, good 0.6-0.74, excellent >0.75. 155 ) In another early study, Manuck et al. 156 recorded poor test-retest reliability of BOLD activation in response to fearful or angry faces in the left amygdala (ICC = −0.08), but fair test-retest reliability in the right amygdala (ICC = 0.59). (We note that although raw ICC’s are reported here, it is common to interpret negative ICC’s as being equivalent to zero.) In a later study, Plichta et al. 157 were able to record good-to-excellent replicability of the amygdala response to facial expressions at the group-level (ICC’s in the range of 0.62-0.79), even though test-retest reliability was rather poor at the within-subject level (all ICC’s <0.4). Sauder et al. 158 recorded poor-to-fair intra-subject test-retest reliability of the amygdala response to fearful- (ICC’s in the range of 0.32-0.43) but not happy or angry faces (all ICC’s <0.4 for both expressions). A subsequent study by Nord et al. 159 showed poor-to-fair intra-subject reliability of amygdala activation in response to 3 different facial expression tasks, when administered either across multiple sessions, or across multiple runs within single scan sessions (ICC’s in the range of −0.52 to 0.77, although most were below 0.4). These findings were confirmed by Lois et al., 160 who also recorded low within-subject reliability of the amygdala response to IAPS stimuli (ICC’s <0.4), even though quite excellent ICC’s (ie, >0.75) were observed for that same task—as well as 2 different facial expression tasks—at a group-level. Finally, Elliot et al. 161 observed low test-retest reliability (ICC’s <0.4) of the amygdala response to a face matching task in 2 separate datasets. (In fact, the results of that study showed that the ICC’s of most common fMRI tasks outside the realm of amygdala and/or emotion provocation were below 0.4.) In aggregate, this literature clearly shows that the test-retest reliability of amygdala activation by emotional pictures (facial expressions or IAPS-based) is rather poor at the subject-level, even though robust task (re)activity is often observed at the group-level, leading to serious questions in regards to the viability of task-evoked amygdala responsivity as a (clinical) biomarker. We should note, however, that the results of 1 study suggest that the intra-subject reliability of amygdala reactivity may be higher when measuring at 7 Tesla. 162 Moreover, some of the above-cited work tends to show somewhat higher ICC’s for task runs acquired within the same (as compared to across) scan session(s), which is consistent with the results of a study by Infantolino et al. 163 who recorded excellent split-half reliability for blocks of facial stimuli across runs within the same scan session, but only when blocks of fixation were used for contrast discriminability (split-half reliability = 0.97), and not when non-facial control stimuli (ie, geometric shapes) were instead used as a baseline (split-half reliability = −0.06). Of further interest, 1 study by Plichta et al. 164 suggests that the habituation of the amygdala’s BOLD signal may be a much more reliable intra-subject marker (ICC = 0.53) than the magnitude of the region’s task responsivity. Ironically, even though many of the above ICC papers point to the importance of larger sample sizes, only 2 studies cited in this section had a sample size exceeding 30 participants; ie, Lois et al. 160 (N = 46) and Infantolino et al. 163 (N = 139). The median sample size was N = 26.5 participants (IQR = 22.5-29).

To our knowledge, no study has ever specifically examined the test-retest reliability of amygdala-based RSFC. By and by, however, research focusing on the general test-retest reliability of RSFC tends to record rather low ICC’s of seed-based connectivity metrics, with higher ICC’s often being observed for network-based connectivity measures. For instance, in a meta-analysis of all test-retest reliability studies conducted on seed-based RSFC conducted (up until that point), Noble et al. 165 recorded a mean ICC of only 0.29. In a systematic review conducted in that same study, Noble et al. 165 found that connections within the same connectivity networks were generally stronger, particularly those within the DMN or CEN. These latter results are largely consistent with a replicability study of networks extracted via ICA by Zuo et al., 166 although Wisner et al. 167 recorded rather lower internal consistencies of large-scale connectivity networks in another (similar) study—especially at the intra-subject level. Furthermore, although Noble et al. 165 did not explicitly target the amygdala in their systematic review/meta-analysis, they did observe that the seed-based connectivity of subcortical brain regions was relatively low when compared to cortical areas. Finally, 1 study by Nord et al. 168 showed that amygdala’s PPI with the DMPFC during emotion provocation exhibited good test-retest reliability at the intra-subject level (ie, most ICC’s close to or above 0.59). However, this last finding awaits further confirmation/replication.

Amygdala Real-Time fMRI Neurofeedback

Many of the milestones of fMRI research discussed thus far can trace their roots to proof-of-concept papers already published in the 1990s. Real-time fMRI (rt-fMRI) is no exception. 169 Initially, this branch of research focused primarily on optimizing methodological aspects such as online quality assurance and motion correction/realignment. The first studies to apply rt-fMRI in a neurofeedback setting were published in the early 2000s (see Weiskopf 170 for a historical overview).

Neurofeedback is a form of biofeedback that has participants receiving “live” and ongoing information on their own brain (re)activity, so that they may learn to gain volitional control over it. Applications of neurofeedback in humans were initially based on electroencephalography (EEG) recordings. However, due to the lack of localization precision and limited coverage of EEG, many researchers were keen to discover novel ways of administering brain-based biofeedback to their study participants. As mentioned, the first studies to deliver on this promise and successfully apply rt-fMRI neurofeedback were published in the early 2000s. One of these early rt-fMRI neurofeedback studies already targeted the amygdala. In that study, Posse et al. 171 provided their participants with real-time feedback on amygdala activation in order to (successfully) augment neutral or sad feelings in their subjects via pictures of (corresponding) facial expressions. The majority of amygdala neurofeedback studies was published roughly ten years after this initial report by Posse et al., 171 in the 2010s (see Figure 1 , lower panel). Invariably, the express goal of these later studies was to employ neurofeedback in order to reduce the amygdala’s responsiveness to stimuli that were explicitly emotional in nature 172 - 188 (see Linhartová et al. 189 for a review), even though the general consensus in the field had already shifted towards a more domain-general and far less central view of the amygdala’s role in salience detection. Notably, none of these studies had a sample size exceeding 30 participants (median N = 14; IQR = 9-16). (We also note that many of the research articles cited in this section were actually based on the same or partly overlapping datasets. For instance, Yuan et al. 173 and Young et al. 178 are based on partly overlapping datasets; as are Nicholson et al. 187 and Nicholson et al., 186 as well as Young et al. 174 and Young et al., 176 and the same goes for Zotev et al., 172 Misaki et al., 175 and Misaki et al. 190 . The analyses of Paret et al. 183 and Paret al. 185 are even based on identical datasets.) Only 2 of these inquiries targeted the amygdala based on localizer data collected immediately prior to the neurofeedback runs: 191 , 192 In the work of Johnston et al., 191 only 2 out of thirteen subjects showed preferential amygdala activation during the localization stage (ie, in favor of other potential target regions); in Hamilton et al., 192 not a single participant showed any localizer-induced activation of the amygdala above and beyond that of either the dorsal ACC or insula, the 2 other main components of the salience network mask that these authors considered. These findings show that—when viewed as a salience detection area, rather than a structure dedicated specifically to the processing of emotion—the amygdala may not be an optimal target for rt-fMRI neurofeedback training.

With the exception of 1 study by Brühl et al., 180 who described the use of a facial expression task, most other neurofeedback works cited here used either IAPS stimuli (eg, 181 , 183 , 184 ), autobiographical (happy) memories (eg, 173 , 176 , 179 , 182 ), or personalized (trauma) words 187 to elicit an emotional amygdala response in their study participants. This is a bit surprising, given the predominance of facial expressions in other areas of amygdala fMRI. In some of these inquiries, only healthy volunteers were included, 179 - 183 while in others, patients suffering from psychiatric disorders, such as MDD 173 , 174 , 176 , 178 (see Young et al. 193 for a review), PTSD, 172 , 175 , 186 - 188 , 190 or BPD 184 (also) participated. Importantly, in all this work, at least some degree of self-regulation success was reported by the authors, with the observed (and expected) direction of effect (ie, up- or down-regulation) depending on task instructions. Insofar as clinical populations were recruited, successful BOLD regulation was frequently associated with significant reductions in symptom self-report questionnaire scores (eg, 172 , 174 , 177 , 178 , 184 ). One study even recorded an increase in hippocampal volume one-to-two weeks after self-regulation training of the amygdala’s BOLD activity in a sample of PTSD patients. 190 Overall, these findings tend to show that it is possible to gain volitional control over the amygdala’s activity via rt-fMRI neurofeedback, and that significant (clinical) improvements in emotion regulation may follow after (successful) amygdala neurofeedback training. 189

Finally, some of the rt-fMRI neurofeedback work discussed thus far has also examined the amygdala’s connectivity with other brain regions either during active feedback runs (ie, via PPI), 181 , 184 , 185 , 187 or immediately thereafter, during rest. 173 , 175 , 176 , 184 Overall, this (small) body of research tends to report an increase in RSFC of the amygdala with regions such as the VLPFC, DLPFC, ACC, PCC, and precuneus, from pre- to post-training, with more variable effects being recorded in the hippocampus and parahippocampal gyrus. With the addition of the insula and ventral- and dorsal MPFC, largely these same brain regions have been associated with an increase in amygdala PPI during active neurofeedback runs. Interestingly, 1 study based their neurofeedback on task-evoked effective connectivity between the DMPFC and amygdala, rather than the magnitude of the amygdala’s BOLD responsivity, 194 showing effects similar to the other works discussed here. In sum, these are largely the same brain regions for which amygdala-based connectivity effects were recorded previously, in the literature described in sections “Amygdala PPI fMRI” and “Amygdala RSFC fMRI.”

Integration

In this review, an overview was presented of the major developments that have occurred within the field of amygdala fMRI since its first appearance in 1996. We note that the body of literature discussed here should be considered as a general overview, and that it by no means is meant to be exhaustive; wherever possible or relevant, we have referred to other (systematic) reviews and meta-analyses for further reading. We also wish to emphasize that the conclusions drawn here are based entirely on our review of the fMRI literature, inspired by our personal experiences in that field; it does not cover preclinical (ie, animal) work on the amygdala’s role in emotion processing. For an overview of that line of research, we refer the reader to other sources (eg, Maren & Holmes 195 ). To visually complement the narrative provided here, a timeline of all the major landmark papers cited throughout this manuscript is presented in Figure 2 .

Timeline depicting some of the major landmark publications in amygdala fMRI research, color-coded by theme.

To recapitulate what we have discussed here: In section “Introduction,” we saw how early work in animal models, particularly within the sphere of Pavlovian fear conditioning, has shaped much of our way of thinking about the neurobiology of emotion processing. Next, we saw that soon after the first two amygdala fMRI publications, a veritable goldrush of studies ensued that similarly explored the amygdala’s BOLD response to emotional stimuli, most of which used either facial stimuli or IAPS photographs. Several key findings stand out from this literature: First, although many studies reported an increase in amygdala activation in response to emotional stimuli, there are also quite a few examples in which no such effects could be recorded. Second, as the years went by, the general consensus gradually shifted towards a frame of reference in which the amygdala was no longer seen as a brain region devoted specifically to the processing of emotional information, but more as an area involved in the detection of salience in a much broader sense. This idea resonated well with observations of higher activation magnitudes when using non-emotional and non-salient stimuli as a contrast baseline, such as scrambled pictures, a fixation cross, or a blank screen, rather than emotionally neutral, but potentially still relevant control stimuli (eg, neutral faces). Third, based on fMRI work in clinical populations, abnormal amygdala reactivity (hypo- or hyperactivation) began to be viewed as a potential biomarker of emotion dysregulation pathology. In the third section, we reviewed the literature on task-based effective- (ie, PPI) and RSFC of the amygdala as seed region. We saw that these 2 types of amygdala connectivity converge on many of the same target regions within the prefrontal cortex (OFC, MPFC, DLPFC, and VLPFC), as well as the ACC and insula involved in salience detection. During the resting-state, the amygdala exhibits additional connectivity with other regions involved in associate learning (eg, the hippocampus), as well as with the precuneus/PCC. A separate branch of RSFC research demonstrated the existence of large-scale connectivity networks such as the DMN, CEN and SN, leading to a fundamental shift in our collective understanding of brain functioning. Rather than assuming that complex functions such as emotion processing could be ascribed to the activity of single brain regions such as the amygdala, the connectivity dynamics of entire networks of brain regions gained more of a central focus, with each of these networks supporting a much broader range of psychological faculties that transcend the boundaries of cognitive, affective, and social neuroscience. According to this framework, the interactions (ie, shifting) between networks give rise to complex phenomena such as emotion and cognition, instead of the activity of any 1 brain region acting (more or less) in isolation. 151 This idea resonates well with the patterns of seed-based functional and effective connectivity observed for the amygdala, as many of its notable target regions are part of different large-scale networks, such as the CEN and DMN. Importantly, the amygdala itself is often considered a constituent of the SN—a network anchored around the (dorsal) ACC and anterior insula. While this notion fits well with the amygdala’s purported role in salience detection, it also greatly diminishes its central importance therein, as—according to this viewpoint—the amygdala is only a very small part of a much larger (salience) network. Yet it is difficult to deny the appeal of this network-based perspective, as it does far more to consider the complex nature of brain functioning than do traditional small-scale neurocircuit models on emotion processing. In section “Amygdala test-retest reliability fMRI,” we saw that, even though robust activation of the amygdala is often observed at a group-level, the test-retest reliability of that (same) task reactivity (as well as the amygdala’s seed-based RSFC) is quite poor at the single-subject level. We note that these results are consistent with some of our own observations. 196 In spite of this poor intra-subject reliability, however, there have been many recent studies targeting the amygdala via rt-fMRI neurofeedback, as we have seen in section “Amygdala real-time fMRI neurofeedback.”

So, what part (if any) can amygdala fMRI still play in the current landscape of the affective neurosciences? For 1 thing, if the amygdala is indeed just a small portion of a much larger network devoted to salience detection, and if the activity of the amygdala cannot be measured reliably at the single-subject level, than further targeting only the amygdala via rt-fMRI neurofeedback might be ineffective. Indeed, if the explicit purpose of such an approach is to facilitate emotion processing by influencing how the brain processes potentially salient information, than according to the literature reviewed here, some measure of clinical efficacy might only be expected if at least some of the other brain regions within the same salience network (ie, the anterior insula and/or ACC) are targeted as well. Even then, however, the poor test-retest reliability of amygdala fMRI suggests that the method may not (yet) be viable for real-time neurofeedback applications. How then should we interpret the body of amygdala rt-fMRI neurofeedback research reviewed in section “Amygdala real-time fMRI neurofeedback”? To answer this question, it is perhaps best to quote Thibault et al., 197 who’s critical assessment of the (larger) rt-fMRI neurofeedback literature aligns well with our own observations: “For someone perusing the literature, the aggregate of the above studies might give the impression of a robust base of converging findings in support of fMRI neurofeedback, whereas in fact, positive findings remain scattered across select runs and chosen participants. Statistical nuances can further frame the available evidence with an overly positive spin.” Extrapolating beyond the realm of rt-fMRI neurofeedback, given the available evidence, it is perhaps time to move away from a classical neurocircuit model that places the amygdala at the center of all things emotion. The evidence garnered over the years simply does not fit this notion very well. That is not to say that the amygdala is not involved in emotion processing at all , or that it is not (functionally) connected to brain regions such as the MPFC; it very likely is. For instance, preclinical work has often demonstrated the importance of the MPFC-amygdala circuit in the acquisition and extinction of conditioned fear in animal models (eg, see Maren & Holmes 195 for an overview). However, as we have seen, the amygdala does not respond selectively, or even very consistently, to emotional stimuli—at least not when measured with fMRI. Rather, it responds to all manner of cognitive, emotional or social information that signals some form of personal relevance or threat (ie, salience), and does so as part of a much larger network devoted to that same purpose. The amygdala is likely neither sufficient nor entirely necessary in that capacity. Of course, what constitutes as salient information is likely to vary considerably from person to person, as well as within individuals at any given time of day, which may help to explain why null-findings have been so prevalent in the amygdala activation fMRI literature, as well as why habituation of the amygdala’s BOLD response to emotion provocation is perhaps the region’s most replicable quality (at least, at the subject-level).

Whatever the precise function of the amygdala may be, however, the reliability of its task-induced BOLD reactivity, ie, insofar as emotion provocation fMRI is concerned, is at present simply too low to warrant its reputation as a robust single-subject neuroimaging biomarker of emotion processing. Interestingly, a recent overview of the most common 3 Tesla scanning protocols used in amygdala fMRI, suggests that methodological aspects such as the type of scan sequence, the spatial resolution (voxel size), imaging plane (axial, coronal, sagittal), brain coverage, scan time, and type of radiofrequency coil used, can all significantly impact the quality of the data (Foster et al. 198 ). These observations highlight the possibility that suboptimal imaging parameters, along with other methodological details, may lie at the root (at least partly) of the reliability-related issues amygdala fMRI currently faces. We certainly do not discount this possibility. Hence, we encourage future research efforts to take (even) further steps to identify the optimal scan parameters for adequately imaging the amygdala in vivo.

As mentioned above, our review of the amygdala fMRI literature is by no means meant to be exhaustive; rather, it is intended as a broad-strokes historical overview of the major themes in the field of amygdala fMRI. There are several lines of fMRI research that we have not discussed here that, although important in their own right, have had—at least in our opinion—somewhat less of an impact on the field overall. Examples of these include the effective connectivity of the amygdala as measured via Granger causality (eg, see Liao et al. 199 ) and/or dynamic causal modeling (DCM; eg, see Sladky et al. 200 ), the dynamic functional connectivity of the amygdala (eg, Cisler 201 ), which measures changes in intrinsic connectivity that occur over shorter periods of time, and the (fractional) amplitude of low frequency fluctuation ([f]ALFF) of the amygdala (eg, Sato et al. 202 )—a measure of the magnitude of spontaneous (versus task-based) fluctuations in the BOLD-signal. In addition, we re-emphasize that the current work does not cover the developments that took place over the years in preclinical/animal research on the role of the amygdala in emotion processing. Although such work was instrumental for providing much of the foundation on which the field of amygdala fMRI was eventually able to flourish 5 —a point we already highlighted in section “Introduction”—the preclinical field has since progressed—largely independently—in its own disparate directions. We do note, however, that the overall picture emerging from the preclinical/animal literature is, by and large, mostly compatible with a domain-general role of the amygdala in salience processing as described here (eg, see Maren & Holmes, 195 McEwen et al., 203 and Zhang et al. 204 ; see also Koen et al. 205 for a more translational perspective).

We started this review by reiterating the question Merboldt et al. 1 posed in the title of their commentary: “Functional MRI of the Human Amygdala?”. In answer to this question: If within the confines of emotion processing, than barring some justified exceptions, it is perhaps time we set our sights towards a new—or at least, a broader—horizon, 1 in which the intricacies of emotion processing are understood as the complex interplay between entire constellations of interacting brain regions, rather than any single brain region acting more or less in isolation. The amygdala simply does not respond selectively—or even very reliably—to emotional content; it responds to all things that are new, exciting, threatening or otherwise relevant to an individual at any given time of day, and does so as part of a much larger network devoted to that same purpose. In our opinion, these are important conclusions to draw from roughly 30 years of fMRI research on the amygdala’s role in emotion processing. We hope that further improvements in imaging equipment and methodology will help amygdala fMRI to finally fulfill its long-standing promise to the broader field of affective neuroscience. In the meantime, however, we are forced to reassess the possible therapeutic efficacy of rt-fMRI neurofeedback training regimens that target only the amygdala in the treatment of emotion regulation disorders. Based on the literature reviewed here, such a strategy is unlikely to bear much fruit at present.

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Dutch Ministry of Defence.

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Critical Thinking

Critical thinking is a widely accepted educational goal. Its definition is contested, but the competing definitions can be understood as differing conceptions of the same basic concept: careful thinking directed to a goal. Conceptions differ with respect to the scope of such thinking, the type of goal, the criteria and norms for thinking carefully, and the thinking components on which they focus. Its adoption as an educational goal has been recommended on the basis of respect for students’ autonomy and preparing students for success in life and for democratic citizenship. “Critical thinkers” have the dispositions and abilities that lead them to think critically when appropriate. The abilities can be identified directly; the dispositions indirectly, by considering what factors contribute to or impede exercise of the abilities. Standardized tests have been developed to assess the degree to which a person possesses such dispositions and abilities. Educational intervention has been shown experimentally to improve them, particularly when it includes dialogue, anchored instruction, and mentoring. Controversies have arisen over the generalizability of critical thinking across domains, over alleged bias in critical thinking theories and instruction, and over the relationship of critical thinking to other types of thinking.

2.1 Dewey’s Three Main Examples

2.2 dewey’s other examples, 2.3 further examples, 2.4 non-examples, 3. the definition of critical thinking, 4. its value, 5. the process of thinking critically, 6. components of the process, 7. contributory dispositions and abilities, 8.1 initiating dispositions, 8.2 internal dispositions, 9. critical thinking abilities, 10. required knowledge, 11. educational methods, 12.1 the generalizability of critical thinking, 12.2 bias in critical thinking theory and pedagogy, 12.3 relationship of critical thinking to other types of thinking, other internet resources, related entries.

Use of the term ‘critical thinking’ to describe an educational goal goes back to the American philosopher John Dewey (1910), who more commonly called it ‘reflective thinking’. He defined it as

active, persistent and careful consideration of any belief or supposed form of knowledge in the light of the grounds that support it, and the further conclusions to which it tends. (Dewey 1910: 6; 1933: 9)

and identified a habit of such consideration with a scientific attitude of mind. His lengthy quotations of Francis Bacon, John Locke, and John Stuart Mill indicate that he was not the first person to propose development of a scientific attitude of mind as an educational goal.

In the 1930s, many of the schools that participated in the Eight-Year Study of the Progressive Education Association (Aikin 1942) adopted critical thinking as an educational goal, for whose achievement the study’s Evaluation Staff developed tests (Smith, Tyler, & Evaluation Staff 1942). Glaser (1941) showed experimentally that it was possible to improve the critical thinking of high school students. Bloom’s influential taxonomy of cognitive educational objectives (Bloom et al. 1956) incorporated critical thinking abilities. Ennis (1962) proposed 12 aspects of critical thinking as a basis for research on the teaching and evaluation of critical thinking ability.

Since 1980, an annual international conference in California on critical thinking and educational reform has attracted tens of thousands of educators from all levels of education and from many parts of the world. Also since 1980, the state university system in California has required all undergraduate students to take a critical thinking course. Since 1983, the Association for Informal Logic and Critical Thinking has sponsored sessions in conjunction with the divisional meetings of the American Philosophical Association (APA). In 1987, the APA’s Committee on Pre-College Philosophy commissioned a consensus statement on critical thinking for purposes of educational assessment and instruction (Facione 1990a). Researchers have developed standardized tests of critical thinking abilities and dispositions; for details, see the Supplement on Assessment . Educational jurisdictions around the world now include critical thinking in guidelines for curriculum and assessment. Political and business leaders endorse its importance.

For details on this history, see the Supplement on History .

2. Examples and Non-Examples

Before considering the definition of critical thinking, it will be helpful to have in mind some examples of critical thinking, as well as some examples of kinds of thinking that would apparently not count as critical thinking.

Dewey (1910: 68–71; 1933: 91–94) takes as paradigms of reflective thinking three class papers of students in which they describe their thinking. The examples range from the everyday to the scientific.

Transit : “The other day, when I was down town on 16th Street, a clock caught my eye. I saw that the hands pointed to 12:20. This suggested that I had an engagement at 124th Street, at one o'clock. I reasoned that as it had taken me an hour to come down on a surface car, I should probably be twenty minutes late if I returned the same way. I might save twenty minutes by a subway express. But was there a station near? If not, I might lose more than twenty minutes in looking for one. Then I thought of the elevated, and I saw there was such a line within two blocks. But where was the station? If it were several blocks above or below the street I was on, I should lose time instead of gaining it. My mind went back to the subway express as quicker than the elevated; furthermore, I remembered that it went nearer than the elevated to the part of 124th Street I wished to reach, so that time would be saved at the end of the journey. I concluded in favor of the subway, and reached my destination by one o’clock.” (Dewey 1910: 68-69; 1933: 91-92)

Ferryboat : “Projecting nearly horizontally from the upper deck of the ferryboat on which I daily cross the river is a long white pole, having a gilded ball at its tip. It suggested a flagpole when I first saw it; its color, shape, and gilded ball agreed with this idea, and these reasons seemed to justify me in this belief. But soon difficulties presented themselves. The pole was nearly horizontal, an unusual position for a flagpole; in the next place, there was no pulley, ring, or cord by which to attach a flag; finally, there were elsewhere on the boat two vertical staffs from which flags were occasionally flown. It seemed probable that the pole was not there for flag-flying.

“I then tried to imagine all possible purposes of the pole, and to consider for which of these it was best suited: (a) Possibly it was an ornament. But as all the ferryboats and even the tugboats carried poles, this hypothesis was rejected. (b) Possibly it was the terminal of a wireless telegraph. But the same considerations made this improbable. Besides, the more natural place for such a terminal would be the highest part of the boat, on top of the pilot house. (c) Its purpose might be to point out the direction in which the boat is moving.

“In support of this conclusion, I discovered that the pole was lower than the pilot house, so that the steersman could easily see it. Moreover, the tip was enough higher than the base, so that, from the pilot's position, it must appear to project far out in front of the boat. Morevoer, the pilot being near the front of the boat, he would need some such guide as to its direction. Tugboats would also need poles for such a purpose. This hypothesis was so much more probable than the others that I accepted it. I formed the conclusion that the pole was set up for the purpose of showing the pilot the direction in which the boat pointed, to enable him to steer correctly.” (Dewey 1910: 69-70; 1933: 92-93)

Bubbles : “In washing tumblers in hot soapsuds and placing them mouth downward on a plate, bubbles appeared on the outside of the mouth of the tumblers and then went inside. Why? The presence of bubbles suggests air, which I note must come from inside the tumbler. I see that the soapy water on the plate prevents escape of the air save as it may be caught in bubbles. But why should air leave the tumbler? There was no substance entering to force it out. It must have expanded. It expands by increase of heat, or by decrease of pressure, or both. Could the air have become heated after the tumbler was taken from the hot suds? Clearly not the air that was already entangled in the water. If heated air was the cause, cold air must have entered in transferring the tumblers from the suds to the plate. I test to see if this supposition is true by taking several more tumblers out. Some I shake so as to make sure of entrapping cold air in them. Some I take out holding mouth downward in order to prevent cold air from entering. Bubbles appear on the outside of every one of the former and on none of the latter. I must be right in my inference. Air from the outside must have been expanded by the heat of the tumbler, which explains the appearance of the bubbles on the outside. But why do they then go inside? Cold contracts. The tumbler cooled and also the air inside it. Tension was removed, and hence bubbles appeared inside. To be sure of this, I test by placing a cup of ice on the tumbler while the bubbles are still forming outside. They soon reverse” (Dewey 1910: 70–71; 1933: 93–94).

Dewey (1910, 1933) sprinkles his book with other examples of critical thinking. We will refer to the following.

Weather : A man on a walk notices that it has suddenly become cool, thinks that it is probably going to rain, looks up and sees a dark cloud obscuring the sun, and quickens his steps (1910: 6–10; 1933: 9–13).

Disorder : A man finds his rooms on his return to them in disorder with his belongings thrown about, thinks at first of burglary as an explanation, then thinks of mischievous children as being an alternative explanation, then looks to see whether valuables are missing, and discovers that they are (1910: 82–83; 1933: 166–168).

Typhoid : A physician diagnosing a patient whose conspicuous symptoms suggest typhoid avoids drawing a conclusion until more data are gathered by questioning the patient and by making tests (1910: 85–86; 1933: 170).

Blur : A moving blur catches our eye in the distance, we ask ourselves whether it is a cloud of whirling dust or a tree moving its branches or a man signaling to us, we think of other traits that should be found on each of those possibilities, and we look and see if those traits are found (1910: 102, 108; 1933: 121, 133).

Suction pump : In thinking about the suction pump, the scientist first notes that it will draw water only to a maximum height of 33 feet at sea level and to a lesser maximum height at higher elevations, selects for attention the differing atmospheric pressure at these elevations, sets up experiments in which the air is removed from a vessel containing water (when suction no longer works) and in which the weight of air at various levels is calculated, compares the results of reasoning about the height to which a given weight of air will allow a suction pump to raise water with the observed maximum height at different elevations, and finally assimilates the suction pump to such apparently different phenomena as the siphon and the rising of a balloon (1910: 150–153; 1933: 195–198).

Diamond : A passenger in a car driving in a diamond lane reserved for vehicles with at least one passenger notices that the diamond marks on the pavement are far apart in some places and close together in others. Why? The driver suggests that the reason may be that the diamond marks are not needed where there is a solid double line separating the diamond line from the adjoining lane, but are needed when there is a dotted single line permitting crossing into the diamond lane. Further observation confirms that the diamonds are close together when a dotted line separates the diamond lane from its neighbour, but otherwise far apart.

Rash : A woman suddenly develops a very itchy red rash on her throat and upper chest. She recently noticed a mark on the back of her right hand, but was not sure whether the mark was a rash or a scrape. She lies down in bed and thinks about what might be causing the rash and what to do about it. About two weeks before, she began taking blood pressure medication that contained a sulfa drug, and the pharmacist had warned her, in view of a previous allergic reaction to a medication containing a sulfa drug, to be on the alert for an allergic reaction; however, she had been taking the medication for two weeks with no such effect. The day before, she began using a new cream on her neck and upper chest; against the new cream as the cause was mark on the back of her hand, which had not been exposed to the cream. She began taking probiotics about a month before. She also recently started new eye drops, but she supposed that manufacturers of eye drops would be careful not to include allergy-causing components in the medication. The rash might be a heat rash, since she recently was sweating profusely from her upper body. Since she is about to go away on a short vacation, where she would not have access to her usual physician, she decides to keep taking the probiotics and using the new eye drops but to discontinue the blood pressure medication and to switch back to the old cream for her neck and upper chest. She forms a plan to consult her regular physician on her return about the blood pressure medication.

Candidate : Although Dewey included no examples of thinking directed at appraising the arguments of others, such thinking has come to be considered a kind of critical thinking. We find an example of such thinking in the performance task on the Collegiate Learning Assessment (CLA+), which its sponsoring organization describes as

a performance-based assessment that provides a measure of an institution’s contribution to the development of critical-thinking and written communication skills of its students. (Council for Aid to Education 2017)

A sample task posted on its website requires the test-taker to write a report for public distribution evaluating a fictional candidate’s policy proposals and their supporting arguments, using supplied background documents, with a recommendation on whether to endorse the candidate.

Immediate acceptance of an idea that suggests itself as a solution to a problem (e.g., a possible explanation of an event or phenomenon, an action that seems likely to produce a desired result) is “uncritical thinking, the minimum of reflection” (Dewey 1910: 13). On-going suspension of judgment in the light of doubt about a possible solution is not critical thinking (Dewey 1910: 108). Critique driven by a dogmatically held political or religious ideology is not critical thinking; thus Paulo Freire (1968 [1970]) is using the term (e.g., at 1970: 71, 81, 100, 146) in a more politically freighted sense that includes not only reflection but also revolutionary action against oppression. Derivation of a conclusion from given data using an algorithm is not critical thinking.

What is critical thinking? There are many definitions. Ennis (2016) lists 14 philosophically oriented scholarly definitions and three dictionary definitions. Following Rawls (1971), who distinguished his conception of justice from a utilitarian conception but regarded them as rival conceptions of the same concept, Ennis maintains that the 17 definitions are different conceptions of the same concept. Rawls articulated the shared concept of justice as

a characteristic set of principles for assigning basic rights and duties and for determining… the proper distribution of the benefits and burdens of social cooperation. (Rawls 1971: 5)

Bailin et al. (1999b) claim that, if one considers what sorts of thinking an educator would take not to be critical thinking and what sorts to be critical thinking, one can conclude that educators typically understand critical thinking to have at least three features.

• It is done for the purpose of making up one’s mind about what to believe or do.
• The person engaging in the thinking is trying to fulfill standards of adequacy and accuracy appropriate to the thinking.
• The thinking fulfills the relevant standards to some threshold level.

One could sum up the core concept that involves these three features by saying that critical thinking is careful goal-directed thinking. This core concept seems to apply to all the examples of critical thinking described in the previous section. As for the non-examples, their exclusion depends on construing careful thinking as excluding jumping immediately to conclusions, suspending judgment no matter how strong the evidence, reasoning from an unquestioned ideological or religious perspective, and routinely using an algorithm to answer a question.

If the core of critical thinking is careful goal-directed thinking, conceptions of it can vary according to its presumed scope, its presumed goal, one’s criteria and threshold for being careful, and the thinking component on which one focuses As to its scope, some conceptions (e.g., Dewey 1910, 1933) restrict it to constructive thinking on the basis of one’s own observations and experiments, others (e.g., Ennis 1962; Fisher & Scriven 1997; Johnson 1992) to appraisal of the products of such thinking. Ennis (1991) and Bailin et al. (1999b) take it to cover both construction and appraisal. As to its goal, some conceptions restrict it to forming a judgment (Dewey 1910, 1933; Lipman 1987; Facione 1990a). Others allow for actions as well as beliefs as the end point of a process of critical thinking (Ennis 1991; Bailin et al. 1999b). As to the criteria and threshold for being careful, definitions vary in the term used to indicate that critical thinking satisfies certain norms: “intellectually disciplined” (Scriven & Paul 1987), “reasonable” (Ennis 1991), “skillful” (Lipman 1987), “skilled” (Fisher & Scriven 1997), “careful” (Bailin & Battersby 2009). Some definitions specify these norms, referring variously to “consideration of any belief or supposed form of knowledge in the light of the grounds that support it and the further conclusions to which it tends” (Dewey 1910, 1933); “the methods of logical inquiry and reasoning” (Glaser 1941); “conceptualizing, applying, analyzing, synthesizing, and/or evaluating information gathered from, or generated by, observation, experience, reflection, reasoning, or communication” (Scriven & Paul 1987); the requirement that “it is sensitive to context, relies on criteria, and is self-correcting” (Lipman 1987); “evidential, conceptual, methodological, criteriological, or contextual considerations” (Facione 1990a); and “plus-minus considerations of the product in terms of appropriate standards (or criteria)” (Johnson 1992). Stanovich and Stanovich (2010) propose to ground the concept of critical thinking in the concept of rationality, which they understand as combining epistemic rationality (fitting one’s beliefs to the world) and instrumental rationality (optimizing goal fulfillment); a critical thinker, in their view, is someone with “a propensity to override suboptimal responses from the autonomous mind” (2010: 227). These variant specifications of norms for critical thinking are not necessarily incompatible with one another, and in any case presuppose the core notion of thinking carefully. As to the thinking component singled out, some definitions focus on suspension of judgment during the thinking (Dewey 1910; McPeck 1981), others on inquiry while judgment is suspended (Bailin & Battersby 2009), others on the resulting judgment (Facione 1990a), and still others on the subsequent emotive response (Siegel 1988).

In educational contexts, a definition of critical thinking is a “programmatic definition” (Scheffler 1960: 19). It expresses a practical program for achieving an educational goal. For this purpose, a one-sentence formulaic definition is much less useful than articulation of a critical thinking process, with criteria and standards for the kinds of thinking that the process may involve. The real educational goal is recognition, adoption and implementation by students of those criteria and standards. That adoption and implementation in turn consists in acquiring the knowledge, abilities and dispositions of a critical thinker.

Conceptions of critical thinking generally do not include moral integrity as part of the concept. Dewey, for example, took critical thinking to be the ultimate intellectual goal of education, but distinguished it from the development of social cooperation among school children, which he took to be the central moral goal. Ennis (1996, 2011) added to his previous list of critical thinking dispositions a group of dispositions to care about the dignity and worth of every person, which he described as a “correlative” (1996) disposition without which critical thinking would be less valuable and perhaps harmful. An educational program that aimed at developing critical thinking but not the correlative disposition to care about the dignity and worth of every person, he asserted, “would be deficient and perhaps dangerous” (Ennis 1996: 172).

Dewey thought that education for reflective thinking would be of value to both the individual and society; recognition in educational practice of the kinship to the scientific attitude of children’s native curiosity, fertile imagination and love of experimental inquiry “would make for individual happiness and the reduction of social waste” (Dewey 1910: iii). Schools participating in the Eight-Year Study took development of the habit of reflective thinking and skill in solving problems as a means to leading young people to understand, appreciate and live the democratic way of life characteristic of the United States (Aikin 1942: 17–18, 81). Harvey Siegel (1988: 55–61) has offered four considerations in support of adopting critical thinking as an educational ideal. (1) Respect for persons requires that schools and teachers honour students’ demands for reasons and explanations, deal with students honestly, and recognize the need to confront students’ independent judgment; these requirements concern the manner in which teachers treat students. (2) Education has the task of preparing children to be successful adults, a task that requires development of their self-sufficiency. (3) Education should initiate children into the rational traditions in such fields as history, science and mathematics. (4) Education should prepare children to become democratic citizens, which requires reasoned procedures and critical talents and attitudes. To supplement these considerations, Siegel (1988: 62–90) responds to two objections: the ideology objection that adoption of any educational ideal requires a prior ideological commitment and the indoctrination objection that cultivation of critical thinking cannot escape being a form of indoctrination.

Despite the diversity of our 11 examples, one can recognize a common pattern. Dewey analyzed it as consisting of five phases:

• suggestions , in which the mind leaps forward to a possible solution;
• an intellectualization of the difficulty or perplexity into a problem to be solved, a question for which the answer must be sought;
• the use of one suggestion after another as a leading idea, or hypothesis , to initiate and guide observation and other operations in collection of factual material;
• the mental elaboration of the idea or supposition as an idea or supposition ( reasoning , in the sense on which reasoning is a part, not the whole, of inference); and
• testing the hypothesis by overt or imaginative action. (Dewey 1933: 106–107; italics in original)

The process of reflective thinking consisting of these phases would be preceded by a perplexed, troubled or confused situation and followed by a cleared-up, unified, resolved situation (Dewey 1933: 106). The term ‘phases’ replaced the term ‘steps’ (Dewey 1910: 72), thus removing the earlier suggestion of an invariant sequence. Variants of the above analysis appeared in (Dewey 1916: 177) and (Dewey 1938: 101–119).

The variant formulations indicate the difficulty of giving a single logical analysis of such a varied process. The process of critical thinking may have a spiral pattern, with the problem being redefined in the light of obstacles to solving it as originally formulated. For example, the person in Transit might have concluded that getting to the appointment at the scheduled time was impossible and have reformulated the problem as that of rescheduling the appointment for a mutually convenient time. Further, defining a problem does not always follow after or lead immediately to an idea of a suggested solution. Nor should it do so, as Dewey himself recognized in describing the physician in Typhoid as avoiding any strong preference for this or that conclusion before getting further information (Dewey 1910: 85; 1933: 170). People with a hypothesis in mind, even one to which they have a very weak commitment, have a so-called “confirmation bias” (Nickerson 1998): they are likely to pay attention to evidence that confirms the hypothesis and to ignore evidence that counts against it or for some competing hypothesis. Detectives, intelligence agencies, and investigators of airplane accidents are well advised to gather relevant evidence systematically and to postpone even tentative adoption of an explanatory hypothesis until the collected evidence rules out with the appropriate degree of certainty all but one explanation. Dewey’s analysis of the critical thinking process can be faulted as well for requiring acceptance or rejection of a possible solution to a defined problem, with no allowance for deciding in the light of the available evidence to suspend judgment. Further, given the great variety of kinds of problems for which reflection is appropriate, there is likely to be variation in its component events. Perhaps the best way to conceptualize the critical thinking process is as a checklist whose component events can occur in a variety of orders, selectively, and more than once. These component events might include (1) noticing a difficulty, (2) defining the problem, (3) dividing the problem into manageable sub-problems, (4) formulating a variety of possible solutions to the problem or sub-problem, (5) determining what evidence is relevant to deciding among possible solutions to the problem or sub-problem, (6) devising a plan of systematic observation or experiment that will uncover the relevant evidence, (7) carrying out the plan of systematic observation or experimentation, (8) noting the results of the systematic observation or experiment, (9) gathering relevant testimony and information from others, (10) judging the credibility of testimony and information gathered from others, (11) drawing conclusions from gathered evidence and accepted testimony, and (12) accepting a solution that the evidence adequately supports (cf. Hitchcock 2017: 485).

Checklist conceptions of the process of critical thinking are open to the objection that they are too mechanical and procedural to fit the multi-dimensional and emotionally charged issues for which critical thinking is urgently needed (Paul 1984). For such issues, a more dialectical process is advocated, in which competing relevant world views are identified, their implications explored, and some sort of creative synthesis attempted.

If one considers the critical thinking process illustrated by the 11 examples, one can identify distinct kinds of mental acts and mental states that form part of it. To distinguish, label and briefly characterize these components is a useful preliminary to identifying abilities, skills, dispositions, attitudes, habits and the like that contribute causally to thinking critically. Identifying such abilities and habits is in turn a useful preliminary to setting educational goals. Setting the goals is in its turn a useful preliminary to designing strategies for helping learners to achieve the goals and to designing ways of measuring the extent to which learners have done so. Such measures provide both feedback to learners on their achievement and a basis for experimental research on the effectiveness of various strategies for educating people to think critically. Let us begin, then, by distinguishing the kinds of mental acts and mental events that can occur in a critical thinking process.

• Observing : One notices something in one’s immediate environment (sudden cooling of temperature in Weather , bubbles forming outside a glass and then going inside in Bubbles , a moving blur in the distance in Blur , a rash in Rash ). Or one notes the results of an experiment or systematic observation (valuables missing in Disorder , no suction without air pressure in Suction pump )
• Feeling : One feels puzzled or uncertain about something (how to get to an appointment on time in Transit , why the diamonds vary in frequency in Diamond ). One wants to resolve this perplexity. One feels satisfaction once one has worked out an answer (to take the subway express in Transit , diamonds closer when needed as a warning in Diamond ).
• Wondering : One formulates a question to be addressed (why bubbles form outside a tumbler taken from hot water in Bubbles , how suction pumps work in Suction pump , what caused the rash in Rash ).
• Imagining : One thinks of possible answers (bus or subway or elevated in Transit , flagpole or ornament or wireless communication aid or direction indicator in Ferryboat , allergic reaction or heat rash in Rash ).
• Inferring : One works out what would be the case if a possible answer were assumed (valuables missing if there has been a burglary in Disorder , earlier start to the rash if it is an allergic reaction to a sulfa drug in Rash ). Or one draws a conclusion once sufficient relevant evidence is gathered (take the subway in Transit , burglary in Disorder , discontinue blood pressure medication and new cream in Rash ).
• Knowledge : One uses stored knowledge of the subject-matter to generate possible answers or to infer what would be expected on the assumption of a particular answer (knowledge of a city’s public transit system in Transit , of the requirements for a flagpole in Ferryboat , of Boyle’s law in Bubbles , of allergic reactions in Rash ).
• Experimenting : One designs and carries out an experiment or a systematic observation to find out whether the results deduced from a possible answer will occur (looking at the location of the flagpole in relation to the pilot’s position in Ferryboat , putting an ice cube on top of a tumbler taken from hot water in Bubbles , measuring the height to which a suction pump will draw water at different elevations in Suction pump , noticing the frequency of diamonds when movement to or from a diamond lane is allowed in Diamond ).
• Consulting : One finds a source of information, gets the information from the source, and makes a judgment on whether to accept it. None of our 11 examples include searching for sources of information. In this respect they are unrepresentative, since most people nowadays have almost instant access to information relevant to answering any question, including many of those illustrated by the examples. However, Candidate includes the activities of extracting information from sources and evaluating its credibility.
• Identifying and analyzing arguments : One notices an argument and works out its structure and content as a preliminary to evaluating its strength. This activity is central to Candidate . It is an important part of a critical thinking process in which one surveys arguments for various positions on an issue.
• Judging : One makes a judgment on the basis of accumulated evidence and reasoning, such as the judgment in Ferryboat that the purpose of the pole is to provide direction to the pilot.
• Deciding : One makes a decision on what to do or on what policy to adopt, as in the decision in Transit to take the subway.

By definition, a person who does something voluntarily is both willing and able to do that thing at that time. Both the willingness and the ability contribute causally to the person’s action, in the sense that the voluntary action would not occur if either (or both) of these were lacking. For example, suppose that one is standing with one’s arms at one’s sides and one voluntarily lifts one’s right arm to an extended horizontal position. One would not do so if one were unable to lift one’s arm, if for example one’s right side was paralyzed as the result of a stroke. Nor would one do so if one were unwilling to lift one’s arm, if for example one were participating in a street demonstration at which a white supremacist was urging the crowd to lift their right arm in a Nazi salute and one were unwilling to express support in this way for the racist Nazi ideology. The same analysis applies to a voluntary mental process of thinking critically. It requires both willingness and ability to think critically, including willingness and ability to perform each of the mental acts that compose the process and to coordinate those acts in a sequence that is directed at resolving the initiating perplexity.

Consider willingness first. We can identify causal contributors to willingness to think critically by considering factors that would cause a person who was able to think critically about an issue nevertheless not to do so (Hamby 2014). For each factor, the opposite condition thus contributes causally to willingness to think critically on a particular occasion. For example, people who habitually jump to conclusions without considering alternatives will not think critically about issues that arise, even if they have the required abilities. The contrary condition of willingness to suspend judgment is thus a causal contributor to thinking critically.

Now consider ability. In contrast to the ability to move one’s arm, which can be completely absent because a stroke has left the arm paralyzed, the ability to think critically is a developed ability, whose absence is not a complete absence of ability to think but absence of ability to think well. We can identify the ability to think well directly, in terms of the norms and standards for good thinking. In general, to be able do well the thinking activities that can be components of a critical thinking process, one needs to know the concepts and principles that characterize their good performance, to recognize in particular cases that the concepts and principles apply, and to apply them. The knowledge, recognition and application may be procedural rather than declarative. It may be domain-specific rather than widely applicable, and in either case may need subject-matter knowledge, sometimes of a deep kind.

Reflections of the sort illustrated by the previous two paragraphs have led scholars to identify the knowledge, abilities and dispositions of a “critical thinker”, i.e., someone who thinks critically whenever it is appropriate to do so. We turn now to these three types of causal contributors to thinking critically. We start with dispositions, since arguably these are the most powerful contributors to being a critical thinker, can be fostered at an early stage of a child’s development, and are susceptible to general improvement (Glaser 1941: 175)

8. Critical Thinking Dispositions

Educational researchers use the term ‘dispositions’ broadly for the habits of mind and attitudes that contribute causally to being a critical thinker. Some writers (e.g., Paul & Elder 2006; Hamby 2014; Bailin & Battersby 2016) propose to use the term ‘virtues’ for this dimension of a critical thinker. The virtues in question, although they are virtues of character, concern the person’s ways of thinking rather than the person’s ways of behaving towards others. They are not moral virtues but intellectual virtues, of the sort articulated by Zagzebski (1996) and discussed by Turri, Alfano, and Greco (2017).

On a realistic conception, thinking dispositions or intellectual virtues are real properties of thinkers. They are general tendencies, propensities, or inclinations to think in particular ways in particular circumstances, and can be genuinely explanatory (Siegel 1999). Sceptics argue that there is no evidence for a specific mental basis for the habits of mind that contribute to thinking critically, and that it is pedagogically misleading to posit such a basis (Bailin et al. 1999a). Whatever their status, critical thinking dispositions need motivation for their initial formation in a child—motivation that may be external or internal. As children develop, the force of habit will gradually become important in sustaining the disposition (Nieto & Valenzuela 2012). Mere force of habit, however, is unlikely to sustain critical thinking dispositions. Critical thinkers must value and enjoy using their knowledge and abilities to think things through for themselves. They must be committed to, and lovers of, inquiry.

A person may have a critical thinking disposition with respect to only some kinds of issues. For example, one could be open-minded about scientific issues but not about religious issues. Similarly, one could be confident in one’s ability to reason about the theological implications of the existence of evil in the world but not in one’s ability to reason about the best design for a guided ballistic missile.

Critical thinking dispositions can usefully be divided into initiating dispositions (those that contribute causally to starting to think critically about an issue) and internal dispositions (those that contribute causally to doing a good job of thinking critically once one has started) (Facione 1990a: 25). The two categories are not mutually exclusive. For example, open-mindedness, in the sense of willingness to consider alternative points of view to one’s own, is both an initiating and an internal disposition.

Using the strategy of considering factors that would block people with the ability to think critically from doing so, we can identify as initiating dispositions for thinking critically attentiveness, a habit of inquiry, self-confidence, courage, open-mindedness, willingness to suspend judgment, trust in reason, wanting evidence for one’s beliefs, and seeking the truth. We consider briefly what each of these dispositions amounts to, in each case citing sources that acknowledge them.

• Attentiveness : One will not think critically if one fails to recognize an issue that needs to be thought through. For example, the pedestrian in Weather would not have looked up if he had not noticed that the air was suddenly cooler. To be a critical thinker, then, one needs to be habitually attentive to one’s surroundings, noticing not only what one senses but also sources of perplexity in messages received and in one’s own beliefs and attitudes (Facione 1990a: 25; Facione, Facione, & Giancarlo 2001).
• Habit of inquiry : Inquiry is effortful, and one needs an internal push to engage in it. For example, the student in Bubbles could easily have stopped at idle wondering about the cause of the bubbles rather than reasoning to a hypothesis, then designing and executing an experiment to test it. Thus willingness to think critically needs mental energy and initiative. What can supply that energy? Love of inquiry, or perhaps just a habit of inquiry. Hamby (2015) has argued that willingness to inquire is the central critical thinking virtue, one that encompasses all the others. It is recognized as a critical thinking disposition by Dewey (1910: 29; 1933: 35), Glaser (1941: 5), Ennis (1987: 12; 1991: 8), Facione (1990a: 25), Bailin et al. (1999b: 294), Halpern (1998: 452), and Facione, Facione, & Giancarlo (2001).
• Self-confidence : Lack of confidence in one’s abilities can block critical thinking. For example, if the woman in Rash lacked confidence in her ability to figure things out for herself, she might just have assumed that the rash on her chest was the allergic reaction to her medication against which the pharmacist had warned her. Thus willingness to think critically requires confidence in one’s ability to inquire (Facione 1990a: 25; Facione, Facione, & Giancarlo 2001).
• Courage : Fear of thinking for oneself can stop one from doing it. Thus willingness to think critically requires intellectual courage (Paul & Elder 2006: 16).
• Open-mindedness : A dogmatic attitude will impede thinking critically. For example, a person who adheres rigidly to a “pro-choice” position on the issue of the legal status of induced abortion is likely to be unwilling to consider seriously the issue of when in its development an unborn child acquires a moral right to life. Thus willingness to think critically requires open-mindedness, in the sense of a willingness to examine questions to which one already accepts an answer but which further evidence or reasoning might cause one to answer differently (Dewey 1933; Facione 1990a; Ennis 1991; Bailin et al. 1999b; Halpern 1998, Facione, Facione, & Giancarlo 2001). Paul (1981) emphasizes open-mindedness about alternative world-views, and recommends a dialectical approach to integrating such views as central to what he calls “strong sense” critical thinking.
• Willingness to suspend judgment : Premature closure on an initial solution will block critical thinking. Thus willingness to think critically requires a willingness to suspend judgment while alternatives are explored (Facione 1990a; Ennis 1991; Halpern 1998).
• Trust in reason : Since distrust in the processes of reasoned inquiry will dissuade one from engaging in it, trust in them is an initiating critical thinking disposition (Facione 1990a, 25; Bailin et al. 1999b: 294; Facione, Facione, & Giancarlo 2001; Paul & Elder 2006). In reaction to an allegedly exclusive emphasis on reason in critical thinking theory and pedagogy, Thayer-Bacon (2000) argues that intuition, imagination, and emotion have important roles to play in an adequate conception of critical thinking that she calls “constructive thinking”. From her point of view, critical thinking requires trust not only in reason but also in intuition, imagination, and emotion.
• Seeking the truth : If one does not care about the truth but is content to stick with one’s initial bias on an issue, then one will not think critically about it. Seeking the truth is thus an initiating critical thinking disposition (Bailin et al. 1999b: 294; Facione, Facione, & Giancarlo 2001). A disposition to seek the truth is implicit in more specific critical thinking dispositions, such as trying to be well-informed, considering seriously points of view other than one’s own, looking for alternatives, suspending judgment when the evidence is insufficient, and adopting a position when the evidence supporting it is sufficient.

Some of the initiating dispositions, such as open-mindedness and willingness to suspend judgment, are also internal critical thinking dispositions, in the sense of mental habits or attitudes that contribute causally to doing a good job of critical thinking once one starts the process. But there are many other internal critical thinking dispositions. Some of them are parasitic on one’s conception of good thinking. For example, it is constitutive of good thinking about an issue to formulate the issue clearly and to maintain focus on it. For this purpose, one needs not only the corresponding ability but also the corresponding disposition. Ennis (1991: 8) describes it as the disposition “to determine and maintain focus on the conclusion or question”, Facione (1990a: 25) as “clarity in stating the question or concern”. Other internal dispositions are motivators to continue or adjust the critical thinking process, such as willingness to persist in a complex task and willingness to abandon nonproductive strategies in an attempt to self-correct (Halpern 1998: 452). For a list of identified internal critical thinking dispositions, see the Supplement on Internal Critical Thinking Dispositions .

Some theorists postulate skills, i.e., acquired abilities, as operative in critical thinking. It is not obvious, however, that a good mental act is the exercise of a generic acquired skill. Inferring an expected time of arrival, as in Transit , has some generic components but also uses non-generic subject-matter knowledge. Bailin et al. (1999a) argue against viewing critical thinking skills as generic and discrete, on the ground that skilled performance at a critical thinking task cannot be separated from knowledge of concepts and from domain-specific principles of good thinking. Talk of skills, they concede, is unproblematic if it means merely that a person with critical thinking skills is capable of intelligent performance.

Despite such scepticism, theorists of critical thinking have listed as general contributors to critical thinking what they variously call abilities (Glaser 1941; Ennis 1962, 1991), skills (Facione 1990a; Halpern 1998) or competencies (Fisher & Scriven 1997). Amalgamating these lists would produce a confusing and chaotic cornucopia of more than 50 possible educational objectives, with only partial overlap among them. It makes sense instead to try to understand the reasons for the multiplicity and diversity, and to make a selection according to one’s own reasons for singling out abilities to be developed in a critical thinking curriculum. Two reasons for diversity among lists of critical thinking abilities are the underlying conception of critical thinking and the envisaged educational level. Appraisal-only conceptions, for example, involve a different suite of abilities than constructive-only conceptions. Some lists, such as those in (Glaser 1941), are put forward as educational objectives for secondary school students, whereas others are proposed as objectives for college students (e.g., Facione 1990a).

The abilities described in the remaining paragraphs of this section emerge from reflection on the general abilities needed to do well the thinking activities identified in section 6 as components of the critical thinking process described in section 5 . The derivation of each collection of abilities is accompanied by citation of sources that list such abilities and of standardized tests that claim to test them.

Observational abilities : Careful and accurate observation sometimes requires specialist expertise and practice, as in the case of observing birds and observing accident scenes. However, there are general abilities of noticing what one’s senses are picking up from one’s environment and of being able to articulate clearly and accurately to oneself and others what one has observed. It helps in exercising them to be able to recognize and take into account factors that make one’s observation less trustworthy, such as prior framing of the situation, inadequate time, deficient senses, poor observation conditions, and the like. It helps as well to be skilled at taking steps to make one’s observation more trustworthy, such as moving closer to get a better look, measuring something three times and taking the average, and checking what one thinks one is observing with someone else who is in a good position to observe it. It also helps to be skilled at recognizing respects in which one’s report of one’s observation involves inference rather than direct observation, so that one can then consider whether the inference is justified. These abilities come into play as well when one thinks about whether and with what degree of confidence to accept an observation report, for example in the study of history or in a criminal investigation or in assessing news reports. Observational abilities show up in some lists of critical thinking abilities (Ennis 1962: 90; Facione 1990a: 16; Ennis 1991: 9). There are items testing a person’s ability to judge the credibility of observation reports in the Cornell Critical Thinking Tests, Levels X and Z (Ennis & Millman 1971; Ennis, Millman, & Tomko 1985, 2005). Norris and King (1983, 1985, 1990a, 1990b) is a test of ability to appraise observation reports.

Emotional abilities : The emotions that drive a critical thinking process are perplexity or puzzlement, a wish to resolve it, and satisfaction at achieving the desired resolution. Children experience these emotions at an early age, without being trained to do so. Education that takes critical thinking as a goal needs only to channel these emotions and to make sure not to stifle them. Collaborative critical thinking benefits from ability to recognize one’s own and others’ emotional commitments and reactions.

Questioning abilities : A critical thinking process needs transformation of an inchoate sense of perplexity into a clear question. Formulating a question well requires not building in questionable assumptions, not prejudging the issue, and using language that in context is unambiguous and precise enough (Ennis 1962: 97; 1991: 9).

Imaginative abilities : Thinking directed at finding the correct causal explanation of a general phenomenon or particular event requires an ability to imagine possible explanations. Thinking about what policy or plan of action to adopt requires generation of options and consideration of possible consequences of each option. Domain knowledge is required for such creative activity, but a general ability to imagine alternatives is helpful and can be nurtured so as to become easier, quicker, more extensive, and deeper (Dewey 1910: 34–39; 1933: 40–47). Facione (1990a) and Halpern (1998) include the ability to imagine alternatives as a critical thinking ability.

Inferential abilities : The ability to draw conclusions from given information, and to recognize with what degree of certainty one’s own or others’ conclusions follow, is universally recognized as a general critical thinking ability. All 11 examples in section 2 of this article include inferences, some from hypotheses or options (as in Transit , Ferryboat and Disorder ), others from something observed (as in Weather and Rash ). None of these inferences is formally valid. Rather, they are licensed by general, sometimes qualified substantive rules of inference (Toulmin 1958) that rest on domain knowledge—that a bus trip takes about the same time in each direction, that the terminal of a wireless telegraph would be located on the highest possible place, that sudden cooling is often followed by rain, that an allergic reaction to a sulfa drug generally shows up soon after one starts taking it. It is a matter of controversy to what extent the specialized ability to deduce conclusions from premisses using formal rules of inference is needed for critical thinking. Dewey (1933) locates logical forms in setting out the products of reflection rather than in the process of reflection. Ennis (1981a), on the other hand, maintains that a liberally-educated person should have the following abilities: to translate natural-language statements into statements using the standard logical operators, to use appropriately the language of necessary and sufficient conditions, to deal with argument forms and arguments containing symbols, to determine whether in virtue of an argument’s form its conclusion follows necessarily from its premisses, to reason with logically complex propositions, and to apply the rules and procedures of deductive logic. Inferential abilities are recognized as critical thinking abilities by Glaser (1941: 6), Facione (1990a: 9), Ennis (1991: 9), Fisher & Scriven (1997: 99, 111), and Halpern (1998: 452). Items testing inferential abilities constitute two of the five subtests of the Watson Glaser Critical Thinking Appraisal (Watson & Glaser 1980a, 1980b, 1994), two of the four sections in the Cornell Critical Thinking Test Level X (Ennis & Millman 1971; Ennis, Millman, & Tomko 1985, 2005), three of the seven sections in the Cornell Critical Thinking Test Level Z (Ennis & Millman 1971; Ennis, Millman, & Tomko 1985, 2005), 11 of the 34 items on Forms A and B of the California Critical Thinking Skills Test (Facione 1990b, 1992), and a high but variable proportion of the 25 selected-response questions in the Collegiate Learning Assessment (Council for Aid to Education 2017).

Experimenting abilities : Knowing how to design and execute an experiment is important not just in scientific research but also in everyday life, as in Rash . Dewey devoted a whole chapter of his How We Think (1910: 145–156; 1933: 190–202) to the superiority of experimentation over observation in advancing knowledge. Experimenting abilities come into play at one remove in appraising reports of scientific studies. Skill in designing and executing experiments includes the acknowledged abilities to appraise evidence (Glaser 1941: 6), to carry out experiments and to apply appropriate statistical inference techniques (Facione 1990a: 9), to judge inductions to an explanatory hypothesis (Ennis 1991: 9), and to recognize the need for an adequately large sample size (Halpern 1998). The Cornell Critical Thinking Test Level Z (Ennis & Millman 1971; Ennis, Millman, & Tomko 1985, 2005) includes four items (out of 52) on experimental design. The Collegiate Learning Assessment (Council for Aid to Education 2017) makes room for appraisal of study design in both its performance task and its selected-response questions.

Consulting abilities : Skill at consulting sources of information comes into play when one seeks information to help resolve a problem, as in Candidate . Ability to find and appraise information includes ability to gather and marshal pertinent information (Glaser 1941: 6), to judge whether a statement made by an alleged authority is acceptable (Ennis 1962: 84), to plan a search for desired information (Facione 1990a: 9), and to judge the credibility of a source (Ennis 1991: 9). Ability to judge the credibility of statements is tested by 24 items (out of 76) in the Cornell Critical Thinking Test Level X (Ennis & Millman 1971; Ennis, Millman, & Tomko 1985, 2005) and by four items (out of 52) in the Cornell Critical Thinking Test Level Z (Ennis & Millman 1971; Ennis, Millman, & Tomko 1985, 2005). The College Learning Assessment’s performance task requires evaluation of whether information in documents is credible or unreliable (Council for Aid to Education 2017).

Argument analysis abilities : The ability to identify and analyze arguments contributes to the process of surveying arguments on an issue in order to form one’s own reasoned judgment, as in Candidate . The ability to detect and analyze arguments is recognized as a critical thinking skill by Facione (1990a: 7–8), Ennis (1991: 9) and Halpern (1998). Five items (out of 34) on the California Critical Thinking Skills Test (Facione 1990b, 1992) test skill at argument analysis. The College Learning Assessment (Council for Aid to Education 2017) incorporates argument analysis in its selected-response tests of critical reading and evaluation and of critiquing an argument.

Judging skills and deciding skills : Skill at judging and deciding is skill at recognizing what judgment or decision the available evidence and argument supports, and with what degree of confidence. It is thus a component of the inferential skills already discussed.

Lists and tests of critical thinking abilities often include two more abilities: identifying assumptions and constructing and evaluating definitions.

In addition to dispositions and abilities, critical thinking needs knowledge: of critical thinking concepts, of critical thinking principles, and of the subject-matter of the thinking.

We can derive a short list of concepts whose understanding contributes to critical thinking from the critical thinking abilities described in the preceding section. Observational abilities require an understanding of the difference between observation and inference. Questioning abilities require an understanding of the concepts of ambiguity and vagueness. Inferential abilities require an understanding of the difference between conclusive and defeasible inference (traditionally, between deduction and induction), as well as of the difference between necessary and sufficient conditions. Experimenting abilities require an understanding of the concepts of hypothesis, null hypothesis, assumption and prediction, as well as of the concept of statistical significance and of its difference from importance. They also require an understanding of the difference between an experiment and an observational study, and in particular of the difference between a randomized controlled trial, a prospective correlational study and a retrospective (case-control) study. Argument analysis abilities require an understanding of the concepts of argument, premiss, assumption, conclusion and counter-consideration. Additional critical thinking concepts are proposed by Bailin et al. (1999b: 293), Fisher & Scriven (1997: 105–106), and Black (2012).

According to Glaser (1941: 25), ability to think critically requires knowledge of the methods of logical inquiry and reasoning. If we review the list of abilities in the preceding section, however, we can see that some of them can be acquired and exercised merely through practice, possibly guided in an educational setting, followed by feedback. Searching intelligently for a causal explanation of some phenomenon or event requires that one consider a full range of possible causal contributors, but it seems more important that one implements this principle in one’s practice than that one is able to articulate it. What is important is “operational knowledge” of the standards and principles of good thinking (Bailin et al. 1999b: 291–293). But the development of such critical thinking abilities as designing an experiment or constructing an operational definition can benefit from learning their underlying theory. Further, explicit knowledge of quirks of human thinking seems useful as a cautionary guide. Human memory is not just fallible about details, as people learn from their own experiences of misremembering, but is so malleable that a detailed, clear and vivid recollection of an event can be a total fabrication (Loftus 2017). People seek or interpret evidence in ways that are partial to their existing beliefs and expectations, often unconscious of their “confirmation bias” (Nickerson 1998). Not only are people subject to this and other cognitive biases (Kahneman 2011), of which they are typically unaware, but it may be counter-productive for one to make oneself aware of them and try consciously to counteract them or to counteract social biases such as racial or sexual stereotypes (Kenyon & Beaulac 2014). It is helpful to be aware of these facts and of the superior effectiveness of blocking the operation of biases—for example, by making an immediate record of one’s observations, refraining from forming a preliminary explanatory hypothesis, blind refereeing, double-blind randomized trials, and blind grading of students’ work.

Critical thinking about an issue requires substantive knowledge of the domain to which the issue belongs. Critical thinking abilities are not a magic elixir that can be applied to any issue whatever by somebody who has no knowledge of the facts relevant to exploring that issue. For example, the student in Bubbles needed to know that gases do not penetrate solid objects like a glass, that air expands when heated, that the volume of an enclosed gas varies directly with its temperature and inversely with its pressure, and that hot objects will spontaneously cool down to the ambient temperature of their surroundings unless kept hot by insulation or a source of heat. Critical thinkers thus need a rich fund of subject-matter knowledge relevant to the variety of situations they encounter. This fact is recognized in the inclusion among critical thinking dispositions of a concern to become and remain generally well informed.

Experimental educational interventions, with control groups, have shown that education can improve critical thinking skills and dispositions, as measured by standardized tests. For information about these tests, see the Supplement on Assessment .

What educational methods are most effective at developing the dispositions, abilities and knowledge of a critical thinker? Abrami et al. (2015) found that in the experimental and quasi-experimental studies that they analyzed dialogue, anchored instruction, and mentoring each increased the effectiveness of the educational intervention, and that they were most effective when combined. They also found that in these studies a combination of separate instruction in critical thinking with subject-matter instruction in which students are encouraged to think critically was more effective than either by itself. However, the difference was not statistically significant; that is, it might have arisen by chance.

Most of these studies lack the longitudinal follow-up required to determine whether the observed differential improvements in critical thinking abilities or dispositions continue over time, for example until high school or college graduation. For details on studies of methods of developing critical thinking skills and dispositions, see the Supplement on Educational Methods .

12. Controversies

Scholars have denied the generalizability of critical thinking abilities across subject domains, have alleged bias in critical thinking theory and pedagogy, and have investigated the relationship of critical thinking to other kinds of thinking.

McPeck (1981) attacked the thinking skills movement of the 1970s, including the critical thinking movement. He argued that there are no general thinking skills, since thinking is always thinking about some subject-matter. It is futile, he claimed, for schools and colleges to teach thinking as if it were a separate subject. Rather, teachers should lead their pupils to become autonomous thinkers by teaching school subjects in a way that brings out their cognitive structure and that encourages and rewards discussion and argument. As some of his critics (e.g., Paul 1985; Siegel 1985) pointed out, McPeck’s central argument needs elaboration, since it has obvious counter-examples in writing and speaking, for which (up to a certain level of complexity) there are teachable general abilities even though they are always about some subject-matter. To make his argument convincing, McPeck needs to explain how thinking differs from writing and speaking in a way that does not permit useful abstraction of its components from the subject-matters with which it deals. He has not done so. Nevertheless, his position that the dispositions and abilities of a critical thinker are best developed in the context of subject-matter instruction is shared by many theorists of critical thinking, including Dewey (1910, 1933), Glaser (1941), Passmore (1980), Weinstein (1990), and Bailin et al. (1999b).

McPeck’s challenge prompted reflection on the extent to which critical thinking is subject-specific. McPeck argued for a strong subject-specificity thesis, according to which it is a conceptual truth that all critical thinking abilities are specific to a subject. (He did not however extend his subject-specificity thesis to critical thinking dispositions. In particular, he took the disposition to suspend judgment in situations of cognitive dissonance to be a general disposition.) Conceptual subject-specificity is subject to obvious counter-examples, such as the general ability to recognize confusion of necessary and sufficient conditions. A more modest thesis, also endorsed by McPeck, is epistemological subject-specificity, according to which the norms of good thinking vary from one field to another. Epistemological subject-specificity clearly holds to a certain extent; for example, the principles in accordance with which one solves a differential equation are quite different from the principles in accordance with which one determines whether a painting is a genuine Picasso. But the thesis suffers, as Ennis (1989) points out, from vagueness of the concept of a field or subject and from the obvious existence of inter-field principles, however broadly the concept of a field is construed. For example, the principles of hypothetico-deductive reasoning hold for all the varied fields in which such reasoning occurs. A third kind of subject-specificity is empirical subject-specificity, according to which as a matter of empirically observable fact a person with the abilities and dispositions of a critical thinker in one area of investigation will not necessarily have them in another area of investigation.

The thesis of empirical subject-specificity raises the general problem of transfer. If critical thinking abilities and dispositions have to be developed independently in each school subject, how are they of any use in dealing with the problems of everyday life and the political and social issues of contemporary society, most of which do not fit into the framework of a traditional school subject? Proponents of empirical subject-specificity tend to argue that transfer is more likely to occur if there is critical thinking instruction in a variety of domains, with explicit attention to dispositions and abilities that cut across domains. But evidence for this claim is scanty. There is a need for well-designed empirical studies that investigate the conditions that make transfer more likely.

It is common ground in debates about the generality or subject-specificity of critical thinking dispositions and abilities that critical thinking about any topic requires background knowledge about the topic. For example, the most sophisticated understanding of the principles of hypothetico-deductive reasoning is of no help unless accompanied by some knowledge of what might be plausible explanations of some phenomenon under investigation.

Critics have objected to bias in the theory, pedagogy and practice of critical thinking. Commentators (e.g., Alston 1995; Ennis 1998) have noted that anyone who takes a position has a bias in the neutral sense of being inclined in one direction rather than others. The critics, however, are objecting to bias in the pejorative sense of an unjustified favoring of certain ways of knowing over others, frequently alleging that the unjustly favoured ways are those of a dominant sex or culture (Bailin 1995). These ways favour:

• reinforcement of egocentric and sociocentric biases over dialectical engagement with opposing world-views (Paul 1981, 1984; Warren 1998)
• distancing from the object of inquiry over closeness to it (Martin 1992; Thayer-Bacon 1992)
• indifference to the situation of others over care for them (Martin 1992)
• orientation to thought over orientation to action (Martin 1992)
• being reasonable over caring to understand people’s ideas (Thayer-Bacon 1993)
• being neutral and objective over being embodied and situated (Thayer-Bacon 1995a)
• doubting over believing (Thayer-Bacon 1995b)
• reason over emotion, imagination and intuition (Thayer-Bacon 2000)
• solitary thinking over collaborative thinking (Thayer-Bacon 2000)
• written and spoken assignments over other forms of expression (Alston 2001)
• attention to written and spoken communications over attention to human problems (Alston 2001)
• winning debates in the public sphere over making and understanding meaning (Alston 2001)

A common thread in this smorgasbord of accusations is dissatisfaction with focusing on the logical analysis and evaluation of reasoning and arguments. While these authors acknowledge that such analysis and evaluation is part of critical thinking and should be part of its conceptualization and pedagogy, they insist that it is only a part. Paul (1981), for example, bemoans the tendency of atomistic teaching of methods of analyzing and evaluating arguments to turn students into more able sophists, adept at finding fault with positions and arguments with which they disagree but even more entrenched in the egocentric and sociocentric biases with which they began. Martin (1992) and Thayer-Bacon (1992) cite with approval the self-reported intimacy with their subject-matter of leading researchers in biology and medicine, an intimacy that conflicts with the distancing allegedly recommended in standard conceptions and pedagogy of critical thinking. Thayer-Bacon (2000) contrasts the embodied and socially embedded learning of her elementary school students in a Montessori school, who used their imagination, intuition and emotions as well as their reason, with conceptions of critical thinking as

thinking that is used to critique arguments, offer justifications, and make judgments about what are the good reasons, or the right answers. (Thayer-Bacon 2000: 127–128)

Alston (2001) reports that her students in a women’s studies class were able to see the flaws in the Cinderella myth that pervades much romantic fiction but in their own romantic relationships still acted as if all failures were the woman’s fault and still accepted the notions of love at first sight and living happily ever after. Students, she writes, should

be able to connect their intellectual critique to a more affective, somatic, and ethical account of making risky choices that have sexist, racist, classist, familial, sexual, or other consequences for themselves and those both near and far… critical thinking that reads arguments, texts, or practices merely on the surface without connections to feeling/desiring/doing or action lacks an ethical depth that should infuse the difference between mere cognitive activity and something we want to call critical thinking. (Alston 2001: 34)

Some critics portray such biases as unfair to women. Thayer-Bacon (1992), for example, has charged modern critical thinking theory with being sexist, on the ground that it separates the self from the object and causes one to lose touch with one’s inner voice, and thus stigmatizes women, who (she asserts) link self to object and listen to their inner voice. Her charge does not imply that women as a group are on average less able than men to analyze and evaluate arguments. Facione (1990c) found no difference by sex in performance on his California Critical Thinking Skills Test. Kuhn (1991: 280–281) found no difference by sex in either the disposition or the competence to engage in argumentative thinking.

The critics propose a variety of remedies for the biases that they allege. In general, they do not propose to eliminate or downplay critical thinking as an educational goal. Rather, they propose to conceptualize critical thinking differently and to change its pedagogy accordingly. Their pedagogical proposals arise logically from their objections. They can be summarized as follows:

• Focus on argument networks with dialectical exchanges reflecting contesting points of view rather than on atomic arguments, so as to develop “strong sense” critical thinking that transcends egocentric and sociocentric biases (Paul 1981, 1984).
• Foster closeness to the subject-matter and feeling connected to others in order to inform a humane democracy (Martin 1992).
• Develop “constructive thinking” as a social activity in a community of physically embodied and socially embedded inquirers with personal voices who value not only reason but also imagination, intuition and emotion (Thayer-Bacon 2000).
• In developing critical thinking in school subjects, treat as important neither skills nor dispositions but opening worlds of meaning (Alston 2001).
• Attend to the development of critical thinking dispositions as well as skills, and adopt the “critical pedagogy” practised and advocated by Freire (1968 [1970]) and hooks (1994) (Dalgleish, Girard, & Davies 2017).

A common thread in these proposals is treatment of critical thinking as a social, interactive, personally engaged activity like that of a quilting bee or a barn-raising (Thayer-Bacon 2000) rather than as an individual, solitary, distanced activity symbolized by Rodin’s The Thinker . One can get a vivid description of education with the former type of goal from the writings of bell hooks (1994, 2010). Critical thinking for her is open-minded dialectical exchange across opposing standpoints and from multiple perspectives, a conception similar to Paul’s “strong sense” critical thinking (Paul 1981). She abandons the structure of domination in the traditional classroom. In an introductory course on black women writers, for example, she assigns students to write an autobiographical paragraph about an early racial memory, then to read it aloud as the others listen, thus affirming the uniqueness and value of each voice and creating a communal awareness of the diversity of the group’s experiences (hooks 1994: 84). Her “engaged pedagogy” is thus similar to the “freedom under guidance” implemented in John Dewey’s Laboratory School of Chicago in the late 1890s and early 1900s. It incorporates the dialogue, anchored instruction, and mentoring that Abrami (2015) found to be most effective in improving critical thinking skills and dispositions.

What is the relationship of critical thinking to problem solving, decision-making, higher-order thinking, creative thinking, and other recognized types of thinking? One’s answer to this question obviously depends on how one defines the terms used in the question. If critical thinking is conceived broadly to cover any careful thinking about any topic for any purpose, then problem solving and decision making will be kinds of critical thinking, if they are done carefully. Historically, ‘critical thinking’ and ‘problem solving’ were two names for the same thing. If critical thinking is conceived more narrowly as consisting solely of appraisal of intellectual products, then it will be disjoint with problem solving and decision making, which are constructive.

Bloom’s taxonomy of educational objectives used the phrase “intellectual abilities and skills” for what had been labeled “critical thinking” by some, “reflective thinking” by Dewey and others, and “problem solving” by still others (Bloom et al. 1956: 38). Thus, the so-called “higher-order thinking skills” at the taxonomy’s top levels of analysis, synthesis and evaluation are just critical thinking skills, although they do not come with general criteria for their assessment (Ennis 1981b). The revised version of Bloom’s taxonomy (Anderson et al. 2001) likewise treats critical thinking as cutting across those types of cognitive process that involve more than remembering (Anderson et al. 2001: 269–270). For details, see the Supplement on History .

As to creative thinking, it overlaps with critical thinking (Bailin 1987, 1988). Thinking about the explanation of some phenomenon or event, as in Ferryboat , requires creative imagination in constructing plausible explanatory hypotheses. Likewise, thinking about a policy question, as in Candidate , requires creativity in coming up with options. Conversely, creativity in any field needs to be balanced by critical appraisal of the draft painting or novel or mathematical theory.

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How to cite this entry . Preview the PDF version of this entry at the Friends of the SEP Society . Look up this entry topic at the Internet Philosophy Ontology Project (InPhO). Enhanced bibliography for this entry at PhilPapers , with links to its database.

• Association for Informal Logic and Critical Thinking (AILACT)
• Center for Teaching Thinking (CTT)
• Critical Thinking Across the European Higher Education Curricula (CRITHINKEDU)
• Critical Thinking Definition, Instruction, and Assessment: A Rigorous Approach (criticalTHINKING.net)
• Critical Thinking Research (RAIL)
• Foundation for Critical Thinking
• Insight Assessment
• Partnership for 21st Century Learning (P21)
• The Critical Thinking Consortium
• The Nature of Critical Thinking: An Outline of Critical Thinking Dispositions and Abilities , by Robert H. Ennis

abilities | bias, implicit | children, philosophy for | civic education | decision-making capacity | Dewey, John | dispositions | education, philosophy of | epistemology: virtue | logic: informal

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He Still Thought He Could Win: Inside Biden’s Decision to Drop Out

People close to President Biden say he believes he could have won a second term. But he came to realize that the fight would rip apart the Democratic Party that he had served his whole life.

President Biden exited the 2024 race on a weekend in late July, keeping his deliberations within a tight circle. Credit... Eric Lee/The New York Times

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By Michael D. Shear Katie Rogers and Adam Entous

Reporting from Washington

• Aug. 15, 2024

In the end, he was alone.

Confined to a spare bedroom in his vacation home and fighting off bouts of coughing from Covid, President Biden was exhausted when he turned in for the night on Saturday, July 20. Whether he slept soundly or fitfully or not at all, people close to him said he took the long hours by himself to mull over the historic decision he was about to make.

He had just been through a brutal two days in Rehoboth Beach, Del., as he huddled with his wife, Jill Biden, and his closest aides, who rotated from a screened-in porch to a sitting area off the dining room.

Steve Ricchetti, the president’s eyes and ears on Capitol Hill, and Mike Donilon, his chief strategist, had shared internal polling with the president that Saturday that mirrored what Americans had been seeing for weeks: Mr. Biden was falling behind, nationally and in key battleground states.

There was still a path to victory, they advised him, but the fight would be ugly. The president would be pitted against his donors, half of his party in Congress and Democratic voters who had concluded that he was too old to win.

For more than three weeks, Mr. Biden had insisted he would stay in the race. Only the “ Lord Almighty ,” he said, could get him to drop out.

But by that Saturday evening, something had shifted.

It was not just about the polls, people close to Mr. Biden say. Despite everything, Mr. Biden believed he could still claim the Democratic nomination and beat former President Donald J. Trump. Aides say that he still believes that.

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