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Critical Thinking: A Model of Intelligence for Solving Real-World Problems

Diane f. halpern.

1 Department of Psychology, Claremont McKenna College, Emerita, Altadena, CA 91001, USA

Dana S. Dunn

2 Department of Psychology, Moravian College, Bethlehem, PA 18018, USA; ude.naivarom@nnud

Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. A high IQ is correlated with many important outcomes (e.g., academic prominence, reduced crime), but it does not protect against cognitive biases, partisan thinking, reactance, or confirmation bias, among others. There are several newer theories that directly address the question about solving real-world problems. Prominent among them is Sternberg’s adaptive intelligence with “adaptation to the environment” as the central premise, a construct that does not exist on standardized IQ tests. Similarly, some scholars argue that standardized tests of intelligence are not measures of rational thought—the sort of skill/ability that would be needed to address complex real-world problems. Other investigators advocate for critical thinking as a model of intelligence specifically designed for addressing real-world problems. Yes, intelligence (i.e., critical thinking) can be enhanced and used for solving a real-world problem such as COVID-19, which we use as an example of contemporary problems that need a new approach.

1. Introduction

The editors of this Special Issue asked authors to respond to a deceptively simple statement: “How Intelligence Can Be a Solution to Consequential World Problems.” This statement holds many complexities, including how intelligence is defined and which theories are designed to address real-world problems.

2. The Problem with Using Standardized IQ Measures for Real-World Problems

For the most part, we identify high intelligence as having a high score on a standardized test of intelligence. Like any test score, IQ can only reflect what is on the given test. Most contemporary standardized measures of intelligence include vocabulary, working memory, spatial skills, analogies, processing speed, and puzzle-like elements (e.g., Wechsler Adult Intelligence Scale Fourth Edition; see ( Drozdick et al. 2012 )). Measures of IQ correlate with many important outcomes, including academic performance ( Kretzschmar et al. 2016 ), job-related skills ( Hunter and Schmidt 1996 ), reduced likelihood of criminal behavior ( Burhan et al. 2014 ), and for those with exceptionally high IQs, obtaining a doctorate and publishing scholarly articles ( McCabe et al. 2020 ). Gottfredson ( 1997, p. 81 ) summarized these effects when she said the “predictive validity of g is ubiquitous.” More recent research using longitudinal data, found that general mental abilities and specific abilities are good predictors of several work variables including job prestige, and income ( Lang and Kell 2020 ). Although assessments of IQ are useful in many contexts, having a high IQ does not protect against falling for common cognitive fallacies (e.g., blind spot bias, reactance, anecdotal reasoning), relying on biased and blatantly one-sided information sources, failing to consider information that does not conform to one’s preferred view of reality (confirmation bias), resisting pressure to think and act in a certain way, among others. This point was clearly articulated by Stanovich ( 2009, p. 3 ) when he stated that,” IQ tests measure only a small set of the thinking abilities that people need.”

3. Which Theories of Intelligence Are Relevant to the Question?

Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. For example, Grossmann et al. ( 2013 ) cite many studies in which IQ scores have not predicted well-being, including life satisfaction and longevity. Using a stratified random sample of Americans, these investigators found that wise reasoning is associated with life satisfaction, and that “there was no association between intelligence and well-being” (p. 944). (critical thinking [CT] is often referred to as “wise reasoning” or “rational thinking,”). Similar results were reported by Wirthwein and Rost ( 2011 ) who compared life satisfaction in several domains for gifted adults and adults of average intelligence. There were no differences in any of the measures of subjective well-being, except for leisure, which was significantly lower for the gifted adults. Additional research in a series of experiments by Stanovich and West ( 2008 ) found that participants with high cognitive ability were as likely as others to endorse positions that are consistent with their biases, and they were equally likely to prefer one-sided arguments over those that provided a balanced argument. There are several newer theories that directly address the question about solving real-world problems. Prominent among them is Sternberg’s adaptive intelligence with “adaptation to the environment” as the central premise, a construct that does not exist on standardized IQ tests (e.g., Sternberg 2019 ). Similarly, Stanovich and West ( 2014 ) argue that standardized tests of intelligence are not measures of rational thought—the sort of skill/ability that would be needed to address complex real-world problems. Halpern and Butler ( 2020 ) advocate for CT as a useful model of intelligence for addressing real-world problems because it was designed for this purpose. Although there is much overlap among these more recent theories, often using different terms for similar concepts, we use Halpern and Butler’s conceptualization to make our point: Yes, intelligence (i.e., CT) can be enhanced and used for solving a real-world problem like COVID-19.

4. Critical Thinking as an Applied Model for Intelligence

One definition of intelligence that directly addresses the question about intelligence and real-world problem solving comes from Nickerson ( 2020, p. 205 ): “the ability to learn, to reason well, to solve novel problems, and to deal effectively with novel problems—often unpredictable—that confront one in daily life.” Using this definition, the question of whether intelligent thinking can solve a world problem like the novel coronavirus is a resounding “yes” because solutions to real-world novel problems are part of his definition. This is a popular idea in the general public. For example, over 1000 business managers and hiring executives said that they want employees who can think critically based on the belief that CT skills will help them solve work-related problems ( Hart Research Associates 2018 ).

We define CT as the use of those cognitive skills or strategies that increase the probability of a desirable outcome. It is used to describe thinking that is purposeful, reasoned, and goal directed--the kind of thinking involved in solving problems, formulating inferences, calculating likelihoods, and making decisions, when the thinker is using skills that are thoughtful and effective for the particular context and type of thinking task. International surveys conducted by the OECD ( 2019, p. 16 ) established “key information-processing competencies” that are “highly transferable, in that they are relevant to many social contexts and work situations; and ‘learnable’ and therefore subject to the influence of policy.” One of these skills is problem solving, which is one subset of CT skills.

The CT model of intelligence is comprised of two components: (1) understanding information at a deep, meaningful level and (2) appropriate use of CT skills. The underlying idea is that CT skills can be identified, taught, and learned, and when they are recognized and applied in novel settings, the individual is demonstrating intelligent thought. CT skills include judging the credibility of an information source, making cost–benefit calculations, recognizing regression to the mean, understanding the limits of extrapolation, muting reactance responses, using analogical reasoning, rating the strength of reasons that support and fail to support a conclusion, and recognizing hindsight bias or confirmation bias, among others. Critical thinkers use these skills appropriately, without prompting, and usually with conscious intent in a variety of settings.

One of the key concepts in this model is that CT skills transfer in appropriate situations. Thus, assessments using situational judgments are needed to assess whether particular skills have transferred to a novel situation where it is appropriate. In an assessment created by the first author ( Halpern 2018 ), short paragraphs provide information about 20 different everyday scenarios (e.g., A speaker at the meeting of your local school board reported that when drug use rises, grades decline; so schools need to enforce a “war on drugs” to improve student grades); participants provide two response formats for every scenario: (a) constructed responses where they respond with short written responses, followed by (b) forced choice responses (e.g., multiple choice, rating or ranking of alternatives) for the same situations.

There is a large and growing empirical literature to support the assertion that CT skills can be learned and will transfer (when taught for transfer). See for example, Holmes et al. ( 2015 ), who wrote in the prestigious Proceedings of the National Academy of Sciences , that there was “significant and sustained improvement in students’ critical thinking behavior” (p. 11,199) for students who received CT instruction. Abrami et al. ( 2015, para. 1 ) concluded from a meta-analysis that “there are effective strategies for teaching CT skills, both generic and content specific, and CT dispositions, at all educational levels and across all disciplinary areas.” Abrami et al. ( 2008, para. 1 ), included 341 effect sizes in a meta-analysis. They wrote: “findings make it clear that improvement in students’ CT skills and dispositions cannot be a matter of implicit expectation.” A strong test of whether CT skills can be used for real-word problems comes from research by Butler et al. ( 2017 ). Community adults and college students (N = 244) completed several scales including an assessment of CT, an intelligence test, and an inventory of real-life events. Both CT scores and intelligence scores predicted individual outcomes on the inventory of real-life events, but CT was a stronger predictor.

Heijltjes et al. ( 2015, p. 487 ) randomly assigned participants to either a CT instruction group or one of six other control conditions. They found that “only participants assigned to CT instruction improved their reasoning skills.” Similarly, when Halpern et al. ( 2012 ) used random assignment of participants to either a learning group where they were taught scientific reasoning skills using a game format or a control condition (which also used computerized learning and was similar in length), participants in the scientific skills learning group showed higher proportional learning gains than students who did not play the game. As the body of additional supportive research is too large to report here, interested readers can find additional lists of CT skills and support for the assertion that these skills can be learned and will transfer in Halpern and Dunn ( Forthcoming ). There is a clear need for more high-quality research on the application and transfer of CT and its relationship to IQ.

5. Pandemics: COVID-19 as a Consequential Real-World Problem

A pandemic occurs when a disease runs rampant over an entire country or even the world. Pandemics have occurred throughout history: At the time of writing this article, COVID-19 is a world-wide pandemic whose actual death rate is unknown but estimated with projections of several million over the course of 2021 and beyond ( Mega 2020 ). Although vaccines are available, it will take some time to inoculate most or much of the world’s population. Since March 2020, national and international health agencies have created a list of actions that can slow and hopefully stop the spread of COVID (e.g., wearing face masks, practicing social distancing, avoiding group gatherings), yet many people in the United States and other countries have resisted their advice.

Could instruction in CT encourage more people to accept and comply with simple life-saving measures? There are many possible reasons to believe that by increasing citizens’ CT abilities, this problematic trend can be reversed for, at least, some unknown percentage of the population. We recognize the long history of social and cognitive research showing that changing attitudes and behaviors is difficult, and it would be unrealistic to expect that individuals with extreme beliefs supported by their social group and consistent with their political ideologies are likely to change. For example, an Iranian cleric and an orthodox rabbi both claimed (separately) that the COVID-19 vaccine can make people gay ( Marr 2021 ). These unfounded opinions are based on deeply held prejudicial beliefs that we expect to be resistant to CT. We are targeting those individuals who beliefs are less extreme and may be based on reasonable reservations, such as concern about the hasty development of the vaccine and the lack of long-term data on its effects. There should be some unknown proportion of individuals who can change their COVID-19-related beliefs and actions with appropriate instruction in CT. CT can be a (partial) antidote for the chaos of the modern world with armies of bots creating content on social media, political and other forces deliberately attempting to confuse issues, and almost all media labeled “fake news” by social influencers (i.e., people with followers that sometimes run to millions on various social media). Here, are some CT skills that could be helpful in getting more people to think more critically about pandemic-related issues.

Reasoning by Analogy and Judging the Credibility of the Source of Information

Early communications about the ability of masks to prevent the spread of COVID from national health agencies were not consistent. In many regions of the world, the benefits of wearing masks incited prolonged and acrimonious debates ( Tang 2020 ). However, after the initial confusion, virtually all of the global and national health organizations (e.g., WHO, National Health Service in the U. K., U. S. Centers for Disease Control and Prevention) endorse masks as a way to slow the spread of COVID ( Cheng et al. 2020 ; Chu et al. 2020 ). However, as we know, some people do not trust governmental agencies and often cite the conflicting information that was originally given as a reason for not wearing a mask. There are varied reasons for refusing to wear a mask, but the one most often cited is that it is against civil liberties ( Smith 2020 ). Reasoning by analogy is an appropriate CT skill for evaluating this belief (and a key skill in legal thinking). It might be useful to cite some of the many laws that already regulate our behavior such as, requiring health inspections for restaurants, setting speed limits, mandating seat belts when riding in a car, and establishing the age at which someone can consume alcohol. Individuals would be asked to consider how the mandate to wear a mask compares to these and other regulatory laws.

Another reason why some people resist the measures suggested by virtually every health agency concerns questions about whom to believe. Could training in CT change the beliefs and actions of even a small percentage of those opposed to wearing masks? Such training would include considering the following questions with practice across a wide domain of knowledge: (a) Does the source have sufficient expertise? (b) Is the expertise recent and relevant? (c) Is there a potential for gain by the information source, such as financial gain? (d) What would the ideal information source be and how close is the current source to the ideal? (e) Does the information source offer evidence that what they are recommending is likely to be correct? (f) Have you traced URLs to determine if the information in front of you really came from the alleged source?, etc. Of course, not everyone will respond in the same way to each question, so there is little likelihood that we would all think alike, but these questions provide a framework for evaluating credibility. Donovan et al. ( 2015 ) were successful using a similar approach to improve dynamic decision-making by asking participants to reflect on questions that relate to the decision. Imagine the effect of rigorous large-scale education in CT from elementary through secondary schools, as well as at the university-level. As stated above, empirical evidence has shown that people can become better thinkers with appropriate instruction in CT. With training, could we encourage some portion of the population to become more astute at judging the credibility of a source of information? It is an experiment worth trying.

6. Making Cost—Benefit Assessments for Actions That Would Slow the Spread of COVID-19

Historical records show that refusal to wear a mask during a pandemic is not a new reaction. The epidemic of 1918 also included mandates to wear masks, which drew public backlash. Then, as now, many people refused, even when they were told that it was a symbol of “wartime patriotism” because the 1918 pandemic occurred during World War I ( Lovelace 2020 ). CT instruction would include instruction in why and how to compute cost–benefit analyses. Estimates of “lives saved” by wearing a mask can be made meaningful with graphical displays that allow more people to understand large numbers. Gigerenzer ( 2020 ) found that people can understand risk ratios in medicine when the numbers are presented as frequencies instead of probabilities. If this information were used when presenting the likelihood of illness and death from COVID-19, could we increase the numbers of people who understand the severity of this disease? Small scale studies by Gigerenzer have shown that it is possible.

Analyzing Arguments to Determine Degree of Support for a Conclusion

The process of analyzing arguments requires that individuals rate the strength of support for and against a conclusion. By engaging in this practice, they must consider evidence and reasoning that may run counter to a preferred outcome. Kozyreva et al. ( 2020 ) call the deliberate failure to consider both supporting and conflicting data “deliberate ignorance”—avoiding or failing to consider information that could be useful in decision-making because it may collide with an existing belief. When applied to COVID-19, people would have to decide if the evidence for and against wearing a face mask is a reasonable way to stop the spread of this disease, and if they conclude that it is not, what are the costs and benefits of not wearing masks at a time when governmental health organizations are making them mandatory in public spaces? Again, we wonder if rigorous and systematic instruction in argument analysis would result in more positive attitudes and behaviors that relate to wearing a mask or other real-world problems. We believe that it is an experiment worth doing.

7. Conclusions

We believe that teaching CT is a worthwhile approach for educating the general public in order to improve reasoning and motivate actions to address, avert, or ameliorate real-world problems like the COVID-19 pandemic. Evidence suggests that CT can guide intelligent responses to societal and global problems. We are NOT claiming that CT skills will be a universal solution for the many real-world problems that we confront in contemporary society, or that everyone will substitute CT for other decision-making practices, but we do believe that systematic education in CT can help many people become better thinkers, and we believe that this is an important step toward creating a society that values and practices routine CT. The challenges are great, but the tools to tackle them are available, if we are willing to use them.

Author Contributions

Conceptualization, D.F.H. and D.S.D.; resources, D.F.H.; data curation, writing—original draft preparation, D.F.H.; writing—review and editing, D.F.H. and D.S.D. All authors have read and agreed to the published version of the manuscript.

This research received no external funding.

Institutional Review Board Statement

No IRB Review.

Informed Consent Statement

No Informed Consent.

Conflicts of Interest

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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APS

  • Teaching Tips

A Brief Guide for Teaching and Assessing Critical Thinking in Psychology

In my first year of college teaching, a student approached me one day after class and politely asked, “What did you mean by the word ‘evidence’?” I tried to hide my shock at what I took to be a very naive question. Upon further reflection, however, I realized that this was actually a good question, for which the usual approaches to teaching psychology provided too few answers. During the next several years, I developed lessons and techniques to help psychology students learn how to evaluate the strengths and weaknesses of scientific and nonscientific kinds of evidence and to help them draw sound conclusions. It seemed to me that learning about the quality of evidence and drawing appropriate conclusions from scientific research were central to teaching critical thinking (CT) in psychology.

In this article, I have attempted to provide guidelines to psychol­ogy instructors on how to teach CT, describing techniques I devel­oped over 20 years of teaching. More importantly, the techniques and approach described below are ones that are supported by scientific research. Classroom examples illustrate the use of the guidelines and how assessment can be integrated into CT skill instruction.

Overview of the Guidelines

Confusion about the definition of CT has been a major obstacle to teaching and assessing it (Halonen, 1995; Williams, 1999). To deal with this problem, we have defined CT as reflective think­ing involved in the evaluation of evidence relevant to a claim so that a sound or good conclusion can be drawn from the evidence (Bensley, 1998). One virtue of this definition is it can be applied to many thinking tasks in psychology. The claims and conclusions psychological scientists make include hypotheses, theoretical state­ments, interpretation of research findings, or diagnoses of mental disorders. Evidence can be the results of an experiment, case study, naturalistic observation study, or psychological test. Less formally, evidence can be anecdotes, introspective reports, commonsense beliefs, or statements of authority. Evaluating evidence and drawing appropriate conclusions along with other skills, such as distin­guishing arguments from nonarguments and finding assumptions, are collectively called argument analysis skills. Many CT experts take argument analysis skills to be fundamental CT skills (e.g., Ennis, 1987; Halpern, 1998). Psychology students need argument analysis skills to evaluate psychological claims in their work and in everyday discourse.

Some instructors expect their students will improve CT skills like argument analysis skills by simply immersing them in challenging course work. Others expect improvement because they use a textbook with special CT questions or modules, give lectures that critically review the literature, or have students complete written assignments. While these and other traditional techniques may help, a growing body of research suggests they are not sufficient to efficiently produce measurable changes in CT skills. Our research on acquisition of argument analysis skills in psychology (Bensley, Crowe, Bernhardt, Buchner, & Allman, in press) and on critical reading skills (Bensley & Haynes, 1995; Spero & Bensley, 2009) suggests that more explicit, direct instruction of CT skills is necessary. These results concur with results of an earlier review of CT programs by Chance (1986) and a recent meta-analysis by Abrami et al., (2008).

Based on these and other findings, the following guidelines describe an approach to explicit instruction in which instructors can directly infuse CT skills and assessment into their courses. With infusion, instructors can use relevant content to teach CT rules and concepts along with the subject matter. Directly infus­ing CT skills into course work involves targeting specific CT skills, making CT rules, criteria, and methods explicit, providing guided practice in the form of exercises focused on assessing skills, and giving feedback on practice and assessments. These components are similar to ones found in effective, direct instruc­tion approaches (Walberg, 2006). They also resemble approaches to teaching CT proposed by Angelo (1995), Beyer (1997), and Halpern (1998). Importantly, this approach has been successful in teaching CT skills in psychology (e.g., Bensley, et al., in press; Bensley & Haynes, 1995; Nieto & Saiz, 2008; Penningroth, Despain, & Gray, 2007). Directly infusing CT skill instruction can also enrich content instruction without sacrificing learning of subject matter (Solon, 2003). The following seven guidelines, illustrated by CT lessons and assessments, explicate this process.

Seven Guidelines for Teaching and Assessing Critical Thinking

1. Motivate your students to think critically

Critical thinking takes effort. Without proper motivation, students are less inclined to engage in it. Therefore, it is good to arouse interest right away and foster commitment to improving CT throughout a course. One motivational strategy is to explain why CT is important to effective, professional behavior. Often, telling a compelling story that illustrates the consequences of failing to think critically can mo­tivate students. For example, the tragic death of 10-year-old Candace Newmaker at the hands of her therapists practicing attachment therapy illustrates the perils of using a therapy that has not been supported by good empirical evidence (Lilienfeld, 2007).

Instructors can also pique interest by taking a class poll posing an interesting question on which students are likely to have an opinion. For example, asking students how many think that the full moon can lead to increases in abnormal behavior can be used to introduce the difference between empirical fact and opinion or common sense belief. After asking students how psychologists answer such questions, instructors might go over the meta-analysis of Rotton and Kelly (1985). Their review found that almost all of the 37 studies they reviewed showed no association between the phase of the moon and abnormal behavior with only a few, usually poorly, controlled studies supporting it. Effect size over all stud­ies was very small (.01). Instructors can use this to illustrate how psychologists draw a conclusion based on the quality and quantity of research studies as opposed to what many people commonly believe. For other interesting thinking errors and misconceptions related to psychology, see Bensley (1998; 2002; 2008), Halpern (2003), Ruscio (2006), Stanovich (2007), and Sternberg (2007).

Attitudes and dispositions can also affect motivation to think critically. If students lack certain CT dispositions such as open-mindedness, fair-mindedness, and skepticism, they will be less likely to think critically even if they have CT skills (Halpern, 1998). Instructors might point out that even great scientists noted for their powers of reasoning sometimes fail to think critically when they are not disposed to use their skills. For example, Alfred Russel Wallace who used his considerable CT skills to help develop the concept of natural selection also believed in spiritualistic contact with the dead. Despite considerable evidence that mediums claiming to contact the dead were really faking such contact, Wallace continued to believe in it (Bensley, 2006). Likewise, the great American psychologist William James, whose reasoning skills helped him develop the seeds of important contemporary theories, believed in spiritualism despite evidence to the contrary.

2. Clearly state the CT goals and objectives for your class

Once students are motivated, the instructor should focus them on what skills they will work on during the course. The APA task force on learning goals and objectives for psychology listed CT as one of 10 major goals for students (Halonen et al., 2002). Under critical thinking they have further specified outcomes such as evaluating the quality of information, identifying and evaluating the source and credibility of information, recognizing and defending against think­ing errors and fallacies. Instructors should publish goals like these in their CT course objectives in their syllabi and more specifically as assignment objectives in their assignments. Given the pragmatic penchant of students for studying what is needed to succeed in a course, this should help motivate and focus them.

To make instruction efficient, course objectives and lesson ob­jectives should explicitly target CT skills to be improved. Objectives should specify the behavior that will change in a way that can be measured. A course objective might read, “After taking this course, you will be able to analyze arguments found in psychological and everyday discussions.” When the goal of a lesson is to practice and improve specific microskills that make up argument analysis, an assignment objective might read “After successfully completing this assignment, you will be able to identify different kinds of evidence in a psychological discussion.” Or another might read “After suc­cessfully completing this assignment, you will be able to distinguish arguments from nonarguments.” Students might demonstrate they have reached these objectives by showing the behavior of correctly labeling the kinds of evidence presented in a passage or by indicating whether an argument or merely a claim has been made. By stating objectives in the form of assessable behaviors, the instructor can test these as assessment hypotheses.

Sometimes when the goal is to teach students how to decide which CT skills are appropriate in a situation, the instructor may not want to identify specific skills. Instead, a lesson objective might read, “After successfully completing this assignment, you will be able to decide which skills and knowledge are appropriate for criti­cally analyzing a discussion in psychology.”

3. Find opportunities to infuse CT that fit content and skill requirements of your course

To improve their CT skills, students must be given opportunities to practice them. Different courses present different opportunities for infusion and practice. Stand-alone CT courses usually provide the most opportunities to infuse CT. For example, the Frostburg State University Psychology Department has a senior seminar called “Thinking like a Psychologist” in which students complete lessons giving them practice in argument analysis, critical reading, critically evaluating information on the Internet, distinguishing science from pseudoscience, applying their knowledge and CT skills in simula­tions of psychological practice, and other activities.

In more typical subject-oriented courses, instructors must find specific content and types of tasks conducive to explicit CT skill instruction. For example, research methods courses present several opportunities to teach argument analysis skills. Instructors can have students critically evaluate the quality of evidence provided by studies using different research methods and designs they find in PsycINFO and Internet sources. This, in turn, could help students write better critical evaluations of research for research reports.

A cognitive psychology teacher might assign a critical evalu­ation of the evidence on an interesting question discussed in text­book literature reviews. For example, students might evaluate the evidence relevant to the question of whether people have flashbulb memories such as accurately remembering the 9-11 attack. This provides the opportunity to teach them that many of the studies, although informative, are quasi-experimental and cannot show causation. Or, students might analyze the arguments in a TV pro­gram such as the fascinating Nova program Kidnapped by Aliens on people who recall having been abducted by aliens.

4. Use guided practice, explicitly modeling and scaffolding CT.

Guided practice involves modeling and supporting the practice of target skills, and providing feedback on progress towards skill attainment. Research has shown that guided practice helps student more efficiently acquire thinking skills than unguided and discovery approaches (Meyer, 2004).

Instructors can model the use of CT rules, criteria, and proce­dures for evaluating evidence and drawing conclusions in many ways. They could provide worked examples of problems, writing samples displaying good CT, or real-world examples of good and bad thinking found in the media. They might also think out loud as they evaluate arguments in class to model the process of thinking.

To help students learn to use complex rules in thinking, instruc­tors should initially scaffold student thinking. Scaffolding involves providing product guidelines, rules, and other frameworks to support the process of thinking. Table 1 shows guidelines like those found in Bensley (1998) describing nonscientific kinds of evidence that can support student efforts to evaluate evidence in everyday psychologi­cal discussions. Likewise, Table 2 provides guidelines like those found in Bensley (1998) and Wade and Tavris (2005) describing various kinds of scientific research methods and designs that differ in the quality of evidence they provide for psychological arguments.

In the cognitive lesson on flashbulb memory described earlier, students use the framework in Table 2 to evaluate the kinds of evidence in the literature review. Table 1 can help them evaluate the kinds of evidence found in the Nova video Kidnapped by Aliens . Specifically, they could use it to contrast scientific authority with less credible authority. The video includes statements by scientific authorities like Elizabeth Loftus based on her extensive research contrasted with the nonscientific authority of Bud Hopkins, an artist turned hypnotherapist and author of popular books on alien abduction. Loftus argues that the memories of alien abduction in the children interviewed by Hopkins were reconstructed around the suggestive interview questions he posed. Therefore, his conclu­sion that the children and other people in the video were recalling actual abduction experiences was based on anecdotes, unreliable self-reports, and other weak evidence.

Modeling, scaffolding, and guided practice are especially useful in helping students first acquire CT skills. After sufficient practice, however, instructors should fade these and have students do more challenging assignments without these supports to promote transfer.

5. Align assessment with practice of specific CT skills

Test questions and other assessments of performance should be similar to practice questions and problems in the skills targeted but differ in content. For example, we have developed a series of practice and quiz questions about the kinds of evidence found in Table 1 used in everyday situations but which differ in subject matter from practice to quiz. Likewise, other questions employ research evidence examples corresponding to Table 2. Questions ask students to identify kinds of evidence, evaluate the quality of the evidence, distinguish arguments from nonarguments, and find assumptions in the examples with practice examples differing in content from assessment items.

6. Provide feedback and encourage students to reflect on it

Instructors should focus feedback on the degree of attainment of CT skill objectives in the lesson or assessment. The purpose of feedback is to help students learn how to correct faulty thinking so that in the future they monitor their thinking and avoid such problems. This should increase their metacognition or awareness and control of their thinking, an important goal of CT instruction (Halpern, 1998).

Students must use their feedback for it to improve their CT skills. In the CT exercises and critical reading assignments, students receive feedback in the form of corrected responses and written feedback on open-ended questions. They should be advised that paying attention to feedback on earlier work and assessments should improve their performance on later assessments.

7. Reflect on feedback and assessment results to improve CT instruction

Instructors should use the feedback they provide to students and the results of ongoing assessments to ‘close the loop,’ that is, use these outcomes to address deficiencies in performance and improve instruction. In actual practice, teaching and assessment strategies rarely work optimally the first time. Instructors must be willing to tinker with these to make needed improvements. Reflec­tion on reliable and valid assessment results provides a scientific means to systematically improve instruction and assessment.

Instructors may find the direct infusion approach as summarized in the seven guidelines to be efficient, especially in helping students acquire basic CT skills, as research has shown. They may especially appreciate how it allows them to take a scientific approach to the improvement of instruction. Although the direct infusion approach seems to efficiently promote acquisition of CT skills, more research is needed to find out if students transfer their skills outside of the class­room or whether this approach needs adjustment to promote transfer.

Table 1. Strengths and Weaknesses of Nonscientific Sources and Kinds of Evidence

Table 2. Strengths and Weaknesses of Scientific Research Methods/Designs Used as Sources of Evidence

Abrami, P. C., Bernard, R. M., Borokhovhovski, E., Wade, A., Surkes, M. A., Tamim, R., et al., (2008). Instructional interventions affecting critical thinking skills and dispositions: A stage 1 meta-analysis. Review of Educational Research, 4 , 1102–1134.

Angelo, T. A. (1995). Classroom assessment for critical thinking. Teaching of Psychology , 22(1), 6–7.

Bensley, D.A. (1998). Critical thinking in psychology: A unified skills approach. Pacific Grove, CA: Brooks/Cole.

Bensley, D.A. (2002). Science and pseudoscience: A critical thinking primer. In M. Shermer (Ed.), The Skeptic encyclopedia of pseudoscience. (pp. 195–203). Santa Barbara, CA: ABC–CLIO.

Bensley, D.A. (2006). Why great thinkers sometimes fail to think critically. Skeptical Inquirer, 30, 47–52.

Bensley, D.A. (2008). Can you learn to think more like a psychologist? The Psychologist, 21, 128–129.

Bensley, D.A., Crowe, D., Bernhardt, P., Buckner, C., & Allman, A. (in press). Teaching and assessing critical thinking skills for argument analysis in psychology. Teaching of Psychology .

Bensley, D.A. & Haynes, C. (1995). The acquisition of general purpose strategic knowledge for argumentation. Teaching of Psychology, 22 , 41–45.

Beyer, B.K. (1997). Improving student thinking: A comprehensive approach . Boston: Allyn & Bacon.

Chance, P. (1986) Thinking in the classroom: A review of programs . New York: Instructors College Press.

Ennis, R.H. (1987). A taxonomy of critical thinking dispositions and abilities. In J. B. Baron & R. F. Sternberg (Eds.). Teaching thinking skills: Theory and practice (pp. 9–26). New York: Freeman.

Halonen, J.S. (1995). Demystifying critical thinking. Teaching of Psychology, 22 , 75–81.

Halonen, J.S., Appleby, D.C., Brewer, C.L., Buskist, W., Gillem, A. R., Halpern, D. F., et al. (APA Task Force on Undergraduate Major Competencies). (2002) Undergraduate psychology major learning goals and outcomes: A report. Washington, DC: American Psychological Association. Retrieved August 27, 2008, from http://www.apa.org/ed/pcue/reports.html .

Halpern, D.F. (1998). Teaching critical thinking for transfer across domains: Dispositions, skills, structure training, and metacognitive monitoring. American Psychologist , 53 , 449–455.

Halpern, D.F. (2003). Thought and knowledge: An introduction to critical thinking . (3rd ed.). Mahwah, NJ: Erlbaum.

Lilienfeld, S.O. (2007). Psychological treatments that cause harm. Perspectives on Psychological Science , 2 , 53–70.

Meyer, R.E. (2004). Should there be a three-strikes rule against pure discovery learning? The case for guided methods of instruction. American Psychologist , 59 , 14–19.

Nieto, A.M., & Saiz, C. (2008). Evaluation of Halpern’s “structural component” for improving critical thinking. The Spanish Journal of Psychology , 11 ( 1 ), 266–274.

Penningroth, S.L., Despain, L.H., & Gray, M.J. (2007). A course designed to improve psychological critical thinking. Teaching of Psychology , 34 , 153–157.

Rotton, J., & Kelly, I. (1985). Much ado about the full moon: A meta-analysis of lunar-lunacy research. Psychological Bulletin , 97 , 286–306.

Ruscio, J. (2006). Critical thinking in psychology: Separating sense from nonsense. Belmont, CA: Wadsworth.

Solon, T. (2007). Generic critical thinking infusion and course content learning in introductory psychology. Journal of Instructional Psychology , 34(2), 972–987.

Stanovich, K.E. (2007). How to think straight about psychology . (8th ed.). Boston: Pearson.

Sternberg, R.J. (2007). Critical thinking in psychology: It really is critical. In R. J. Sternberg, H. L. Roediger, & D. F. Halpern (Eds.), Critical thinking in psychology. (pp. 289–296) . Cambridge, UK: Cambridge University Press.

Wade, C., & Tavris, C. (2005) Invitation to psychology. (3rd ed.). Upper Saddle River, NJ: Prentice Hall.

Walberg, H.J. (2006). Improving educational productivity: A review of extant research. In R. F. Subotnik & H. J. Walberg (Eds.), The scientific basis of educational productivity (pp. 103–159). Greenwich, CT: Information Age.

Williams, R.L. (1999). Operational definitions and assessment of higher-order cognitive constructs. Educational Psychology Review , 11 , 411–427.

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About the Author

D. Alan Bensley is Professor of Psychology at Frostburg State University. He received his Master’s and PhD degrees in cognitive psychology from Rutgers University. His main teaching and research interests concern the improvement of critical thinking and other cognitive skills. He coordinates assessment for his department and is developing a battery of instruments to assess critical thinking in psychology. He can be reached by email at [email protected] Association for Psychological Science December 2010 — Vol. 23, No. 10

critical thinking used in psychology

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In This Article Expand or collapse the "in this article" section Critical Thinking

Introduction, general overviews.

  • Importance of Thinking Critically
  • Defining Critical Thinking
  • General Skills
  • Specific Skills
  • Metacognitive Monitoring Skills
  • Critical Thinking Dispositions
  • Teaching Specific Skills
  • Encouraging a Disposition toward Thinking Critically
  • Transfer to Other Domains
  • Metacognitive Monitoring
  • General or Comprehensive Assessments
  • Metacognition Assessments
  • Critical Thinking Disposition Assessments
  • Thinking Critically about Critical Thinking

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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.

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. Moreover, 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 lane 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, 2021), others on the resulting judgment (Facione 1990a), and still others on responsiveness to reasons (Siegel 1988). Kuhn (2019) takes critical thinking to be more a dialogic practice of advancing and responding to arguments than an individual ability.

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 spacing 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 spacing 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 2016a) 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.

Facione (1990a: 25) divides “affective dispositions” of critical thinking into approaches to life and living in general and approaches to specific issues, questions or problems. Adapting this distinction, one can usefully divide critical thinking dispositions 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). 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. In three studies, Haran, Ritov, & Mellers (2013) found that actively open-minded thinking, including “the tendency to weigh new evidence against a favored belief, to spend sufficient time on a problem before giving up, and to consider carefully the opinions of others in forming one’s own”, led study participants to acquire information and thus to make accurate estimations.
  • 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), Black (2012), and Blair (2021).

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. It is also helpful to be aware of the prevalence of “noise” (unwanted unsystematic variability of judgments), of how to detect noise (through a noise audit), and of how to reduce noise: make accuracy the goal, think statistically, break a process of arriving at a judgment into independent tasks, resist premature intuitions, in a group get independent judgments first, favour comparative judgments and scales (Kahneman, Sibony, & Sunstein 2021). It is helpful as well to be aware of the concept of “bounded rationality” in decision-making and of the related distinction between “satisficing” and optimizing (Simon 1956; Gigerenzer 2001).

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? In a comprehensive meta-analysis of experimental and quasi-experimental studies of strategies for teaching students to think critically, Abrami et al. (2015) found that 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), Bailin et al. (1999b), and Willingham (2019).

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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Facilitating Complex Thinking

Critical Thinking

Critical thinking  requires skill at analyzing the reliability and validity of information, as well as the attitude or disposition to do so. The skill and attitude may be displayed with regard to a particular subject matter or topic, but in principle, it can occur in any realm of knowledge (Halpern, 2003; Williams, Oliver, & Stockade, 2004). A critical thinker does not necessarily have a negative attitude in the everyday sense of constantly criticizing someone or something. Instead, he or she can be thought of as  astute : the critical thinker asks key questions, evaluates the evidence for ideas, reasons for problems both logically and objectively, and expresses ideas and conclusions clearly and precisely. Last (but not least), the critical thinker can apply these habits of mind in more than one realm of life or knowledge.

critical thinking used in psychology

Figure 5.2.1.  Model of critical thinking.

With such a broad definition, it is not surprising that educators have suggested a variety of specific cognitive skills as contributing to critical thinking. In one study, for example, the researcher found how critical thinking can be reflected in regard to a published article that was stimulated by  annotation —writing questions and comments in the margins of the article (Liu, 2006). In this study, students were initially instructed in ways of annotating reading materials. Later, when the students completed additional readings for assignments, it was found that some students in fact used their annotation skills much more than others—some simply underlined passages, for example, with a highlighting pen. When essays written about the readings were later analyzed, the ones written by the annotators were found to be better reasoned—more critically astute—than the essays written by the other students.

In another study, on the other hand, a researcher found that critical thinking can also involve oral discussion of personal issues or dilemmas (Hawkins, 2006). In this study, students were asked to verbally describe a recent, personal incident that disturbed them. Classmates then discussed the incident together in order to identify the precise reasons why the incident was disturbing, as well as the assumptions that the student made in describing the incident. The original student—the one who had first told the story—then used the results of the group discussion to frame a topic for a research essay. In one story of a troubling incident, a student told of a time when a store clerk has snubbed or rejected the student during a recent shopping errand. Through discussion, classmates decided that an assumption underlying the student’s disturbance was her suspicion that she had been a victim of racial profiling based on her skin color. The student then used this idea as the basis for a research essay on the topic of “racial profiling in retail stores.” The oral discussion thus stimulated critical thinking in the student and the classmates, but it also  relied  on their prior critical thinking skills at the same time.

Notice that in both of these research studies, as in others like them, what made the thinking “critical” was students’ use of  metacognition —strategies for thinking  about  thinking and for monitoring the success and quality of one’s own thinking. This concept was discussed in the chapter, “The learning process,” as a feature of constructivist views about learning. There we pointed out that when students acquire experience in building their own knowledge, they also become skilled both at knowing  how  they learn, and at knowing  whether  they have learned something well. These are two defining qualities of metacognition, but they are part of critical thinking as well. In fostering critical thinking, a teacher is really fostering a student’s ability to construct or control his or her own thinking and to avoid being controlled by ideas unreflectively.

How best to teach critical thinking remains a matter of debate. One issue is whether to infuse critical skills into existing courses or to teach them through separate, free-standing units or courses. The first approach has the potential advantage of integrating critical thinking into students’ entire educations. But it risks diluting students’ understanding and use of critical thinking simply because critical thinking takes on a different form in each learning context. Its details and appearance vary among courses and teachers. The free-standing approach has the opposite qualities: it stands a better chance of being understood clearly and coherently but at the cost of obscuring how it is related to other courses, tasks, and activities. This dilemma is the issue—again—of  transfer.  Unfortunately, research to compare the different strategies for teaching critical thinking does not settle the matter. The research suggests simply that either infusion or free-standing approaches can work as long as it is implemented thoroughly and teachers are committed to the value of critical thinking (Halpern, 2003).

A related issue about teaching critical thinking is about deciding who needs to learn critical thinking skills the most. Should it be all students or only some of them? Teaching all students seems the more democratic alternative and thus appropriate for educators. Surveys have found, however, that teachers sometimes favor the teaching of critical thinking only to high-advantage students—the ones who already achieve well, who come from relatively high-income families, or (for high school students) who take courses intended for university entrance (Warburton & Torff, 2005). Presumably, the rationale for this bias is that high-advantage students can benefit and/or understand and use critical thinking better than other students. Yet, there is little research evidence to support this idea, even if it were not ethically questionable. The study by Hawkins (2006) described above, for example, is that critical thinking was fostered even with students considered low-advantage.

Video 5.2.1. Challenging Students  to Think Critically  suggests was to encourage critical thinking.

Teaching Critical Thinking

For suggestions on teaching and fostering critical thinking skills at all academic levels, visit the library at   The Foundation for Critical Thinking.

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Christopher Dwyer Ph.D.

3 Core Critical Thinking Skills Every Thinker Should Have

Critically thinking about critical thinking skills..

Posted March 13, 2020 | Reviewed by Ekua Hagan

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I recently received an email from an educator friend, asking me to briefly describe the skills necessary for critical thinking. They were happy to fill in the blanks themselves from outside reading but wanted to know what specific skills they should focus on teaching their students. I took this as a good opportunity to dedicate a post here to such discussion, in order to provide my friend and any other interested parties with an overview.

To understand critical thinking skills and how they factor into critical thinking, one first needs a definition of the latter. Critical thinking (CT) is a metacognitive process, consisting of a number of skills and dispositions, that when used through self-regulatory reflective judgment, increases the chances of producing a logical conclusion to an argument or solution to a problem (Dwyer, 2017; Dwyer, Hogan & Stewart, 2014). On the surface, this definition clarifies two issues. First, critical thinking is metacognitive—simply, it requires the individual to think about thinking; second, its main components are reflective judgment, dispositions, and skills.

Below the surface, this description requires clarification; hence the impetus for this entry—what is meant by reflective judgment, disposition towards CT, and CT skills? Reflective judgment (i.e. an individuals' understanding of the nature, limits, and certainty of knowing and how this can affect their judgments [King & Kitchener, 1994]) and disposition towards CT (i.e. an inclination, tendency or willingness to perform a given thinking skill [Dwyer, 2017; Facione, Facione & Giancarlo, 1997; Ku, 2009; Norris, 1992; Siegel, 1999; Valenzuela, Nieto & Saiz, 2011]) have both already been covered in my posts; so, consistent with the aim of this piece, let’s discuss CT skills.

CT skills allow individuals to transcend lower-order, memorization-based learning strategies to gain a more complex understanding of the information or problems they encounter (Halpern, 2014). Though debate is ongoing over the definition of CT, one list stands out as a reasonable consensus conceptualization of CT skills. In 1988, a committee of 46 experts in the field of CT gathered to discuss CT conceptualisations, resulting in the Delphi Report; within which was overwhelmingly agreement (i.e. 95% consensus) that analysis , evaluation and inference were the core skills necessary for CT (Facione, 1990). Indeed, over 30 years later, these three CT skills remain the most commonly cited.

1. Analysis

Analysis is a core CT skill used to identify and examine the structure of an argument, the propositions within an argument and the role they play (e.g. the main conclusion, the premises and reasons provided to support the conclusion, objections to the conclusion and inferential relationships among propositions), as well as the sources of the propositions (e.g. personal experience, common belief, and research).

When it comes to analysing the basis for a standpoint, the structure of the argument can be extracted for subsequent evaluation (e.g. from dialogue and text). This can be accomplished through looking for propositions that either support or refute the central claim or other reasons and objections. Through analysis, the argument’s hierarchical structure begins to appear. Notably, argument mapping can aid the visual representation of this hierarchical structure and is supported by research as having positive effects on critical thinking (Butchart et al., 2009; Dwyer, 2011; Dwyer, Hogan & Stewart, 2012; van Gelder, Bisset & Cumming, 2004).

2. Evaluation

Evaluation is a core CT skill that is used in the assessment of propositions and claims (identified through the previous analysis ) with respect to their credibility; relevance; balance, bias (and potential omissions); as well as the logical strength amongst propositions (i.e. the strength of the inferential relationships). Such assessment allows for informed judgment regarding the overall strength or weakness of an argument (Dwyer, 2017; Facione, 1990). If an argument (or its propositions) is not credible, relevant, logical, and unbiased, you should consider excluding it or discussing its weaknesses as an objection.

Evaluating the credibility of claims and arguments involves progressing beyond merely identifying the source of propositions in an argument, to actually examining the "trustworthiness" of those identified sources (e.g. personal experiences, common beliefs/opinions, expert/authority opinion and scientific evidence). This is particularly important because some sources are more credible than others. Evaluation also implies deep consideration of the relevance of claims within an argument, which is accomplished by assessing the contextual relevance of claims and premises—that is, the pertinence or applicability of one proposition to another.

With respect to balance, bias (and potential omissions), it's important to consider the "slant" of an argument—if it seems imbalanced in favour of one line of thinking, then it’s quite possible that the argument has omitted key, opposing points that should also be considered. Imbalance may also imply some level of bias in the argument—another factor that should also be assessed.

critical thinking used in psychology

However, just because an argument is balanced does not mean that it isn’t biased. It may very well be the case that the "opposing views" presented have been "cherry-picked" because they are easily disputed (akin to building a strawman ); thus, making supporting reasons appear stronger than they may actually be—and this is just one example of how a balanced argument may, in fact, be biased. The take-home message regarding balance, bias, and potential omissions should be that, in any argument, you should construct an understanding of the author or speaker’s motivations and consider how these might influence the structure and contents of the argument.

Finally, evaluating the logical strength of an argument is accomplished through monitoring both the logical relationships amongst propositions and the claims they infer. Assessment of logical strength can actually be aided through subsequent inference, as a means of double-checking the logical strength. For example, this can be checked by asking whether or not a particular proposition can actually be inferred based on the propositions that precede it. A useful means of developing this sub-skill is through practicing syllogistic reasoning .

3. Inference

Similar to other educational concepts like synthesis (e.g., see Bloom et al., 1956; Dwyer, 2011; 2017), the final core CT skill, inference , involves the “gathering” of credible, relevant and logical evidence based on the previous analysis and evaluation, for the purpose of drawing a reasonable conclusion (Dwyer, 2017; Facione, 1990). Drawing a conclusion always implies some act of synthesis (i.e. the ability to put parts of information together to form a new whole; see Dwyer, 2011). However, inference is a unique form of synthesis in that it involves the formulation of a set of conclusions derived from a series of arguments or a body of evidence. This inference may imply accepting a conclusion pointed to by an author in light of the evidence they present, or "conjecturing an alternative," equally logical, conclusion or argument based on the available evidence (Facione, 1990). The ability to infer a conclusion in this manner can be completed through formal logic strategies, informal logic strategies (or both) in order to derive intermediate conclusions, as well as central claims.

Another important aspect of inference involves the querying of available evidence, for example, by recognising the need for additional information, gathering it and judging the plausibility of utilising such information for the purpose of drawing a conclusion. Notably, in the context of querying evidence and conjecturing alternative conclusions, inference overlaps with evaluation to a certain degree in that both skills are used to judge the relevance and acceptability of a claim or argument. Furthermore, after inferring a conclusion, the resulting argument should be re-evaluated to ensure that it is reasonable to draw the conclusion that was derived.

Overall, the application of critical thinking skills is a process—one must analyse, evaluate and then infer; and this process can be repeated to ensure that a reasonable conclusion has been drawn. In an effort to simplify the description of this process, for the past few years, I’ve used the analogy of picking apples for baking . We begin by picking apples from a tree. Consider the tree as an analogy, in its own right, for an argument, which is often hierarchically structured like a tree-diagram. By picking apples, I mean identifying propositions and the role they play (i.e. analysis). Once we pick an apple, we evaluate it—we make sure it isn’t rotten (i.e. lacks credibility, is biased) and is suitable for baking (i.e. relevant and logically strong). Finally, we infer— we gather the apples in a basket and bring them home and group them together based on some rationale for construction— maybe four for a pie, three for a crumble and another four for a tart. By the end of the process, we have baked some apple-based goods, or developed a conclusion, solution or decision through critical thinking.

Of course, there is more to critical thinking than the application of skills—a critical thinker must also have the disposition to think critically and engage reflective judgment. However, without the appropriate skills—analysis, evaluation, and inference, it is not likely that CT will be applied. For example, though one might be willing to use CT skills and engage reflective judgment, they may not know how to do so. Conversely, though one might be aware of which CT skills to use in a given context and may have the capacity to perform well when using these skills, they may not be disposed to use them (Valenzuela, Nieto & Saiz, 2011). Though the core CT skills of analysis, evaluation, and inference are not the only important aspects of CT, they are essential for its application.

Bloom, B.S. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook 1: Cognitive domain. New York: McKay.

Butchart, S., Bigelow, J., Oppy, G., Korb, K., & Gold, I. (2009). Improving critical thinking using web-based argument mapping exercises with automated feedback. Australasian Journal of Educational Technology, 25, 2, 268-291.

Dwyer, C.P. (2011). The evaluation of argument mapping as a learning tool. Doctoral Thesis. National University of Ireland, Galway.

Dwyer, C.P. (2017). Critical thinking: Conceptual perspectives and practical guidelines.Cambridge, UK: Cambridge University Press.

Dwyer, C.P., Hogan, M.J., & Stewart, I. (2012). An evaluation of argument mapping as a method of enhancing critical thinking performance in e-learning environments. Metacognition and Learning, 7, 219-244.

Dwyer, C. P., Hogan, M. J., & Stewart, I. (2014). An integrated critical thinking framework for the 21st century. Thinking Skills & Creativity, 12, 43–52.

Facione, P.A. (1990). The Delphi report: Committee on pre-college philosophy. Millbrae, CA: California Academic Press.

Facione, P.A., Facione, N.C., & Giancarlo, C.A. (1997). Setting expectations for student learning: New directions for higher education. Millbrae: California Academic Press.

Halpern, D.F. (2014). Thought & knowledge: An introduction to critical thinking (5th Ed.). UK: Psychology Press.

King, P. M., & Kitchener, K. S. (1994). Developing reflective judgment: Understanding and promoting intellectual growth and critical thinking in adolescents and adults. San Francisco: Jossey Bass.

Ku, K.Y.L. (2009). Assessing students’ critical thinking performance: Urging for measurements using multi-response format. Thinking Skills and Creativity, 4, 1, 70- 76.

Norris, S. P. (Ed.). (1992). The generalizability of critical thinking: Multiple perspectives on an educational ideal. New York: Teachers College Press.

Siegel, H. (1999). What (good) are thinking dispositions? Educational Theory, 49, 2, 207-221.

Valenzuela, J., Nieto, A.M., & Saiz, C. (2011). Critical thinking motivational scale: A contribution to the study of relationship between critical thinking and motivation. Journal of Research in Educational Psychology, 9, 2, 823-848.

van Gelder, T.J., Bissett, M., & Cumming, G. (2004). Enhancing expertise in informal reasoning. Canadian Journal of Experimental Psychology 58, 142-52.

Christopher Dwyer Ph.D.

Christopher Dwyer, Ph.D., is a lecturer at the Technological University of the Shannon in Athlone, Ireland.

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41+ Critical Thinking Examples (Definition + Practices)

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Critical thinking is an essential skill in our information-overloaded world, where figuring out what is fact and fiction has become increasingly challenging.

But why is critical thinking essential? Put, critical thinking empowers us to make better decisions, challenge and validate our beliefs and assumptions, and understand and interact with the world more effectively and meaningfully.

Critical thinking is like using your brain's "superpowers" to make smart choices. Whether it's picking the right insurance, deciding what to do in a job, or discussing topics in school, thinking deeply helps a lot. In the next parts, we'll share real-life examples of when this superpower comes in handy and give you some fun exercises to practice it.

Critical Thinking Process Outline

a woman thinking

Critical thinking means thinking clearly and fairly without letting personal feelings get in the way. It's like being a detective, trying to solve a mystery by using clues and thinking hard about them.

It isn't always easy to think critically, as it can take a pretty smart person to see some of the questions that aren't being answered in a certain situation. But, we can train our brains to think more like puzzle solvers, which can help develop our critical thinking skills.

Here's what it looks like step by step:

Spotting the Problem: It's like discovering a puzzle to solve. You see that there's something you need to figure out or decide.

Collecting Clues: Now, you need to gather information. Maybe you read about it, watch a video, talk to people, or do some research. It's like getting all the pieces to solve your puzzle.

Breaking It Down: This is where you look at all your clues and try to see how they fit together. You're asking questions like: Why did this happen? What could happen next?

Checking Your Clues: You want to make sure your information is good. This means seeing if what you found out is true and if you can trust where it came from.

Making a Guess: After looking at all your clues, you think about what they mean and come up with an answer. This answer is like your best guess based on what you know.

Explaining Your Thoughts: Now, you tell others how you solved the puzzle. You explain how you thought about it and how you answered. 

Checking Your Work: This is like looking back and seeing if you missed anything. Did you make any mistakes? Did you let any personal feelings get in the way? This step helps make sure your thinking is clear and fair.

And remember, you might sometimes need to go back and redo some steps if you discover something new. If you realize you missed an important clue, you might have to go back and collect more information.

Critical Thinking Methods

Just like doing push-ups or running helps our bodies get stronger, there are special exercises that help our brains think better. These brain workouts push us to think harder, look at things closely, and ask many questions.

It's not always about finding the "right" answer. Instead, it's about the journey of thinking and asking "why" or "how." Doing these exercises often helps us become better thinkers and makes us curious to know more about the world.

Now, let's look at some brain workouts to help us think better:

1. "What If" Scenarios

Imagine crazy things happening, like, "What if there was no internet for a month? What would we do?" These games help us think of new and different ideas.

Pick a hot topic. Argue one side of it and then try arguing the opposite. This makes us see different viewpoints and think deeply about a topic.

3. Analyze Visual Data

Check out charts or pictures with lots of numbers and info but no explanations. What story are they telling? This helps us get better at understanding information just by looking at it.

4. Mind Mapping

Write an idea in the center and then draw lines to related ideas. It's like making a map of your thoughts. This helps us see how everything is connected.

There's lots of mind-mapping software , but it's also nice to do this by hand.

5. Weekly Diary

Every week, write about what happened, the choices you made, and what you learned. Writing helps us think about our actions and how we can do better.

6. Evaluating Information Sources

Collect stories or articles about one topic from newspapers or blogs. Which ones are trustworthy? Which ones might be a little biased? This teaches us to be smart about where we get our info.

There are many resources to help you determine if information sources are factual or not.

7. Socratic Questioning

This way of thinking is called the Socrates Method, named after an old-time thinker from Greece. It's about asking lots of questions to understand a topic. You can do this by yourself or chat with a friend.

Start with a Big Question:

"What does 'success' mean?"

Dive Deeper with More Questions:

"Why do you think of success that way?" "Do TV shows, friends, or family make you think that?" "Does everyone think about success the same way?"

"Can someone be a winner even if they aren't rich or famous?" "Can someone feel like they didn't succeed, even if everyone else thinks they did?"

Look for Real-life Examples:

"Who is someone you think is successful? Why?" "Was there a time you felt like a winner? What happened?"

Think About Other People's Views:

"How might a person from another country think about success?" "Does the idea of success change as we grow up or as our life changes?"

Think About What It Means:

"How does your idea of success shape what you want in life?" "Are there problems with only wanting to be rich or famous?"

Look Back and Think:

"After talking about this, did your idea of success change? How?" "Did you learn something new about what success means?"

socratic dialogue statues

8. Six Thinking Hats 

Edward de Bono came up with a cool way to solve problems by thinking in six different ways, like wearing different colored hats. You can do this independently, but it might be more effective in a group so everyone can have a different hat color. Each color has its way of thinking:

White Hat (Facts): Just the facts! Ask, "What do we know? What do we need to find out?"

Red Hat (Feelings): Talk about feelings. Ask, "How do I feel about this?"

Black Hat (Careful Thinking): Be cautious. Ask, "What could go wrong?"

Yellow Hat (Positive Thinking): Look on the bright side. Ask, "What's good about this?"

Green Hat (Creative Thinking): Think of new ideas. Ask, "What's another way to look at this?"

Blue Hat (Planning): Organize the talk. Ask, "What should we do next?"

When using this method with a group:

  • Explain all the hats.
  • Decide which hat to wear first.
  • Make sure everyone switches hats at the same time.
  • Finish with the Blue Hat to plan the next steps.

9. SWOT Analysis

SWOT Analysis is like a game plan for businesses to know where they stand and where they should go. "SWOT" stands for Strengths, Weaknesses, Opportunities, and Threats.

There are a lot of SWOT templates out there for how to do this visually, but you can also think it through. It doesn't just apply to businesses but can be a good way to decide if a project you're working on is working.

Strengths: What's working well? Ask, "What are we good at?"

Weaknesses: Where can we do better? Ask, "Where can we improve?"

Opportunities: What good things might come our way? Ask, "What chances can we grab?"

Threats: What challenges might we face? Ask, "What might make things tough for us?"

Steps to do a SWOT Analysis:

  • Goal: Decide what you want to find out.
  • Research: Learn about your business and the world around it.
  • Brainstorm: Get a group and think together. Talk about strengths, weaknesses, opportunities, and threats.
  • Pick the Most Important Points: Some things might be more urgent or important than others.
  • Make a Plan: Decide what to do based on your SWOT list.
  • Check Again Later: Things change, so look at your SWOT again after a while to update it.

Now that you have a few tools for thinking critically, let’s get into some specific examples.

Everyday Examples

Life is a series of decisions. From the moment we wake up, we're faced with choices – some trivial, like choosing a breakfast cereal, and some more significant, like buying a home or confronting an ethical dilemma at work. While it might seem that these decisions are disparate, they all benefit from the application of critical thinking.

10. Deciding to buy something

Imagine you want a new phone. Don't just buy it because the ad looks cool. Think about what you need in a phone. Look up different phones and see what people say about them. Choose the one that's the best deal for what you want.

11. Deciding what is true

There's a lot of news everywhere. Don't believe everything right away. Think about why someone might be telling you this. Check if what you're reading or watching is true. Make up your mind after you've looked into it.

12. Deciding when you’re wrong

Sometimes, friends can have disagreements. Don't just get mad right away. Try to see where they're coming from. Talk about what's going on. Find a way to fix the problem that's fair for everyone.

13. Deciding what to eat

There's always a new diet or exercise that's popular. Don't just follow it because it's trendy. Find out if it's good for you. Ask someone who knows, like a doctor. Make choices that make you feel good and stay healthy.

14. Deciding what to do today

Everyone is busy with school, chores, and hobbies. Make a list of things you need to do. Decide which ones are most important. Plan your day so you can get things done and still have fun.

15. Making Tough Choices

Sometimes, it's hard to know what's right. Think about how each choice will affect you and others. Talk to people you trust about it. Choose what feels right in your heart and is fair to others.

16. Planning for the Future

Big decisions, like where to go to school, can be tricky. Think about what you want in the future. Look at the good and bad of each choice. Talk to people who know about it. Pick what feels best for your dreams and goals.

choosing a house

Job Examples

17. solving problems.

Workers brainstorm ways to fix a machine quickly without making things worse when a machine breaks at a factory.

18. Decision Making

A store manager decides which products to order more of based on what's selling best.

19. Setting Goals

A team leader helps their team decide what tasks are most important to finish this month and which can wait.

20. Evaluating Ideas

At a team meeting, everyone shares ideas for a new project. The group discusses each idea's pros and cons before picking one.

21. Handling Conflict

Two workers disagree on how to do a job. Instead of arguing, they talk calmly, listen to each other, and find a solution they both like.

22. Improving Processes

A cashier thinks of a faster way to ring up items so customers don't have to wait as long.

23. Asking Questions

Before starting a big task, an employee asks for clear instructions and checks if they have the necessary tools.

24. Checking Facts

Before presenting a report, someone double-checks all their information to make sure there are no mistakes.

25. Planning for the Future

A business owner thinks about what might happen in the next few years, like new competitors or changes in what customers want, and makes plans based on those thoughts.

26. Understanding Perspectives

A team is designing a new toy. They think about what kids and parents would both like instead of just what they think is fun.

School Examples

27. researching a topic.

For a history project, a student looks up different sources to understand an event from multiple viewpoints.

28. Debating an Issue

In a class discussion, students pick sides on a topic, like school uniforms, and share reasons to support their views.

29. Evaluating Sources

While writing an essay, a student checks if the information from a website is trustworthy or might be biased.

30. Problem Solving in Math

When stuck on a tricky math problem, a student tries different methods to find the answer instead of giving up.

31. Analyzing Literature

In English class, students discuss why a character in a book made certain choices and what those decisions reveal about them.

32. Testing a Hypothesis

For a science experiment, students guess what will happen and then conduct tests to see if they're right or wrong.

33. Giving Peer Feedback

After reading a classmate's essay, a student offers suggestions for improving it.

34. Questioning Assumptions

In a geography lesson, students consider why certain countries are called "developed" and what that label means.

35. Designing a Study

For a psychology project, students plan an experiment to understand how people's memories work and think of ways to ensure accurate results.

36. Interpreting Data

In a science class, students look at charts and graphs from a study, then discuss what the information tells them and if there are any patterns.

Critical Thinking Puzzles

critical thinking tree

Not all scenarios will have a single correct answer that can be figured out by thinking critically. Sometimes we have to think critically about ethical choices or moral behaviors. 

Here are some mind games and scenarios you can solve using critical thinking. You can see the solution(s) at the end of the post.

37. The Farmer, Fox, Chicken, and Grain Problem

A farmer is at a riverbank with a fox, a chicken, and a grain bag. He needs to get all three items across the river. However, his boat can only carry himself and one of the three items at a time. 

Here's the challenge:

  • If the fox is left alone with the chicken, the fox will eat the chicken.
  • If the chicken is left alone with the grain, the chicken will eat the grain.

How can the farmer get all three items across the river without any item being eaten? 

38. The Rope, Jar, and Pebbles Problem

You are in a room with two long ropes hanging from the ceiling. Each rope is just out of arm's reach from the other, so you can't hold onto one rope and reach the other simultaneously. 

Your task is to tie the two rope ends together, but you can't move the position where they hang from the ceiling.

You are given a jar full of pebbles. How do you complete the task?

39. The Two Guards Problem

Imagine there are two doors. One door leads to certain doom, and the other leads to freedom. You don't know which is which.

In front of each door stands a guard. One guard always tells the truth. The other guard always lies. You don't know which guard is which.

You can ask only one question to one of the guards. What question should you ask to find the door that leads to freedom?

40. The Hourglass Problem

You have two hourglasses. One measures 7 minutes when turned over, and the other measures 4 minutes. Using just these hourglasses, how can you time exactly 9 minutes?

41. The Lifeboat Dilemma

Imagine you're on a ship that's sinking. You get on a lifeboat, but it's already too full and might flip over. 

Nearby in the water, five people are struggling: a scientist close to finding a cure for a sickness, an old couple who've been together for a long time, a mom with three kids waiting at home, and a tired teenager who helped save others but is now in danger. 

You can only save one person without making the boat flip. Who would you choose?

42. The Tech Dilemma

You work at a tech company and help make a computer program to help small businesses. You're almost ready to share it with everyone, but you find out there might be a small chance it has a problem that could show users' private info. 

If you decide to fix it, you must wait two more months before sharing it. But your bosses want you to share it now. What would you do?

43. The History Mystery

Dr. Amelia is a history expert. She's studying where a group of people traveled long ago. She reads old letters and documents to learn about it. But she finds some letters that tell a different story than what most people believe. 

If she says this new story is true, it could change what people learn in school and what they think about history. What should she do?

The Role of Bias in Critical Thinking

Have you ever decided you don’t like someone before you even know them? Or maybe someone shared an idea with you that you immediately loved without even knowing all the details. 

This experience is called bias, which occurs when you like or dislike something or someone without a good reason or knowing why. It can also take shape in certain reactions to situations, like a habit or instinct. 

Bias comes from our own experiences, what friends or family tell us, or even things we are born believing. Sometimes, bias can help us stay safe, but other times it stops us from seeing the truth.

Not all bias is bad. Bias can be a mechanism for assessing our potential safety in a new situation. If we are biased to think that anything long, thin, and curled up is a snake, we might assume the rope is something to be afraid of before we know it is just a rope.

While bias might serve us in some situations (like jumping out of the way of an actual snake before we have time to process that we need to be jumping out of the way), it often harms our ability to think critically.

How Bias Gets in the Way of Good Thinking

Selective Perception: We only notice things that match our ideas and ignore the rest. 

It's like only picking red candies from a mixed bowl because you think they taste the best, but they taste the same as every other candy in the bowl. It could also be when we see all the signs that our partner is cheating on us but choose to ignore them because we are happy the way we are (or at least, we think we are).

Agreeing with Yourself: This is called “ confirmation bias ” when we only listen to ideas that match our own and seek, interpret, and remember information in a way that confirms what we already think we know or believe. 

An example is when someone wants to know if it is safe to vaccinate their children but already believes that vaccines are not safe, so they only look for information supporting the idea that vaccines are bad.

Thinking We Know It All: Similar to confirmation bias, this is called “overconfidence bias.” Sometimes we think our ideas are the best and don't listen to others. This can stop us from learning.

Have you ever met someone who you consider a “know it”? Probably, they have a lot of overconfidence bias because while they may know many things accurately, they can’t know everything. Still, if they act like they do, they show overconfidence bias.

There's a weird kind of bias similar to this called the Dunning Kruger Effect, and that is when someone is bad at what they do, but they believe and act like they are the best .

Following the Crowd: This is formally called “groupthink”. It's hard to speak up with a different idea if everyone agrees. But this can lead to mistakes.

An example of this we’ve all likely seen is the cool clique in primary school. There is usually one person that is the head of the group, the “coolest kid in school”, and everyone listens to them and does what they want, even if they don’t think it’s a good idea.

How to Overcome Biases

Here are a few ways to learn to think better, free from our biases (or at least aware of them!).

Know Your Biases: Realize that everyone has biases. If we know about them, we can think better.

Listen to Different People: Talking to different kinds of people can give us new ideas.

Ask Why: Always ask yourself why you believe something. Is it true, or is it just a bias?

Understand Others: Try to think about how others feel. It helps you see things in new ways.

Keep Learning: Always be curious and open to new information.

city in a globe connection

In today's world, everything changes fast, and there's so much information everywhere. This makes critical thinking super important. It helps us distinguish between what's real and what's made up. It also helps us make good choices. But thinking this way can be tough sometimes because of biases. These are like sneaky thoughts that can trick us. The good news is we can learn to see them and think better.

There are cool tools and ways we've talked about, like the "Socratic Questioning" method and the "Six Thinking Hats." These tools help us get better at thinking. These thinking skills can also help us in school, work, and everyday life.

We’ve also looked at specific scenarios where critical thinking would be helpful, such as deciding what diet to follow and checking facts.

Thinking isn't just a skill—it's a special talent we improve over time. Working on it lets us see things more clearly and understand the world better. So, keep practicing and asking questions! It'll make you a smarter thinker and help you see the world differently.

Critical Thinking Puzzles (Solutions)

The farmer, fox, chicken, and grain problem.

  • The farmer first takes the chicken across the river and leaves it on the other side.
  • He returns to the original side and takes the fox across the river.
  • After leaving the fox on the other side, he returns the chicken to the starting side.
  • He leaves the chicken on the starting side and takes the grain bag across the river.
  • He leaves the grain with the fox on the other side and returns to get the chicken.
  • The farmer takes the chicken across, and now all three items -- the fox, the chicken, and the grain -- are safely on the other side of the river.

The Rope, Jar, and Pebbles Problem

  • Take one rope and tie the jar of pebbles to its end.
  • Swing the rope with the jar in a pendulum motion.
  • While the rope is swinging, grab the other rope and wait.
  • As the swinging rope comes back within reach due to its pendulum motion, grab it.
  • With both ropes within reach, untie the jar and tie the rope ends together.

The Two Guards Problem

The question is, "What would the other guard say is the door to doom?" Then choose the opposite door.

The Hourglass Problem

  • Start both hourglasses. 
  • When the 4-minute hourglass runs out, turn it over.
  • When the 7-minute hourglass runs out, the 4-minute hourglass will have been running for 3 minutes. Turn the 7-minute hourglass over. 
  • When the 4-minute hourglass runs out for the second time (a total of 8 minutes have passed), the 7-minute hourglass will run for 1 minute. Turn the 7-minute hourglass again for 1 minute to empty the hourglass (a total of 9 minutes passed).

The Boat and Weights Problem

Take the cat over first and leave it on the other side. Then, return and take the fish across next. When you get there, take the cat back with you. Leave the cat on the starting side and take the cat food across. Lastly, return to get the cat and bring it to the other side.

The Lifeboat Dilemma

There isn’t one correct answer to this problem. Here are some elements to consider:

  • Moral Principles: What values guide your decision? Is it the potential greater good for humanity (the scientist)? What is the value of long-standing love and commitment (the elderly couple)? What is the future of young children who depend on their mothers? Or the selfless bravery of the teenager?
  • Future Implications: Consider the future consequences of each choice. Saving the scientist might benefit millions in the future, but what moral message does it send about the value of individual lives?
  • Emotional vs. Logical Thinking: While it's essential to engage empathy, it's also crucial not to let emotions cloud judgment entirely. For instance, while the teenager's bravery is commendable, does it make him more deserving of a spot on the boat than the others?
  • Acknowledging Uncertainty: The scientist claims to be close to a significant breakthrough, but there's no certainty. How does this uncertainty factor into your decision?
  • Personal Bias: Recognize and challenge any personal biases, such as biases towards age, profession, or familial status.

The Tech Dilemma

Again, there isn’t one correct answer to this problem. Here are some elements to consider:

  • Evaluate the Risk: How severe is the potential vulnerability? Can it be easily exploited, or would it require significant expertise? Even if the circumstances are rare, what would be the consequences if the vulnerability were exploited?
  • Stakeholder Considerations: Different stakeholders will have different priorities. Upper management might prioritize financial projections, the marketing team might be concerned about the product's reputation, and customers might prioritize the security of their data. How do you balance these competing interests?
  • Short-Term vs. Long-Term Implications: While launching on time could meet immediate financial goals, consider the potential long-term damage to the company's reputation if the vulnerability is exploited. Would the short-term gains be worth the potential long-term costs?
  • Ethical Implications : Beyond the financial and reputational aspects, there's an ethical dimension to consider. Is it right to release a product with a known vulnerability, even if the chances of it being exploited are low?
  • Seek External Input: Consulting with cybersecurity experts outside your company might be beneficial. They could provide a more objective risk assessment and potential mitigation strategies.
  • Communication: How will you communicate the decision, whatever it may be, both internally to your team and upper management and externally to your customers and potential users?

The History Mystery

Dr. Amelia should take the following steps:

  • Verify the Letters: Before making any claims, she should check if the letters are actual and not fake. She can do this by seeing when and where they were written and if they match with other things from that time.
  • Get a Second Opinion: It's always good to have someone else look at what you've found. Dr. Amelia could show the letters to other history experts and see their thoughts.
  • Research More: Maybe there are more documents or letters out there that support this new story. Dr. Amelia should keep looking to see if she can find more evidence.
  • Share the Findings: If Dr. Amelia believes the letters are true after all her checks, she should tell others. This can be through books, talks, or articles.
  • Stay Open to Feedback: Some people might agree with Dr. Amelia, and others might not. She should listen to everyone and be ready to learn more or change her mind if new information arises.

Ultimately, Dr. Amelia's job is to find out the truth about history and share it. It's okay if this new truth differs from what people used to believe. History is about learning from the past, no matter the story.

Related posts:

  • Experimenter Bias (Definition + Examples)
  • Hasty Generalization Fallacy (31 Examples + Similar Names)
  • Ad Hoc Fallacy (29 Examples + Other Names)
  • Confirmation Bias (Examples + Definition)
  • Equivocation Fallacy (26 Examples + Description)

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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.

critical thinking used in psychology

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:

critical thinking used in psychology

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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Is critical thinking a superpower in the ai era.

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Critical thinking skills are crucial for AI.

AI, particularly generative AI, is having an immediate and dramatic impact on our lives, both personally and professionally. AI enables everyone to become better writers, content creators, coders, and artists. Interestingly, to derive effective value from AI systems, we must also develop our "soft skills”, of which critical thinking becomes one of the most important.

Just a few years ago, to get real benefit from AI, you needed to build and train AI systems which required “hard” skills such as math, programming, or data engineering skills. Now, because of generative AI, you no longer need to be an expert in statistics & probability, calculus, or linear algebra to get value from using Generative AI. You also don’t need knowledge of different algorithms & modeling skills. Instead, you need to use soft skills such as communication, curiosity, problem solving, adaptability, and critical thinking.

Why Critical Thinking is Crucial for AI

There’s no doubt that in today's fast-paced business environment, workers will need to use AI tools to stay ahead in the market. While AI systems will let anyone get a basic grasp of hard skills, the soft skills are proving to be the most important to get value from AI systems. In particular, the soft skill of critical thinking is proving indispensable. Put simply, critical thinking is the ability to get a solid, reliable, and as truthful as possible understanding of information, and then use that understanding to make sound decisions based on that knowledge. This means scrutinizing information, questioning assumptions, and ensuring that conclusions are supported by solid evidence.

When it comes to using generative AI systems, being able to observe, analyze, discern, and ask the right questions is what not only allows you to get the required results from the AI, but also to determine if the outputs are credible, lack bias, and truthful. Critical thinking approaches provide the necessary mental tools to iteratively refine prompts and hone in to get more effective results. Trying different approaches using thinking skills leads to clearer, more accurate results. The ability to analyze complex requirements helps in designing effective prompts and assessing the quality of AI-generated responses.

How To Develop Critical Thinking Skills

Critical thinking skills will only become more important in our AI-driven organizations. This means that people of all ages will need to make sure to develop and use critical thinking skills to be able to stay ahead of the pack. A key approach to develop and refine critical thinking skills is to always approach interactions with AI systems with a healthy dose of skepticism, and question assumptions, especially your own. Ask yourself whether the information going into and out of AI systems make sense and what assumptions are being made. Look for evidence to support or refute these assumptions.

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Additionally, you’ll want to seek evidence. It goes without saying that especially in an AI-generated world, you can’t take what you see, hear, or read at face value. Large language models are known to hallucinate, or confidently provide you with the wrong information. Verify the sources of your information and ensure that your conclusions are backed by solid proof, research, or findings, and dive deeper to find supporting evidence.

Critical thinking also requires you to be aware of potential informational and data biases. Those biases could be represented in your thinking, data, analyses, outputs of LLM systems, or the way in which you utilize or scrutinize AI outputs. Work to observe and identify patterns and trends in data. This involves not just looking at the data, but understanding the context and relationships between different variables.

Key Benefits Of Critical Thinking in an AI-Centric World

As you continue to work on your critical thinking skills, you’ll see many key benefits, especially as more people make use of AI to augment or assist their work. Professionals are often required to make decisions based on various data points and pieces of information. Critical thinking enables you to sift through the mountains of AI-generated information, identify what is relevant, and then make decisions based on accurate interpretations. This is especially the case with generative AI. Without critical thinking, there is a risk of making decisions based on incomplete or incorrect information, which can lead to erroneous, suboptimal, or misleading results.

A key to critical thinking is problem solving skills. Critical thinking helps professionals approach problems systematically, considering all possible solutions and their implications before making decisions. This thorough approach reduces the likelihood of overlooking important factors and increases the chances of finding effective solutions. It also helps you become a better prompt engineer as you’ll not stop until you get a satisfactory response. You are able to evaluate complex situations to make informed decisions. This analytical ability helps in designing effective prompts and assessing the quality of AI-generated responses.

Setting Yourself Apart With Critical Thinking

Individuals who excel in critical thinking will stand out when it comes to the use of AI. These individuals can navigate complex information landscapes, create better results and responses from LLMs, make better informed decisions, iterate more effectively to get desired outcomes, and be more effective when it comes to communicating and sharing results.

The ability to critically evaluate and interpret information is a strategic advantage for those who are working with AI systems. As AI becomes an increasing part of our every day business processes, tools, and interactions, those with strong critical thinking abilities will be better equipped to harness AI’s full potential, driving innovation, better insights, and answers.

Kathleen Walch

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Pavlov’s Dogs Experiment and Pavlovian Conditioning Response

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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

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

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Like many great scientific advances, Pavlovian conditioning (aka classical conditioning) was discovered accidentally. Ivan Petrovich Pavlov (1849–1936) was a physiologist, not a psychologist.

During the 1890s, Pavlov researched salivation in dogs in response to being fed. He inserted a small test tube into the cheek of each dog to measure saliva when the dogs were fed (with a powder made from meat).

Pavlov predicted the dogs would salivate in response to the food in front of them, but he noticed that his dogs would begin to salivate whenever they heard the footsteps of his assistant, who was bringing them the food.

When Pavlov discovered that any object or event that the dogs learned to associate with food (such as the lab assistant) would trigger the same response, he realized that he had made an important scientific discovery.

Accordingly, he devoted the rest of his career to studying this type of learning.

Pavlovian Conditioning: Theory of Learning

Pavlov’s theory of learning, known as classical conditioning, or Pavlovian conditioning, posits that behaviors can be learned through the association between different stimuli.

Classical conditioning (later developed by Watson, in 1913) involves learning to associate an unconditioned stimulus that already brings about a particular response (i.e., a reflex) with a new (conditioned) stimulus, so that the new stimulus brings about the same response.

Pavlov developed some rather unfriendly technical terms to describe this process:
  • Neutral Stimulus (NS) : A stimulus that initially does not elicit a particular response or reflex action. In other words, before any conditioning takes place, the neutral stimulus has no effect on the behavior or physiological response of interest. For example, in Pavlov’s experiment, the sound of a metronome was a neutral stimulus initially, as it did not cause the dogs to salivate.
  • Unconditioned Stimulus (UCS): This is a stimulus that naturally and automatically triggers a response without any learning needed. In Pavlov’s experiment, the food was the unconditioned stimulus as it automatically induced salivation in the dogs.
  • Conditioned Stimulus (CS): This is a previously neutral stimulus that, after being repeatedly associated with an unconditioned stimulus, comes to trigger a conditioned response. For instance, in Pavlov’s experiment, the metronome became a conditioned stimulus when the dogs learned to associate it with food.
  • Conditioned Response (CR): This is a learned response to the conditioned stimulus. It typically resembles the unconditioned response but is triggered by the conditioned stimulus instead of the unconditioned stimulus. In Pavlov’s experiment, salivating in response to the metronome was the conditioned response.
  • Unconditioned Response (UR): This is an automatic, innate reaction to an unconditioned stimulus. It does not require any learning. In Pavlov’s experiment, the dogs’ automatic salivation in response to the food is an example of an unconditioned response.

Pavlov’s Dog Experiment

Pavlov (1902) started from the idea that there are some things that a dog does not need to learn. For example, dogs don’t learn to salivate whenever they see food. This reflex is ‘hard-wired’ into the dog.

Pavlov showed that dogs could be conditioned to salivate at the sound of a bell if that sound was repeatedly presented at the same time that they were given food.

Pavlov’s studies of classical conditioning have become famous since his early work between 1890 and 1930. Classical conditioning is “classical” in that it is the first systematic study of the basic laws of learning (also known as conditioning).

Pavlov’s dogs were individually situated in secluded environments, secured within harnesses. A food bowl was positioned before them, and a device was employed to gauge the frequency of their salivary gland secretions.

The data from these measurements were systematically recorded onto a rotating drum, allowing Pavlov to meticulously monitor the rates of salivation throughout the course of the experiments.

First, the dogs were presented with the food, and they salivated. The food was the unconditioned stimulus and salivation was an unconditioned (innate) response. (i.e., a stimulus-response connection that required no learning).

Unconditioned Stimulus (Food) > Unconditioned Response (Salivate)

In his experiment, Pavlov used a metronome as his neutral stimulus. By itself, the metronome did not elicit a response from the dogs. 

Neutral Stimulus (Metronome) > No Response

Next, Pavlov began the conditioning procedure, whereby the clicking metronome was introduced just before he gave food to his dogs. After a number of repeats (trials) of this procedure, he presented the metronome on its own.

As you might expect, the sound of the clicking metronome on its own now caused an increase in salivation.

Conditioned Stimulus (Metronome) > Conditioned Response (Salivate)

So, the dog had learned an association between the metronome and the food, and a new behavior had been learned.

Because this response was learned (or conditioned), it is called a conditioned response (and also known as a Pavlovian response). The neutral stimulus has become a conditioned stimulus.

Pavlovs Dogs Experiment

Temporal contiguity

Pavlov found that for associations to be made, the two stimuli had to be presented close together in time (such as a bell).

He called this the law of temporal contiguity. If the time between the conditioned stimulus (bell) and the unconditioned stimulus (food) is too great, then learning will not occur.

‘Unconditioning’ through experimental extinction

In extinction, the conditioned stimulus (the bell) is repeatedly presented without the unconditioned stimulus (the food).

Over time, the dog stops associating the sound of the bell with the food, and the conditioned response (salivation) weakens and eventually disappears.

In other words, the conditioned response is “unconditioned” or “extinguished.”

Spontaneous recovery

Pavlov noted the occurrence of “spontaneous recovery,” where the conditioned response can briefly reappear when the conditioned stimulus is presented after a rest period, even though the response has been extinguished.

This discovery added to the understanding of conditioning and extinction, indicating that these learned associations, while they can fade, are not completely forgotten.

Generalization

The principle of generalization suggests that after a subject has been conditioned to respond in a certain way to a specific stimulus, the subject will also respond in a similar manner to stimuli that are similar to the original one.

In Pavlov’s famous experiments with dogs, he found that after conditioning dogs to salivate at the sound of a bell (which was paired with food), the dogs would also salivate in response to similar sounds, like a buzzer.

This demonstrated the principle of generalization in classical conditioning.

However, the response tends to be more pronounced when the new stimulus closely resembles the original one used in conditioning.

This relationship between the similarity of the stimulus and the strength of the response is known as the generalization gradient.

This principle has been exemplified in research, including a study conducted by Meulders and colleagues in 2013.

Impact of Pavlov’s Research

Ivan Pavlov’s key contribution to psychology was the discovery of classical conditioning, demonstrating how learned associations between stimuli can influence behavior.

His work laid the foundation for behaviorism, influenced therapeutic techniques, and informed our understanding of learning and memory processes.

Behaviorism: Pavlov’s work laid the foundation for behaviorism , a major school of thought in psychology. The principles of classical conditioning have been used to explain a wide range of behaviors, from phobias to food aversions.

Therapy Techniques: Techniques based on classical conditioning, such as systematic desensitization and exposure therapy , have been developed to treat a variety of psychological disorders, including phobias and post-traumatic stress disorder (PTSD).

In these therapies, a conditioned response (such as fear) can be gradually “unlearned” by changing the association between a specific stimulus and its response.

  • Little Albert Experiment : The Little Albert experiment, conducted by John B. Watson in 1920, demonstrated that emotional responses could be classically conditioned in humans. A young child, “Little Albert,” was conditioned to fear a white rat, which generalized to similar objects. 

Educational Strategies: Educational strategies, like repetitive learning and rote memorization, can be seen as applications of the principles of classical conditioning. The repeated association between stimulus and response can help to reinforce learning.

Marketing and Advertising: Principles from Pavlov’s conditioning experiments are often used in advertising to build brand recognition and positive associations.

For instance, a brand may pair its product with appealing stimuli (like enjoyable music or attractive visuals) to create a positive emotional response in consumers, who then associate the product with it.

Critical Evaluation

Pavlovian conditioning is traditionally described as learning an association between a neutral conditioned stimulus (CS) and an unconditioned stimulus (US), such that the CS comes to elicit a conditioned response (CR). This fits many lab studies but misses the adaptive function of conditioning (Domjan, 2005).

From a functional perspective, conditioning likely evolves to help organisms effectively interact with biologically important unconditioned stimuli (US) in their natural environment.

For conditioning to happen naturally, the conditioned stimulus (CS) can’t be arbitrary, but must have a real ecological relationship to the US as a precursor or feature of the US object.

Pavlovian conditioning prepares organisms for important biological events by conditioning compensatory responses that improve the organism’s ability to cope.

The critical behavior change from conditioning may not be conditioned responses (CRs), but rather conditioned modifications of unconditioned responses (URs) to the US that improve the organism’s interactions with it.

Evidence shows conditioning occurs readily with naturalistic CSs, like tastes before illness, infant cues before nursing, prey sights before attack. This conditioning is more robust and resistant to effects like blocking.

Traditional descriptions of Pavlovian conditioning as simply the acquired ability of one stimulus to evoke the original response to another stimulus paired with it are inadequate and misleading (Rescorla, 1988).

New research shows conditioning is actually about learning relationships between events, which allows organisms to build mental representations of their environment.

Just pairing stimuli together doesn’t necessarily cause conditioning. It depends on whether one stimulus gives information about the other.

Conditioning rapidly encodes relations among a broad range of stimuli, not just between a neutral stimulus and one eliciting a response. The learned associations allow complex representations of the world.

Recently, Honey et al. (2020, 2022) presented simulations using an alternative model called HeiDI that accounts for Rescorla’s findings. HeiDI differs by allowing reciprocal CS-US and US-CS associations. It uses consistent learning rules applied to all stimulus pairs.

The simulations suggest HeiDI explains Rescorla’s results via two mechanisms:

  • Changes in US-CS associations during compound conditioning, allowing greater change in some US-CS links
  • Indirect influences of CS-CS associations enabling compounds to recruit associative strength from absent stimuli

HeiDI integrates various conditioning phenomena and retains key Rescorla-Wagner insights about surprise driving learning. However, it moves beyond the limitations of Rescorla-Wagner by providing a framework to address how learning translates into performance.

HeiDI refers to the authors of the model (Honey, Dwyer, Iliescu) as well as highlighting a key feature of the model – the bidirectional or reciprocal associations it proposes between conditioned stimuli and unconditioned stimuli.

H – Honey (the lead author’s surname), ei – Bidirectional (referring to the reciprocal associations), D – Dwyer (the second author’s surname), I – Iliescu (the third author’s surname).

  • Domjan, M. (2005). Pavlovian conditioning: A functional perspective.  Annu. Rev. Psychol. ,  56 , 179-206.
  • Honey, R.C., Dwyer, D.M., & Iliescu, A.F. (2020a). HeiDI: A model for Pavlovian learning and performance with reciprocal associations. Psychological Review, 127, 829-852.
  • Honey, R. C., Dwyer, D. M., & Iliescu, A. F. (2022). Associative change in Pavlovian conditioning: A reappraisal .  Journal of Experimental Psychology: Animal Learning and Cognition .
  • Meulders A, Vandebroek, N. Vervliet, B. and Vlaeyen, J.W.S. (2013). Generalization Gradients in Cued and Contextual Pain-Related Fear: An Experimental Study in Health Participants .  Frontiers in Human Neuroscience ,  7 (345). 1-12.
  • Pavlov, I. P. (1897/1902). The work of the digestive glands. London: Griffin.
  • Pavlov, I. P. (1928). Lectures on conditioned reflexes . (Translated by W.H. Gantt) London: Allen and Unwin.
  • Pavlov, I. P. (1927). Conditioned Reflexes: An Investigation of the Physiological Activity of the Cerebral Cortex . Translated and edited by Anrep, GV (Oxford University Press, London, 1927).
  • Rescorla, R. A. (1988). Pavlovian conditioning: It’s not what you think it is .  American Psychologist ,  43 (3), 151.
  • Pavlov, I. P. (1955). Selected works . Moscow: Foreign Languages Publishing House.
  • Watson, J.B. (1913). Psychology as the behaviorist Views It. Psychological Review, 20 , 158-177.
  • Watson, J. B., & Rayner, R. (1920). Conditioned emotional reactions.  Journal of experimental psychology ,  3 (1), 1.

Further Reading

  • Logan, C. A. (2002). When scientific knowledge becomes scientific discovery: The disappearance of classical conditioning before Pavlov. Journal of the History of the Behavioral Sciences, 38 (4), 393-403.
  • Learning and Behavior PowerPoint

What was the main point of Ivan Pavlov’s experiment with dogs?

The main point of Ivan Pavlov’s experiment with dogs was to study and demonstrate the concept of classical conditioning.

Pavlov showed that dogs could be conditioned to associate a neutral stimulus (such as a bell) with a reflexive response (such as salivation) by repeatedly pairing the two stimuli together.

This experiment highlighted the learning process through the association of stimuli and laid the foundation for understanding how behaviors can be modified through conditioning.

What is Pavlovian response?

The Pavlovian response, also known as a conditioned response, refers to a learned, automatic, and involuntary response elicited by a previously neutral stimulus through classical conditioning. It is a key concept in Pavlov’s experiments, where dogs learned to salivate in response to a bell.

When did Pavlov discover classical conditioning?

Ivan Pavlov discovered classical conditioning during his dog experiments in the late 1890s and early 1900s. His seminal work on classical conditioning, often called Pavlovian conditioning, laid the foundation for our understanding of associative learning and its role in behavior modification.

pavlovs dogs

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