the view that intelligence is developed by logical thinking reasoning and problem solving approach

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List

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.

• Abrami Philip C., Bernard Robert M., Borokhovski Evgueni, Wade C. Anne, Surkes Michael A., Tamim Rana, Zhang Dai. Instructional interventions affecting critical thinking skills and dispositions: A Stage 1 meta-analysis. Review of Educational Research. 2008; 78 :1102–34. doi: 10.3102/0034654308326084. [ CrossRef ] [ Google Scholar ]
• Abrami Philip C., Bernard Robert M., Borokhovski Evgueni, Waddington David I., Wade C. Anne. Strategies for teaching students to think critically: A meta-analysis. Review of Educational Research. 2015; 85 :275–341. doi: 10.3102/0034654314551063. [ CrossRef ] [ Google Scholar ]
• Burhan Nik Ahmad Sufian, Kurniawan Yohan, Sidek Abdul Halim, Mohamad Mohd Rosli. Crimes and the Bell curve: Th e role of people with high, average, and low intelligence. Intelligence. 2014; 47 :12–22. doi: 10.1016/j.intell.2014.08.005. [ CrossRef ] [ Google Scholar ]
• Butler Heather A., Pentoney Christopher, Bong Maebelle P. Predicting real-world outcomes: Critical thinking ability is a better predictor of life decisions than intelligence. Thinking Skills and Creativity. 2017; 25 :38–46. doi: 10.1016/j.tsc.2017.06.005. [ CrossRef ] [ Google Scholar ]
• Cheng Vincent Chi-Chung, Wong Shuk-Ching, Chuang Vivien Wai-Man, So Simon Yung-Chun, Chen Jonathan Hon-Kwan, Sridhar Sidharth, To Kelvin Kai-Wwang, Chan Jasper Fuk-Wu, Hung Ivan Fan-Ngai, Ho Pak-Leung, et al. The role of community-wide wearing of face mask for control of coronavirus disease 2019 (COVID-19) epidemic due to SARS-CoV-2. Journal of Infectious Disease. 2020; 81 :107–14. doi: 10.1016/j.jinf.2020.04.024. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Chu Derek K., Aki Elie A., Duda Stephanie, Solo Karla, Yaacoub Sally, Schunemann Holger J. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: A system atic review and meta-analysis. Lancet. 2020; 395 :1973–87. doi: 10.1016/S0140-6736(20)31142-9. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Donovan Sarah J., Guss C. Dominick, Naslund Dag. Improving dynamic decision-making through training and self-re flection. Judgment and Decision Making. 2015; 10 :284–95. [ Google Scholar ]
• Drozdick Lisa Whipple, Wahlstrom Dustin, Zhu Jianjun, Weiss Lawrence G. The Wechsler Adult Intelligence Scale—Fourth Edition and the Wechsler Memory Scale—Fourth Edition. In: Flanagan Dawn P., Harrison Patti L., editors. Contemporary Intellectual as Sessment: Theories, Tests, and Issues. The Guilford Press; New York: 2012. pp. 197–223. [ Google Scholar ]
• Gigerenzer Gerd. When all is just a click away: Is critical thinking obsolete in the digital age? In: Sternberg Robert J., Halpern Diane F., editors. Critical Thinking IN Psychology. 2nd ed. Cambridge University Press; Cambridge: 2020. pp. 197–223. [ Google Scholar ]
• Gottfredson Linda S. Why g matters: The complexity of everyday life. Intelligence. 1997; 24 :79–132. doi: 10.1016/S0160-2896(97)90014-3. [ CrossRef ] [ Google Scholar ]
• Grossmann Igor, Varnum Michael E. W., Na Jinkyung, Kitayama Shinobu, Nisbett Richard E. A route to well-being: Intelligence ver sus wise reasoning. Journal of Experimental Psychology: General. 2013; 142 :944–53. doi: 10.1037/a0029560. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Halpern Diane F. Halpern Critical Thinking Assessment. Schuhfried Test Publishers; Modling: 2018. [(accessed on 30 March 2021)]. Available online: www.schuhfried.com [ Google Scholar ]
• Halpern Diane F., Butler Heather A. Is critical thinking a better model of intelligence? In: Sternberg Robert J., editor. The nature of Intelligence. 2nd ed. Cambridge University Press; Cambridge: 2020. pp. 183–96. [ Google Scholar ]
• Halpern Diane F., Dunn Dana S. Thought and Knowledge: An Introduction to Critical Thinking. 6th ed. Taylor & Francis; New York: Forthcoming. in press. [ Google Scholar ]
• Halpern Diane F., Millis Keith, Graesser Arthur, Butler Heather, Forsyth Carol, Cai Zhiqiang. Operation ARA: A computerized learn ing game that teaches critical thinking and scientific reasoning. Thinking Skills and Creativity. 2012; 7 :93–100. doi: 10.1016/j.tsc.2012.03.006. [ CrossRef ] [ Google Scholar ]
• Hart Research Associates [(accessed on 30 March 2021)]; Employers Express Confidence in Colleges and Universities: See College as Worth the Investment, New Research Finds. 2018 Aug 29; Available online: https://hartresearch.com/employers-express-confidence-in-colleges-and-universities-see-college-as-worth-the-investment-new-research-finds/
• Heijltjes Anita, Gog Tamara van, Lippink Jimmie, Paas Fred. Unraveling the effects of critical thinking instructions, practice, and self-explanation on students’ reasoning performance. Instructional Science. 2015; 43 :487–506. doi: 10.1007/s11251-015-9347-8. [ CrossRef ] [ Google Scholar ]
• Holmes Natasha G., Wieman Carl E., Bonn DougA. Teaching critical thinking. Proceedings of the National Academy of Sciences. 2015; 112 :11199–204. doi: 10.1073/pnas.1505329112. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hunter John E., Schmidt Frank L. Intelligence and job performance: Economic and social implications. Psychology, Public Policy, and Law. 1996; 2 :447–72. doi: 10.1037/1076-8971.2.3-4.447. [ CrossRef ] [ Google Scholar ]
• Kozyreva Anastasia, Lewandowsky Stephan, Hertwig Ralph. Citizens versus the internet: Confronting digital challenges with cognitive tools. [(accessed on 30 March 2021)]; Psychological Science in the Public Interest. 2020 21 doi: 10.1177/1529100620946707. Available online: https://www.psychologi calscience.org/publications/confronting-digital-challenges-with-cognitive-tools.html [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kretzschmar Andre, Neubert Jonas C., Wusternberg Sascha, Greiff Samuel. Construct validity of complex problem- solv ing: A comprehensive view on different facts of intelligence and school grades. Intelligence. 2016; 54 :55–69. doi: 10.1016/j.intell.2015.11.004. [ CrossRef ] [ Google Scholar ]
• Lang Jonas W.B., Kell Harrison J. General mental ability and specific abilities: Their relative importance for extrinsic career success. Journal of Applied Psychology. 2020; 105 :1047–61. doi: 10.1037/apl0000472. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Lovelace Berkeley., Jr. Medical Historians Compare the Coronavirus to the 1918 Flu Pandemic: Both Were Highly Political. [(accessed on 30 March 2021)]; CNBC. 2020 Available online: https://www.cnbc.com/2020/09/28/comparing-1918-flu-vs-corona virus.html?fbclid=IwAR1RAVRUOIdN9qqvNnMPimf5Q4XfV-pn_qdC3DwcfnPu9kavwumDI2zq9Xs
• Marr Rhuaridh. Iranian Cleric Claims COVID-19 Vaccine Can Make People Gay. [(accessed on 30 March 2021)]; Metro Weekly. 2021 Available online: https://www.metroweekly.com/2021/02/iranian-cleric-claims-covid-19-vaccine-can-make-people-gay/
• McCabe Kira O., Lubinski David, Benbow Camilla P. Who shines most among the brightest?: A 25-year longitudinal study of elite STEM graduate students. Journal of Personality and Social Psychology. 2020; 119 :390–416. doi: 10.1037/pspp0000239. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mega Emiliano R. COVID Has Killed more than One Million People. How Many more will Die? [(accessed on 30 March 2021)]; Nature. 2020 Available online: https://www.nature.com/articles/d41586-020-02762-y [ PubMed ]
• Nickerson Raymond S. Developing intelligence through instruction. In: Sternberg Robert J., editor. The Cambridge Handbook of Intelligence. 2nd ed. Cambridge University Press; Cambridge: 2020. pp. 205–37. [ Google Scholar ]
• OECD . The Survey of Adult Skills: Reader’s Companion. 3rd ed. OECD Publishing; Paris: 2019. OECD Skills Studies. [ CrossRef ] [ Google Scholar ]
• Smith Matthew. Why won’t Britons Wear Face Masks? [(accessed on 30 March 2021)]; YouGov. 2020 Available online: https://yougov.co.uk/topics/health/articles-reports/2020/07/15/why-wont-britons-wear-face-masks
• Stanovich Keith E. What Intelligence Tests Miss: The Psychology of Rational Thought. Yale University Press; New Haven: 2009. [ Google Scholar ]
• Stanovich Keith E., West Richard F. On the failure of cognitive ability to predict my-side bias and one-sided thinking biases. Thinking & Reasoning. 2008; 14 :129–67. doi: 10.1080/13546780701679764. [ CrossRef ] [ Google Scholar ]
• Stanovich Keith E., West Richard F. What intelligence tests miss. The Psychologist. 2014; 27 :80–83. doi: 10.5840/inquiryctnews201126216. [ CrossRef ] [ Google Scholar ]
• Sternberg Robert J. A theory of adaptive intelligence and its relation to general intelligence. Journal of Intelligence. 2019; 7 :23. doi: 10.3390/jintelligence7040023. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Tang Julian W. COVID-19: Interpreting scientific evidence—Uncertainty, confusion, and delays. BMC Infectious Diseases. 2020; 20 :653. doi: 10.1186/s12879-020-05387-8. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wirthwein Linda, Rost Detlef H. Giftedness and subjective well-being: A study with adults. Learning and Individuals Differences. 2011; 21 :182–86. doi: 10.1016/j.lindif.2011.01.001. [ CrossRef ] [ Google Scholar ]

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2023 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

Theories of Intelligence in Psychology

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

Amy Morin, LCSW, is a psychotherapist and international bestselling author. Her books, including "13 Things Mentally Strong People Don't Do," have been translated into more than 40 languages. Her TEDx talk,  "The Secret of Becoming Mentally Strong," is one of the most viewed talks of all time.

What Is Intelligence?

Other types of intelligence, intelligence (iq) testing, frequently asked questions.

Intelligence is one of the most talked-about subjects in psychology , but no standard definition exists. Some researchers have suggested that intelligence is a single, general ability. Other theories of intelligence hold that intelligence encompasses a range of aptitudes, skills, and talents.

Despite substantial interest in the subject, there still isn't a consensus among experts about the components of intelligence or whether accurate measurements of intelligence are even possible.

Although contemporary definitions of intelligence vary considerably, experts generally agree that intelligence involves mental abilities such as logic, reasoning, problem-solving , and planning. Specifically, current definitions tend to suggest that intelligence is the ability to:

• Learn from experience :   The acquisition , retention, and use of knowledge is an important component of intelligence.
• Recognize problems : To use knowledge, people first must identify the problems it might address.
• Solve problems :   People must then use what they have learned to come up with solutions to problems.

Research on intelligence plays a significant role in many areas including educational program funding, job applicant screening, and testing to identify children who need additional academic help.

Main Theories of Intelligence in Psychology

Given the intense interest in the concept of intelligence, some of the field's greatest minds have explored it from numerous angles. Following are some of the major theories of intelligence that have emerged in the last 100 years.

Major Types of Intelligence Theories

• General intelligence
• Primary mental abilities
• Multiple intelligences
• The triarchic approach to intelligence

General Intelligence

British psychologist Charles Spearman (1863–1945) described the concept of general intelligence , or the "g factor." After using factor analysis to examine mental aptitude tests, Spearman concluded that scores on these tests were remarkably similar.

People who performed well on one cognitive test tended to perform well on other tests, while those who scored badly on one test tended to score badly on others. He concluded that intelligence is a general cognitive ability that researchers can measure and express numerically.

Primary Mental Abilities

Psychologist Louis L. Thurstone (1887–1955) focused on seven primary mental abilities rather than a single, general ability. These include:

• Associative memory : The ability to memorize and recall
• Numerical ability : The ability to solve mathematical problems
• Perceptual speed : The ability to see differences and similarities among objects
• Reasoning : The ability to find rules
• Spatial visualization : The ability to visualize relationships
• Verbal comprehension : The ability to define and understand words
• Word fluency : The ability to produce words rapidly

Multiple Intelligences

Among more recent ideas about intelligence is Howard Gardner's theory of multiple intelligences . He proposed that traditional IQ testing does not fully and accurately depict a person's abilities. He proposed eight different intelligences based on skills and abilities that are valued in various cultures:

• Bodily-kinesthetic intelligence : The ability to control body movements and handle objects skillfully
• Interpersonal intelligence : The capacity to detect and respond appropriately to the moods, motivations, and desires of others
• Intrapersonal intelligence : The capacity to be self-aware and in tune with inner feelings, values, beliefs, and thinking processes
• Logical-mathematical intelligence : The ability to think conceptually and abstractly, and to discern logical or numerical patterns
• Musical intelligence : The ability to produce and appreciate rhythm, pitch, and timbre
• Naturalistic intelligence : The ability to recognize and categorize animals, plants, and other objects in nature
• Verbal-linguistic intelligence : Well-developed verbal skills and sensitivity to the sounds, meanings, and rhythms of words
• Visual-spatial intelligence : The capacity to think in images and visualize accurately and abstractly

What Kind of Intelligence Do You Have?

If you'd like to know more about your intelligence style, try our fast and free quiz to learn more about what makes you tick.

The Triarchic Approach to Intelligence

Psychologist Robert Sternberg defined intelligence as "mental activity directed toward purposive adaptation to, selection, and shaping of real-world environments relevant to one's life."

Although he agreed with Gardner that intelligence is much broader than a single, general ability, he suggested that some of Gardner's types of intelligence are better viewed as individual talents. Sternberg proposed the concept of "successful intelligence," which involves three factors:

• Analytical intelligence : The ability to evaluate information and solve problems
• Creative intelligence : The ability to come up with new ideas
• Practical intelligence : The ability to adapt to a changing environment

Of course, there are many other theories on the types of intelligence humans possess.

Fluid vs. Crystallized Intelligence

Psychologist Raymon Cattell, along with his student John Horn, created the theory of fluid vs. crystallized intelligence . Fluid intelligence involves the ability to solve new problems without relying on knowledge from previous experiences.

According to the theory, a person's fluid intelligence declines as they get older. Crystallized intelligence, on the other hand, increases with age—this type of intelligence is based on concrete facts and experiences.

Emotional Intelligence

Emotional intelligence (sometimes called EQ) refers to a person's ability to regulate emotions, and use their emotions to relate to others. Signs of emotional intelligence include strong self-awareness , empathy , embracing change, and managing emotions in difficult situations.

Efforts to quantify intelligence took a significant leap forward when German psychologist William Stern first coined the term "intelligence quotient" (IQ) in the early 20th century.

Psychologist Alfred Binet developed the very first intelligence tests to help the French government identify schoolchildren who needed extra academic assistance.

Binet was the first to introduce the concept of mental age: a set of abilities that children of a certain age possess.

Since that time, intelligence testing has emerged as a widely used tool that has led to many other tests of skill and aptitude.

However, IQ testing continues to spur debate over its use, cultural biases, influences on intelligence, and even the very way we define intelligence.

How Psychologists and Psychiatrists Measure Intelligence

Experts use a variety of standardized tests to measure intelligence. Some are aptitude tests administered in a group setting such as the Scholastic Assessment Test (SAT) and the American College Test (ACT). Others are IQ tests given to individuals.

IQ test scores average around 100. Most children with intellectual disabilities (85%) score between 55 and 70. Severe disabilities usually correspond to still lower scores.

The following is a brief history of IQ tests as they were developed:

• Binet-Simon intelligence scale : This was the first IQ test ever made, and was developed in 1905 by Alfred Binet and Theodore Simon.
• Stanford-Binet IQ test : This was psychologist Lewis Terman's adaptation of the Binet-Simon test. Scores are based on a person's mental age divided by their chronological age (mental age/chronological age x 100).
• Wechsler Adult Intelligence Scale (WAIS) : This was the first intelligence test for adults, developed by David Wechsler in 1939. It was the first to use standardized normal distribution in scoring and is commonly used today. It is divided into verbal and performance measures. Like most modern tests, it scores on a bell curve.

Other tests that psychologists and psychiatrists use today include the Woodcock-Johnson Tests of Cognitive Abilities, the Kaufman Assessment Battery for Children, the Cognitive Assessment System, and the Differential Ability Scale.

Questions About IQ Testing

The study of the human mind is difficult, in part, because the most important tool in the effort is the same as the subject itself.

As humans, researchers bring not only their knowledge and expertise, but also their biases, experiences, cultural backgrounds, and beliefs to the table; like all scientific experts, they must combat their own humanness to strive for objectivity.

In addition, there's the sheer complexity of the human mind and the challenges in measuring a trait that has so many conflicting definitions and nuances. No single standard for intelligence or its quantification as yet exists.

It's no surprise, then, that important questions about intelligence and IQ testing remain unanswered, at least in part. Some of these include:

• Are intelligence tests biased?
• Is intelligence a single ability, or does it involve multiple skills and abilities?
• Is intelligence inherited, or does the environment play a larger role?
• What do intelligence scores predict, if anything?

To explore these questions, psychologists continue to research the nature, influences, and effects of intelligence. Their ongoing findings resonate across society, from education and the workplace to medical and behavioral diagnostic and therapeutic approaches.

A Word From Verywell

Despite considerable debate, no definitive conceptualization of intelligence has emerged in the field of psychology. Today, psychologists often account for the many theoretical viewpoints when discussing intelligence and acknowledge that the debate is ongoing.

Early theories of intelligence focused on logic, problem-solving abilities, and critical thinking skills. In 1920, Edward Thorndike postulated three kinds of intelligence: social, mechanical, and abstract. Building on this, contemporary theories such as that proposed by Harvard psychologist  Howard Gardner tend to break intelligence into separate categories (e.g., emotional, spatial, etc.).

Emotional intelligence (EI or EQ) is the ability to perceive, control, and evaluate emotions. Some researchers suggest that emotional intelligence can be learned and strengthened; others claim it's an inborn characteristic. Generally, EI is measured by self-report and ability tests.

Fluid intelligence is the ability to apply logic and think flexibly. Raymond Cattell defined fluid intelligence as "the ability to perceive relationships independent of previous specific practice or instruction concerning those relationships."

Intelligence develops and changes throughout life, generally peaking in midlife . A study published in  Psychological Science suggested that certain elements of fluid intelligence peak as late as 40.

Jaarsveld S, Lachmann T. Intelligence and creativity in problem solving: The importance of test features in cognition research .  Front Psychol . 2017;8. doi:10.3389/fpsyg.2017.00134

Spearman C. "General intelligence," objectively determined and measured .  The American Journal of Psychology . 1904;15(2):201. doi:10.2307/1412107

Thurstone LL.  Primary Mental Abilities . Chicago: University of Chicago Press; 1938.

Gardner H. Frames of Mind, The Theory of Multiple Intelligences . Basic Books; 2011.

Sternberg RJ. Beyond IQ, A Triarchic Theory of Human Intelligence . CUP Archive; 1985.

Horn JL, Cattell RB.  Refinement and test of the theory of fluid and crystallized general intelligences .  Journal of Educational Psychology . 1966;57(5):253-270. doi:10.1037/h0023816

Ghisletta P, Rabbitt P, Lunn M, Lindenberger U.  Two thirds of the age-based changes in fluid and crystallized intelligence, perceptual speed, and memory in adulthood are shared .  Intelligence . 2012;40(3):260-268. doi:10.1016/j.intell.2012.02.008

Barbey AK.  Network neuroscience theory of human intelligence .  Trends Cogn Sci (Regul Ed) . 2018;22(1):8-20. doi:10.1016/j.tics.2017.10.001

Drigas AS, Papoutsi C.  A new layered model on emotional intelligence . Behav Sci (Basel). 2018;8(5):45. doi:10.3390/bs8050045

Nicolas S, Andrieu B, Croizet JC, Sanitioso RB, Burman JT. Sick? Or slow? On the origins of intelligence as a psychological object .  Intelligence . 2013;41(5):699-711. doi:10.1016/j.intell.2013.08.006

HealthyChildren.org. Children with intellectual disabilities . American Academy of Pediatrics.

Richardson K, Norgate SH. Does IQ really predict job performance? .  Applied Developmental Science . 2015;19(3):153-169. doi:10.1080/10888691.2014.983635

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

• school Campus Bookshelves
• menu_book Bookshelves
• perm_media Learning Objects
• login Login
• how_to_reg Request Instructor Account
• hub Instructor Commons
• Download Page (PDF)
• Download Full Book (PDF)
• Periodic Table
• Physics Constants
• Scientific Calculator
• Reference & Cite
• Tools expand_more
• Readability

selected template will load here

This action is not available.

6.5: Introduction to Thinking and Intelligence

• Last updated
• Save as PDF
• Page ID 82870

Why is it so difficult to break habits—like reaching for your ringing phone even when you shouldn’t, such as when you’re driving? How does a person who has never seen or touched snow in real life develop an understanding of the concept of snow? How do young children acquire the ability to learn language with no formal instruction? Psychologists who study thinking explore questions like these.

Cognitive psychologists also study intelligence. What is intelligence, and how does it vary from person to person? Are “street smarts” a kind of intelligence, and if so, how do they relate to other types of intelligence? What does an IQ test really measure? These questions and more will be explored in this chapter as you study thinking and intelligence.

In other chapters, we discussed the cognitive processes of perception, learning, and memory. In this chapter, we will focus on high-level cognitive processes. As a part of this discussion, we will consider thinking and briefly explore the development and use of language. We will also discuss problem solving and creativity before ending with a discussion of how intelligence is measured and how our biology and environments interact to affect intelligence. After finishing this chapter, you will have a greater appreciation of the higher-level cognitive processes that contribute to our distinctiveness as a species.

What Is Cognition?

Learning outcomes.

By the end of this section, you will be able to:

• Describe cognition
• Distinguish concepts and prototypes
• Explain the difference between natural and artificial concepts

Imagine all of your thoughts as if they were physical entities, swirling rapidly inside your mind. How is it possible that the brain is able to move from one thought to the next in an organized, orderly fashion? The brain is endlessly perceiving, processing, planning, organizing, and remembering—it is always active. Yet, you don’t notice most of your brain’s activity as you move throughout your daily routine. This is only one facet of the complex processes involved in cognition. Simply put, cognition is thinking, and it encompasses the processes associated with perception, knowledge, problem solving, judgment, language, and memory. Scientists who study cognition are searching for ways to understand how we integrate, organize, and utilize our conscious cognitive experiences without being aware of all of the unconscious work that our brains are doing (for example, Kahneman, 2011).

Upon waking each morning, you begin thinking—contemplating the tasks that you must complete that day. In what order should you run your errands? Should you go to the bank, the cleaners, or the grocery store first? Can you get these things done before you head to class or will they need to wait until school is done? These thoughts are one example of cognition at work. Exceptionally complex, cognition is an essential feature of human consciousness, yet not all aspects of cognition are consciously experienced.

Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem solving, in addition to other cognitive processes. Cognitive psychologists strive to determine and measure different types of intelligence, why some people are better at problem solving than others, and how emotional intelligence affects success in the workplace, among countless other topics. They also sometimes focus on how we organize thoughts and information gathered from our environments into meaningful categories of thought, which will be discussed later.

CONCEPTS AND PROTOTYPES

The human nervous system is capable of handling endless streams of information. The senses serve as the interface between the mind and the external environment, receiving stimuli and translating it into nervous impulses that are transmitted to the brain. The brain then processes this information and uses the relevant pieces to create thoughts, which can then be expressed through language or stored in memory for future use. To make this process more complex, the brain does not gather information from external environments only. When thoughts are formed, the brain also pulls information from emotions and memories ( Figure ). Emotion and memory are powerful influences on both our thoughts and behaviors.

In order to organize this staggering amount of information, the brain has developed a file cabinet of sorts in the mind. The different files stored in the file cabinet are called concepts. Concepts are categories or groupings of linguistic information, images, ideas, or memories, such as life experiences. Concepts are, in many ways, big ideas that are generated by observing details, and categorizing and combining these details into cognitive structures. You use concepts to see the relationships among the different elements of your experiences and to keep the information in your mind organized and accessible.

Concepts are informed by our semantic memory (you learned about this concept when you studied memory) and are present in every aspect of our lives; however, one of the easiest places to notice concepts is inside a classroom, where they are discussed explicitly. When you study United States history, for example, you learn about more than just individual events that have happened in America’s past. You absorb a large quantity of information by listening to and participating in discussions, examining maps, and reading first-hand accounts of people’s lives. Your brain analyzes these details and develops an overall understanding of American history. In the process, your brain gathers details that inform and refine your understanding of related concepts like democracy, power, and freedom.

Concepts can be complex and abstract, like justice, or more concrete, like types of birds. In psychology, for example, Piaget’s stages of development are abstract concepts. Some concepts, like tolerance, are agreed upon by many people, because they have been used in various ways over many years. Other concepts, like the characteristics of your ideal friend or your family’s birthday traditions, are personal and individualized. In this way, concepts touch every aspect of our lives, from our many daily routines to the guiding principles behind the way governments function.

Another technique used by your brain to organize information is the identification of prototypes for the concepts you have developed. A prototype is the best example or representation of a concept. For example, for the category of civil disobedience, your prototype could be Rosa Parks. Her peaceful resistance to segregation on a city bus in Montgomery, Alabama, is a recognizable example of civil disobedience. Or your prototype could be Mohandas Gandhi, sometimes called Mahatma Gandhi (“Mahatma” is an honorific title) ( Figure ).

Mohandas Gandhi served as a nonviolent force for independence for India while simultaneously demanding that Buddhist, Hindu, Muslim, and Christian leaders—both Indian and British—collaborate peacefully. Although he was not always successful in preventing violence around him, his life provides a steadfast example of the civil disobedience prototype (Constitutional Rights Foundation, 2013). Just as concepts can be abstract or concrete, we can make a distinction between concepts that are functions of our direct experience with the world and those that are more artificial in nature.

NATURAL AND ARTIFICIAL CONCEPTS

In psychology, concepts can be divided into two categories, natural and artificial. Natural concepts are created “naturally” through your experiences and can be developed from either direct or indirect experiences. For example, if you live in Essex Junction, Vermont, you have probably had a lot of direct experience with snow. You’ve watched it fall from the sky, you’ve seen lightly falling snow that barely covers the windshield of your car, and you’ve shoveled out 18 inches of fluffy white snow as you’ve thought, “This is perfect for skiing.” You’ve thrown snowballs at your best friend and gone sledding down the steepest hill in town. In short, you know snow. You know what it looks like, smells like, tastes like, and feels like. If, however, you’ve lived your whole life on the island of Saint Vincent in the Caribbean, you may never have actually seen snow, much less tasted, smelled, or touched it. You know snow from the indirect experience of seeing pictures of falling snow—or from watching films that feature snow as part of the setting. Either way, snow is a natural concept because you can construct an understanding of it through direct observations or experiences of snow ( Figure ).

An artificial concept, on the other hand, is a concept that is defined by a specific set of characteristics. Various properties of geometric shapes, like squares and triangles, serve as useful examples of artificial concepts. A triangle always has three angles and three sides. A square always has four equal sides and four right angles. Mathematical formulas, like the equation for area (length × width) are artificial concepts defined by specific sets of characteristics that are always the same. Artificial concepts can enhance the understanding of a topic by building on one another. For example, before learning the concept of “area of a square” (and the formula to find it), you must understand what a square is. Once the concept of “area of a square” is understood, an understanding of area for other geometric shapes can be built upon the original understanding of area. The use of artificial concepts to define an idea is crucial to communicating with others and engaging in complex thought. According to Goldstone and Kersten (2003), concepts act as building blocks and can be connected in countless combinations to create complex thoughts.

A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.

There are several types of schemata. A role schema makes assumptions about how individuals in certain roles will behave (Callero, 1994). For example, imagine you meet someone who introduces himself as a firefighter. When this happens, your brain automatically activates the “firefighter schema” and begins making assumptions that this person is brave, selfless, and community-oriented. Despite not knowing this person, already you have unknowingly made judgments about him. Schemata also help you fill in gaps in the information you receive from the world around you. While schemata allow for more efficient information processing, there can be problems with schemata, regardless of whether they are accurate: Perhaps this particular firefighter is not brave, he just works as a firefighter to pay the bills while studying to become a children’s librarian.

An event schema, also known as a cognitive script, is a set of behaviors that can feel like a routine. Think about what you do when you walk into an elevator ( Figure ). First, the doors open and you wait to let exiting passengers leave the elevator car. Then, you step into the elevator and turn around to face the doors, looking for the correct button to push. You never face the back of the elevator, do you? And when you’re riding in a crowded elevator and you can’t face the front, it feels uncomfortable, doesn’t it? Interestingly, event schemata can vary widely among different cultures and countries. For example, while it is quite common for people to greet one another with a handshake in the United States, in Tibet, you greet someone by sticking your tongue out at them, and in Belize, you bump fists (Cairns Regional Council, n.d.)

Because event schemata are automatic, they can be difficult to change. Imagine that you are driving home from work or school. This event schema involves getting in the car, shutting the door, and buckling your seatbelt before putting the key in the ignition. You might perform this script two or three times each day. As you drive home, you hear your phone’s ring tone. Typically, the event schema that occurs when you hear your phone ringing involves locating the phone and answering it or responding to your latest text message. So without thinking, you reach for your phone, which could be in your pocket, in your bag, or on the passenger seat of the car. This powerful event schema is informed by your pattern of behavior and the pleasurable stimulation that a phone call or text message gives your brain. Because it is a schema, it is extremely challenging for us to stop reaching for the phone, even though we know that we endanger our own lives and the lives of others while we do it (Neyfakh, 2013) ( Figure ).

Remember the elevator? It feels almost impossible to walk in and  not  face the door. Our powerful event schema dictates our behavior in the elevator, and it is no different with our phones. Current research suggests that it is the habit, or event schema, of checking our phones in many different situations that makes refraining from checking them while driving especially difficult (Bayer & Campbell, 2012). Because texting and driving has become a dangerous epidemic in recent years, psychologists are looking at ways to help people interrupt the “phone schema” while driving. Event schemata like these are the reason why many habits are difficult to break once they have been acquired. As we continue to examine thinking, keep in mind how powerful the forces of concepts and schemata are to our understanding of the world.

In this section, you were introduced to cognitive psychology, which is the study of cognition, or the brain’s ability to think, perceive, plan, analyze, and remember. Concepts and their corresponding prototypes help us quickly organize our thinking by creating categories into which we can sort new information. We also develop schemata, which are clusters of related concepts. Some schemata involve routines of thought and behavior, and these help us function properly in various situations without having to “think twice” about them. Schemata show up in social situations and routines of daily behavior.

Review Questions

Cognitive psychology is the branch of psychology that focuses on the study of ________.

• human development
• human thinking
• human behavior
• human society

Which of the following is an example of a prototype for the concept of leadership on an athletic team?

• the equipment manager
• the star player
• the head coach
• the scorekeeper

Which of the following is an example of an artificial concept?

• a triangle’s area

An event schema is also known as a cognitive ________.

Critical Thinking Questions

Describe a social schema that you would notice at a sporting event.

Explain why event schemata have so much power over human behavior.

Personal Application Question

Describe a natural concept that you know fully but that would be difficult for someone else to understand and explain why it would be difficult.

[glossary-page] [glossary-term]artificial concept:[/glossary-term] [glossary-definition]concept that is defined by a very specific set of characteristics[/glossary-definition]

[glossary-term]cognition:[/glossary-term] [glossary-definition]thinking, including perception, learning, problem solving, judgment, and memory[/glossary-definition]

[glossary-term]cognitive psychology:[/glossary-term] [glossary-definition]field of psychology dedicated to studying every aspect of how people think[/glossary-definition]

[glossary-term]concept:[/glossary-term] [glossary-definition]category or grouping of linguistic information, objects, ideas, or life experiences[/glossary-definition]

[glossary-term]cognitive script:[/glossary-term] [glossary-definition]set of behaviors that are performed the same way each time; also referred to as an event schema[/glossary-definition]

[glossary-term]event schema:[/glossary-term] [glossary-definition]set of behaviors that are performed the same way each time; also referred to as a cognitive script[/glossary-definition]

[glossary-term]natural concept:[/glossary-term] [glossary-definition]mental groupings that are created “naturally” through your experiences[/glossary-definition]

[glossary-term]prototype:[/glossary-term] [glossary-definition]best representation of a concept[/glossary-definition]

[glossary-term]role schema:[/glossary-term] [glossary-definition]set of expectations that define the behaviors of a person occupying a particular role[/glossary-definition]

[glossary-term]schema:[/glossary-term] [glossary-definition](plural = schemata) mental construct consisting of a cluster or collection of related concepts[/glossary-definition] [/glossary-page]

• Introduction. Provided by : OpenStax CNX. Located at : https://cnx.org/contents/[email protected]:3DT0XBfK@3/Introduction . License : CC BY-SA: Attribution-ShareAlike
• What is Cognition?. Provided by : OpenStax CNX. Located at : https://cnx.org/contents/[email protected]:u8MlFxBQ@3/What-Is-Cognition . License : CC BY-SA: Attribution-ShareAlike

Howard Gardner’s Theory of Multiple Intelligences

Michele Marenus

Research Scientist

B.A., Psychology, Ed.M., Harvard Graduate School of Education

Michele Marenus is a Ph.D. candidate at the University of Michigan with over seven years of experience in psychology research.

Learn about our Editorial Process

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.

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

On This Page:

Howard Gardner first proposed the theory of multiple intelligences in his 1983 book “Frames of Mind”, where he broadens the definition of intelligence and outlines several distinct types of intellectual competencies.

Gardner developed a series of eight inclusion criteria while evaluating each “candidate” intelligence that was based on a variety of scientific disciplines.

He writes that we may all have these intelligences, but our profile of these intelligences may differ individually based on genetics or experience.

Gardner defines intelligence as a “biopsychological potential to process information that can be activated in a cultural setting to solve problems or create products that are of value in a culture” (Gardner, 2000, p.28).

What is Multiple Intelligences Theory?

• Howard Gardner’s theory of multiple intelligences proposes that people are not born with all of the intelligence they will ever have.
• This theory challenged the traditional notion that there is one single type of intelligence, sometimes known as “g” for general intelligence, that only focuses on cognitive abilities.
• To broaden this notion of intelligence, Gardner introduced eight different types of intelligences consisting of: Linguistic, Logical/Mathematical, Spatial, Bodily-Kinesthetic, Musical, Interpersonal, Intrapersonal, and Naturalist.
• Gardner notes that the linguistic and logical-mathematical modalities are most typed valued in school and society.
• Gardner also suggests that there may other “candidate” intelligences—such as spiritual intelligence, existential intelligence, and moral intelligence—but does not believe these meet his original inclusion criteria. (Gardner, 2011).

Linguistic Intelligence (word smart)

Linguistic Intelligence is a part of Howard Gardner’s multiple intelligence theory that deals with sensitivity to the spoken and written language, ability to learn languages, and capacity to use language to accomplish certain goals.

Linguistic intelligence involves the ability to use language masterfully to express oneself rhetorically or poetically. It includes the ability to manipulate syntax, structure, semantics, and phonology of language.

People with linguistic intelligence, such as William Shakespeare and Oprah Winfrey, have the ability to analyze information and create products involving oral and written language, such as speeches, books, and memos.

Potential Career Choices

Careers you could dominate with your linguistic intelligence:

Lawyer Speaker / Host Author Journalist Curator

Logical-Mathematical Intelligence (number/reasoning smart)

Logical-mathematical intelligence refers to the capacity to analyze problems logically, carry out mathematical operations, and investigate issues scientifically.

Logical-mathematical intelligence involves the ability to use logic, abstractions, reasoning, and critical thinking to solve problems. It includes the capacity to understand the underlying principles of some kind of causal system.

People with logical-mathematical intelligence, such as Albert Einstein and Bill Gates, have an ability to develop equations and proofs, make calculations, and solve abstract problems.

Careers you could dominate with your logical-mathematical intelligence:

Mathematician Accountant Statistician Scientist Computer Analyst

Spatial Intelligence (picture smart)

Spatial intelligence involves the ability to perceive the visual-spatial world accurately. It includes the ability to transform, modify, or manipulate visual information. People with high spatial intelligence are good at visualization, drawing, sense of direction, puzzle building, and reading maps.

Spatial intelligence features the potential to recognize and manipulate the patterns of wide space (those used, for instance, by navigators and pilots) as well as the patterns of more confined areas, such as those of importance to sculptors, surgeons, chess players, graphic artists, or architects.

People with spatial intelligence, such as Frank Lloyd Wright and Amelia Earhart, have the ability to recognize and manipulate large-scale and fine-grained spatial images.

Careers you could dominate with your spatial intelligence:

Pilot Surgeon Architect Graphic Artist Interior Decorator

Bodily-Kinesthetic Intelligence (body smart)

Bodily-kinesthetic intelligence is the potential of using one’s whole body or parts of the body (like the hand or the mouth) to solve problems or to fashion products.

Bodily-kinesthetic intelligence involves using the body with finesse, grace, and skill. It includes physical coordination, balance, dexterity, strength, and flexibility. People with high bodily-kinesthetic intelligence are good at sports, dance, acting, and physical crafts.

People with bodily-kinesthetic intelligence, such as Michael Jordan and Simone Biles, can use one’s own body to create products, perform skills, or solve problems through mind–body union.

Careers you could dominate with your bodily-kinesthetic intelligence:

Dancer Athlete Surgeon Mechanic Carpenter Physical Therapist

Musical Intelligence (music smart)

Musical intelligence refers to the skill in the performance, composition, and appreciation of musical patterns.

Musical intelligence involves the ability to perceive, discriminate, create, and express musical forms. It includes sensitivity to rhythm, pitch, melody, and tone color. People with high musical intelligence are good at singing, playing instruments, and composing music.

People with musical intelligence, such as Beethoven and Ed Sheeran, have the ability to recognize and create musical pitch, rhythm, timbre, and tone.

Careers you could dominate with your musical intelligence:

Singer Composer DJ Musician

Interpersonal Intelligence (people smart)

Interpersonal intelligence is the capacity to understand the intentions, motivations, and desires of other people and, consequently, to work effectively with others.

Interpersonal intelligence involves the ability to understand and interact effectively with others. It includes sensitivity to other people’s moods, temperaments, motivations, and desires. People with high interpersonal intelligence communicate well and can build rapport.

People with interpersonal intelligence, such as Mahatma Gandhi and Mother Teresa, have the ability to recognize and understand other people’s moods, desires, motivations, and intentions.

Careers you could dominate with your interpersonal intelligence:

Teacher Psychologist Manager Salespeople Public Relations

Intrapersonal Intelligence (self-smart)

Intrapersonal intelligence is the capacity to understand oneself, to have an effective working model of oneself, including one’s desires, fears, and capacities—and to use such information effectively in regulating one’s own life.

It includes self-awareness, personal cognizance, and the ability to refine, analyze, and articulate one’s emotional life.

People with intrapersonal intelligence, such as Aristotle and Maya Angelou, have the ability to recognize and understand his or her own moods, desires, motivations, and intentions.

This type of intelligence can help a person understand which life goals are important and how to achieve them.

Careers you could dominate with your intrapersonal intelligence:

Therapist Psychologist Counselor Entrepreneur Clergy

Naturalist intelligence (nature smart)

Naturalist intelligence involves the ability to recognize, categorize, and draw upon patterns in the natural environment. It includes sensitivity to the flora, fauna, and phenomena in nature. People with high naturalist intelligence are good at classifying natural forms.

Naturalistic intelligence involves expertise in recognizing and classifying the numerous species—the flora and fauna—of his or her environment.

People with naturalistic intelligence, such as Charles Darwin and Jane Goddall, have the ability to identify and distinguish among different types of plants, animals, and weather formations that are found in the natural world.

Careers you could dominate with your naturalist intelligence:

Botanist Biologist Astronomer Meteorologist Geologist

Critical Evaluation

Most resistance to multiple intelligences theory has come from cognitive psychologists and psychometricians. Cognitive psychologists such as Waterhouse (2006) claimed that there is no empirical evidence to the validity of the theory of multiple intelligences.

Psychometricians, or psychologists involved in testing, argue that intelligence tests support the concept for a single general intelligence, “g”, rather than the eight distinct competencies (Gottfredson, 2004). Other researchers argue that Gardner’s intelligences comes second or third to the “g” factor (Visser, Ashton, & Vernon, 2006).

Some responses to this criticism include that the multiple intelligences theory doesn’t dispute the existence of the “g” factor; it proposes that it is equal along with the other intelligences. Many critics overlook the inclusion criteria Gardner set forth.

These criteria are strongly supported by empirical evidence in psychology, biology, neuroscience, among others. Gardner admits that traditional psychologists were valid in criticizing the lack of operational definitions for the intelligences, that is, to figure out how to measure and test the various competencies (Davis et al., 2011).

Gardner was surprised to find that Multiple Intelligences theory has been used most widely in educational contexts. He developed this theory to challenge academic psychologists, and therefore, he did not present many educational suggestions. For this reason, teachers and educators were able to take the theory and apply it as they saw fit.

As it gained popularity in this field, Gardner has maintained that practitioners should determine the theory’s best use in classrooms. He has often declined opportunities to aid in curriculum development that uses multiple intelligences theory, opting to only provide feedback at most (Gardner, 2011).

Most of the criticism has come from those removed from the classroom, such as journalists and academics. Educators are not typically tied to the same standard of evidence and are less concerned with abstract inconsistencies, which has given them the freedom to apply it with their students and let the results speak for itself (Armstrong, 2019).

Shearer (2020) provides extensive empirical evidence from neuroscience research supporting MI theory.

Shearer reviewed evidence from over 500 functional neuroimaging studies that associate patterns of brain activation with the cognitive components of each intelligence.

The visual network was associated with the visual-spatial intelligence, somatomotor networks with kinesthetic intelligence, fronto-parietal networks with logical and general intelligence, auditory networks with musical intelligence, and default mode networks with intra- and interpersonal intelligences. The coherence and distinctiveness of these networks provides robust support for the neural validity of MI theory

He concludes that human intelligence is best characterized as being multiple rather than singular, with each person possessing unique neural potentials aligned with specific intelligences.

Implications for Learning

The most important educational implications of the theory of multiple intelligences can be summed up through individuation and pluralization. Individuation posits that because each person differs from other another there is no logical reason to teach and assess students identically.

Individualized education has typically been reserved for the wealthy and others who could afford to hire tutors to address individual student’s needs.

Technology has now made it possible for more people to access a variety of teachings and assessments depending on their needs. Pluralization, the idea that topics and skills should be taught in more than one way, activates an individual’s multiple intelligences.

Presenting a variety of activities and approaches to learning helps reach all students and encourages them to be able to think about the subjects from various perspectives, deepening their knowledge of that topic (Gardner, 2011b).

A common misconception about the theory of multiple intelligences is that it is synonymous with learning styles. Gardner states that learning styles refer to the way an individual is most comfortable approaching a range of tasks and materials.

Multiple intelligences theory states that everyone has all eight intelligences at varying degrees of proficiency and an individual’s learning style is unrelated to the areas in which they are the most intelligent.

For example, someone with linguistic intelligence may not necessarily learn best through writing and reading. Classifying students by their learning styles or intelligences alone may limit their potential for learning.

Research shows that students are more engaged and learn best when they are given various ways to demonstrate their knowledge and skills, which also helps teachers more accurately assess student learning (Darling-Hammond, 2010).

Therapeutic Benefits of Incorporating Multiple Intelligences Within Therapy

Pearson et al. (2015) investigated the experiences of 8 counselors who introduced multiple intelligences (MI) theory and activities into therapy sessions with adult clients. The counselors participated in a 1-day MI training intervention and were interviewed 3 months later about their experiences using MI in practice.

The major themes that emerged from qualitative analysis of the interviews were:

• MI helped enhance therapeutic alliances. Counselors felt incorporating MI strengthened their connections with clients, increased counselor and client comfort, and reduced client suspicion/resistance.
• MI led to more effective professional work. Counselors felt MI provided more tools and flexibility in responding to clients. This matches findings from education research on the benefits of MI.
• Clients responded positively to identifying strengths through MI. The MI survey helped clients recognize talents/abilities, which counselors saw as identity-building. This aligns with the literature on strength-based approaches.
• Clients appreciated the MI preference survey. It provided conversation starters, increased self-reflection, and was sometimes a catalyst for using music therapeutically.
• Counselors felt comfortable with MI. They experienced increased confidence and professional comfort. Counselor confidence contributes to alliance building (Ackerman & Hilsenroth, 2003).
• Music use stood out as impactful. In-session and extratherapeutic music use improved client well-being after identifying musicality through the MI survey. This matches the established benefits of music therapy (Koelsch, 2009).
• MI training opened up therapeutic possibilities. Counselors valued the experiential MI training. MI appeared to expand their skills and activities.

The authors conclude that MI may enhance alliances, effectiveness, and counselor confidence. They recommend further research on long-term impacts and optimal training approaches. Counselor education could teach MI theory, assessment, and tailored interventions.

Frequently Asked Questions

How can understanding the theory of multiple intelligences contribute to self-awareness and personal growth.

Understanding the theory of multiple intelligences can contribute to self-awareness and personal growth by providing a framework for recognizing and valuing different strengths and abilities.

By identifying their own unique mix of intelligences, individuals can gain a greater understanding of their own strengths and limitations and develop a more well-rounded sense of self.

Additionally, recognizing and valuing the diverse strengths and abilities of others can promote empathy , respect, and cooperation in personal and professional relationships.

Why is multiple intelligence theory important?

Understanding multiple intelligences is important because it helps individuals recognize that intelligence is not just about academic achievement or IQ scores, but also includes a range of different abilities and strengths.

By identifying their own unique mix of intelligences, individuals can develop a greater sense of self-awareness and self-esteem, as well as pursue career paths that align with their strengths and interests.

Additionally, understanding multiple intelligences can promote more inclusive and personalized approaches to education and learning that recognize and value the diverse strengths and abilities of all students.

Are certain types of intelligence more valued or prioritized in society than others?

Yes, certain types of intelligence, such as linguistic and logical-mathematical intelligence, are often prioritized in traditional education and assessment methods.

However, the theory of multiple intelligences challenges this narrow definition of intelligence and recognizes the value of a diverse range of strengths and abilities.

By promoting a more inclusive and personalized approach to education and learning, the theory of multiple intelligences can help individuals recognize and develop their unique mix of intelligences, regardless of whether they align with traditional societal expectations.

What is the difference between multiple intelligences and learning styles?

The theory of multiple intelligences proposes that individuals possess a range of different types of intelligence. In contrast, learning styles refer to an individual’s preferred way of processing information, such as visual, auditory, or kinesthetic.

While both theories emphasize the importance of recognizing and valuing individual differences in learning and development, multiple intelligence theory proposes a broader and more diverse range of intelligences beyond traditional academic abilities, while learning styles are focused on preferences for processing information.

Armstrong, T. (2009). Multiple intelligences in the classroom . Ascd.

Darling-Hammond, L. (2010). Performance Counts: Assessment Systems That Support High-Quality Learning . Council of Chief State School Officers .

Davis, K., Christodoulou, J., Seider, S., & Gardner, H. E. (2011). The theory of multiple intelligences.  Davis, K., Christodoulou, J., Seider, S., & Gardner, H.(2011). The theory of multiple intelligences . In RJ Sternberg & SB Kaufman (Eds.), Cambridge Handbook of Intelligence , 485-503.

Edutopia. (2013, March 8). Multiple Intelligences: What Does the Research Say? https://www.edutopia.org/multiple-intelligences-research

Gardner, H. E. (2000). Intelligence reframed: Multiple intelligences for the 21st century . Hachette UK.

Gardner, H. (2011a). Frames of mind: The theory of multiple intelligences . Hachette Uk.

Gardner, H. (2011b). The theory of multiple intelligences: As psychology, as education, as social science. Address delivered at José Cela University on October, 29, 2011.

Gottfredson, L. S. (2004). Schools and the g factor . The Wilson Quarterly (1976-), 28 (3), 35-45.

Pearson, M., O’Brien, P., & Bulsara, C. (2015). A multiple intelligences approach to counseling: Enhancing alliances with a focus on strengths.  Journal of Psychotherapy Integration, 25 (2), 128–142

Shearer, C. B. (2020). A resting state functional connectivity analysis of human intelligence: Broad theoretical and practical implications for multiple intelligences theory.  Psychology & Neuroscience, 13 (2), 127–148.

Visser, B. A., Ashton, M. C., & Vernon, P. A. (2006). Beyond g: Putting multiple intelligences theory to the test . Intelligence, 34 (5), 487-502.

Waterhouse, L. (2006). Inadequate evidence for multiple intelligences, Mozart effect, and emotional intelligence theories . Educational Psychologist, 41 (4), 247-255.

Further Information

• Multiple Intelligences Criticisms
• The Theory of Multiple Intelligences
• Multiple Intelligences FAQ
• “In a Nutshell,” the first chapter of Multiple Intelligences: New Horizons
• Multiple Intelligences After Twenty Years”
• Intelligence: Definition, Theories and Testing
• Fluid vs Crystallized Intelligence

Thinking and Intelligence

Why It Matters: Thinking and Intelligence

Why is it so difficult to break habits—like reaching for your ringing phone even when you shouldn’t, such as when you’re driving? How does a person who has never seen or touched snow in real life develop an understanding of the concept of snow? How do young children acquire the ability to learn language with no formal instruction? Psychologists who study thinking explore questions like these.

Cognitive psychologists also study intelligence. What is intelligence, and how does it vary from person to person? Are “street smarts” a kind of intelligence, and if so, how do they relate to other types of intelligence? What does an IQ test really measure? These questions and more will be explored in this module as you study thinking and intelligence.

As a part of this discussion, we will consider thinking and briefly explore the development and use of language. We will also discuss problem solving and creativity, intelligence testing, and how our biology and environments interact to affect intelligence. After finishing this module, you will have a greater appreciation of the higher-level cognitive processes that contribute to our distinctiveness as a species.

Abler, W. (2013). Sapir, Harris, and Chomsky in the twentieth century. Cognitive Critique, 7, 29–48.

American Association on Intellectual and Developmental Disabilities. (2013). Definition of intellectual disability. Retrieved from http://aaidd.org/intellectual-disability/definition#.UmkR2xD2Bh4

American Psychological Association. (2013). In Diagnostic and statistical manual of psychological disorders (5th ed., pp. 34–36). Washington, D. C.: American Psychological Association.

Aronson, E. (Ed.). (1995). Social cognition. In The social animal (p. 151). New York: W.H. Freeman and Company.

Atkins v. Virginia, 00-8452 (2002).

Bartels, M., Rietveld, M., Van Baal, G., & Boomsma, D. I. (2002). Genetic and environmental influences on the development of intelligence. Behavior Genetics, 32(4), 237–238.

Bartlett, F. C. (1932). Remembering: A study in experimental and social psychology. Cambridge, England: Cambridge University Press.

Bayer, J. B., & Campbell, S. W. (2012). Texting while driving on automatic: Considering the frequency-independent side of habit. Computers in Human Behavior, 28, 2083–2090.

Barton, S. M. (2003). Classroom accommodations for students with dyslexia. Learning Disabilities Journal, 13, 10–14.

Berlin, B., & Kay, P. (1969). Basic color terms: Their universality and evolution. Berkley: University of California Press.

Berninger, V. W. (2008). Defining and differentiating dysgraphia, dyslexia, and language learning disability within a working memory model. In M. Mody & E. R. Silliman (Eds.), Brain, behavior, and learning in language and reading disorders (pp. 103–134). New York: The Guilford Press.

Blossom, M., & Morgan, J. L. (2006). Does the face say what the mouth says? A study of infants’ sensitivity to visual prosody. In the 30th annual Boston University Conference on Language Development, Somerville, MA.

Boake, C. (2002, May 24). From the Binet-Simon to the Wechsler-Bellevue: Tracing the history of intelligence testing. Journal of Clinical and Experimental Neuropsychology, 24(3), 383–405.

Boroditsky, L. (2001). Does language shape thought? Mandarin and English speakers’ conceptions of time. Cognitive Psychology, 43, 1–22.

Boroditsky, L. (2011, February). How language shapes thought. Scientific American, 63–65.Chomsky, N. (1965). Aspects of the theory of syntax. Cambridge, MA: MIT Press

Bouchard, T. J., Lykken, D. T., McGue, M., Segal, N. L., & Tellegen, A. (1990). Sources of human psychological differences: The Minnesota Study of Twins Reared Apart. Science, 250, 223–228.

Cairns Regional Council. (n.d.). Cultural greetings. Retrieved from http://www.cairns.qld.gov.au/__data/assets/pdf_file/0007/8953/CulturalGreetingExercise.pdf

Callero, P. L. (1994). From role-playing to role-using: Understanding role as resource. Social Psychology Quarterly, 57, 228–243.

Cattell, R. (1963). Theory of fluid and crystallized intelligence: A critical experiment. Journal of Educational Psychology, 54(1), 1–22.

Cianciolo, A. T., & Sternberg, R. J. (2004). Intelligence: A brief history. Malden, MA: Blackwell Publishing.

Chomsky, N.(1965). Aspects of the theory of syntax. Cambridge, MA: MIT Press

Corballis, M. C., & Suddendorf, T. (2007). Memory, time, and language. In C. Pasternak (Ed.), What makes us human (pp. 17–36). Oxford, UK: Oneworld Publications.

Constitutional Rights Foundation. (2013). Gandhi and civil disobedience. Retrieved from http://www.crf-usa.org/black-history-month/gandhi-and-civil-disobedience

Cropley, A. (2006). In praise of convergent thinking. Creativity Research Journal, 18(3), 391–404.

Csikszentmihalyi, M., & Csikszentmihalyi, I. (1993). Family influences on the development of giftedness. Ciba Foundation Symposium, 178, 187–206.

Curtiss, S. (1981). Dissociations between language and cognition: Cases and implications. Journal of Autism and Developmental Disorders, 11(1), 15–30.

Cyclopedia of Puzzles. (n.d.) Retrieved from http://www.mathpuzzle.com/loyd/

Dates and Events. (n.d.). Oprah Winfrey timeline. Retrieved from http://www.datesandevents.org/people-timelines/05-oprah-winfrey-timeline.htm

Fernández, E. M., & Cairns, H. S. (2011). Fundamentals of psycholinguistics. West Sussex, UK: Wiley-Blackwell.

Flanagan, D., & Kaufman, A. (2004). Essentials of WISC-IV assessment. Hoboken: John Wiley and Sons, Inc.

Flynn, J., Shaughnessy, M. F., & Fulgham, S. W. (2012) Interview with Jim Flynn about the Flynn effect. North American Journal of Psychology, 14(1), 25–38.

Fox, M. (2012, November 1). Arthur R. Jensen dies at 89; Set off debate about I.Q. New York Times, p. B15.

Fromkin, V., Krashen, S., Curtiss, S., Rigler, D., & Rigler, M. (1974). The development of language in Genie: A case of language acquisition beyond the critical period. Brain and Language, 1, 81–107.

Furnham, A. (2009). The validity of a new, self-report measure of multiple intelligence. Current Psychology: A Journal for Diverse Perspectives on Diverse Psychological Issues, 28, 225–239.

Gardner, H. (1983). Frames of mind: The theory of multiple intelligences. New York: Basic Books.

Gardner, H., & Moran, S. (2006). The science of multiple intelligences theory: A response to Lynn Waterhouse. Educational Psychologist, 41, 227–232.

German, T. P., & Barrett, H. C. (2005). Functional fixedness in a technologically sparse culture. Psychological Science, 16, 1–5.

Goad, B. (2013, January 25). SSA wants to stop calling people ‘mentally retarded.’ Retrieved from http://thehill.com/blogs/regwatch/pending-regs/279399-ssa-wants-to-stop-calling-people-mentally-retarded

Goldstone, R. L., & Kersten, A. (2003). Concepts and categorization. In A. F. Healy, R. W. Proctor, & I.B. Weiner (Eds.), Handbook of psychology (Volume IV, pp. 599–622). Hoboken, New Jersey: John Wiley & Sons, Inc.

Goleman, D. (1995). Emotional intelligence; Why it can matter more than IQ. New York: Bantam Books.

Gordon, O. E. (1995). Francis Galton (1822–1911). Retrieved from http://www.psych.utah.edu/gordon/Classes/Psy4905Docs/PsychHistory/Cards/Galton.html

Gresham, F. M., & Witt, J. C. (1997). Utility of intelligence tests for treatment planning, classification, and placement decisions: Recent empirical findings and future directions. School Psychology Quarterly, 12(3), 249–267.

Guilford, J. P. (1967). The nature of human intelligence. New York, NY: McGraw Hill.

Heaton, S. (2004). Making the switch: Unlocking the mystery of the WISC-IV. Case Conference. University of Florida.

Jensen, J. (2011). Phoneme acquisition: Infants and second language learners. The Language Teacher, 35(6), 24–28.

Johnson, J. S., & Newport, E. L. (1989). Critical period effects in second language learning: The influence of maturational state on the acquisition of English as a second language. Cognitive Psychology, 21, 60–99.

Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus, and Giroux.

Kishyama, M. M., Boyce, W. T., Jimenez, A. M., Perry, L. M., & Knight, R. T. (2009). Socioeconomic disparities affect prefrontal function in children. Journal of Cognitive Neuroscience, 21(6), 1106–1115.

Klein, P. D. (1997). Multiplying the problems of intelligence by eight: A critique of Gardner’s theory. Canadian Journal of Education, 22, 377-94.

Larry P v. Riles, C-71-2270 RFP. (1979).

Lenneberg, E. (1967). Biological foundations of language. New York: Wiley.

Liptak, A. (2008, January 19). Lawyer reveals secret, toppling death sentence. New York Times. Retrieved from http://www.nytimes.com/2008/01/19/us/19death.html?_r=0

Locke, E. A. (2005, April 14). Why emotional intelligence is an invalid concept. Journal of Organizational Behavior, 26, 425–431.

Mayer, J. D., Salovey, P., & Caruso, D. (2004). Emotional intelligence: Theory, findings, and implications, Psychological Inquiry, 15(3), 197–215.

Modgil, S., & Routledge, C. M. (Eds.). (1987). Arthur Jensen: Consensus and controversy. New York: Falmer Press.

Morgan, H. (1996). An analysis of Gardner’s theory of multiple intelligence. Roeper Review: A Journal on Gifted Education, 18, 263–269.

Moskowitz, B. A. (1978). The acquisition of language. Scientific American, 239, 92–108. Petitto, L. A., Holowka, S., Sergio, L. E., Levy, B., & Ostry, D. J. (2004). Baby hands that move to the rhythm of language: Hearing babies acquiring sign languages babble silently on the hands. Cognition, 93, 43–73.

Neyfakh, L. (2013, October 7). “Why you can’t stop checking your phone.” Retrieved from http://www.bostonglobe.com/ideas/2013/10/06/why-you-can-stop-checking-your-phone/rrBJzyBGDAr1YlEH5JQDcM/story.html

Parker, J. D., Saklofske, D. H., & Stough, C. (Eds.). (2009). Assessing emotional intelligence: Theory, research, and applications. New York: Springer.

Petitto, L. A., Holowka, S., Sergio, L. E., Levy, B., & Ostry, D. J. (2004). Baby hands that move to the rhythm of language: Hearing babies acquiring sign languages babble silently on the hands. Cognition, 93, 43–73.

Pickens, J. (1994). Full-term and preterm infants’ perception of face-voice synchrony. Infant Behavior and Development, 17, 447–455.

Pratkanis, A. (1989). The cognitive representation of attitudes. In A. R. Pratkanis, S. J. Breckler, & A. G. Greenwald (Eds.), Attitude structure and function (pp. 71–98). Hillsdale, NJ: Erlbaum.

Regier, T., & Kay, P. (2009). Language, thought, and color: Whorf was half right. Trends in Cognitive Sciences, 13(10), 439–446.

Riccio, C. A., Gonzales, J. J., & Hynd, G. W. (1994). Attention-deficit Hyperactivity Disorder (ADHD) and learning disabilities. Learning Disability Quarterly, 17, 311–322.

Richardson, K. (2002). What IQ tests test. Theory & Psychology, 12(3), 283–314.

Roberts, D. (2014, May 27). U.S. Supreme Court bars Florida from using IQ score cutoff for executions. The Guardian. Retrieved from http://www.theguardian.com/world/2014/may/27/us-supreme-court-iq-score-cutoff-florida-execution

Rushton, J. P., & Jensen, A. R. (2005). Thirty years of research on race differences in cognitive ability. Psychology, public policy, and law, 11(2), 235–294.

Rymer, R. (1993). Genie: A Scientific Tragedy. New York: Harper Collins.

Sapir, E. (1964). Culture, language, and personality. Berkley: University of California Press. (Original work published 1941)

Schlinger, H. D. (2003). The myth of intelligence. The Psychological Record, 53(1), 15–32.

Severson, K. (2011, December 9). Thousands sterilized, a state weighs restitution. The New York Times. Retrieved from http://www.nytimes.com/2011/12/10/us/redress-weighed-for-forced-sterilizations-in-north-carolina.html?pagewanted=all&_r=0

Singleton, D. M. (1995). Introduction: A critical look at the critical period hypothesis in second language acquisition research. In D.M. Singleton & Z. Lengyel (Eds.), The age factor in second language acquisition: A critical look at the critical period hypothesis in second language acquisition research (pp. 1–29). Avon, UK: Multilingual Matters Ltd.

Skinner, B. F. (1957). Verbal behavior. Acton, MA: Copley Publishing Group.

Smits-Engelsman, B. C. M., & Van Galen, G. P. (1997). Dysgraphia in children: Lasting psychomotor deficiency or transient developmental delay? Journal of Experimental Child Psychology, 67, 164–184.

Spelke, E. S., & Cortelyou, A. (1981). Perceptual aspects of social knowing: Looking and listening in infancy. In M.E. Lamb & L.R. Sherrod (Eds.), Infant social cognition: Empirical and theoretical considerations (pp. 61–83). Hillsdale, NJ: Erlbaum.

Steitz, T. (2010). Thomas A. Steitz – Biographical. (K. Grandin, Ed.) Retrieved from http://www.nobelprize.org/nobel_prizes/chemistry/laureates/2009/steitz-bio.html

Sternberg, R. J. (1988). The triarchic mind: A new theory of intelligence. New York: Viking-Penguin.

Terman, L. M. (1925). Mental and physical traits of a thousand gifted children (I). Stanford, CA: Stanford University Press.

Terman, L. M., & Oden, M. H. (1947). The gifted child grows up: 25 years’ follow-up of a superior group: Genetic studies of genius (Vol. 4). Standord, CA: Stanford University Press.

Terman, L. M. (1916). The measurement of intelligence. Boston: Houghton-Mifflin.

Tomasello, M., & Rakoczy, H. (2003). What makes human cognition unique? From individual to shared to collective intentionality. Mind & Language, 18(2), 121–147.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

van Troyer, G. (1994). Linguistic determinism and mutability: The Sapir-Whorf “hypothesis” and intercultural communication. JALT Journal, 2, 163–178.

Wechsler, D. (1958). The measurement of adult intelligence. Baltimore: Williams & Wilkins.

Wechsler, D. (1981). Manual for the Wechsler Adult Intelligence Scale—revised. New York: Psychological Corporation.

Wechsler, D. (2002 ). WPPSI-R manual. New York: Psychological Corporation.

Werker, J. F., & Lalonde, C. E. (1988). Cross-language speech perception: Initial capabilities and developmental change. Developmental Psychology, 24, 672–683.

Werker, J. F., & Tees, R. C. (1984). Cross-language speech perception: Evidence for perceptual reorganization during the first year of life. Infant Behavior and Development, 7, 49–63.

Whorf, B. L. (1956). Language, thought and relativity. Cambridge, MA: MIT Press.

Williams, R. L., (1970). Danger: Testing and dehumanizing black children. Clinical Child Psychology Newsletter, 9(1), 5–6.

Zwicker, J. G. (2005). Effectiveness of occupational therapy in remediating handwriting difficulties in primary students: Cognitive versus multisensory interventions. Unpublished master’s thesis, University of Victoria, Victoria, British Columbia, Canada). Retrieved from http://dspace.library.uvic.ca:8080/bitstream/handle/1828/49/Zwicker%20thesis.pdf?sequence=1

CC licensed content, Shared previously

• Introduction to Thinking and Intelligence. Authored by : OpenStax College. Located at : https://openstax.org/books/psychology-2e/pages/7-introduction . License : CC BY: Attribution . License Terms : Download for free at https://openstax.org/books/psychology-2e/pages/1-introduction

General Psychology Copyright © by OpenStax and Lumen Learning is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

Share This Book

Thinking: Problem Solving and Reasoning

Cite this chapter.

• Donald H. Kausler 2  

137 Accesses

1 Citations

Bourne et al. (1979) reminded us that real-life problems come in all shapes and sizes. Earlier we observed that these real-life problems are faced by adults of all ages. Our concern is with what happens to problem-solving proficiency over the course of the adult segment of the life span and with what accounts for age changes in proficiency. To study problem-solving behavior in the laboratory, psychologists have introduced a number of specific problem situations that are intended to simulate a myriad of problem situations encountered in the real world. Several of these problems are given in Table 11.1. Our initial step will be to examine the processes that have been postulated by both associationists and cognitive psychologists to enter into the solving of these kinds of problems (see Bourne, Dominowski, Loftus, & Healy, 1986; Bourne et al., 1979; Glass, Holyoak, & Santa, 1979; and Newell & Simon, 1972; for more detailed reviews). Along the way, we will indicate likely candidates for age sensitivity.

ArticleNote Problems come in all shapes and sizes but generally share the characteristic that the individual must discover what to do in order to achieve a goal. Whether looking for the screwdriver that isn’t where it’s supposed to be, searching for a friend’s house in an unfamiliar neighborhood, trying to figure out why the car won’t start, or working on a mathematics exam in school, a person faces a situation in which the correct response is somewhat uncertain. (Bourne, Dominowski, & Loftus, 1979, p. 232)

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Unable to display preview.  Download preview PDF.

Author information

Authors and affiliations.

Department of Psychology, University of Missouri-Columbia, 65211, Columbia, Missouri, USA

Donald H. Kausler

You can also search for this author in PubMed   Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 1991 Springer-Verlag New York Inc.

About this chapter

Kausler, D.H. (1991). Thinking: Problem Solving and Reasoning. In: Experimental Psychology, Cognition, and Human Aging. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-9695-6_11

Download citation

DOI : https://doi.org/10.1007/978-1-4613-9695-6_11

Publisher Name : Springer, New York, NY

Print ISBN : 978-1-4613-9697-0

Online ISBN : 978-1-4613-9695-6

eBook Packages : Springer Book Archive

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

• Search Menu
• Browse content in Arts and Humanities
• Browse content in Archaeology
• Anglo-Saxon and Medieval Archaeology
• Archaeological Methodology and Techniques
• Archaeology by Region
• Archaeology of Religion
• Archaeology of Trade and Exchange
• Biblical Archaeology
• Contemporary and Public Archaeology
• Environmental Archaeology
• Historical Archaeology
• History and Theory of Archaeology
• Industrial Archaeology
• Landscape Archaeology
• Mortuary Archaeology
• Prehistoric Archaeology
• Underwater Archaeology
• Urban Archaeology
• Zooarchaeology
• Browse content in Architecture
• Architectural Structure and Design
• History of Architecture
• Residential and Domestic Buildings
• Theory of Architecture
• Browse content in Art
• Art Subjects and Themes
• History of Art
• Industrial and Commercial Art
• Theory of Art
• Biographical Studies
• Byzantine Studies
• Browse content in Classical Studies
• Classical Literature
• Classical Reception
• Classical History
• Classical Philosophy
• Classical Mythology
• Classical Art and Architecture
• Classical Oratory and Rhetoric
• Greek and Roman Archaeology
• Greek and Roman Papyrology
• Greek and Roman Epigraphy
• Greek and Roman Law
• Late Antiquity
• Religion in the Ancient World
• Digital Humanities
• Browse content in History
• Colonialism and Imperialism
• Diplomatic History
• Environmental History
• Genealogy, Heraldry, Names, and Honours
• Genocide and Ethnic Cleansing
• Historical Geography
• History by Period
• History of Agriculture
• History of Education
• History of Emotions
• History of Gender and Sexuality
• Industrial History
• Intellectual History
• International History
• Labour History
• Legal and Constitutional History
• Local and Family History
• Maritime History
• Military History
• National Liberation and Post-Colonialism
• Oral History
• Political History
• Public History
• Regional and National History
• Revolutions and Rebellions
• Slavery and Abolition of Slavery
• Social and Cultural History
• Theory, Methods, and Historiography
• Urban History
• World History
• Browse content in Language Teaching and Learning
• Language Learning (Specific Skills)
• Language Teaching Theory and Methods
• Browse content in Linguistics
• Applied Linguistics
• Cognitive Linguistics
• Computational Linguistics
• Forensic Linguistics
• Grammar, Syntax and Morphology
• Historical and Diachronic Linguistics
• History of English
• Language Variation
• Language Families
• Language Evolution
• Language Reference
• Language Acquisition
• Lexicography
• Linguistic Theories
• Linguistic Typology
• Linguistic Anthropology
• Phonetics and Phonology
• Psycholinguistics
• Sociolinguistics
• Translation and Interpretation
• Writing Systems
• Browse content in Literature
• Bibliography
• Children's Literature Studies
• Literary Studies (Modernism)
• Literary Studies (Romanticism)
• Literary Studies (American)
• Literary Studies (Asian)
• Literary Studies (European)
• Literary Studies (Eco-criticism)
• Literary Studies - World
• Literary Studies (1500 to 1800)
• Literary Studies (19th Century)
• Literary Studies (20th Century onwards)
• Literary Studies (African American Literature)
• Literary Studies (British and Irish)
• Literary Studies (Early and Medieval)
• Literary Studies (Fiction, Novelists, and Prose Writers)
• Literary Studies (Gender Studies)
• Literary Studies (Graphic Novels)
• Literary Studies (History of the Book)
• Literary Studies (Plays and Playwrights)
• Literary Studies (Poetry and Poets)
• Literary Studies (Postcolonial Literature)
• Literary Studies (Queer Studies)
• Literary Studies (Science Fiction)
• Literary Studies (Travel Literature)
• Literary Studies (War Literature)
• Literary Studies (Women's Writing)
• Literary Theory and Cultural Studies
• Mythology and Folklore
• Shakespeare Studies and Criticism
• Browse content in Media Studies
• Browse content in Music
• Applied Music
• Dance and Music
• Ethics in Music
• Ethnomusicology
• Gender and Sexuality in Music
• Medicine and Music
• Music Cultures
• Music and Culture
• Music and Media
• Music and Religion
• Music Education and Pedagogy
• Music Theory and Analysis
• Musical Scores, Lyrics, and Libretti
• Musical Structures, Styles, and Techniques
• Musicology and Music History
• Performance Practice and Studies
• Race and Ethnicity in Music
• Sound Studies
• Browse content in Performing Arts
• Browse content in Philosophy
• Aesthetics and Philosophy of Art
• Epistemology
• Feminist Philosophy
• History of Western Philosophy
• Metaphysics
• Moral Philosophy
• Non-Western Philosophy
• Philosophy of Action
• Philosophy of Law
• Philosophy of Religion
• Philosophy of Language
• Philosophy of Mind
• Philosophy of Perception
• Philosophy of Science
• Philosophy of Mathematics and Logic
• Practical Ethics
• Social and Political Philosophy
• Browse content in Religion
• Biblical Studies
• Christianity
• East Asian Religions
• History of Religion
• Judaism and Jewish Studies
• Qumran Studies
• Religion and Education
• Religion and Health
• Religion and Politics
• Religion and Science
• Religion and Law
• Religion and Art, Literature, and Music
• Religious Studies
• Browse content in Society and Culture
• Cookery, Food, and Drink
• Cultural Studies
• Customs and Traditions
• Ethical Issues and Debates
• Hobbies, Games, Arts and Crafts
• Lifestyle, Home, and Garden
• Natural world, Country Life, and Pets
• Popular Beliefs and Controversial Knowledge
• Sports and Outdoor Recreation
• Technology and Society
• Travel and Holiday
• Visual Culture
• Browse content in Law
• Arbitration
• Browse content in Company and Commercial Law
• Commercial Law
• Company Law
• Browse content in Comparative Law
• Systems of Law
• Competition Law
• Browse content in Constitutional and Administrative Law
• Government Powers
• Judicial Review
• Local Government Law
• Military and Defence Law
• Parliamentary and Legislative Practice
• Construction Law
• Contract Law
• Browse content in Criminal Law
• Criminal Procedure
• Criminal Evidence Law
• Sentencing and Punishment
• Employment and Labour Law
• Environment and Energy Law
• Browse content in Financial Law
• Banking Law
• Insolvency Law
• History of Law
• Human Rights and Immigration
• Intellectual Property Law
• Browse content in International Law
• Private International Law and Conflict of Laws
• Public International Law
• IT and Communications Law
• Jurisprudence and Philosophy of Law
• Law and Society
• Law and Politics
• Browse content in Legal System and Practice
• Courts and Procedure
• Legal Skills and Practice
• Primary Sources of Law
• Regulation of Legal Profession
• Medical and Healthcare Law
• Browse content in Policing
• Criminal Investigation and Detection
• Police and Security Services
• Police Procedure and Law
• Police Regional Planning
• Browse content in Property Law
• Personal Property Law
• Study and Revision
• Terrorism and National Security Law
• Browse content in Trusts Law
• Wills and Probate or Succession
• Browse content in Medicine and Health
• Browse content in Allied Health Professions
• Arts Therapies
• Clinical Science
• Dietetics and Nutrition
• Occupational Therapy
• Operating Department Practice
• Physiotherapy
• Radiography
• Speech and Language Therapy
• Browse content in Anaesthetics
• General Anaesthesia
• Neuroanaesthesia
• Clinical Neuroscience
• Browse content in Clinical Medicine
• Acute Medicine
• Cardiovascular Medicine
• Clinical Genetics
• Clinical Pharmacology and Therapeutics
• Dermatology
• Endocrinology and Diabetes
• Gastroenterology
• Genito-urinary Medicine
• Geriatric Medicine
• Infectious Diseases
• Medical Oncology
• Medical Toxicology
• Pain Medicine
• Palliative Medicine
• Rehabilitation Medicine
• Respiratory Medicine and Pulmonology
• Rheumatology
• Sleep Medicine
• Sports and Exercise Medicine
• Community Medical Services
• Critical Care
• Emergency Medicine
• Forensic Medicine
• Haematology
• History of Medicine
• Medical Ethics
• Browse content in Medical Skills
• Clinical Skills
• Communication Skills
• Nursing Skills
• Surgical Skills
• Browse content in Medical Dentistry
• Oral and Maxillofacial Surgery
• Paediatric Dentistry
• Restorative Dentistry and Orthodontics
• Surgical Dentistry
• Medical Statistics and Methodology
• Browse content in Neurology
• Clinical Neurophysiology
• Neuropathology
• Nursing Studies
• Browse content in Obstetrics and Gynaecology
• Gynaecology
• Occupational Medicine
• Ophthalmology
• Otolaryngology (ENT)
• Browse content in Paediatrics
• Neonatology
• Browse content in Pathology
• Chemical Pathology
• Clinical Cytogenetics and Molecular Genetics
• Histopathology
• Medical Microbiology and Virology
• Patient Education and Information
• Browse content in Pharmacology
• Psychopharmacology
• Browse content in Popular Health
• Caring for Others
• Complementary and Alternative Medicine
• Self-help and Personal Development
• Browse content in Preclinical Medicine
• Cell Biology
• Molecular Biology and Genetics
• Reproduction, Growth and Development
• Primary Care
• Professional Development in Medicine
• Browse content in Psychiatry
• Addiction Medicine
• Child and Adolescent Psychiatry
• Forensic Psychiatry
• Learning Disabilities
• Old Age Psychiatry
• Psychotherapy
• Browse content in Public Health and Epidemiology
• Epidemiology
• Public Health
• Browse content in Radiology
• Clinical Radiology
• Interventional Radiology
• Nuclear Medicine
• Radiation Oncology
• Reproductive Medicine
• Browse content in Surgery
• Cardiothoracic Surgery
• Gastro-intestinal and Colorectal Surgery
• General Surgery
• Neurosurgery
• Paediatric Surgery
• Peri-operative Care
• Plastic and Reconstructive Surgery
• Surgical Oncology
• Transplant Surgery
• Trauma and Orthopaedic Surgery
• Vascular Surgery
• Browse content in Science and Mathematics
• Browse content in Biological Sciences
• Aquatic Biology
• Biochemistry
• Bioinformatics and Computational Biology
• Developmental Biology
• Ecology and Conservation
• Evolutionary Biology
• Genetics and Genomics
• Microbiology
• Molecular and Cell Biology
• Natural History
• Plant Sciences and Forestry
• Research Methods in Life Sciences
• Structural Biology
• Systems Biology
• Zoology and Animal Sciences
• Browse content in Chemistry
• Analytical Chemistry
• Computational Chemistry
• Crystallography
• Environmental Chemistry
• Industrial Chemistry
• Inorganic Chemistry
• Materials Chemistry
• Medicinal Chemistry
• Mineralogy and Gems
• Organic Chemistry
• Physical Chemistry
• Polymer Chemistry
• Study and Communication Skills in Chemistry
• Theoretical Chemistry
• Browse content in Computer Science
• Artificial Intelligence
• Computer Architecture and Logic Design
• Game Studies
• Human-Computer Interaction
• Mathematical Theory of Computation
• Programming Languages
• Software Engineering
• Systems Analysis and Design
• Virtual Reality
• Browse content in Computing
• Business Applications
• Computer Games
• Computer Security
• Computer Networking and Communications
• Digital Lifestyle
• Graphical and Digital Media Applications
• Operating Systems
• Browse content in Earth Sciences and Geography
• Atmospheric Sciences
• Environmental Geography
• Geology and the Lithosphere
• Maps and Map-making
• Meteorology and Climatology
• Oceanography and Hydrology
• Palaeontology
• Physical Geography and Topography
• Regional Geography
• Soil Science
• Urban Geography
• Browse content in Engineering and Technology
• Agriculture and Farming
• Biological Engineering
• Civil Engineering, Surveying, and Building
• Electronics and Communications Engineering
• Energy Technology
• Engineering (General)
• Environmental Science, Engineering, and Technology
• History of Engineering and Technology
• Mechanical Engineering and Materials
• Technology of Industrial Chemistry
• Transport Technology and Trades
• Browse content in Environmental Science
• Applied Ecology (Environmental Science)
• Conservation of the Environment (Environmental Science)
• Environmental Sustainability
• Environmentalist Thought and Ideology (Environmental Science)
• Management of Land and Natural Resources (Environmental Science)
• Natural Disasters (Environmental Science)
• Nuclear Issues (Environmental Science)
• Pollution and Threats to the Environment (Environmental Science)
• Social Impact of Environmental Issues (Environmental Science)
• History of Science and Technology
• Browse content in Materials Science
• Ceramics and Glasses
• Composite Materials
• Metals, Alloying, and Corrosion
• Nanotechnology
• Browse content in Mathematics
• Applied Mathematics
• Biomathematics and Statistics
• History of Mathematics
• Mathematical Education
• Mathematical Finance
• Mathematical Analysis
• Numerical and Computational Mathematics
• Probability and Statistics
• Pure Mathematics
• Browse content in Neuroscience
• Cognition and Behavioural Neuroscience
• Development of the Nervous System
• Disorders of the Nervous System
• History of Neuroscience
• Invertebrate Neurobiology
• Molecular and Cellular Systems
• Neuroendocrinology and Autonomic Nervous System
• Neuroscientific Techniques
• Sensory and Motor Systems
• Browse content in Physics
• Astronomy and Astrophysics
• Atomic, Molecular, and Optical Physics
• Biological and Medical Physics
• Classical Mechanics
• Computational Physics
• Condensed Matter Physics
• Electromagnetism, Optics, and Acoustics
• History of Physics
• Mathematical and Statistical Physics
• Measurement Science
• Nuclear Physics
• Particles and Fields
• Plasma Physics
• Quantum Physics
• Relativity and Gravitation
• Semiconductor and Mesoscopic Physics
• Browse content in Psychology
• Affective Sciences
• Clinical Psychology
• Cognitive Neuroscience
• Cognitive Psychology
• Criminal and Forensic Psychology
• Developmental Psychology
• Educational Psychology
• Evolutionary Psychology
• Health Psychology
• History and Systems in Psychology
• Music Psychology
• Neuropsychology
• Organizational Psychology
• Psychological Assessment and Testing
• Psychology of Human-Technology Interaction
• Psychology Professional Development and Training
• Research Methods in Psychology
• Social Psychology
• Browse content in Social Sciences
• Browse content in Anthropology
• Anthropology of Religion
• Human Evolution
• Medical Anthropology
• Physical Anthropology
• Regional Anthropology
• Social and Cultural Anthropology
• Theory and Practice of Anthropology
• Browse content in Business and Management
• Business History
• Business Ethics
• Business Strategy
• Business and Technology
• Business and Government
• Business and the Environment
• Comparative Management
• Corporate Governance
• Corporate Social Responsibility
• Entrepreneurship
• Health Management
• Human Resource Management
• Industrial and Employment Relations
• Industry Studies
• Information and Communication Technologies
• International Business
• Knowledge Management
• Management and Management Techniques
• Operations Management
• Organizational Theory and Behaviour
• Pensions and Pension Management
• Public and Nonprofit Management
• Strategic Management
• Supply Chain Management
• Browse content in Criminology and Criminal Justice
• Criminal Justice
• Criminology
• Forms of Crime
• International and Comparative Criminology
• Youth Violence and Juvenile Justice
• Development Studies
• Browse content in Economics
• Agricultural, Environmental, and Natural Resource Economics
• Asian Economics
• Behavioural Finance
• Behavioural Economics and Neuroeconomics
• Econometrics and Mathematical Economics
• Economic Methodology
• Economic History
• Economic Systems
• Economic Development and Growth
• Financial Markets
• Financial Institutions and Services
• General Economics and Teaching
• Health, Education, and Welfare
• History of Economic Thought
• International Economics
• Labour and Demographic Economics
• Law and Economics
• Macroeconomics and Monetary Economics
• Microeconomics
• Public Economics
• Urban, Rural, and Regional Economics
• Welfare Economics
• Browse content in Education
• Adult Education and Continuous Learning
• Care and Counselling of Students
• Early Childhood and Elementary Education
• Educational Equipment and Technology
• Educational Strategies and Policy
• Higher and Further Education
• Organization and Management of Education
• Philosophy and Theory of Education
• Schools Studies
• Secondary Education
• Teaching of a Specific Subject
• Teaching of Specific Groups and Special Educational Needs
• Teaching Skills and Techniques
• Browse content in Environment
• Applied Ecology (Social Science)
• Climate Change
• Conservation of the Environment (Social Science)
• Environmentalist Thought and Ideology (Social Science)
• Natural Disasters (Environment)
• Social Impact of Environmental Issues (Social Science)
• Browse content in Human Geography
• Cultural Geography
• Economic Geography
• Political Geography
• Browse content in Interdisciplinary Studies
• Communication Studies
• Museums, Libraries, and Information Sciences
• Browse content in Politics
• African Politics
• Asian Politics
• Chinese Politics
• Comparative Politics
• Conflict Politics
• Elections and Electoral Studies
• Environmental Politics
• European Union
• Foreign Policy
• Gender and Politics
• Human Rights and Politics
• Indian Politics
• International Relations
• International Organization (Politics)
• International Political Economy
• Irish Politics
• Latin American Politics
• Middle Eastern Politics
• Political Theory
• Political Behaviour
• Political Economy
• Political Institutions
• Political Methodology
• Political Communication
• Political Philosophy
• Political Sociology
• Politics and Law
• Public Policy
• Public Administration
• Quantitative Political Methodology
• Regional Political Studies
• Russian Politics
• Security Studies
• State and Local Government
• UK Politics
• US Politics
• Browse content in Regional and Area Studies
• African Studies
• Asian Studies
• East Asian Studies
• Japanese Studies
• Latin American Studies
• Middle Eastern Studies
• Native American Studies
• Scottish Studies
• Browse content in Research and Information
• Research Methods
• Browse content in Social Work
• Addictions and Substance Misuse
• Adoption and Fostering
• Care of the Elderly
• Child and Adolescent Social Work
• Couple and Family Social Work
• Developmental and Physical Disabilities Social Work
• Direct Practice and Clinical Social Work
• Emergency Services
• Human Behaviour and the Social Environment
• International and Global Issues in Social Work
• Mental and Behavioural Health
• Social Justice and Human Rights
• Social Policy and Advocacy
• Social Work and Crime and Justice
• Social Work Macro Practice
• Social Work Practice Settings
• Social Work Research and Evidence-based Practice
• Welfare and Benefit Systems
• Browse content in Sociology
• Childhood Studies
• Community Development
• Comparative and Historical Sociology
• Economic Sociology
• Gender and Sexuality
• Gerontology and Ageing
• Health, Illness, and Medicine
• Marriage and the Family
• Migration Studies
• Occupations, Professions, and Work
• Organizations
• Population and Demography
• Race and Ethnicity
• Social Theory
• Social Movements and Social Change
• Social Research and Statistics
• Social Stratification, Inequality, and Mobility
• Sociology of Religion
• Sociology of Education
• Sport and Leisure
• Urban and Rural Studies
• Browse content in Warfare and Defence
• Defence Strategy, Planning, and Research
• Land Forces and Warfare
• Military Administration
• Military Life and Institutions
• Naval Forces and Warfare
• Other Warfare and Defence Issues
• Peace Studies and Conflict Resolution
• Weapons and Equipment

• < Previous chapter
• Next chapter >

2 (page 17) p. 17 Problem solving

• Published: September 2017
• Cite Icon Cite
• Permissions Icon Permissions

Problem solving is clearly a key feature of human intelligence. Human intelligence does not, in the main, rely on behaviour patterns fixed by evolution and nor does it depend on habit learning. To understand human intelligence, we need to study how humans can solve both ill-defined and well-defined problems. ‘Problem solving’ considers both types of problems and the different approaches used to solve them: the computational approach, insight, and expertise. It also looks at dual-process theory and explains that fast, intuitive processes can be both a source of error and also a cause of success, depending on the context and the prior knowledge of the problem solver.

Signed in as

Institutional accounts.

• Google Scholar Indexing
• GoogleCrawler [DO NOT DELETE]

Personal account

• Sign in with email/username & password
• Get email alerts
• Save searches
• Purchase content
• Activate your purchase/trial code

Institutional access

• Sign in with a library card Sign in with username/password Recommend to your librarian
• Institutional account management
• Get help with access

Access to content on Oxford Academic is often provided through institutional subscriptions and purchases. If you are a member of an institution with an active account, you may be able to access content in one of the following ways:

IP based access

Typically, access is provided across an institutional network to a range of IP addresses. This authentication occurs automatically, and it is not possible to sign out of an IP authenticated account.

Sign in through your institution

Choose this option to get remote access when outside your institution. Shibboleth/Open Athens technology is used to provide single sign-on between your institution’s website and Oxford Academic.

• Click Sign in through your institution.
• Select your institution from the list provided, which will take you to your institution's website to sign in.
• When on the institution site, please use the credentials provided by your institution. Do not use an Oxford Academic personal account.
• Following successful sign in, you will be returned to Oxford Academic.

If your institution is not listed or you cannot sign in to your institution’s website, please contact your librarian or administrator.

Sign in with a library card

Enter your library card number to sign in. If you cannot sign in, please contact your librarian.

Society Members

Society member access to a journal is achieved in one of the following ways:

Sign in through society site

Many societies offer single sign-on between the society website and Oxford Academic. If you see ‘Sign in through society site’ in the sign in pane within a journal:

• Click Sign in through society site.
• When on the society site, please use the credentials provided by that society. Do not use an Oxford Academic personal account.

If you do not have a society account or have forgotten your username or password, please contact your society.

Sign in using a personal account

Some societies use Oxford Academic personal accounts to provide access to their members. See below.

A personal account can be used to get email alerts, save searches, purchase content, and activate subscriptions.

Some societies use Oxford Academic personal accounts to provide access to their members.

Viewing your signed in accounts

Click the account icon in the top right to:

• View your signed in personal account and access account management features.
• View the institutional accounts that are providing access.

Signed in but can't access content

Oxford Academic is home to a wide variety of products. The institutional subscription may not cover the content that you are trying to access. If you believe you should have access to that content, please contact your librarian.

For librarians and administrators, your personal account also provides access to institutional account management. Here you will find options to view and activate subscriptions, manage institutional settings and access options, access usage statistics, and more.

Our books are available by subscription or purchase to libraries and institutions.

• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Rights and permissions
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

Thinking and Intelligence

Putting it together: thinking and intelligence, learning objectives.

In this module, you learned to

• describe cognition and problem-solving strategies
• describe language acquisition and the role language plays in communication and thought
• describe intelligence theories and intelligence testing

For many people, intelligence is one of those concepts that seems to make sense and should be relatively easy to define, until you have to think too deeply about it. What exactly is it, anyway? Is it a good memory, a quick wit, a special ability in mathematical skills? Remember from your reading that Charles Spearman identified intelligence as a general thing, that consists of general enhanced abilities in reasoning, verbal abilities, and logic. Robert Sternberg said intelligence is comprised of three parts: practical, creative, and analytical intelligence. Howard Gardner identified eight distinct intelligences. Others still found things like emotional intelligence and creativity of critical importance.

Just as it is difficult to narrowly define IQ, it is also difficult to measure it. Through the process of standardization and decades of administering IQ tests, researchers have a decent understanding that IQ can be generally measured, and that it is relatively stable over time. Even this belief in the validity and reliability of IQ testing continues to be challenged, however.

Figure 1 . Do you think motivation impacts intelligence?

In 2011, Angela Duckworth (who is well known for her studies on grit), headed up a team of researchers who conducted a meta-analysis of nearly fifty previous studies. These studies examined the effect of monetary incentives on IQ tests, with varying values of money offered. Some were offered small incentives of a few dollars or less, others given moderate sums, and some received larger rewards of $10 or more. Duckworth and her team wanted to know if these incentives would impact IQ scores. What do you think happened? Sure enough, the study found that incentives increased IQ scores by an average of 0.64 standard deviations, which is roughly a 10 point difference on the IQ scale! The effect of motivation was even more dramatic with larger rewards, and also had a larger impact on those who first reported lower-than-average baseline IQ scores. The impact of the motivation was much smaller with those with above-average IQs and was not even measured on those with baseline IQs above 120. Duckwork and her colleagues essentially conclude that motivation, as well as other external factors such as employment, years of education, and academic achievement, all have an influence on IQ scores. She warns against jumping to extreme conclusions, however, because both motivation and intelligence are needed to perform well on an IQ test. [1]

You can see that this field of research is ever-growing and evolving. Contemporary studies are examining the genetic components that correlate with high intelligence, and new studies will assuredly reveal more about where intelligence comes from and how it is best measured.

Link to Learning

Yet another interesting investigation into intelligence reveals that people have a curious tendency to prefer those with “natural” intelligence over those who have to strive for success. Read more about it in this Harvard Business Review article .

Contribute!

Improve this page Learn More

• Duckworth, A. L., Quinn, P. D., Lynam, D. R., Loeber, R., & Stouthamer-Loeber, M. (n.d.). Role of test motivation in intelligence testing. Proceedings of the National Academy of Sciences of the United States of America, 108 (19), 7716-7720. doi:0.1073/pnas.1018601108 ↵
• Putting It Together: Thinking and Intelligence. Provided by : Lumen Learning. License : CC BY: Attribution
• exam image. Authored by : Alberto G.. Provided by : Flickr. Located at : https://www.flickr.com/photos/albertogp123/5843577306 . License : CC BY: Attribution

Intelligence Theories

July 16, 2023

Explore diverse theories of intelligence, from traditional IQ-based models to innovative concepts like multiple intelligences.

Main, P (2023, July 16). Intelligence Theories. Retrieved from https://www.structural-learning.com/post/intelligence-theories

What is Intelligence?

Intelligence, a central concept in psychology, is a multifaceted construct that extends beyond a single definition. It's typically characterized as the ability to learn, understand, and apply knowledge, as well as the capacity to solve problems and adapt to new situations.

Historically, intelligence has been quantified through the Intelligence Quotient (IQ) test, which primarily assesses logical-mathematical and linguistic abilities . However, this approach has been critiqued for its narrow perspective, as it may overlook other significant aspects of intelligence.

Indeed, there are alternative theories that propose a broader understanding of intelligence. One such theory, proposed by Howard Gardner, suggests the existence of multiple intelligences, each representing unique ways of processing information. However, it's important to note that this is just one of many perspectives on intelligence.

Critics argue for a more unified approach to understanding intelligence, suggesting that a comprehensive perspective is needed. Despite the debates, it's clear that intelligence is a complex concept that encompasses a variety of cognitive abilities.

While traditional definitions of intelligence have been scrutinized for their narrow focus, the field continues to evolve, offering a more inclusive understanding of human intelligence. This broad overview sets the stage for a deeper exploration of specific theories and perspectives, such as Spearman's two-factor theory of intelligence.

Spearman's g Factor and Beyond

Charles Spearman, an English psychologist, developed the two-factor theory of intelligence in the early 20th century. Central to his theory is the concept of the g-factor (general intelligence) and the s-factor (specific intelligence).

According to Spearman, the g-factor represents the overall or general intelligence that underlies a person's performance across various cognitive tasks. This factor is responsible for an individual's ability to reason, solve problems, and comprehend complex information. In other words, the g-factor represents a person's general mental capacity.

In addition to the g-factor, Spearman proposed the s-factor, which refers to specific abilities or skills that are task-specific. These specific abilities include talents in areas such as music, art, or athletics. Unlike the g-factor, the s-factor is independent of the general mental capacit y and represents more specialized abilities that are not related to overall intelligence.

To support his theory, Spearman used factor analysis, a statistical technique that examines patterns of correlation between different variables. He applied this technique to intelligence test scores from a large sample of individuals.

Through factor analysis, Spearman observed that performance in different areas of an intelligence test, such as verbal comprehension , math, or spatial reasoning, were positively correlated. This suggested the presence of a general factor (the g-factor) underlying these diverse cognitive abilities.

Spearman's two-factor theory of intelligence provided a framework to understand the relationship between general and specific abilities . While the g-factor represents the foundation of overall intelligence, the s-factor acknowledges the presence of diverse talents and skills that contribute to human abilities beyond general mental capacity.

Gardner's Revolutionary Perspective

Howard Gardner's theory of multiple intelligences has revolutionized the way we think about intelligence and its role in education. According to Gardner, traditional views of intelligence, which focused solely on cognitive abilities measured by IQ tests, were too limited. He proposed that there are actually distinct, independent multiple intelligences, each representing unique skills and talents.

Gardner initially identified seven intelligences: linguistic intelligence, logical-mathematical intelligence, spatial intelligence, musical intelligence, bodily-kinesthetic intelligence, interpersonal intelligence, and intrapersonal intelligence.

Each of these intelligences encompasses different ways of understanding and interacting with the world. For example, linguistic intelligence involves skilled use of language , while logical-mathematical intelligence involves reasoning and problem-solving abilities.

As Gardner's theory evolved, he later added an eighth intelligence: naturalist intelligence. This intelligence pertains to a person's ability to recognize and categorize patterns in nature and to understand the natural world.

Gardner's theory has had a profound impact on education by emphasizing the importance of acknowledging and developing all intelligences, not just those traditionally measured by IQ tests. It has led to more diverse and inclusive approaches to teaching and learning , recognizing that students have different strengths and talents.

This perspective has allowed educators to tailor their teaching methods to fit the unique intelligences of their students, fostering a more holistic understanding of intelligence in the classroom.

Triarchic Theory of Intelligence

The Triarchic Theory of Intelligence, developed by Robert Sternberg, offers a comprehensive and nuanced understanding of intelligence. Unlike Gardner's theory, which focused on multiple intelligences, the Triarchic Theory breaks down intelligence into three distinct aspects: componential intelligence, experiential intelligence, and contextual intelligence.

Componential intelligence encompasses the analytical or problem-solving abilities that allow individuals to break down complex tasks and find efficient solutions. This aspect of intelligence involves skills such as critical thinking, logical reasoning, and strategic planning.

Experiential intelligence refers to the ability to approach new situations creatively and adaptively . It includes the capacity for insight, imagination, and the use of previous knowledge in novel ways. Individuals with high experiential intelligence are often innovative, able to view problems from unique perspectives, and find creative solutions .

Contextual intelligence, the third aspect of the Triarchic Theory, involves the application of intelligence to real-world settings and understanding the cultural and social context in which a person operates. It includes the ability to adapt to different environments, effectively communicate , and demonstrate practical problem-solving skills in everyday situations.

Sternberg's Triarchic Theory builds upon Gardner's broader definition of intelligence by offering a more specific framework that captures the diverse ways in which individuals demonstrate intelligence.

By considering the components, experiences, and contexts that influence intellectual abilities, the Triarchic Theory provides a more comprehensive understanding of intelligence and its applicability to various domains of human functioning .

Emotional Intelligence

Emotional intelligence is a concept in the field of psychology that refers to an individual's ability to perceive, understand, express, and regulate emotions effectively. Unlike traditional intelligence, which primarily measures cognitive abilities, emotional intelligence focuses on one's mental capacity to recognize and manage emotions in oneself and others.

There has been much debate regarding the categorization of emotional intelligence as either a collection of personality traits or a distinct form of intelligence. Some argue that emotional intelligence is simply a reflection of certain personality traits, such as empathy and self-awareness.

However, others believe that it constitutes a separate kind of intelligence that is vital for navigating social interactions and adapting to new situations.

Key abilities associated with emotional intelligence include perceiving emotions accurately, both in oneself and in others. This involves recognizing facial expressions, body language, and vocal cues. Expressing emotions appropriately is another aspect of emotional intelligence, involving the ability to convey feelings effectively and assertively.

Understanding emotions is essential in emotional intelligence, as it entails comprehending complex emotional states and their underlying causes. Lastly, regulating emotions is a crucial ability, enabling individuals to manage and control their own emotions, as well as positively influence the emotions of others in different situations.

Emotional intelligence encompasses a range of skills that go beyond traditional intelligence, allowing individuals to navigate social interactions successfully and adapt to new situations. While the debate over its categorization continues, the importance of emotional intelligence in understanding and managing emotions remains indisputable.

Biological Basis of Intelligence

The biological basis of intelligence refers to the underlying biological factors that contribute to individual differences in cognitive abilities. This includes the role of genetics and environmental influences, as well as the relationship between brain structure and function .

Genetics play a significant role in shaping intelligence. Studies have shown that intelligence is heritable, meaning that a portion of individual differences in intelligence can be attributed to genetic factors. Twin and adoption studies have provided evidence for the heritability of intelligence, showing that biological siblings raised in different environments still tend to have similar levels of intelligence.

However, environmental factors also play a crucial role in intelligence. Early experiences, such as nutrition, exposure to toxins, and quality of education, can profoundly impact cognitive development . Stimulating and enriching environments, including supportive parenting and educational opportunities, have been associated with higher intelligence scores.

Brain structure and function are closely related to cognitive abilities. Various brain regions are involved in different aspects of intelligence, including the prefrontal cortex, which is responsible for executive functions like problem-solving and reasoning. The connectivity between different brain regions also influences intelligence, with greater connectivity associated with higher cognitive abilities.

Neurotransmitters and hormones play a role in modulating intelligence. For example, dopamine is involved in reward processing and motivation, which are important for cognitive performance . Hormones like cortisol and testosterone can affect cognitive functioning, with prolonged exposure to high levels of cortisol potentially impairing cognitive abilities.

The biological basis of intelligence involves a complex interplay between genetic and environmental factors, brain structure and function, as well as neurotransmitters and hormones. Understanding these factors can provide valuable insights into individual differences in cognitive abilities .

Fluid vs. Crystallized Intelligence

Raymond Cattell's theory of intelligence includes the concepts of fluid and crystallized intelligence . Fluid intelligence refers to the ability to think in novel ways and solve abstract problems. It involves the capacity to reason, identify patterns, and solve new problems that do not rely on pre-existing knowledge.

Fluid intelligence is independent of specific learning or cultural experiences and is considered to be a measure of one's raw intellectual potential.

In contrast, crystallized intelligence refers to the acquisition and application of knowledge and skills. It encompasses the accumulation of information, facts, and expertise gained through education, cultural influences, and life experiences.

Crystallized intelligence relies on the utilization of previously acquired knowledge to solve problems and make informed decisions.

As individuals age, there is typically a decline in fluid intelligence while crystallized intelligence tends to increase or remain stable. This can be attributed to the decline in cognitive processing speed and working memory capacity that occurs with age.

However, the accumulated knowledge and expertise over a lifetime can enhance and compensate for any decline in fluid intelligence.

In summary, fluid intelligence involves the ability to think in novel ways and solve abstract problems, while crystallized intelligence refers to the acquisition and application of knowledge and skills . While fluid intelligence declines slightly as we age, crystallized intelligence can increase or remain stable due to accumulated knowledge and life experiences.

These concepts are integral to Raymond Cattell's theory of intelligence.

How Psychologists Measure Intelligence

Psychologists use standardized tests to measure intelligence, such as the Scholastic Assessment Test (SAT), the American College Test (ACT), and IQ tests. Standardized tests provide a quantifiable measure of an individual's cognitive abilities and are designed to assess various aspects of intelligence.

The history of IQ tests dates back to the early twentieth century with the development of the Binet-Simon intelligence scale by Alfred Binet and Theodore Simon. This scale aimed to identify children who needed additional educational support . Later, the Stanford-Binet IQ test, developed by Lewis Terman, expanded on the Binet-Simon scale and became widely used in the United States.

Another prominent IQ test is the Wechsler Adult Intelligence Scale (WAIS), developed by David Wechsler. The WAIS assesses intellectual abilities in adults and is widely used in clinical and educational settings.

These tests measure different cognitive abilities, including verbal reasoning, logical thinking, problem-solving, and abstract reasoning. Results from these tests are typically reported as an intelligence quotient (IQ), which compares an individual's performance to a standardized population.

It is important to note that these tests have been subject to criticisms and controversies, as they may not capture the entirety of human intelligence. Nonetheless, they provide valuable information for understanding individuals' cognitive abilities and predicting academic and cognitive success .

Criticism of Intelligence Testing

While IQ tests have been widely used to measure intellectual abilities, they have faced significant criticism regarding cultural biases and the validity of their results. One major criticism is that these tests may be influenced by cultural biases, favoring individuals from certain backgrounds while disadvantaging those from different cultures or socio-economic statuses.

The questions and content of IQ tests often reflect the experiences and knowledge that are more commonly found in mainstream Western culture, making it challenging for individuals from diverse cultural backgrounds to perform at their full potential.

Another concern is the phenomenon of stereotype threat, which refers to the fear of confirming negative stereotypes about one's own group. It has been found that individuals who belong to stigmatized groups, such as ethnic minorities or women in STEM fields, may experience heightened anxiety and perform worse on IQ tests due to the pressure of confirming negative stereotypes.

Furthermore, there is an ongoing debate surrounding the very definition and use of intelligence. Some argue that intelligence cannot be adequately captured by a single IQ score and that it is a multidimensional concept with various aspects, such as emotional intelligence, practical intelligence, and creative intelligence. This perspective challenges the narrow focus on cognitive abilities that traditional IQ tests emphasize.

Over time, IQ testing has evolved through the contributions of prominent psychologists . William Stern introduced the concept of the intelligence quotient (IQ) and popularized its use.

Alfred Binet and Theodore Simon developed the Binet-Simon scale, which laid the foundation for modern IQ tests. James McKeen Cattell and Clark Wissler continued the work, bringing the Galtonian tradition of intelligence testing to the United States.

Criticisms of intelligence testing highlight issues of cultural biases, stereotype threat, and the limited scope of traditional IQ tests. The field of intelligence testing has evolved, influenced by psychologists such as William Stern, Alfred Binet, James McKeen Cattell , and Clark Wissler.

Recognizing the diverse traditions and challenges in intelligence testing is crucial for developing more inclusive and accurate ways to assess intellectual abilities.

Changing Perspectives of Intelligence in Children

In the face of rapid technological advances and evolving workplace dynamics, our understanding of intelligence is being reshaped. Theories of intelligence have traditionally been dominated by psychometric views, focusing on cognitive abilities measured by standardised tests. However, these tests may not fully capture the breadth of human intelligence.

They often overlook existential intelligence, the capacity to ponder deep questions about existence, and other types of intelligence that are crucial in daily life.

For instance, consider a student with an exceptional musical ability or athletic ability. These talents are forms of intelligence, yet they are not typically assessed in academic settings. As educators, we must broaden our perspective and recognise these diverse mental abilities.

One study found that musical training can enhance verbal intelligence and executive functions, illustrating the interconnectedness of different intelligence factors.

The philosopher Howard Gardner proposed one of the major theories that challenges the traditional view. He suggested that humans have multiple intelligences, each relatively independent but all contributing to one's overall intellectual capacity. This perspective encourages us to appreciate the unique strengths of each student.

However, this shift in understanding poses a challenge: how do we measure academic achievement in a way that reflects this broader conception of intelligence?

As the renowned educational researcher Dr. Linda Darling-Hammond stated, "We must shift from 'a paradigm of testing' to 'a paradigm of teaching'". This implies a move towards more holistic, formative assessments that value creativity, critical thinking, and problem-solving skills.

In conclusion, embracing a multifaceted understanding of intelligence can enrich our teaching practices and provide a more inclusive , equitable learning environment. It's time to rethink how we define and measure intelligence in the classroom.

Enhance Learner Outcomes Across Your School

Download an Overview of our Support and Resources

We'll send it over now.

Please fill in the details so we can send over the resources.

What type of school are you?

We'll get you the right resource

Is your school involved in any staff development projects?

Are your colleagues running any research projects or courses?

Do you have any immediate school priorities?

Please check the ones that apply.

Download your resource

Thanks for taking the time to complete this form, submit the form to get the tool.

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

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

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

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

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

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

7.1. Different kinds of thought

7.2. Reasoning and Judgment

7.3. Problem Solving

READING WITH PURPOSE

Remember and understand.

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

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

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

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

Analyze, Evaluate, and Create

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

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

7.1. Different kinds of thought and knowledge

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

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

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

Factual and conceptual knowledge

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

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

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

Procedural knowledge

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

Metacognitive knowledge

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

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

The Dunning-Kruger Effect

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

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

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

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

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

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

Critical thinking

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

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

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

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

A Critical Thinker’s Toolkit 

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

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

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

Here are some common sources of biases:

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

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

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

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

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

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

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

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

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

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

bias : an inclination, tendency, leaning, or prejudice

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

7.2 Reasoning and Judgment

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

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

Deductive reasoning

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

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

Statement 2: You get an A on the final exam

Conclusion: You will get an A for the course

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

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

therefore q

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

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

I won’t have pizza (not p)

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

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

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

if p, then q

therefore, not p

Concrete version:

If I eat dinner, then I will have dessert

I did not have dessert

Therefore, I did not eat dinner

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

Students who like school study a lot

Students who study a lot get good grades

Jane does not like school

Therefore, Jane does not get good grades

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

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

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

You are not eleven feet tall

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

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

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

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

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

Inductive reasoning and judgment

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

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

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

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

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

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

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

Statement #1: Psychology is not my best subject

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

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

Judgment: The next exam will probably be very difficult.

Decision: I will study tonight instead of watching Netflix.

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

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

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

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

Statement #1: It is late at night.

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

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

Judgment: Albert will have no difficulty walking home.

Decision: He walks home alone.

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

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

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

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

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

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

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

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

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

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

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

Judgment: Breast cancer is the most common type.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

7.3 Problem Solving

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

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

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

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

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

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

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

Defining and Mentally Representing Problems in Order to Solve Them

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

insight :  a sudden realization of a solution to a problem

Solving Problems by Trial and Error

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

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

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

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

Solving Problems with Algorithms and Heuristics

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

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

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

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

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

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

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

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

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

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

An Effective Problem-Solving Sequence

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

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

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

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

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

a mental representation of a category of things in the world

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

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

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

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

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

an inclination, tendency, leaning, or prejudice

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

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

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

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

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

fast, automatic, and emotional thinking

slow, effortful, and logical thinking

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

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

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

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

noticing, comprehending and forming a mental conception of a problem

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

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

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

a sudden realization of a solution to a problem

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

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

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

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

Share This Book

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Students’ logical-mathematical intelligence through the problem-solving approach

2020, Journal of Physics: Conference Series

Logical-mathematical intelligence is one of the most dominant components of multiple intelligences in mathematics learning because it can be built in all topics in mathematics. Logical-mathematical intelligence is the ability of students in terms of numbers and logic, which involves the skills to process words and numbers, to use logic and analyze problems logically, to find formulas and to do investigations scientifically. The purpose of this study is to describe the logical-mathematical abilities of high school students. A total of 25 seventh-grade students in a junior high school in Banda Aceh participated in this study, but only three of them, with high, medium, and low criteria of logical-mathematical intelligence based on the test results, were selected to observe and analyze their logical-mathematical abilities. Data were conducted from a test and interview. The instrument used in this study was a student test sheet. The results showed that only a small number of students (th...

Related Papers

ijifr journal

The logical mathematical intelligence is the most securely documented of the intelligence. This intelligence derives from the handling of objects, grows into the ability to think concretely about those objects, then develops into the ability to think concretely about those objects, and then develops into the ability to think formally of relations without objects. Problem solving is a process by which an individual uses previously acquired knowledge, understanding, and skill to satisfy the demands of an unfamiliar situation. This study focus on the logical intelligence and problem solving ability in mathematics among secondary school students. Normative survey method was used for the research. Sample includes secondary students. Stratified sampling technique was used. The statistical technique used was correlation and t test. The hypotheses state that. 1) There will be significant correlation between logical intelligence and problem solving ability of secondary school students; 2) There will not be significant difference between male and female students in their logical intelligence Emotional intelligence & 3) There will not be significant difference between male and female students in their problem solving ability.. 1. NEED AND SIGNIFICANCE OF THE STUDY Logical – mathematical intelligence is the ability to calculate, quantify, consider propositions and hypotheses, and carry out complete mathematical operations. Problem solving is a deliberate or purposeful act on the part of an individual to realize the set of goals by inventing some novel methods or systematically following some planned steps for the removal of interferences of the obstacles in the path. Problem solving is an important strategy in mathematics learning. Logical/mathematical intelligence involves

Aan Subhan Pamungkas

The process of solving problems carried out by students in stages, namely understanding problems, planning solutions, carrying out solutions and checking again. Solving student problems varies according to the basic characteristics of students&#39; interests, talents and potential. Learning will be more optimal if it is adjusted to the intelligence possessed by students. The goal is that teachers can facilitate learning according to the intelligence possessed by students, so the teacher must know the intelligence possessed by students. This research is a qualitative study using two subjects, namely the subject of linguistics and the subject of mathematical logic. The results showed that at the problem-understanding stage, SLM completed using formulas, completed according to plan and checked by recalculating. SL uses more trial-and-error reasoning, understanding information by reading sentences quickly as well as checking again.

CERN European Organization for Nuclear Research - Zenodo

Renuka Sonny

Journal of Educational and Social Research

rommel alali

This study discussed the level of logical mathematical intelligence of pre-service female mathematics teachers. The problem arises in adopting traditional curricula for teaching mathematics, which leads to low student achievement. The study objectives to measure the students&#39; level of logical mathematical intelligence, and find out the level of students’ achievement, and measuring the level of intelligence impact on the academic achievement. The study adopted the descriptive-analytical approach. The study population consisted of (45) pre-service female math teachers. A comprehensive sample was chosen. A questionnaire was used according to the (Likert) five-point scale, taking advantage of the MIDAS scale of multiple intelligences, which consisted of (17) statements, then the researchers developed the questionnaire up to (25) statements. The validity and reliability of the questionnaire were confirmed. The findings revealed that: The general average of the logical-mathematical in...

Salman Daoud

This paper shows a new method to develop the Logical-Mathematical Intelligence of the students by using the logical concepts and entities of Information Technology (IT), a far cry from the traditional methods using Mathematics or other topics. The first idea of our method is to set forth a new concept and design a scheme that shows the relationship between the eight types of intelligences adopted by Howard Gardner in his theory (Multiple-Intelligences Theory). Depending on this theory, we have classified the human mind into two types: Complex Mind and Non-Complex Mind. The second idea, based on the first idea, we have designed a new model called the " Logical-Analytical Model ". This model illustrates a new way to develop the Logical-Mathematical Intelligence of the students. The goal of our method is to move the students, owners of the Non-Complex mind, to become students, owners of a Complex Mind. As well as, to increase the degree of intelligence of the students owners of a Complex Mind, to more high level than they are used to.

Prima: Jurnal Pendidikan Matematika

Dadang Juandi

This research is based on the importance of logical-mathematical thinking skills in solving logical-mathematical problems. The research purpose is to describe high school students&#39; logical thinking abilities on geometric transformation material in terms of mathematical self-concepts. The research used a qualitative approach, with the research subject as many as six students of 12th grades science class from one of Bandung Regency high schools selected by sampling technique. Students&#39; logical thinking ability is known from the test scores in solving compiled problems. The score refers to logical-mathematical thinking ability indicators, and the problem-solving technique refers to the Polya stages. Data analysis techniques used are data reduction, data presentation, descriptive statistical calculations, and conclusions/verification. The results showed that the overall students’ logical-mathematical thinking ability in the geometry transformation material is in the medium categ...

melkior wewe

This study aims to find out the difference between the model of problem-based learning and the mathematical-logical intelligence towards mathematics learning achievement. This study is a true experimental with specific design of post-test only control group design. The population of this study are all fourth grade students of primary schools in Bajawa sub district. Meanwhile, the sample in this study is determined through random sampling. The result of analysis, it is gained that the learning achievement which used problem based learning model is higher than the mathematics learning achievement of the students with the conventional learning technique. The calculation from two ways ANAVA results in Fobs 1.793 with sig = 0.184, there is no significant effect of learning interaction model and mathematic-logical intelligence. Since there is no interaction, it also means that there is no significant effect of problem based learning collaborated with mathematic-logical intelligence to the...

Journal of legal and social studies

Boumediene Senouci

The study aimed to determine level of logical-mathematical intelligence among middle school students, the study sample consists of (200) student from middle school, and to achieve the objective of the study the researchers use logical-mathematical intelligence scale, after collecting and processing information statistically using the statistical package for social science spss, the researchers reached the following results:-there are three levels (weak, medium and high) of logical-mathematical intelligence among middle school students.-there differences in logical-mathematical intelligence among middle school students due to the variable of gender.-there differences in logical-mathematical intelligences among intermediate school students due to the variable of study level.-there an interaction between age and gender in logical-mathematical intelligence among middle school students.

Indonesian Journal of Science and Mathematics Education

warli warli

Problem solving is one of the most important skills for students. Meanwhile, logical thinking is the ability to solve problems by relying on mental abilities. The purpose of this research is to describe the problem solving process of students with different levels of logical thinking. This research is an exploratory qualitative research involving eighth grade students of SMP N 5 Tuban who have different levels of logical thinking as research subjects. The subjects who were interviewed were 4 students. Instruments to measure the level of logical thinking used The Group Assessment of Logical Thinking (GALT) while exploring the process of solving problems using the stages of entry, attack, and review. The results of the analysis show that students with high logical thinking skills meet the entry, attack, and review stage. Students with low logical thinking skills meet the entry stage in ‘know’ and ‘want’ aspects only, at the attack stage they only meet the try and possible aspects, and...

Rahmah Johar

Idawani, Rahmah Johar, Cut Morina Zubainur Abstract—Problem-solving is one of the skills required by 21-century students. Several students&#39; intelligences that can strengthen their problemsolving skill is known as multiple intelligences. The various intelligence leads students to use different strategies in solving a problem. This study employed descriptive research with a quantitative approach to study the students’ strategies in solving a mathematics problem based on their multiple intelligences. In this study, students’ multiple intelligences were investigated through multiple intelligences profiling questionnaire VII (MIPQ VII). Further, an interview was conducted to collect the data of the students’ problem-solving strategies. Twenty-nine students in one of the junior high schools in Banda Aceh participated in the study. The results revealed that there was a variety of intelligence among the students in Aceh. Students with intrapersonal intelligence tended to use the strateg...

RELATED PAPERS

Archivos de …

Mario Alonso-Vanegas

Ahmed Menshawy

Fetty Asmaniati

Giulia Brandolini

International Kimberlite Conference Extended Abstracts: 2008

Kelly Russell

Ogrody Nauk i Sztuk

Weronika Kocela

medigraphic.com

José de Jesús Coria Lorenzo

Proceedings of the VIII Simpósio Brasileiro e Geofísica

Ferdous Aktar

Charlotte Berg

THETA: Jurnal Pendidikan Matematika

Rahmatya Nurmeidina

ACS Applied Nano Materials

Jyoti Kataria

Journal of Blood Medicine

Enoch Muwanguzi

Anne Lorin de Reure

Experimental parasitology

Caroline Wagner

Jurnal Veteriner

henni syawal

Cyril Brochon

Jurnal Geliga Sains: Jurnal Pendidikan Fisika

Kostan Mataubenu

Biophysical Journal

Mohit Kumar

Matthew Overturf

Human-centric Computing and Information Sciences

Abdul Rehman Abbasi

Jurnal Sains dan Edukasi Sains

Tahirah UIM

Louis Walckiers

买莫纳什大学毕业证书成绩单 澳洲Monash文凭学位证书

The Journal of Urology

Lance A Mynderse

Ericka Leon

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

Please log in to save materials. Log in

• Anchoring Bias
• Availability Heuristic
• Confirmation Bias
• Functional Fixedness
• Hindsight Bias
• Problem-solving Strategy
• Representative Bias
• Trial and Error
• Working Backwards

Problem Solving

• Describe problem solving strategies
• Define algorithm and heuristic
• Explain some common roadblocks to effective problem solving

People face problems every day—usually, multiple problems throughout the day. Sometimes these problems are straightforward: To double a recipe for pizza dough, for example, all that is required is that each ingredient in the recipe be doubled. Sometimes, however, the problems we encounter are more complex. For example, say you have a work deadline, and you must mail a printed copy of a report to your supervisor by the end of the business day. The report is time-sensitive and must be sent overnight. You finished the report last night, but your printer will not work today. What should you do? First, you need to identify the problem and then apply a strategy for solving the problem.

PROBLEM-SOLVING STRATEGIES

When you are presented with a problem—whether it is a complex mathematical problem or a broken printer, how do you solve it? Before finding a solution to the problem, the problem must first be clearly identified. After that, one of many problem solving strategies can be applied, hopefully resulting in a solution.

A problem-solving strategy is a plan of action used to find a solution. Different strategies have different action plans associated with them ( Table ). For example, a well-known strategy is trial and error . The old adage, “If at first you don’t succeed, try, try again” describes trial and error. In terms of your broken printer, you could try checking the ink levels, and if that doesn’t work, you could check to make sure the paper tray isn’t jammed. Or maybe the printer isn’t actually connected to your laptop. When using trial and error, you would continue to try different solutions until you solved your problem. Although trial and error is not typically one of the most time-efficient strategies, it is a commonly used one.

Another type of strategy is an algorithm. An algorithm is a problem-solving formula that provides you with step-by-step instructions used to achieve a desired outcome (Kahneman, 2011). You can think of an algorithm as a recipe with highly detailed instructions that produce the same result every time they are performed. Algorithms are used frequently in our everyday lives, especially in computer science. When you run a search on the Internet, search engines like Google use algorithms to decide which entries will appear first in your list of results. Facebook also uses algorithms to decide which posts to display on your newsfeed. Can you identify other situations in which algorithms are used?

A heuristic is another type of problem solving strategy. While an algorithm must be followed exactly to produce a correct result, a heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. A “rule of thumb” is an example of a heuristic. Such a rule saves the person time and energy when making a decision, but despite its time-saving characteristics, it is not always the best method for making a rational decision. Different types of heuristics are used in different types of situations, but the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):

• When one is faced with too much information
• When the time to make a decision is limited
• When the decision to be made is unimportant
• When there is access to very little information to use in making the decision
• When an appropriate heuristic happens to come to mind in the same moment

Working backwards is a useful heuristic in which you begin solving the problem by focusing on the end result. Consider this example: You live in Washington, D.C. and have been invited to a wedding at 4 PM on Saturday in Philadelphia. Knowing that Interstate 95 tends to back up any day of the week, you need to plan your route and time your departure accordingly. If you want to be at the wedding service by 3:30 PM, and it takes 2.5 hours to get to Philadelphia without traffic, what time should you leave your house? You use the working backwards heuristic to plan the events of your day on a regular basis, probably without even thinking about it.

Another useful heuristic is the practice of accomplishing a large goal or task by breaking it into a series of smaller steps. Students often use this common method to complete a large research project or long essay for school. For example, students typically brainstorm, develop a thesis or main topic, research the chosen topic, organize their information into an outline, write a rough draft, revise and edit the rough draft, develop a final draft, organize the references list, and proofread their work before turning in the project. The large task becomes less overwhelming when it is broken down into a series of small steps.

Solving Puzzles

Problem-solving abilities can improve with practice. Many people challenge themselves every day with puzzles and other mental exercises to sharpen their problem-solving skills. Sudoku puzzles appear daily in most newspapers. Typically, a sudoku puzzle is a 9×9 grid. The simple sudoku below ( Figure ) is a 4×4 grid. To solve the puzzle, fill in the empty boxes with a single digit: 1, 2, 3, or 4. Here are the rules: The numbers must total 10 in each bolded box, each row, and each column; however, each digit can only appear once in a bolded box, row, and column. Time yourself as you solve this puzzle and compare your time with a classmate.

Here is another popular type of puzzle ( Figure ) that challenges your spatial reasoning skills. Connect all nine dots with four connecting straight lines without lifting your pencil from the paper:

Take a look at the “Puzzling Scales” logic puzzle below ( Figure ). Sam Loyd, a well-known puzzle master, created and refined countless puzzles throughout his lifetime (Cyclopedia of Puzzles, n.d.).

PITFALLS TO PROBLEM SOLVING

Not all problems are successfully solved, however. What challenges stop us from successfully solving a problem? Albert Einstein once said, “Insanity is doing the same thing over and over again and expecting a different result.” Imagine a person in a room that has four doorways. One doorway that has always been open in the past is now locked. The person, accustomed to exiting the room by that particular doorway, keeps trying to get out through the same doorway even though the other three doorways are open. The person is stuck—but she just needs to go to another doorway, instead of trying to get out through the locked doorway. A mental set is where you persist in approaching a problem in a way that has worked in the past but is clearly not working now.

Functional fixedness is a type of mental set where you cannot perceive an object being used for something other than what it was designed for. During the Apollo 13 mission to the moon, NASA engineers at Mission Control had to overcome functional fixedness to save the lives of the astronauts aboard the spacecraft. An explosion in a module of the spacecraft damaged multiple systems. The astronauts were in danger of being poisoned by rising levels of carbon dioxide because of problems with the carbon dioxide filters. The engineers found a way for the astronauts to use spare plastic bags, tape, and air hoses to create a makeshift air filter, which saved the lives of the astronauts.

Check out this Apollo 13 scene where the group of NASA engineers are given the task of overcoming functional fixedness.

Researchers have investigated whether functional fixedness is affected by culture. In one experiment, individuals from the Shuar group in Ecuador were asked to use an object for a purpose other than that for which the object was originally intended. For example, the participants were told a story about a bear and a rabbit that were separated by a river and asked to select among various objects, including a spoon, a cup, erasers, and so on, to help the animals. The spoon was the only object long enough to span the imaginary river, but if the spoon was presented in a way that reflected its normal usage, it took participants longer to choose the spoon to solve the problem. (German & Barrett, 2005). The researchers wanted to know if exposure to highly specialized tools, as occurs with individuals in industrialized nations, affects their ability to transcend functional fixedness. It was determined that functional fixedness is experienced in both industrialized and nonindustrialized cultures (German & Barrett, 2005).

In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. Sometimes, however, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the $2,000 home? Why would the realtor show you the run-down houses and the nice house? The realtor may be challenging your anchoring bias. An anchoring bias occurs when you focus on one piece of information when making a decision or solving a problem. In this case, you’re so focused on the amount of money you are willing to spend that you may not recognize what kinds of houses are available at that price point.

The confirmation bias is the tendency to focus on information that confirms your existing beliefs. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Representative bias describes a faulty way of thinking, in which you unintentionally stereotype someone or something; for example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.

Finally, the availability heuristic is a heuristic in which you make a decision based on an example, information, or recent experience that is that readily available to you, even though it may not be the best example to inform your decision . Biases tend to “preserve that which is already established—to maintain our preexisting knowledge, beliefs, attitudes, and hypotheses” (Aronson, 1995; Kahneman, 2011). These biases are summarized in Table .

Please visit this site to see a clever music video that a high school teacher made to explain these and other cognitive biases to his AP psychology students.

Were you able to determine how many marbles are needed to balance the scales in Figure ? You need nine. Were you able to solve the problems in Figure and Figure ? Here are the answers ( Figure ).

Many different strategies exist for solving problems. Typical strategies include trial and error, applying algorithms, and using heuristics. To solve a large, complicated problem, it often helps to break the problem into smaller steps that can be accomplished individually, leading to an overall solution. Roadblocks to problem solving include a mental set, functional fixedness, and various biases that can cloud decision making skills.

Review Questions

A specific formula for solving a problem is called ________.

• an algorithm
• a heuristic
• a mental set
• trial and error

A mental shortcut in the form of a general problem-solving framework is called ________.

Which type of bias involves becoming fixated on a single trait of a problem?

• anchoring bias
• confirmation bias
• representative bias
• availability bias

Which type of bias involves relying on a false stereotype to make a decision?

Critical Thinking Questions

What is functional fixedness and how can overcoming it help you solve problems?

Functional fixedness occurs when you cannot see a use for an object other than the use for which it was intended. For example, if you need something to hold up a tarp in the rain, but only have a pitchfork, you must overcome your expectation that a pitchfork can only be used for garden chores before you realize that you could stick it in the ground and drape the tarp on top of it to hold it up.

How does an algorithm save you time and energy when solving a problem?

An algorithm is a proven formula for achieving a desired outcome. It saves time because if you follow it exactly, you will solve the problem without having to figure out how to solve the problem. It is a bit like not reinventing the wheel.

Personal Application Question

Which type of bias do you recognize in your own decision making processes? How has this bias affected how you’ve made decisions in the past and how can you use your awareness of it to improve your decisions making skills in the future?