what is the difference between critical thinking and inference

• Content Is Thinking, Thinking is Content
• Critical Thinking in Every Domain of Knowledge and Belief
• Using Intellectual Standards to Assess Student Reasoning
• Open-minded inquiry
• Valuable Intellectual Traits
• Universal Intellectual Standards
• Thinking With Concepts
• The Analysis & Assessment of Thinking
• Glossary of Critical Thinking Terms
• Distinguishing Between Inert Information, Activated Ignorance, Activated Knowledge
• Critical Thinking: Identifying the Targets

Distinguishing Between Inferences and Assumptions

• Critical Thinking Development: A Stage Theory
• Becoming a Critic Of Your Thinking
• Bertrand Russell on Critical Thinking

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Critical Thinking

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

2.1 Dewey’s Three Main Examples

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

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

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

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

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

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

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

2. Examples and Non-Examples

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

If the core of critical thinking is careful goal-directed thinking, conceptions of it can vary according to its presumed scope, its presumed goal, one’s criteria and threshold for being careful, and the thinking component on which one focuses. As to its scope, some conceptions (e.g., Dewey 1910, 1933) restrict it to constructive thinking on the basis of one’s own observations and experiments, others (e.g., Ennis 1962; Fisher & Scriven 1997; Johnson 1992) to appraisal of the products of such thinking. Ennis (1991) and Bailin et al. (1999b) take it to cover both construction and appraisal. As to its goal, some conceptions restrict it to forming a judgment (Dewey 1910, 1933; Lipman 1987; Facione 1990a). Others allow for actions as well as beliefs as the end point of a process of critical thinking (Ennis 1991; Bailin et al. 1999b). As to the criteria and threshold for being careful, definitions vary in the term used to indicate that critical thinking satisfies certain norms: “intellectually disciplined” (Scriven & Paul 1987), “reasonable” (Ennis 1991), “skillful” (Lipman 1987), “skilled” (Fisher & Scriven 1997), “careful” (Bailin & Battersby 2009). Some definitions specify these norms, referring variously to “consideration of any belief or supposed form of knowledge in the light of the grounds that support it and the further conclusions to which it tends” (Dewey 1910, 1933); “the methods of logical inquiry and reasoning” (Glaser 1941); “conceptualizing, applying, analyzing, synthesizing, and/or evaluating information gathered from, or generated by, observation, experience, reflection, reasoning, or communication” (Scriven & Paul 1987); the requirement that “it is sensitive to context, relies on criteria, and is self-correcting” (Lipman 1987); “evidential, conceptual, methodological, criteriological, or contextual considerations” (Facione 1990a); and “plus-minus considerations of the product in terms of appropriate standards (or criteria)” (Johnson 1992). Stanovich and Stanovich (2010) propose to ground the concept of critical thinking in the concept of rationality, which they understand as combining epistemic rationality (fitting one’s beliefs to the world) and instrumental rationality (optimizing goal fulfillment); a critical thinker, in their view, is someone with “a propensity to override suboptimal responses from the autonomous mind” (2010: 227). These variant specifications of norms for critical thinking are not necessarily incompatible with one another, and in any case presuppose the core notion of thinking carefully. As to the thinking component singled out, some definitions focus on suspension of judgment during the thinking (Dewey 1910; McPeck 1981), others on inquiry while judgment is suspended (Bailin & Battersby 2009, 2021), others on the resulting judgment (Facione 1990a), and still others on responsiveness to reasons (Siegel 1988). Kuhn (2019) takes critical thinking to be more a dialogic practice of advancing and responding to arguments than an individual ability.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

8. Critical Thinking Dispositions

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

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

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

Facione (1990a: 25) divides “affective dispositions” of critical thinking into approaches to life and living in general and approaches to specific issues, questions or problems. Adapting this distinction, one can usefully divide critical thinking dispositions into initiating dispositions (those that contribute causally to starting to think critically about an issue) and internal dispositions (those that contribute causally to doing a good job of thinking critically once one has started). The two categories are not mutually exclusive. For example, open-mindedness, in the sense of willingness to consider alternative points of view to one’s own, is both an initiating and an internal disposition.

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

• Attentiveness : One will not think critically if one fails to recognize an issue that needs to be thought through. For example, the pedestrian in Weather would not have looked up if he had not noticed that the air was suddenly cooler. To be a critical thinker, then, one needs to be habitually attentive to one’s surroundings, noticing not only what one senses but also sources of perplexity in messages received and in one’s own beliefs and attitudes (Facione 1990a: 25; Facione, Facione, & Giancarlo 2001).
• Habit of inquiry : Inquiry is effortful, and one needs an internal push to engage in it. For example, the student in Bubbles could easily have stopped at idle wondering about the cause of the bubbles rather than reasoning to a hypothesis, then designing and executing an experiment to test it. Thus willingness to think critically needs mental energy and initiative. What can supply that energy? Love of inquiry, or perhaps just a habit of inquiry. Hamby (2015) has argued that willingness to inquire is the central critical thinking virtue, one that encompasses all the others. It is recognized as a critical thinking disposition by Dewey (1910: 29; 1933: 35), Glaser (1941: 5), Ennis (1987: 12; 1991: 8), Facione (1990a: 25), Bailin et al. (1999b: 294), Halpern (1998: 452), and Facione, Facione, & Giancarlo (2001).
• Self-confidence : Lack of confidence in one’s abilities can block critical thinking. For example, if the woman in Rash lacked confidence in her ability to figure things out for herself, she might just have assumed that the rash on her chest was the allergic reaction to her medication against which the pharmacist had warned her. Thus willingness to think critically requires confidence in one’s ability to inquire (Facione 1990a: 25; Facione, Facione, & Giancarlo 2001).
• Courage : Fear of thinking for oneself can stop one from doing it. Thus willingness to think critically requires intellectual courage (Paul & Elder 2006: 16).
• Open-mindedness : A dogmatic attitude will impede thinking critically. For example, a person who adheres rigidly to a “pro-choice” position on the issue of the legal status of induced abortion is likely to be unwilling to consider seriously the issue of when in its development an unborn child acquires a moral right to life. Thus willingness to think critically requires open-mindedness, in the sense of a willingness to examine questions to which one already accepts an answer but which further evidence or reasoning might cause one to answer differently (Dewey 1933; Facione 1990a; Ennis 1991; Bailin et al. 1999b; Halpern 1998, Facione, Facione, & Giancarlo 2001). Paul (1981) emphasizes open-mindedness about alternative world-views, and recommends a dialectical approach to integrating such views as central to what he calls “strong sense” critical thinking. In three studies, Haran, Ritov, & Mellers (2013) found that actively open-minded thinking, including “the tendency to weigh new evidence against a favored belief, to spend sufficient time on a problem before giving up, and to consider carefully the opinions of others in forming one’s own”, led study participants to acquire information and thus to make accurate estimations.
• Willingness to suspend judgment : Premature closure on an initial solution will block critical thinking. Thus willingness to think critically requires a willingness to suspend judgment while alternatives are explored (Facione 1990a; Ennis 1991; Halpern 1998).
• Trust in reason : Since distrust in the processes of reasoned inquiry will dissuade one from engaging in it, trust in them is an initiating critical thinking disposition (Facione 1990a, 25; Bailin et al. 1999b: 294; Facione, Facione, & Giancarlo 2001; Paul & Elder 2006). In reaction to an allegedly exclusive emphasis on reason in critical thinking theory and pedagogy, Thayer-Bacon (2000) argues that intuition, imagination, and emotion have important roles to play in an adequate conception of critical thinking that she calls “constructive thinking”. From her point of view, critical thinking requires trust not only in reason but also in intuition, imagination, and emotion.
• Seeking the truth : If one does not care about the truth but is content to stick with one’s initial bias on an issue, then one will not think critically about it. Seeking the truth is thus an initiating critical thinking disposition (Bailin et al. 1999b: 294; Facione, Facione, & Giancarlo 2001). A disposition to seek the truth is implicit in more specific critical thinking dispositions, such as trying to be well-informed, considering seriously points of view other than one’s own, looking for alternatives, suspending judgment when the evidence is insufficient, and adopting a position when the evidence supporting it is sufficient.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

We can derive a short list of concepts whose understanding contributes to critical thinking from the critical thinking abilities described in the preceding section. Observational abilities require an understanding of the difference between observation and inference. Questioning abilities require an understanding of the concepts of ambiguity and vagueness. Inferential abilities require an understanding of the difference between conclusive and defeasible inference (traditionally, between deduction and induction), as well as of the difference between necessary and sufficient conditions. Experimenting abilities require an understanding of the concepts of hypothesis, null hypothesis, assumption and prediction, as well as of the concept of statistical significance and of its difference from importance. They also require an understanding of the difference between an experiment and an observational study, and in particular of the difference between a randomized controlled trial, a prospective correlational study and a retrospective (case-control) study. Argument analysis abilities require an understanding of the concepts of argument, premiss, assumption, conclusion and counter-consideration. Additional critical thinking concepts are proposed by Bailin et al. (1999b: 293), Fisher & Scriven (1997: 105–106), Black (2012), and Blair (2021).

According to Glaser (1941: 25), ability to think critically requires knowledge of the methods of logical inquiry and reasoning. If we review the list of abilities in the preceding section, however, we can see that some of them can be acquired and exercised merely through practice, possibly guided in an educational setting, followed by feedback. Searching intelligently for a causal explanation of some phenomenon or event requires that one consider a full range of possible causal contributors, but it seems more important that one implements this principle in one’s practice than that one is able to articulate it. What is important is “operational knowledge” of the standards and principles of good thinking (Bailin et al. 1999b: 291–293). But the development of such critical thinking abilities as designing an experiment or constructing an operational definition can benefit from learning their underlying theory. Further, explicit knowledge of quirks of human thinking seems useful as a cautionary guide. Human memory is not just fallible about details, as people learn from their own experiences of misremembering, but is so malleable that a detailed, clear and vivid recollection of an event can be a total fabrication (Loftus 2017). People seek or interpret evidence in ways that are partial to their existing beliefs and expectations, often unconscious of their “confirmation bias” (Nickerson 1998). Not only are people subject to this and other cognitive biases (Kahneman 2011), of which they are typically unaware, but it may be counter-productive for one to make oneself aware of them and try consciously to counteract them or to counteract social biases such as racial or sexual stereotypes (Kenyon & Beaulac 2014). It is helpful to be aware of these facts and of the superior effectiveness of blocking the operation of biases—for example, by making an immediate record of one’s observations, refraining from forming a preliminary explanatory hypothesis, blind refereeing, double-blind randomized trials, and blind grading of students’ work. It is also helpful to be aware of the prevalence of “noise” (unwanted unsystematic variability of judgments), of how to detect noise (through a noise audit), and of how to reduce noise: make accuracy the goal, think statistically, break a process of arriving at a judgment into independent tasks, resist premature intuitions, in a group get independent judgments first, favour comparative judgments and scales (Kahneman, Sibony, & Sunstein 2021). It is helpful as well to be aware of the concept of “bounded rationality” in decision-making and of the related distinction between “satisficing” and optimizing (Simon 1956; Gigerenzer 2001).

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

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

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

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

12. Controversies

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

McPeck (1981) attacked the thinking skills movement of the 1970s, including the critical thinking movement. He argued that there are no general thinking skills, since thinking is always thinking about some subject-matter. It is futile, he claimed, for schools and colleges to teach thinking as if it were a separate subject. Rather, teachers should lead their pupils to become autonomous thinkers by teaching school subjects in a way that brings out their cognitive structure and that encourages and rewards discussion and argument. As some of his critics (e.g., Paul 1985; Siegel 1985) pointed out, McPeck’s central argument needs elaboration, since it has obvious counter-examples in writing and speaking, for which (up to a certain level of complexity) there are teachable general abilities even though they are always about some subject-matter. To make his argument convincing, McPeck needs to explain how thinking differs from writing and speaking in a way that does not permit useful abstraction of its components from the subject-matters with which it deals. He has not done so. Nevertheless, his position that the dispositions and abilities of a critical thinker are best developed in the context of subject-matter instruction is shared by many theorists of critical thinking, including Dewey (1910, 1933), Glaser (1941), Passmore (1980), Weinstein (1990), Bailin et al. (1999b), and Willingham (2019).

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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• v.17(1); Spring 2018

Understanding the Complex Relationship between Critical Thinking and Science Reasoning among Undergraduate Thesis Writers

Jason e. dowd.

† Department of Biology, Duke University, Durham, NC 27708

Robert J. Thompson, Jr.

‡ Department of Psychology and Neuroscience, Duke University, Durham, NC 27708

Leslie A. Schiff

§ Department of Microbiology and Immunology, University of Minnesota, Minneapolis, MN 55455

Julie A. Reynolds

Associated data.

This study empirically examines the relationship between students’ critical-thinking skills and scientific reasoning as reflected in undergraduate thesis writing in biology. Writing offers a unique window into studying this relationship, and the findings raise potential implications for instruction.

Developing critical-thinking and scientific reasoning skills are core learning objectives of science education, but little empirical evidence exists regarding the interrelationships between these constructs. Writing effectively fosters students’ development of these constructs, and it offers a unique window into studying how they relate. In this study of undergraduate thesis writing in biology at two universities, we examine how scientific reasoning exhibited in writing (assessed using the Biology Thesis Assessment Protocol) relates to general and specific critical-thinking skills (assessed using the California Critical Thinking Skills Test), and we consider implications for instruction. We find that scientific reasoning in writing is strongly related to inference , while other aspects of science reasoning that emerge in writing (epistemological considerations, writing conventions, etc.) are not significantly related to critical-thinking skills. Science reasoning in writing is not merely a proxy for critical thinking. In linking features of students’ writing to their critical-thinking skills, this study 1) provides a bridge to prior work suggesting that engagement in science writing enhances critical thinking and 2) serves as a foundational step for subsequently determining whether instruction focused explicitly on developing critical-thinking skills (particularly inference ) can actually improve students’ scientific reasoning in their writing.

INTRODUCTION

Critical-thinking and scientific reasoning skills are core learning objectives of science education for all students, regardless of whether or not they intend to pursue a career in science or engineering. Consistent with the view of learning as construction of understanding and meaning ( National Research Council, 2000 ), the pedagogical practice of writing has been found to be effective not only in fostering the development of students’ conceptual and procedural knowledge ( Gerdeman et al. , 2007 ) and communication skills ( Clase et al. , 2010 ), but also scientific reasoning ( Reynolds et al. , 2012 ) and critical-thinking skills ( Quitadamo and Kurtz, 2007 ).

Critical thinking and scientific reasoning are similar but different constructs that include various types of higher-order cognitive processes, metacognitive strategies, and dispositions involved in making meaning of information. Critical thinking is generally understood as the broader construct ( Holyoak and Morrison, 2005 ), comprising an array of cognitive processes and dispostions that are drawn upon differentially in everyday life and across domains of inquiry such as the natural sciences, social sciences, and humanities. Scientific reasoning, then, may be interpreted as the subset of critical-thinking skills (cognitive and metacognitive processes and dispositions) that 1) are involved in making meaning of information in scientific domains and 2) support the epistemological commitment to scientific methodology and paradigm(s).

Although there has been an enduring focus in higher education on promoting critical thinking and reasoning as general or “transferable” skills, research evidence provides increasing support for the view that reasoning and critical thinking are also situational or domain specific ( Beyer et al. , 2013 ). Some researchers, such as Lawson (2010) , present frameworks in which science reasoning is characterized explicitly in terms of critical-thinking skills. There are, however, limited coherent frameworks and empirical evidence regarding either the general or domain-specific interrelationships of scientific reasoning, as it is most broadly defined, and critical-thinking skills.

The Vision and Change in Undergraduate Biology Education Initiative provides a framework for thinking about these constructs and their interrelationship in the context of the core competencies and disciplinary practice they describe ( American Association for the Advancement of Science, 2011 ). These learning objectives aim for undergraduates to “understand the process of science, the interdisciplinary nature of the new biology and how science is closely integrated within society; be competent in communication and collaboration; have quantitative competency and a basic ability to interpret data; and have some experience with modeling, simulation and computational and systems level approaches as well as with using large databases” ( Woodin et al. , 2010 , pp. 71–72). This framework makes clear that science reasoning and critical-thinking skills play key roles in major learning outcomes; for example, “understanding the process of science” requires students to engage in (and be metacognitive about) scientific reasoning, and having the “ability to interpret data” requires critical-thinking skills. To help students better achieve these core competencies, we must better understand the interrelationships of their composite parts. Thus, the next step is to determine which specific critical-thinking skills are drawn upon when students engage in science reasoning in general and with regard to the particular scientific domain being studied. Such a determination could be applied to improve science education for both majors and nonmajors through pedagogical approaches that foster critical-thinking skills that are most relevant to science reasoning.

Writing affords one of the most effective means for making thinking visible ( Reynolds et al. , 2012 ) and learning how to “think like” and “write like” disciplinary experts ( Meizlish et al. , 2013 ). As a result, student writing affords the opportunities to both foster and examine the interrelationship of scientific reasoning and critical-thinking skills within and across disciplinary contexts. The purpose of this study was to better understand the relationship between students’ critical-thinking skills and scientific reasoning skills as reflected in the genre of undergraduate thesis writing in biology departments at two research universities, the University of Minnesota and Duke University.

In the following subsections, we discuss in greater detail the constructs of scientific reasoning and critical thinking, as well as the assessment of scientific reasoning in students’ thesis writing. In subsequent sections, we discuss our study design, findings, and the implications for enhancing educational practices.

Critical Thinking

The advances in cognitive science in the 21st century have increased our understanding of the mental processes involved in thinking and reasoning, as well as memory, learning, and problem solving. Critical thinking is understood to include both a cognitive dimension and a disposition dimension (e.g., reflective thinking) and is defined as “purposeful, self-regulatory judgment which results in interpretation, analysis, evaluation, and inference, as well as explanation of the evidential, conceptual, methodological, criteriological, or contextual considera­tions upon which that judgment is based” ( Facione, 1990, p. 3 ). Although various other definitions of critical thinking have been proposed, researchers have generally coalesced on this consensus: expert view ( Blattner and Frazier, 2002 ; Condon and Kelly-Riley, 2004 ; Bissell and Lemons, 2006 ; Quitadamo and Kurtz, 2007 ) and the corresponding measures of critical-­thinking skills ( August, 2016 ; Stephenson and Sadler-McKnight, 2016 ).

Both the cognitive skills and dispositional components of critical thinking have been recognized as important to science education ( Quitadamo and Kurtz, 2007 ). Empirical research demonstrates that specific pedagogical practices in science courses are effective in fostering students’ critical-thinking skills. Quitadamo and Kurtz (2007) found that students who engaged in a laboratory writing component in the context of a general education biology course significantly improved their overall critical-thinking skills (and their analytical and inference skills, in particular), whereas students engaged in a traditional quiz-based laboratory did not improve their critical-thinking skills. In related work, Quitadamo et al. (2008) found that a community-based inquiry experience, involving inquiry, writing, research, and analysis, was associated with improved critical thinking in a biology course for nonmajors, compared with traditionally taught sections. In both studies, students who exhibited stronger presemester critical-thinking skills exhibited stronger gains, suggesting that “students who have not been explicitly taught how to think critically may not reach the same potential as peers who have been taught these skills” ( Quitadamo and Kurtz, 2007 , p. 151).

Recently, Stephenson and Sadler-McKnight (2016) found that first-year general chemistry students who engaged in a science writing heuristic laboratory, which is an inquiry-based, writing-to-learn approach to instruction ( Hand and Keys, 1999 ), had significantly greater gains in total critical-thinking scores than students who received traditional laboratory instruction. Each of the four components—inquiry, writing, collaboration, and reflection—have been linked to critical thinking ( Stephenson and Sadler-McKnight, 2016 ). Like the other studies, this work highlights the value of targeting critical-thinking skills and the effectiveness of an inquiry-based, writing-to-learn approach to enhance critical thinking. Across studies, authors advocate adopting critical thinking as the course framework ( Pukkila, 2004 ) and developing explicit examples of how critical thinking relates to the scientific method ( Miri et al. , 2007 ).

In these examples, the important connection between writing and critical thinking is highlighted by the fact that each intervention involves the incorporation of writing into science, technology, engineering, and mathematics education (either alone or in combination with other pedagogical practices). However, critical-thinking skills are not always the primary learning outcome; in some contexts, scientific reasoning is the primary outcome that is assessed.

Scientific Reasoning

Scientific reasoning is a complex process that is broadly defined as “the skills involved in inquiry, experimentation, evidence evaluation, and inference that are done in the service of conceptual change or scientific understanding” ( Zimmerman, 2007 , p. 172). Scientific reasoning is understood to include both conceptual knowledge and the cognitive processes involved with generation of hypotheses (i.e., inductive processes involved in the generation of hypotheses and the deductive processes used in the testing of hypotheses), experimentation strategies, and evidence evaluation strategies. These dimensions are interrelated, in that “experimentation and inference strategies are selected based on prior conceptual knowledge of the domain” ( Zimmerman, 2000 , p. 139). Furthermore, conceptual and procedural knowledge and cognitive process dimensions can be general and domain specific (or discipline specific).

With regard to conceptual knowledge, attention has been focused on the acquisition of core methodological concepts fundamental to scientists’ causal reasoning and metacognitive distancing (or decontextualized thinking), which is the ability to reason independently of prior knowledge or beliefs ( Greenhoot et al. , 2004 ). The latter involves what Kuhn and Dean (2004) refer to as the coordination of theory and evidence, which requires that one question existing theories (i.e., prior knowledge and beliefs), seek contradictory evidence, eliminate alternative explanations, and revise one’s prior beliefs in the face of contradictory evidence. Kuhn and colleagues (2008) further elaborate that scientific thinking requires “a mature understanding of the epistemological foundations of science, recognizing scientific knowledge as constructed by humans rather than simply discovered in the world,” and “the ability to engage in skilled argumentation in the scientific domain, with an appreciation of argumentation as entailing the coordination of theory and evidence” ( Kuhn et al. , 2008 , p. 435). “This approach to scientific reasoning not only highlights the skills of generating and evaluating evidence-based inferences, but also encompasses epistemological appreciation of the functions of evidence and theory” ( Ding et al. , 2016 , p. 616). Evaluating evidence-based inferences involves epistemic cognition, which Moshman (2015) defines as the subset of metacognition that is concerned with justification, truth, and associated forms of reasoning. Epistemic cognition is both general and domain specific (or discipline specific; Moshman, 2015 ).

There is empirical support for the contributions of both prior knowledge and an understanding of the epistemological foundations of science to scientific reasoning. In a study of undergraduate science students, advanced scientific reasoning was most often accompanied by accurate prior knowledge as well as sophisticated epistemological commitments; additionally, for students who had comparable levels of prior knowledge, skillful reasoning was associated with a strong epistemological commitment to the consistency of theory with evidence ( Zeineddin and Abd-El-Khalick, 2010 ). These findings highlight the importance of the need for instructional activities that intentionally help learners develop sophisticated epistemological commitments focused on the nature of knowledge and the role of evidence in supporting knowledge claims ( Zeineddin and Abd-El-Khalick, 2010 ).

Scientific Reasoning in Students’ Thesis Writing

Pedagogical approaches that incorporate writing have also focused on enhancing scientific reasoning. Many rubrics have been developed to assess aspects of scientific reasoning in written artifacts. For example, Timmerman and colleagues (2011) , in the course of describing their own rubric for assessing scientific reasoning, highlight several examples of scientific reasoning assessment criteria ( Haaga, 1993 ; Tariq et al. , 1998 ; Topping et al. , 2000 ; Kelly and Takao, 2002 ; Halonen et al. , 2003 ; Willison and O’Regan, 2007 ).

At both the University of Minnesota and Duke University, we have focused on the genre of the undergraduate honors thesis as the rhetorical context in which to study and improve students’ scientific reasoning and writing. We view the process of writing an undergraduate honors thesis as a form of professional development in the sciences (i.e., a way of engaging students in the practices of a community of discourse). We have found that structured courses designed to scaffold the thesis-­writing process and promote metacognition can improve writing and reasoning skills in biology, chemistry, and economics ( Reynolds and Thompson, 2011 ; Dowd et al. , 2015a , b ). In the context of this prior work, we have defined scientific reasoning in writing as the emergent, underlying construct measured across distinct aspects of students’ written discussion of independent research in their undergraduate theses.

The Biology Thesis Assessment Protocol (BioTAP) was developed at Duke University as a tool for systematically guiding students and faculty through a “draft–feedback–revision” writing process, modeled after professional scientific peer-review processes ( Reynolds et al. , 2009 ). BioTAP includes activities and worksheets that allow students to engage in critical peer review and provides detailed descriptions, presented as rubrics, of the questions (i.e., dimensions, shown in Table 1 ) upon which such review should focus. Nine rubric dimensions focus on communication to the broader scientific community, and four rubric dimensions focus on the accuracy and appropriateness of the research. These rubric dimensions provide criteria by which the thesis is assessed, and therefore allow BioTAP to be used as an assessment tool as well as a teaching resource ( Reynolds et al. , 2009 ). Full details are available at www.science-writing.org/biotap.html .

Theses assessment protocol dimensions

In previous work, we have used BioTAP to quantitatively assess students’ undergraduate honors theses and explore the relationship between thesis-writing courses (or specific interventions within the courses) and the strength of students’ science reasoning in writing across different science disciplines: biology ( Reynolds and Thompson, 2011 ); chemistry ( Dowd et al. , 2015b ); and economics ( Dowd et al. , 2015a ). We have focused exclusively on the nine dimensions related to reasoning and writing (questions 1–9), as the other four dimensions (questions 10–13) require topic-specific expertise and are intended to be used by the student’s thesis supervisor.

Beyond considering individual dimensions, we have investigated whether meaningful constructs underlie students’ thesis scores. We conducted exploratory factor analysis of students’ theses in biology, economics, and chemistry and found one dominant underlying factor in each discipline; we termed the factor “scientific reasoning in writing” ( Dowd et al. , 2015a , b , 2016 ). That is, each of the nine dimensions could be understood as reflecting, in different ways and to different degrees, the construct of scientific reasoning in writing. The findings indicated evidence of both general and discipline-specific components to scientific reasoning in writing that relate to epistemic beliefs and paradigms, in keeping with broader ideas about science reasoning discussed earlier. Specifically, scientific reasoning in writing is more strongly associated with formulating a compelling argument for the significance of the research in the context of current literature in biology, making meaning regarding the implications of the findings in chemistry, and providing an organizational framework for interpreting the thesis in economics. We suggested that instruction, whether occurring in writing studios or in writing courses to facilitate thesis preparation, should attend to both components.

Research Question and Study Design

The genre of thesis writing combines the pedagogies of writing and inquiry found to foster scientific reasoning ( Reynolds et al. , 2012 ) and critical thinking ( Quitadamo and Kurtz, 2007 ; Quitadamo et al. , 2008 ; Stephenson and Sadler-­McKnight, 2016 ). However, there is no empirical evidence regarding the general or domain-specific interrelationships of scientific reasoning and critical-thinking skills, particularly in the rhetorical context of the undergraduate thesis. The BioTAP studies discussed earlier indicate that the rubric-based assessment produces evidence of scientific reasoning in the undergraduate thesis, but it was not designed to foster or measure critical thinking. The current study was undertaken to address the research question: How are students’ critical-thinking skills related to scientific reasoning as reflected in the genre of undergraduate thesis writing in biology? Determining these interrelationships could guide efforts to enhance students’ scientific reasoning and writing skills through focusing instruction on specific critical-thinking skills as well as disciplinary conventions.

To address this research question, we focused on undergraduate thesis writers in biology courses at two institutions, Duke University and the University of Minnesota, and examined the extent to which students’ scientific reasoning in writing, assessed in the undergraduate thesis using BioTAP, corresponds to students’ critical-thinking skills, assessed using the California Critical Thinking Skills Test (CCTST; August, 2016 ).

Study Sample

The study sample was composed of students enrolled in courses designed to scaffold the thesis-writing process in the Department of Biology at Duke University and the College of Biological Sciences at the University of Minnesota. Both courses complement students’ individual work with research advisors. The course is required for thesis writers at the University of Minnesota and optional for writers at Duke University. Not all students are required to complete a thesis, though it is required for students to graduate with honors; at the University of Minnesota, such students are enrolled in an honors program within the college. In total, 28 students were enrolled in the course at Duke University and 44 students were enrolled in the course at the University of Minnesota. Of those students, two students did not consent to participate in the study; additionally, five students did not validly complete the CCTST (i.e., attempted fewer than 60% of items or completed the test in less than 15 minutes). Thus, our overall rate of valid participation is 90%, with 27 students from Duke University and 38 students from the University of Minnesota. We found no statistically significant differences in thesis assessment between students with valid CCTST scores and invalid CCTST scores. Therefore, we focus on the 65 students who consented to participate and for whom we have complete and valid data in most of this study. Additionally, in asking students for their consent to participate, we allowed them to choose whether to provide or decline access to academic and demographic background data. Of the 65 students who consented to participate, 52 students granted access to such data. Therefore, for additional analyses involving academic and background data, we focus on the 52 students who consented. We note that the 13 students who participated but declined to share additional data performed slightly lower on the CCTST than the 52 others (perhaps suggesting that they differ by other measures, but we cannot determine this with certainty). Among the 52 students, 60% identified as female and 10% identified as being from underrepresented ethnicities.

In both courses, students completed the CCTST online, either in class or on their own, late in the Spring 2016 semester. This is the same assessment that was used in prior studies of critical thinking ( Quitadamo and Kurtz, 2007 ; Quitadamo et al. , 2008 ; Stephenson and Sadler-McKnight, 2016 ). It is “an objective measure of the core reasoning skills needed for reflective decision making concerning what to believe or what to do” ( Insight Assessment, 2016a ). In the test, students are asked to read and consider information as they answer multiple-choice questions. The questions are intended to be appropriate for all users, so there is no expectation of prior disciplinary knowledge in biology (or any other subject). Although actual test items are protected, sample items are available on the Insight Assessment website ( Insight Assessment, 2016b ). We have included one sample item in the Supplemental Material.

The CCTST is based on a consensus definition of critical thinking, measures cognitive and metacognitive skills associated with critical thinking, and has been evaluated for validity and reliability at the college level ( August, 2016 ; Stephenson and Sadler-McKnight, 2016 ). In addition to providing overall critical-thinking score, the CCTST assesses seven dimensions of critical thinking: analysis, interpretation, inference, evaluation, explanation, induction, and deduction. Scores on each dimension are calculated based on students’ performance on items related to that dimension. Analysis focuses on identifying assumptions, reasons, and claims and examining how they interact to form arguments. Interpretation, related to analysis, focuses on determining the precise meaning and significance of information. Inference focuses on drawing conclusions from reasons and evidence. Evaluation focuses on assessing the credibility of sources of information and claims they make. Explanation, related to evaluation, focuses on describing the evidence, assumptions, or rationale for beliefs and conclusions. Induction focuses on drawing inferences about what is probably true based on evidence. Deduction focuses on drawing conclusions about what must be true when the context completely determines the outcome. These are not independent dimensions; the fact that they are related supports their collective interpretation as critical thinking. Together, the CCTST dimensions provide a basis for evaluating students’ overall strength in using reasoning to form reflective judgments about what to believe or what to do ( August, 2016 ). Each of the seven dimensions and the overall CCTST score are measured on a scale of 0–100, where higher scores indicate superior performance. Scores correspond to superior (86–100), strong (79–85), moderate (70–78), weak (63–69), or not manifested (62 and below) skills.

Scientific Reasoning in Writing

At the end of the semester, students’ final, submitted undergraduate theses were assessed using BioTAP, which consists of nine rubric dimensions that focus on communication to the broader scientific community and four additional dimensions that focus on the exhibition of topic-specific expertise ( Reynolds et al. , 2009 ). These dimensions, framed as questions, are displayed in Table 1 .

Student theses were assessed on questions 1–9 of BioTAP using the same procedures described in previous studies ( Reynolds and Thompson, 2011 ; Dowd et al. , 2015a , b ). In this study, six raters were trained in the valid, reliable use of BioTAP rubrics. Each dimension was rated on a five-point scale: 1 indicates the dimension is missing, incomplete, or below acceptable standards; 3 indicates that the dimension is adequate but not exhibiting mastery; and 5 indicates that the dimension is excellent and exhibits mastery (intermediate ratings of 2 and 4 are appropriate when different parts of the thesis make a single category challenging). After training, two raters independently assessed each thesis and then discussed their independent ratings with one another to form a consensus rating. The consensus score is not an average score, but rather an agreed-upon, discussion-based score. On a five-point scale, raters independently assessed dimensions to be within 1 point of each other 82.4% of the time before discussion and formed consensus ratings 100% of the time after discussion.

In this study, we consider both categorical (mastery/nonmastery, where a score of 5 corresponds to mastery) and numerical treatments of individual BioTAP scores to better relate the manifestation of critical thinking in BioTAP assessment to all of the prior studies. For comprehensive/cumulative measures of BioTAP, we focus on the partial sum of questions 1–5, as these questions relate to higher-order scientific reasoning (whereas questions 6–9 relate to mid- and lower-order writing mechanics [ Reynolds et al. , 2009 ]), and the factor scores (i.e., numerical representations of the extent to which each student exhibits the underlying factor), which are calculated from the factor loadings published by Dowd et al. (2016) . We do not focus on questions 6–9 individually in statistical analyses, because we do not expect critical-thinking skills to relate to mid- and lower-order writing skills.

The final, submitted thesis reflects the student’s writing, the student’s scientific reasoning, the quality of feedback provided to the student by peers and mentors, and the student’s ability to incorporate that feedback into his or her work. Therefore, our assessment is not the same as an assessment of unpolished, unrevised samples of students’ written work. While one might imagine that such an unpolished sample may be more strongly correlated with critical-thinking skills measured by the CCTST, we argue that the complete, submitted thesis, assessed using BioTAP, is ultimately a more appropriate reflection of how students exhibit science reasoning in the scientific community.

Statistical Analyses

We took several steps to analyze the collected data. First, to provide context for subsequent interpretations, we generated descriptive statistics for the CCTST scores of the participants based on the norms for undergraduate CCTST test takers. To determine the strength of relationships among CCTST dimensions (including overall score) and the BioTAP dimensions, partial-sum score (questions 1–5), and factor score, we calculated Pearson’s correlations for each pair of measures. To examine whether falling on one side of the nonmastery/mastery threshold (as opposed to a linear scale of performance) was related to critical thinking, we grouped BioTAP dimensions into categories (mastery/nonmastery) and conducted Student’s t tests to compare the means scores of the two groups on each of the seven dimensions and overall score of the CCTST. Finally, for the strongest relationship that emerged, we included additional academic and background variables as covariates in multiple linear-regression analysis to explore questions about how much observed relationships between critical-thinking skills and science reasoning in writing might be explained by variation in these other factors.

Although BioTAP scores represent discreet, ordinal bins, the five-point scale is intended to capture an underlying continuous construct (from inadequate to exhibiting mastery). It has been argued that five categories is an appropriate cutoff for treating ordinal variables as pseudo-continuous ( Rhemtulla et al. , 2012 )—and therefore using continuous-variable statistical methods (e.g., Pearson’s correlations)—as long as the underlying assumption that ordinal scores are linearly distributed is valid. Although we have no way to statistically test this assumption, we interpret adequate scores to be approximately halfway between inadequate and mastery scores, resulting in a linear scale. In part because this assumption is subject to disagreement, we also consider and interpret a categorical (mastery/nonmastery) treatment of BioTAP variables.

We corrected for multiple comparisons using the Holm-Bonferroni method ( Holm, 1979 ). At the most general level, where we consider the single, comprehensive measures for BioTAP (partial-sum and factor score) and the CCTST (overall score), there is no need to correct for multiple comparisons, because the multiple, individual dimensions are collapsed into single dimensions. When we considered individual CCTST dimensions in relation to comprehensive measures for BioTAP, we accounted for seven comparisons; similarly, when we considered individual dimensions of BioTAP in relation to overall CCTST score, we accounted for five comparisons. When all seven CCTST and five BioTAP dimensions were examined individually and without prior knowledge, we accounted for 35 comparisons; such a rigorous threshold is likely to reject weak and moderate relationships, but it is appropriate if there are no specific pre-existing hypotheses. All p values are presented in tables for complete transparency, and we carefully consider the implications of our interpretation of these data in the Discussion section.

CCTST scores for students in this sample ranged from the 39th to 99th percentile of the general population of undergraduate CCTST test takers (mean percentile = 84.3, median = 85th percentile; Table 2 ); these percentiles reflect overall scores that range from moderate to superior. Scores on individual dimensions and overall scores were sufficiently normal and far enough from the ceiling of the scale to justify subsequent statistical analyses.

Descriptive statistics of CCTST dimensions a

a Scores correspond to superior (86–100), strong (79–85), moderate (70–78), weak (63–69), or not manifested (62 and lower) skills.

The Pearson’s correlations between students’ cumulative scores on BioTAP (the factor score based on loadings published by Dowd et al. , 2016 , and the partial sum of scores on questions 1–5) and students’ overall scores on the CCTST are presented in Table 3 . We found that the partial-sum measure of BioTAP was significantly related to the overall measure of critical thinking ( r = 0.27, p = 0.03), while the BioTAP factor score was marginally related to overall CCTST ( r = 0.24, p = 0.05). When we looked at relationships between comprehensive BioTAP measures and scores for individual dimensions of the CCTST ( Table 3 ), we found significant positive correlations between the both BioTAP partial-sum and factor scores and CCTST inference ( r = 0.45, p < 0.001, and r = 0.41, p < 0.001, respectively). Although some other relationships have p values below 0.05 (e.g., the correlations between BioTAP partial-sum scores and CCTST induction and interpretation scores), they are not significant when we correct for multiple comparisons.

Correlations between dimensions of CCTST and dimensions of BioTAP a

a In each cell, the top number is the correlation, and the bottom, italicized number is the associated p value. Correlations that are statistically significant after correcting for multiple comparisons are shown in bold.

b This is the partial sum of BioTAP scores on questions 1–5.

c This is the factor score calculated from factor loadings published by Dowd et al. (2016) .

When we expanded comparisons to include all 35 potential correlations among individual BioTAP and CCTST dimensions—and, accordingly, corrected for 35 comparisons—we did not find any additional statistically significant relationships. The Pearson’s correlations between students’ scores on each dimension of BioTAP and students’ scores on each dimension of the CCTST range from −0.11 to 0.35 ( Table 3 ); although the relationship between discussion of implications (BioTAP question 5) and inference appears to be relatively large ( r = 0.35), it is not significant ( p = 0.005; the Holm-Bonferroni cutoff is 0.00143). We found no statistically significant relationships between BioTAP questions 6–9 and CCTST dimensions (unpublished data), regardless of whether we correct for multiple comparisons.

The results of Student’s t tests comparing scores on each dimension of the CCTST of students who exhibit mastery with those of students who do not exhibit mastery on each dimension of BioTAP are presented in Table 4 . Focusing first on the overall CCTST scores, we found that the difference between those who exhibit mastery and those who do not in discussing implications of results (BioTAP question 5) is statistically significant ( t = 2.73, p = 0.008, d = 0.71). When we expanded t tests to include all 35 comparisons—and, like above, corrected for 35 comparisons—we found a significant difference in inference scores between students who exhibit mastery on question 5 and students who do not ( t = 3.41, p = 0.0012, d = 0.88), as well as a marginally significant difference in these students’ induction scores ( t = 3.26, p = 0.0018, d = 0.84; the Holm-Bonferroni cutoff is p = 0.00147). Cohen’s d effect sizes, which reveal the strength of the differences for statistically significant relationships, range from 0.71 to 0.88.

The t statistics and effect sizes of differences in ­dimensions of CCTST across dimensions of BioTAP a

a In each cell, the top number is the t statistic for each comparison, and the middle, italicized number is the associated p value. The bottom number is the effect size. Correlations that are statistically significant after correcting for multiple comparisons are shown in bold.

Finally, we more closely examined the strongest relationship that we observed, which was between the CCTST dimension of inference and the BioTAP partial-sum composite score (shown in Table 3 ), using multiple regression analysis ( Table 5 ). Focusing on the 52 students for whom we have background information, we looked at the simple relationship between BioTAP and inference (model 1), a robust background model including multiple covariates that one might expect to explain some part of the variation in BioTAP (model 2), and a combined model including all variables (model 3). As model 3 shows, the covariates explain very little variation in BioTAP scores, and the relationship between inference and BioTAP persists even in the presence of all of the covariates.

Partial sum (questions 1–5) of BioTAP scores ( n = 52)

** p < 0.01.

*** p < 0.001.

The aim of this study was to examine the extent to which the various components of scientific reasoning—manifested in writing in the genre of undergraduate thesis and assessed using BioTAP—draw on general and specific critical-thinking skills (assessed using CCTST) and to consider the implications for educational practices. Although science reasoning involves critical-thinking skills, it also relates to conceptual knowledge and the epistemological foundations of science disciplines ( Kuhn et al. , 2008 ). Moreover, science reasoning in writing , captured in students’ undergraduate theses, reflects habits, conventions, and the incorporation of feedback that may alter evidence of individuals’ critical-thinking skills. Our findings, however, provide empirical evidence that cumulative measures of science reasoning in writing are nonetheless related to students’ overall critical-thinking skills ( Table 3 ). The particularly significant roles of inference skills ( Table 3 ) and the discussion of implications of results (BioTAP question 5; Table 4 ) provide a basis for more specific ideas about how these constructs relate to one another and what educational interventions may have the most success in fostering these skills.

Our results build on previous findings. The genre of thesis writing combines pedagogies of writing and inquiry found to foster scientific reasoning ( Reynolds et al. , 2012 ) and critical thinking ( Quitadamo and Kurtz, 2007 ; Quitadamo et al. , 2008 ; Stephenson and Sadler-McKnight, 2016 ). Quitadamo and Kurtz (2007) reported that students who engaged in a laboratory writing component in a general education biology course significantly improved their inference and analysis skills, and Quitadamo and colleagues (2008) found that participation in a community-based inquiry biology course (that included a writing component) was associated with significant gains in students’ inference and evaluation skills. The shared focus on inference is noteworthy, because these prior studies actually differ from the current study; the former considered critical-­thinking skills as the primary learning outcome of writing-­focused interventions, whereas the latter focused on emergent links between two learning outcomes (science reasoning in writing and critical thinking). In other words, inference skills are impacted by writing as well as manifested in writing.

Inference focuses on drawing conclusions from argument and evidence. According to the consensus definition of critical thinking, the specific skill of inference includes several processes: querying evidence, conjecturing alternatives, and drawing conclusions. All of these activities are central to the independent research at the core of writing an undergraduate thesis. Indeed, a critical part of what we call “science reasoning in writing” might be characterized as a measure of students’ ability to infer and make meaning of information and findings. Because the cumulative BioTAP measures distill underlying similarities and, to an extent, suppress unique aspects of individual dimensions, we argue that it is appropriate to relate inference to scientific reasoning in writing . Even when we control for other potentially relevant background characteristics, the relationship is strong ( Table 5 ).

In taking the complementary view and focusing on BioTAP, when we compared students who exhibit mastery with those who do not, we found that the specific dimension of “discussing the implications of results” (question 5) differentiates students’ performance on several critical-thinking skills. To achieve mastery on this dimension, students must make connections between their results and other published studies and discuss the future directions of the research; in short, they must demonstrate an understanding of the bigger picture. The specific relationship between question 5 and inference is the strongest observed among all individual comparisons. Altogether, perhaps more than any other BioTAP dimension, this aspect of students’ writing provides a clear view of the role of students’ critical-thinking skills (particularly inference and, marginally, induction) in science reasoning.

While inference and discussion of implications emerge as particularly strongly related dimensions in this work, we note that the strongest contribution to “science reasoning in writing in biology,” as determined through exploratory factor analysis, is “argument for the significance of research” (BioTAP question 2, not question 5; Dowd et al. , 2016 ). Question 2 is not clearly related to critical-thinking skills. These findings are not contradictory, but rather suggest that the epistemological and disciplinary-specific aspects of science reasoning that emerge in writing through BioTAP are not completely aligned with aspects related to critical thinking. In other words, science reasoning in writing is not simply a proxy for those critical-thinking skills that play a role in science reasoning.

In a similar vein, the content-related, epistemological aspects of science reasoning, as well as the conventions associated with writing the undergraduate thesis (including feedback from peers and revision), may explain the lack of significant relationships between some science reasoning dimensions and some critical-thinking skills that might otherwise seem counterintuitive (e.g., BioTAP question 2, which relates to making an argument, and the critical-thinking skill of argument). It is possible that an individual’s critical-thinking skills may explain some variation in a particular BioTAP dimension, but other aspects of science reasoning and practice exert much stronger influence. Although these relationships do not emerge in our analyses, the lack of significant correlation does not mean that there is definitively no correlation. Correcting for multiple comparisons suppresses type 1 error at the expense of exacerbating type 2 error, which, combined with the limited sample size, constrains statistical power and makes weak relationships more difficult to detect. Ultimately, though, the relationships that do emerge highlight places where individuals’ distinct critical-thinking skills emerge most coherently in thesis assessment, which is why we are particularly interested in unpacking those relationships.

We recognize that, because only honors students submit theses at these institutions, this study sample is composed of a selective subset of the larger population of biology majors. Although this is an inherent limitation of focusing on thesis writing, links between our findings and results of other studies (with different populations) suggest that observed relationships may occur more broadly. The goal of improved science reasoning and critical thinking is shared among all biology majors, particularly those engaged in capstone research experiences. So while the implications of this work most directly apply to honors thesis writers, we provisionally suggest that all students could benefit from further study of them.

There are several important implications of this study for science education practices. Students’ inference skills relate to the understanding and effective application of scientific content. The fact that we find no statistically significant relationships between BioTAP questions 6–9 and CCTST dimensions suggests that such mid- to lower-order elements of BioTAP ( Reynolds et al. , 2009 ), which tend to be more structural in nature, do not focus on aspects of the finished thesis that draw strongly on critical thinking. In keeping with prior analyses ( Reynolds and Thompson, 2011 ; Dowd et al. , 2016 ), these findings further reinforce the notion that disciplinary instructors, who are most capable of teaching and assessing scientific reasoning and perhaps least interested in the more mechanical aspects of writing, may nonetheless be best suited to effectively model and assess students’ writing.

The goal of the thesis writing course at both Duke University and the University of Minnesota is not merely to improve thesis scores but to move students’ writing into the category of mastery across BioTAP dimensions. Recognizing that students with differing critical-thinking skills (particularly inference) are more or less likely to achieve mastery in the undergraduate thesis (particularly in discussing implications [question 5]) is important for developing and testing targeted pedagogical interventions to improve learning outcomes for all students.

The competencies characterized by the Vision and Change in Undergraduate Biology Education Initiative provide a general framework for recognizing that science reasoning and critical-thinking skills play key roles in major learning outcomes of science education. Our findings highlight places where science reasoning–related competencies (like “understanding the process of science”) connect to critical-thinking skills and places where critical thinking–related competencies might be manifested in scientific products (such as the ability to discuss implications in scientific writing). We encourage broader efforts to build empirical connections between competencies and pedagogical practices to further improve science education.

One specific implication of this work for science education is to focus on providing opportunities for students to develop their critical-thinking skills (particularly inference). Of course, as this correlational study is not designed to test causality, we do not claim that enhancing students’ inference skills will improve science reasoning in writing. However, as prior work shows that science writing activities influence students’ inference skills ( Quitadamo and Kurtz, 2007 ; Quitadamo et al. , 2008 ), there is reason to test such a hypothesis. Nevertheless, the focus must extend beyond inference as an isolated skill; rather, it is important to relate inference to the foundations of the scientific method ( Miri et al. , 2007 ) in terms of the epistemological appreciation of the functions and coordination of evidence ( Kuhn and Dean, 2004 ; Zeineddin and Abd-El-Khalick, 2010 ; Ding et al. , 2016 ) and disciplinary paradigms of truth and justification ( Moshman, 2015 ).

Although this study is limited to the domain of biology at two institutions with a relatively small number of students, the findings represent a foundational step in the direction of achieving success with more integrated learning outcomes. Hopefully, it will spur greater interest in empirically grounding discussions of the constructs of scientific reasoning and critical-thinking skills.

This study contributes to the efforts to improve science education, for both majors and nonmajors, through an empirically driven analysis of the relationships between scientific reasoning reflected in the genre of thesis writing and critical-thinking skills. This work is rooted in the usefulness of BioTAP as a method 1) to facilitate communication and learning and 2) to assess disciplinary-specific and general dimensions of science reasoning. The findings support the important role of the critical-thinking skill of inference in scientific reasoning in writing, while also highlighting ways in which other aspects of science reasoning (epistemological considerations, writing conventions, etc.) are not significantly related to critical thinking. Future research into the impact of interventions focused on specific critical-thinking skills (i.e., inference) for improved science reasoning in writing will build on this work and its implications for science education.

Supplementary Material

Acknowledgments.

We acknowledge the contributions of Kelaine Haas and Alexander Motten to the implementation and collection of data. We also thank Mine Çetinkaya-­Rundel for her insights regarding our statistical analyses. This research was funded by National Science Foundation award DUE-1525602.

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5.2: Assumptions and Inferences

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As we start analyzing a claim we need to realize that we all begin this process with certain preconceived ideas and beliefs that can guide or misguide our thinking. Duncan Hines assumed that Japanese families had ovens, like those families in this country. Stated another way, we all have certain biases and assumptions that influence our thinking. When analyzing a claim, we need to understand the difference between an assumption and an inference we naturally make about the claim being argued.

Inference refers to something we believe to be accurate based on something else we believe to be true. If you email someone and they do not email you back, you may infer that they are mad or upset with you. Inferences can be correct interpretations of our environment or incorrect interpretations of our environment.

Assumption refers to something we already assume or presuppose. As described by Richard Paul and Linda Edler.

“Usually it is something we previously learned and do not question. It is part of our system of beliefs. We assume our beliefs to be true and use them to interpret the world about us. If we believe that it is dangerous to walk late at night in big cities and we are staying in Chicago, we will infer that it is dangerous to go for a walk late at night. We take for granted our belief that it is dangerous to walk late at night in big cities.” (Paul)

Based on our assumptions, we make inferences that guide our decisions and actions. To make sure these assumptions and inferences are accurate, we need to question them.

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2.1: The Brain Is an Inference Machine

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Learning Objectives

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

• Describe the role of emotion in thought.
• Explain how cognitive systems produce inferences without conscious thought.

One of the first steps to becoming a more critical and reflective thinker is to understand how and why you are prone to making mistakes in thinking. These mistakes are not the result of a lack of intelligence but are a function of the way our minds work and how they naturally lead us astray.

From a biological perspective, we have been shaped by hundreds of thousands of years of evolution, which have primed our brains to become extremely effective inference machines. An inference is the mental process that allows us to draw conclusions from evidence. While we tend to think of inference as a deliberative and conscious process, we infer all kinds of things unconsciously, effortlessly, and immediately; in fact, most of sense perception is a kind of inference. Inference making has been crucial to human survival, but our conclusions are not always correct. By becoming aware of how our brains function to ward off threats and provide us with “cognitive ease,” or a feeling of well-being and comfort, we can begin to correct for and guard against faulty thinking.

The Brain’s Adaptive Ability to Plan Ahead

One insight of evolutionary biology is that every cell and organ in our body is adapted to its local environment for the purpose of making it more likely that our genes will survive into the next generation. Consequently, it’s helpful to think about the brain’s role in propagating our genes. Our brains facilitate our survival and promote our ability to find a partner and reproduce by using thought, calculation, prediction, and inference. For this reason, our natural and genetically primed ways of thinking do not necessarily serve the goals of philosophy, science, or truth.

Philosophical Caveats about “Brain Talk”

Before we get much further, note that it is important to be cautious when we talk about brains and minds, which are distinct concepts. In fact, the relationship between mind and brain is one of the central problems of metaphysics, known as the “mind-body problem,” which might just as well be called the “mind-brain problem.” Briefly stated, the mind-body problem is the problem of understanding the relationship between the organic gray and white matter in our skulls (the brain) and the range of conscious awareness (the mind). We know that the brain and central nervous system provide the physical basis for our thoughts, perceptions, emotions, imagination, and desire—in short, our entire mental life. But biology does not tell us what the relationship is between our private mental life and the neurological, electrochemical interactions that take place in the brain. Is the relationship of the mind to the brain like the relationship between lightning and electrical discharge or a rainbow and the refraction of light through water droplets? In other words, is “the mind” just the term we use to label certain kinds of brain activity? Some philosophers think so. However, mental activity is not easily associated with any specific brain activity. Additionally, there seems to be something about the subjective experience of our mental life that is lost when we attempt to explain it fully in terms of brain activity. So other philosophers maintain that the mind is something different from the brain. Nonetheless, the mind and the brain are closely and somewhat mysteriously connected. As a result, it can be helpful to use the resources of psychology and cognitive science (the study of the brain’s processes) to help us understand how to become better thinkers. We can think of the resources from psychology and cognitive science as providing us with a description of how the brain actually behaves. By contrast, when we study critical thinking, we are interested in how we ought to think. Being aware of how we do think may help us devise effective strategies for how we ought to think, but we should understand that the descriptions provided by psychology are not determinative. In this chapter, we explore psychological findings that can help you become more reflective about the ways your thinking can go wrong.

CONNECTIONS

Read more about the nature of the mind and the mind-body problem in the chapter on metaphysics .

Representation as Projection

While you may consider thinking to be made up of ideas or thoughts, philosophers and cognitive scientists use the term representation to describe the basic elements of thinking. Representations are information-bearing units of thought. This notion of representation can be traced back to Aristotle and has played a significant role in the history of philosophy, but in contemporary philosophy the term representation is more precise. When we think about things, whether through perception, imagination, memory, or desire, we represent those things. What is represented may be something present and real, or it may be fictitious, imagined in the future, or remembered from the past. Representations may even be unconscious. That is, the mind may have some defined content that is directed toward an object without the person being aware that they have produced such a representation.

During the process of representation, even in a relatively simple case of visual perception, the brain makes a complex set of inferences. For instance, consider the checkerboard below. You might imagine that when you perceive something like a checkerboard, your brain passively takes a mental picture of the grid. In this analogy, the eye functions like the lens of a camera, and the brain develops the picture to present to the mind. But there are several problems with this model. First, where is the picture in your brain? Who is viewing the picture in your head? There are further problems with the camera analogy that can be revealed when we examine optical illusions. Look at the checkered set of squares in Figure 2.2. Are the horizontal lines parallel?

In fact, the horizontal lines are parallel, but unless you look at the image from the side, it is impossible to visualize this. There are countless examples of these types of perceptual illusions. We represent the world outside as a stable picture that is completely filled in, in full focus, and uniformly colored. In reality, our visual field is limited and hazy around the edges, and colors change dramatically depending on lighting conditions, distance, movement, and a host of other factors. In fact, your brain is not passively capturing the world, like a camera, but is actively projecting the world so that it makes sense to you. In the illusion above, your brain is automatically adjusting your perception of the colored squares by accounting for the shadow cast by the cylinder. So your brain presents square B as if it is lighter than A by adjusting the hue of B to account for the shadow.

Neuroscientist David Eagleman (2011) uses the analogy of the front page of a newspaper to describe how perception works. The front page is a representation of the world’s events for a given day. Of course, it does not present a full or complete picture of the world, but a summary intended to highlight the events of consequence, those that have changed, and those that we are most likely to care about. Like a newspaper editor, your brain is working overtime to project an image of the world based on what is relevant to your survival. You unconsciously adjust the images you perceive to give you the impression that they are far away, nearby, moving, and so forth. Instead of the fully formed, three-dimensional image of the world we seem to see, we actually perceive a kind of sketch, highlighting what we need to know to navigate safely in our environment and obtain what we need. You probably think that sense perception is the clearest and most certain way you can know the world around you. As the adage says, “Seeing is believing.” To become a better critical thinker, however, you will need to become skeptical of some of your basic beliefs. There are times when you absolutely should not believe your lying eyes.

Emotions and Reason: Homeostasis and Allostasis

In addition to the editorial license of mental representation, thinking is not always as rational as we imagine. The neuroscientist Antonio Damasio (1994) was one of the first to popularize the notion that rational thought is tempered by emotions. He is critical of what he perceives as the philosophical bias against emotion in the history of philosophy. In Descartes’ Error , he says modern philosophers have neglected the role of emotions in thought, imagining that the goal of rational thinking is to eliminate the influence of emotions. Instead, his years of clinical work with patients revealed to him that emotions cannot be separated from reason. Our most rational thoughts are, in fact, guided, informed, and influenced by emotions. According to Damasio, reasoning and intelligence function best when we care about something. Without feelings, says Damasio, we are less rational, not more rational.

Damasio (1994) explains that emotions serve to maintain homeostasis in the brain through the chemical messengers known as neurotransmitters. Homeostasis is the biological tendency to find a neutral state of equilibrium (the word stasis means “standing still,” and homeo means “same or similar”). This process relies on a feedback loop where current bodily states are monitored, observed, and then altered to bring the body back into balance. Most homeostatic processes in the body are unconscious, but emotions are linked to conscious awareness. For instance, when your blood sugar is low and your body needs calories, there is a series of chemical processes that give rise to the feeling of hunger. This is a conscious signal that you need to eat; it promotes behavior that ensures survival. Similarly, a rustling sound in the bushes at night will trigger a series of physiological responses (heightened senses, increased heart rate, pupil dilation, etc.) that correspond to the feeling of fear and promote behavior, such as fight or flight, that are necessary for survival. What Damasio demonstrates is that emotions have their own feedback mechanism, so that an idea or image can generate physiological responses even in the absence of an external stimulus. Because emotional responses and conscious thought are closely linked, decision-making can be influenced by this emotional-physiological feedback mechanism. Our thinking can go astray because we are afraid of bad outcomes, and that fear dominates a more rational calculation about which course of action is most beneficial (1994, 172–175).

In addition to maintaining equilibrium, the brain also anticipates future events and circumstances by projecting likely scenarios based on a catalog of past experiences and concepts generated through social norms and social interactions. The process of regulation that prepares the body to anticipate future needs before they arise is called allostasis ( allo means “other or different”). Psychologist Lisa Feldman Barrett (2017) explains that the brain stores neural pathways that are triggered by external or internal stimuli to provide the closest match to the current situation. The neural pathways form a kind of template of action, promoting behavior like increased heart rate, pupil dilation, or motion. Feelings are a goal-oriented response to certain situations: they prepare us to behave and react in certain ways that promote what is beneficial to the body and sharpen and shape our awareness of the world.

In summary, the brain makes inferences about the world through perceptions, emotions, and concepts that are largely unconscious and deeply ingrained in our psyches. This process allows us to navigate fluidly and accurately through a world with so many and varied stimuli. Our reactions to stimuli are partially homeostatic, meaning that the body tends to bring itself back into an optimal state of equilibrium, and partially allostatic, meaning that the body prepares for and anticipates future situations. Together, these impulses construct a picture of the world that we experience seamlessly and dynamically. Our experience is far more complicated than the crude mental model we imagine. We are projecting and constructing the world we experience as much as we are recording and viewing it. And that fact has important consequences for the kind of reflective and critical thought we ought to engage in when we try to think clearly about the world.

The Evolutionary Advantage of Shortcuts

Human beings have evolved to navigate the world most effectively and efficiently by engaging conscious awareness only when necessary. For that reason, you can walk through the grocery store while thinking about what you are going to cook for dinner. You do not have to consciously think about where to go, how to slow down to make way for other people, or how hard to push the shopping cart so that it maintains momentum in front of you even as its weight changes as you add groceries to the basket. All that biomechanical activity can be outsourced to unconscious mechanisms as you scan your shopping list. The brain is quite good at engaging in habitual activities without the assistance of conscious thought. And that is a good thing because conscious thought is expensive in energy terms. Consider the picture that follows.

You are probably immediately able to provide complex inferences about this picture, such as the woman is worried, concerned, or anxious about something. The inferences you make about this image are easy, fast, and complex. They are driven by the kind of emotional and conceptual thought processes that are unconscious and efficient. While these inferences are quick and easy, you may also be aware that they are provisional without more information. Given more data about the circumstances surrounding this picture, you might revise your perception about what is going on. This is exactly the sort of thinking that drives the emotional projections discussed in the previous section.

A different type of thinking is required to solve a math problem. The following example comes from psychologist Daniel Kahneman’s book Thinking Fast and Slow (2013). Try to solve the following in your head:

\[\nonumber 24 \times 14 = \]

Do you know the answer? For most people, multiplying two-digit numbers without pen and paper (or a calculator) is quite difficult. You might need perhaps 10 or 20 seconds of effortful thinking to solve the problem in your head since you do not have the unconscious mechanisms to do so automatically. Long-term social and evolutionary pressures have shaped our brains to find efficient solutions to complex questions about facial expressions. The same cannot be said for math problems. Knowing the solution to a math problem may be useful, but it is not the sort of thing generally required for survival and reproduction. On the other hand, quickly reading other people’s emotions is at times vital for survival. There are other interesting differences between these two kinds of thinking. While it is difficult to solve the math problem, once you solve it, you can be 100 percent certain the answer is correct. By contrast, it is easy to generate a story about facial expressions, but this story is highly susceptible to error, bias, and stereotyping. As a result, critical thinkers should be careful not to jump to the first, most obvious solution.

Energy Demands on Deliberate Thinking

Solving a math problem requires rational thought and effort. When we engage in rational thought, our brains use up precious energy stores that may be required for the maintenance of the body. Because evolutionary pressures seek to keep us alive long enough to pass our genes to the next generation, we have a biological tendency to avoid effortful thinking. In a sense, it is evolutionarily wise to be lazy.

The resources demanded by conscious thought can be understood in terms of the familiar notion of “attention.” When a task requires significant attention, it places increased energy demands on the brain. Periods of high-attention activity can be stressful, as the body increases blood flow to the brain, delivering more glucose and oxygen for increased mental activity. Additionally, attention is limited and focused on specific tasks. Consider the “selective attention test” developed by Daniel Simons and Christopher Chabris. Watch the video below and see how you perform on this test.

Selective Attention Test

Click to view content

How many passes did you count? Did you miss anything in the process? When our attention is focused on a novel and complex task, we become less aware of other stimuli outside the specific area of focus. Additionally, we may become fatigued, stressed, or anxious while engaged in paying close attention. Not surprisingly, our brains prefer automated shortcuts.

Heuristics and Learning

Kahneman (2013) calls these mental shortcuts heuristics , or rules of thumb for drawing inferences. Problem-solving with heuristics is largely unconscious, automated, effortless, and efficient, but it is not always correct. Rational thinking or computation requires conscious attention and effort and may not even be possible without some practice. We are forced to engage in effortful thinking when confronted with something new and possibly dangerous—or even with something slightly outside of our normal routine. For example, you have probably driven home from work or school along a familiar route on “autopilot,” preoccupied with your thoughts. Maybe you have even gotten home and felt as if you cannot remember how you got there. By contrast, you have probably experienced the stress of navigating a new, unfamiliar city. In the first case, navigation can be carried out using easy, largely automatic processing, whereas in the second case, navigation requires the intense resources of active attention and rational calculation.

Sometimes complex activities can become effortless, but unlike when we are on “automatic pilot,” such activities feel pleasant and fulfilling. When you become fully immersed in a complex activity to the point at which it becomes effortless, you have entered the state of “flow” (Csikszentmihalyi 2008).

Flow states are possible only for someone who has achieved some level of proficiency at a task. They are characterized by intense concentration and awareness as well as a sense of personal control or agency, but they are pleasurable because the challenge of engaging in the task is commensurate with your ability. By contrast, a novice may find the same tasks stressful and frustrating. This phenomenon can be illustrated using the notion of the “learning curve” that describes how a novice grows in proficiency.

What this means is that a person may be able to rely on intuitions, gut reactions, and other automatic responses in a field in which they are an expert, but the novice should be skeptical of these methods of thinking. As a novice, your mental heuristics are frequently faulty, so you are susceptible to prejudice, implicit bias, and error.

Consider the case of buying a car. Someone who is deeply familiar with the automobile market as either a buyer or a seller may be able to estimate the true value of a car easily, but the average person would need to do a great deal of research to arrive at a true estimate. Because of the effort required for nonexperts to appraise car value, they are easily influenced by dealer incentives, marked-up list prices, financing options, and other tricks of the trade. Given that we are all susceptible to these types of errors, it seems like a good idea to try to become more self-aware and critical and not rely exclusively on gut reactions or intuitions when encountering new material. Since you are probably a novice in philosophy if you are reading this textbook, you ought to be suspicious of your gut reactions to and intuitions about philosophical questions. Keep an open mind, and don’t assume you already understand the philosophical problems you will encounter in the chapters that follow. Being open to new ideas and allowing yourself to admit some degree of ignorance are important first steps in becoming a better thinker.

Heuristics and Substitution in Decision-Making

The cognitive biases that we will examine in the next section are based on a more fundamental “substitution heuristic.” This term describes our tendency to answer a difficult question or problem by substituting it with an easier question to answer. While substitution often results in an incorrect or inappropriate response, it gives us a sense of satisfaction or “cognitive ease” in thinking we have solved a problem. For instance, when you are asked to evaluate something complex and uncertain, like the future value of an investment or the political prospects of a politician, you are likely to substitute that complex calculation for an easier one. In particular, you may substitute your positive or negative feelings toward the politician or the investment product. But your feelings are likely to be guided by your preconceptions.

When the brain defaults to heuristics that produce a less-than-optimal result or even an incorrect decision, it is operating with a cognitive bias . A cognitive bias is a pattern of “quick” thinking based on the “rule of thumb.” A person operating under a cognitive bias does not use logic or careful reasoning to arrive at a conclusion. Cognitive biases are like perceptual illusions. Just like perceptual illusions, cognitive biases are the result of the natural and, ordinarily, efficient operation of the brain. Even though mental heuristics often work perfectly well to help give us an estimation of reality without the mental effort required to generate a more comprehensive picture, cognitive biases are the result of misleading and faulty patterns that arise from this process.

The Elements of Thought

How we think….

Interpretation and Inference

An Inference is a conclusion we come to by analyzing Information. It is inductive reasoning: looking at facts and then making a conclusion from those facts.

An Interpretation is an Inference from a specific Point of View. Two people might have the same facts, but with different Points of View, they may each come to a different solution to the problem.

Conclusions make sense of the data; they are the unifying ideas of the research. In a conclusion we find a solution to the Question at Issue. We have figured it out.

Is what you have come to the best solution to the problem? Is this the only solution possible? Are there other solutions that may not only work, but are better? Which are inconsequential? Could you be wrong?

When we come to a good conclusion, it’s natural to feel that thinking is done. Actually, now we must work even harder and recheck each of the Elements of Thought. Any answer invariably leads us to more questions.

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5.4 Types of Inferences

Learning objectives.

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

• Define deductive, inductive, and abductive inferences.
• Classify inferences as deductive, inductive, or abductive.
• Explain different explanatory virtues used in abductive reasoning.

Inferences can be deductive, inductive, or abductive. Deductive inferences are the strongest because they can guarantee the truth of their conclusions. Inductive inferences are the most widely used, but they do not guarantee the truth and instead deliver conclusions that are probably true. Abductive inferences also deal in probability.

Deductive Reasoning

Deductive inferences, which are inferences arrived at through deduction (deductive reasoning), can guarantee truth because they focus on the structure of arguments. Here is an example:

• Either you can go to the movies tonight, or you can go to the party tomorrow.
• You cannot go to the movies tonight.
• So, you can go to the party tomorrow.

This argument is good, and you probably knew it was good even without thinking too much about it. The argument uses “or,” which means that at least one of the two statements joined by the “or” must be true. If you find out that one of the two statements joined by “or” is false, you know that the other statement is true by using deduction. Notice that this inference works no matter what the statements are. Take a look at the structure of this form of reasoning:

• X or Y is true.
• X is not true.
• Therefore, Y is true.

By replacing the statements with variables, we get to the form of the initial argument above. No matter what statements you replace X and Y with, if those statements are true, then the conclusion must be true as well. This common argument form is called a disjunctive syllogism.

Valid Deductive Inferences

A good deductive inference is called a valid inference , meaning its structure guarantees the truth of its conclusion given the truth of the premises. Pay attention to this definition. The definition does not say that valid arguments have true conclusions. Validity is a property of the logical forms of arguments, and remember that logic and truth are distinct. The definition states that valid arguments have a form such that if the premises are true, then the conclusion must be true. You can test a deductive inference’s validity by testing whether the premises lead to the conclusion. If it is impossible for the conclusion to be false when the premises are assumed to be true, then the argument is valid.

Deductive reasoning can use a number of valid argument structures:

Disjunctive Syllogism :

• Therefore X.

Modus Ponens :

• If X, then Y.
• Therefore Y.

Modus Tollens :

• Therefore, not X.

You saw the first form, disjunctive syllogism, in the previous example. The second form, modus ponens, uses a conditional, and if you think about necessary and sufficient conditions already discussed, then the validity of this inference becomes apparent. The conditional in premise 1 expresses that X is sufficient for Y. So if X is true, then Y must be true. And premise 2 states that X is true. So the conclusion (the truth of Y) necessarily follows. You can also use your knowledge of necessary and sufficient conditions to understand the last form, modus tollens. Remember, in a conditional, the consequent is the necessary condition. So Y is necessary for X. But premise 2 states that Y is not true. Because Y must be the case if X is the case, and we are told that Y is false, then we know that X is also false. These three examples are only a few of the numerous possible valid inferences.

Invalid Deductive Inferences

A bad deductive inference is called an invalid inference . In invalid inferences, their structure does not guarantee the truth of the conclusion—that is to say, even if the premises are true, the conclusion may be false. This does not mean that the conclusion must be false, but that we simply cannot know whether the conclusion is true or false. Here is an example of an invalid inference:

• If it snows more than three inches, the schools are mandated to close.
• The schools closed.
• Therefore, it snowed more than three inches.

If the premises of this argument are true (and we assume they are), it may or may not have snowed more than three inches. Schools close for many reasons besides snow. Perhaps the school district experienced a power outage or a hurricane warning was issued for the area. Again, you can use your knowledge of necessary and sufficient conditions to understand why this form is invalid. Premise 2 claims that the necessary condition is the case. But the truth of the necessary condition does not guarantee that the sufficient condition is true. The conditional states that the closing of schools is guaranteed when it has snowed more than 3 inches, not that snow of more than 3 inches is guaranteed if the schools are closed.

Invalid deductive inferences can also take general forms. Here are two common invalid inference forms:

Affirming the Consequent:

• Therefore, X.

Denying the Antecedent:

• Therefore, not Y.

You saw the first form, affirming the consequent, in the previous example concerning school closures. The fallacy is so called because the truth of the consequent (the necessary condition) is affirmed to infer the truth of the antecedent statement. The second form, denying the antecedent, occurs when the truth of the antecedent statement is denied to infer that the consequent is false. Your knowledge of sufficiency will help you understand why this inference is invalid. The truth of the antecedent (the sufficient condition) is only enough to know the truth of the consequent. But there may be more than one way for the consequent to be true, which means that the falsity of the sufficient condition does not guarantee that the consequent is false. Going back to an earlier example, that a creature is not a dog does not let you infer that it is not a mammal, even though being a dog is sufficient for being a mammal. Watch the video below for further examples of conditional reasoning. See if you can figure out which incorrect selection is structurally identical to affirming the consequent or denying the antecedent.

The Wason Selection Task

Testing deductive inferences.

Earlier it was explained that logical analysis involves assuming the premises of an argument are true and then determining whether the conclusion logically follows, given the truth of those premises. For deductive arguments, if you can come up with a scenario where the premises are true but the conclusion is false, you have proven that the argument is invalid. An instance of a deductive argument where the premises are all true but the conclusion false is called a counterexample . As with counterexamples to statements, counterexamples to arguments are simply instances that run counter to the argument. Counterexamples to statements show that the statement is false, while counterexamples to deductive arguments show that the argument is invalid. Complete the exercise below to get a better understanding of coming up with counterexamples to prove invalidity.

Think Like a Philosopher

Using the sample arguments given, come up with a counterexample to prove that the argument is invalid. A counterexample is a scenario in which the premises are true but the conclusion is false. Solutions are provided below.

Argument 1:

• If an animal is a dog, then it is a mammal.
• Charlie is not a dog.
• Therefore, Charlie is not a mammal.

Argument 2:

• All desserts are sweet foods.
• Some sweet foods are low fat.
• So all desserts are low fat.

Argument 3:

• If Jad doesn’t finish his homework on time, he won’t go to the party.
• Jad doesn’t go to the party.
• Jad didn’t finish his homework on time.

When you have completed your work on the three arguments, check your answers against the solutions below.

Solution 1: Invalid. If you imagine that Charlie is a cat (or other animal that is not a dog but is a mammal), then both the premises are true, while the conclusion is false. Charlie is not a dog, but Charlie is a mammal.

Solution 2: Invalid. Buttercream cake is a counterexample. Buttercream cake is a dessert and is sweet, which shows that not all desserts are low fat.

Solution3: Invalid. Assuming the first two premises are true, you can still imagine that Jad is too tired after finishing his homework and decides not to go to the party, thus making the conclusion false.

Inductive Inferences

When we reason inductively, we gather evidence using our experience of the world and draw general conclusions based on that experience. Inductive reasoning (induction) is also the process by which we use general beliefs we have about the world to create beliefs about our particular experiences or about what to expect in the future. Someone can use their past experiences of eating beets and absolutely hating them to conclude that they do not like beets of any kind, cooked in any manner. They can then use this conclusion to avoid ordering a beet salad at a restaurant because they have good reason to believe they will not like it. Because of the nature of experience and inductive inference, this method can never guarantee the truth of our beliefs. At best, inductive inference generates only probable true conclusions because it goes beyond the information contained in the premises. In the example, past experience with beets is concrete information, but the person goes beyond that information when making the general claim that they will dislike all beets (even those varieties they’ve never tasted and even methods of preparing beets they’ve never tried).

Consider a belief as certain as “the sun will rise tomorrow.” The Scottish philosopher David Hume famously argued against the certainty of this belief nearly three centuries ago ([1748, 1777] 2011, IV, i). Yes, the sun has risen every morning of recorded history (in truth, we have witnessed what appears to be the sun rising, which is a result of the earth spinning on its axis and creating the phenomenon of night and day). We have the science to explain why the sun will continue to rise (because the earth’s rotation is a stable phenomenon). Based on the current science, we can reasonably conclude that the sun will rise tomorrow morning. But is this proposition certain ? To answer this question, you have to think like a philosopher, which involves thinking critically about alternative possibilities. Say the earth gets hit by a massive asteroid that destroys it, or the sun explodes into a supernova that encompasses the inner planets and incinerates them. These events are extremely unlikely to occur, although no contradiction arises in imagining that they could take place. We believe the sun will rise tomorrow, and we have good reason for this belief, but the sun’s rising is still only probable (even if it is nearly certain).

While inductive inferences are not always a sure thing, they can still be quite reliable. In fact, a good deal of what we think we know is known through induction. Moreover, while deductive reasoning can guarantee the truth of conclusions if the premises are true, many times the premises themselves of deductive arguments are inductively known. In studying philosophy, we need to get used to the possibility that our inductively derived beliefs could be wrong.

There are several types of inductive inferences, but for the sake of brevity, this section will cover the three most common types: reasoning from specific instances to generalities, reasoning from generalities to specific instances, and reasoning from the past to the future.

Reasoning from Specific Instances to Generalities

Perhaps I experience several instances of some phenomenon, and I notice that all instances share a similar feature. For example, I have noticed that every year, around the second week of March, the red-winged blackbirds return from wherever they’ve wintering. So I can conclude that generally the red-winged blackbirds return to the area where I live (and observe them) in the second week of March. All my evidence is gathered from particular instances, but my conclusion is a general one. Here is the pattern:

Instance 1 , Instance 2 , Instance 3  . . . Instance n --> Generalization

And because each instance serves as a reason in support of the generalization, the instances are premises in the argument form of this type of inductive inference:

Specific to General Inductive Argument Form:

• General Conclusion

Reasoning from Generalities to Specific Instances

Induction can work in the opposite direction as well: reasoning from accepted generalizations to specific instances. This feature of induction relies on the fact that we are learners and that we learn from past experiences and from one another. Much of what we learn is captured in generalizations. You have probably accepted many generalizations from your parents, teachers, and peers. You probably believe that a red “STOP” sign on the road means that when you are driving and see this sign, you must bring your car to a full stop. You also probably believe that water freezes at 32° Fahrenheit and that smoking cigarettes is bad for you. When you use accepted generalizations to predict or explain things about the world, you are using induction. For example, when you see that the nighttime low is predicted to be 30°F, you may surmise that the water in your birdbath will be frozen when you get up in the morning.

Some thought processes use more than one type of inductive inference. Take the following example:

Every cat I have ever petted doesn’t tolerate its tail being pulled. So this cat probably will not tolerate having its tail pulled.

Notice that this reasoner has gone through a series of instances to make an inference about one additional instance. In doing so, the reasoner implicitly assumed a generalization along the way. The reasoner’s implicit generalization is that no cat likes its tail being pulled. They then use that generalization to determine that they shouldn’t pull the tail of the cat in front of them now. A reasoner can use several instances in their experience as premises to draw a general conclusion and then use that generalization as a premise to draw a conclusion about a specific new instance.

Inductive reasoning finds its way into everyday expressions, such as “Where there is smoke, there is fire.” When people see smoke, they intuitively come to believe that there is fire. This is the result of inductive reasoning. Consider your own thought process as you examine Figure 5.5 .

Reasoning from Past to Future

We often use inductive reasoning to predict what will happen in the future. Based on our ample experience of the past, we have a basis for prediction. Reasoning from the past to the future is similar to reasoning from specific instances to generalities. We have experience of events across time, we notice patterns concerning the occurrence of those events at particular times, and then we reason that the event will happen again in the future. For example:

I see my neighbor walking her dog every morning. So my neighbor will probably walk her dog this morning.

Could the person reasoning this way be wrong? Yes—the neighbor could be sick, or the dog could be at the vet. But depending upon the regularity of the morning dog walks and on the number of instances (say the neighbor has walked the dog every morning for the past year), the inference could be strong in spite of the fact that it is possible for it to be wrong.

Strong Inductive Inferences

The strength of inductive inferences depends upon the reliability of premises given as evidence and their relation to the conclusions drawn. A strong inductive inference is one where, if the evidence offered is true, then the conclusion is probably true. A weak inductive inference is one where, if the evidence offered is true, the conclusion is not probably true. But just how strong an inference needs to be to be considered good is context dependent. The word “probably” is vague. If something is more probable than not, then it needs at least a 51 percent chance of happening. However, in most instances, we would expect to have a much higher probability bar to consider an inference to be strong. As an example of this context dependence, compare the probability accepted as strong in gambling to the much higher probability of accuracy we expect in determining guilt in a court of law.

Figure 5.6 illustrates three forms of reasoning are used in the scientific method. Induction is used to glean patterns and generalizations, from which hypotheses are made. Hypotheses are tested, and if they remain unfalsified, induction is used again to assume support for the hypothesis.

Abductive Reasoning

Abductive reasoning is similar to inductive reasoning in that both forms of inference are probabilistic. However, they differ in the relationship of the premises to the conclusion. In inductive argumentation, the evidence in the premises is used to justify the conclusion. In abductive reasoning, the conclusion is meant to explain the evidence offered in the premises. In induction the premises explain the conclusion, but in abduction the conclusion explains the premises. 

Inference to the Best Explanation

Because abduction reasons from evidence to the most likely explanation for that evidence, it is often called “inference to the best explanation.” We start with a set of data and attempt to come up with some unifying hypothesis that can best explain the existence of those data. Given this structure, the evidence to be explained is usually accepted as true by all parties involved. The focus is not the truth of the evidence, but rather what the evidence means.

Although you may not be aware, you regularly use this form of reasoning. Let us say your car won’t start, and the engine won’t even turn over. Furthermore, you notice that the radio and display lights are not on, even when the key is in and turned to the ON position. Given this evidence, you conclude that the best explanation is that there is a problem with the battery (either it is not connected or is dead). Or perhaps you made pumpkin bread in the morning, but it is not on the counter where you left it when you get home. There are crumbs on the floor, and the bag it was in is also on the floor, torn to shreds. You own a dog who was inside all day. The dog in question is on the couch, head hanging low, ears back, avoiding eye contact. Given the evidence, you conclude that the best explanation for the missing bread is that the dog ate it.

Detectives and forensic investigators use abduction to come up with the best explanation for how a crime was committed and by whom. This form of reasoning is also indispensable to scientists who use observations (evidence) along with accepted hypotheses to create new hypotheses for testing. You may also recognize abduction as a form of reasoning used in medical diagnoses. A doctor considers all your symptoms and any further evidence gathered from preliminarily tests and reasons to the best possible conclusion (a diagnosis) for your illness.

Explanatory Virtues

Good abductive inferences share certain features. Explanatory virtues are aspects of an explanation that generally make it strong. There are many explanatory virtues, but we will focus on four. A good hypothesis should be explanatory, simple , and conservative and must have depth .

To say that a hypothesis must be explanatory simply means that it must explain all the available evidence. The word “explanatory” for our purposes is being used in a narrower sense than used in everyday language. Take the pumpkin bread example: a person might reason that perhaps their roommate ate the loaf of pumpkin bread. However, such an explanation would not explain why the crumbs and bag were on the floor, nor the guilty posture of the dog. People do not normally eat an entire loaf of pumpkin bread, and if they do, they don’t eviscerate the bag while doing so, and even if they did, they’d probably hide the evidence. Thus, the explanation that your roommate ate the bread isn’t as explanatory as the one that pinpoints your dog as the culprit.

But what if you reason that a different dog got into the house and ate the bread, then got out again, and your dog looks guilty because he did nothing to stop the intruder? This explanation seems to explain the missing bread, but it is not as good as the simpler explanation that your dog is the perpetrator. A good explanation is often simple . You may have heard of Occam’s razor , formulated by William of Ockham (1287–1347), which says that the simplest explanation is the best explanation. Ockham said that “entities should not be multiplied beyond necessity” (Spade & Panaccio 2019). By “entities,” Ockham meant concepts or mechanisms or moving parts.

Examples of explanations that lack simplicity abound. For example, conspiracy theories present the very opposite of simplicity since such explanations are by their very nature complex. Conspiracy theories must posit plots, underhanded dealings, cover-ups (to explain the existence of alternative evidence), and maniacal people to explain phenomena and to further explain away the simpler explanation for those phenomena. Conspiracy theories are never simple, but that is not the only reason they are suspect. Conspiracy theories also generally lack the virtues of being conservative and having depth .

A conservative explanation maintains or conserves much of what we already believe. Conservativeness in science is when a theory or hypothesis fits with other established scientific theories and explanations. For example, a theory that accounts for some physical phenomenon but also does not violate Newton’s first law of motion is an example of a conservative theory. On the other hand, consider the conspiracy theory that we never landed on the moon. Someone might posit that the televised Apollo 11 space landing was filmed in a secret studio somewhere. But the reality of the first televised moon landing is not the only belief we must get rid of to maintain the theory. Five more manned moon landings occurred. Furthermore, the reality of the moon landings fits into beliefs about technological advancement over the next five decades. Many of the technologies developed were later adopted by the military and private sector (NASA, n.d.). Moreover, the Apollo missions are a key factor in understanding the space race of the Cold War era. Accepting the conspiracy theory requires rejecting a wide range of beliefs, and so the theory is not conservative.

A conspiracy theorist may offer alternative explanations to account for the tension between their explanation and established beliefs. However, for each explanation the conspiracist offers, more questions are raised. And a good explanation should not raise more questions than it answers. This characteristic is the virtue of depth . A deep explanation avoids unexplained explainers, or an explanation that itself is in need of explanation. For example, the theorist might claim that John Glenn and the other astronauts were brainwashed to explain the astronauts’ firsthand accounts. But this claim raises a question about how brainwashing works. Furthermore, what about the accounts of the thousands of other personnel who worked on the project? Were they all brainwashed? And if so, how? The conspiracy theorist’s explanation raises more questions than it answers.

Extraordinary Claims Require Extraordinary Evidence

Is it possible that our established beliefs (or scientific theories) could be wrong? Why give precedence to an explanation because it upholds our beliefs? Scientific thought would never have advanced if we deferred to conservative explanations all the time. In fact, the explanatory virtues are not laws but rules of thumb, none of which are supreme or necessary. Sometimes the correct explanation is more complicated, and sometimes the correct explanation will require that we give up long-held beliefs. Novel and revolutionary explanations can be strong if they have evidence to back them up. In the sciences, this approach is expressed in the following principle: Extraordinary claims will require extraordinary evidence. In other words, a novel claim that disrupts accepted knowledge will need more evidence to make it credible than a claim that already aligns with accepted knowledge.

Table 5.2 summarizes the three types of inferences just discussed.

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The Peak Performance Center

The pursuit of performance excellence, critical thinking.

critical thinking

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

Critical Thinkers

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

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

“What information supports that?”

“How was this information obtained?”

“Who obtained the information?”

“How do we know the information is valid?”

“Why is it that way?”

“What makes it do that?”

“How do we know that?”

“Are there other possibilities?”

Combination of analytical and creative thinking

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

Elements of Critical Thinking

Critical thinking involves:

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

Developing Critical Thinking Skills

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

Interpreting : understanding the significance or meaning of information

Analyzing : breaking information down into its parts

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

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

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

Reasoning : creating an argument through logical steps

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

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

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

Blooms Taxonomy

Bloom's Taxonomy Revised

Mind Mapping

Chunking Information

Brainstorming

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M18 Critical Thinking & Reasoning

Critical thinking and reasoning: logic and the role of arguments.

Critical thinkers tend to exhibit certain traits that are common to them. These traits are summarized in Table 6.1: [1]

Recall that critical thinking is an active mode of thinking. Instead of just receiving messages and accepting them as is, we consider what they are saying. We ask if messages are well-supported. We determine if their logic is sound or slightly flawed. In other words, we act on the messages before we take action based on them. When we enact critical thinking on a message, we engage a variety of skills including: listening, analysis, evaluation, inference and interpretation or explanation, and self-regulation [2]

Next, we will examine each of these skills and their role in critical thinking in greater detail. As you read through the explanation of and examples for each skill, think about how it works in conjunction with the others. It’s important to note that while our discussion of the skills is presented in a linear manner, in practice our use of each skill is not so straightforward. We may exercise different skills simultaneously or jump forward and backward.

“ Martha Stewart ” by nrkbeta.  CC-BY-SA .

Without an open-minded mind, you can never be a great success. ~ Martha Stewart

In order to understand listening, we must first understand the difference between listening and hearing . At its most basic, hearing refers to the physiological process of receiving sounds, while listening refers to the  psychological process of interpreting or making sense of those sounds.

Every minute of every day we are surrounded by hundreds of different noises and sounds. If we were to try to make sense of each different sound we would probably spend our day just doing this. While we may hear all of the noises, we filter out many of them. They pass through our lives without further notice. Certain noises, however, jump to the forefront of our consciousness. As we listen to them, we make sense of these sounds. We do this every day without necessarily thinking about the process. Like many other bodily functions, it happens without our willing it to happen.

Critical thinking requires that we consciously listen to messages. We must focus on what is being said – and not said. We must strive not to be distracted by other outside noises or the internal noise of our own preconceived ideas. For the moment we only need to take in the message.

Listening becomes especially difficult when the message contains highly charged information. Think about what happens when you try to discuss a controversial issue such as abortion. As the other person speaks, you may have every good intention of listening to the entire argument.

However, when the person says something you feel strongly about you start formulating a counter-argument in your head. The end result is that both sides end up talking past each other without ever really listening to what the other says.

Once we have listened to a message, we can begin to analyze it. In practice we often begin analyzing messages while still listening to them. When we analyze something, we consider it in greater detail, separating out the main components of the message. In a sense, we are acting like a surgeon on the message, carving out all of the different elements and laying them out for further consideration and possible action.

Let’s return to Shonda’s persuasive speech to see analysis in action. As part of the needs section of her speech, Shonda makes the following remarks:

Americans today are some of the unhealthiest people on Earth. It seems like not a week goes by without some news story relating how we are the fattest country in the world. In addition to being overweight, we suffer from a number of other health problems. When I was conducting research for my speech, I read somewhere that heart attacks are the number one killer of men and the number two killer of women. Think about that. My uncle had a heart attack and had to be rushed to the hospital. They hooked him up to a bunch of different machines to keep him alive. We all thought he was going to die. He’s ok now, but he has to take a bunch of pills every day and eat a special diet. Plus he had to pay thousands of dollars in medical bills. Wouldn’t you like to know how to prevent this from happening to you?

If we were to analyze this part of Shonda’s speech (see Table 6.2), we could begin by looking at the claims she makes. We could then look at the evidence she presents in support of these claims. Having parsed out the various elements, we are then ready to evaluate them and by extension the message as a whole.

When we evaluate something we continue the process of analysis by assessing the various claims and arguments for validity. One way we evaluate a message is to ask questions about what is being said and who is saying it. The following is a list of typical questions we may ask, along with an evaluation of the ideas in Shonda’s speech.

Is the speaker credible?

Yes. While Shonda may not be an expert per se on the issue of health benefits related to wine, she has made herself a mini-expert through conducting research.

Does the statement ring true or false based on common sense?

It sounds kind of fishy. Four or more glasses of wine in one sitting doesn’t seem right. In fact, it seems like it might be bordering on binge drinking.

Does the logic employed hold up to scrutiny?

Based on the little bit of Shonda’s speech we see here, her logic does seem to be sound. As we will see later on, she actually commits a few fallacies.

What questions or objections are raised by the message?

In addition to the possibility of Shonda’s proposal being binge drinking, it also raises the possibility of creating alcoholism or causing other long term health problems.

How will further information affect the message?

More information will probably contradict her claims. In fact, most medical research in this area contradicts the claim that drinking 4 or more glasses of wine a day is a good thing.

Will further information strengthen or weaken the claims?

Most likely Shonda’s claims will be weakened.

What questions or objections are raised by the claims?

In addition to the objections we’ve already discussed, there is also the problem of the credibility of Shonda’s expert “doctor.”

A wise man proportions his belief to the evidence. ~ David Hume

Inference and Interpretation or Explanation

“Imply” or “Infer”?

For two relatively small words, imply and infer seem to generate an inordinately large amount of confusion. Understanding the difference between the two and knowing when to use the right one is not only a useful skill, but it also makes you sound a lot smarter!

Let’s begin with imply. Imply means to suggest or convey an idea. A speaker or a piece of writing implies things. For example, in Shonda’s speech, she implies it is better to drink more red wine. In other words, she never directly says that we need to drink more red wine, but she clearly hints at it when she suggests that drinking four or more glasses a day will provide us with health benefits.

Now let’s consider infer. Infer means that something in a speaker’s words or a piece of writing helps us to draw a conclusion outside of his/her words. We infer a conclusion. Returning to Shonda’s speech, we can infer she would want us to drink more red wine rather than less. She never comes right out and says this. However, by considering her overall message, we can draw this conclusion.

Another way to think of the difference between imply and infer is: A speaker (or writer for that matter) implies. The audience infers.

Therefore, it would be incorrect to say that Shonda infers we should drink more rather than less wine. She implies this. To help you differentiate between the two, remember that an inference is something that comes from outside the spoken or written text.

The next step in critically examining a message is to interpret or explain the conclusions that we draw from it. At this phase we consider the evidence and the claims together. In effect we are reassembling the components that we parsed out during analysis. We are continuing our evaluation by looking at the evidence, alternatives, and possible conclusions.

Before we draw any inferences or attempt any explanations, we should look at the evidence provided. When we consider evidence we must first determine what, if any, kind of support is provided. Of the evidence we then ask:

• Is the evidence sound?
• Does the evidence say what thespeaker says it does?
• Does contradictory evidenceexist?
• Is the evidence from a validcredible source?

Seatbelt by M.Minderhoud, CC-BY-SA .

Even though these are set up as yes or no questions, you’ll probably find in practice that your answers are a bit more complex. For example, let’s say you’re writing a speech on why we should wear our seatbelts at all times while driving. You’ve researched the topic and found solid, credible information setting forth the numerous reasons why wearing a seatbelt can help save your life and decrease the number of injuries experienced during a motor vehicle accident. Certainly, there exists contradictory evidence arguing seat belts can cause more injuries. For example, if you’re in an accident where your car is partially submerged in water, wearing a seatbelt may impede your ability to quickly exit the vehicle. Does the fact that this evidence exists negate your claims? Probably not, but you need to be thorough in evaluating and considering how you use your evidence.

A man who does not think for himself does not think at all. ~ Oscar Wilde

Self-Regulation

The final step in critically examining a message is actually a skill we should exercise throughout the entire process. With self-regulation, we consider our pre-existing thoughts on the subject and any biases we may have. We examine how what we think on an issue may have influenced the way we understand (or think we understand) the message and any conclusions we have drawn. Just as contradictory evidence doesn’t automatically negate our claims or invalidate our arguments, our biases don’t necessarily make our conclusions wrong. The goal of practicing self-regulation is not to disavow or deny our opinions. The goal is to create distance between our opinions and the messages we evaluate.

Man thinking on bus , by IG8. CC-BY .

The Value of Critical Thinking

In public speaking, the value of being a critical thinker cannot be overstressed. Critical thinking helps us to determine the truth or validity of arguments. However, it also helps us to formulate strong arguments for our speeches. Exercising critical thinking at all steps of the speech writing and delivering process can help us avoid situations like Shonda found herself in. Critical thinking is not a magical panacea that will make us super speakers. However, it is another tool that we can add to our speech toolbox.

As we will learn in the following pages, we construct arguments based on logic. Understanding the ways logic can be used and possibly misused is a vital skill. To help stress the importance of it, the Foundation for Critical Thinking has set forth universal standards of reasoning. These standards can be found in Table 6.3.

When the mind is thinking, it is talking to itself. ~ Plato

Logic and the Role of Arguments

“Sharia Law Billboard” by Matt57. Public domain.

We use logic every day. Even if we have never formally studied logical reasoning and fallacies, we can often tell when a person’s statement doesn’t sound right. Think about the claims we see in many advertisements today—Buy product X, and you will be beautiful/thin/happy or have the carefree life depicted in the advertisement. With very little critical thought, we know intuitively that simply buying a product will not magically change our lives. Even if we can’t identify the specific fallacy at work in the argument (non causa in this case), we know there is some flaw in the argument.

By studying logic and fallacies we can learn to formulate stronger and more cohesive arguments, avoiding problems like that mentioned above. The study of logic has a long history. We can trace the roots of modern logical study back to Aristotle in ancient Greece. Aristotle’s simple definition of logic as the means by which we come to know anything still provides a concise understanding of logic. [3] Of the classical pillars of a core liberal arts education of logic, grammar, and rhetoric, logic has developed as a fairly independent branch of philosophical studies. We use logic everyday when we construct statements, argue our point of view, and in myriad other ways. Understanding how logic is used will help us communicate more efficiently and effectively.

Defining Arguments

When we think and speak logically, we pull together statements that combine reasoning with evidence to support an assertion, arguments. A logical argument should not be confused with the type of argument you have with your sister or brother or any other person. When you argue with your sibling, you participate in a conflict in which you disagree about something. You may, however, use a logical argument in the midst of the argument with your sibling. Consider this example:

“Man and Woman Arguing” by mzacha. morgueFile .

Brother and sister, Sydney and Harrison are arguing about whose turn it is to clean their bathroom. Harrison tells Sydney she should do it because she is a girl and girls are better at cleaning. Sydney responds that being a girl has nothing to do with whose turn it is. She reminds Harrison that according to their work chart, they are responsible for cleaning the bathroom on alternate weeks. She tells him she cleaned the bathroom last week; therefore, it is his turn this week. Harrison, still unconvinced, refuses to take responsibility for the chore. Sydney then points to the work chart and shows him where it specifically says it is his turn this week. Defeated, Harrison digs out the cleaning supplies.

Throughout their bathroom argument, both Harrison and Sydney use logical arguments to advance their point. You may ask why Sydney is successful and Harrison is not. This is a good question. Let’s critically think about each of their arguments to see why one fails and one succeeds.

Let’s start with Harrison’s argument. We can summarize it into three points:

• Girls are better at cleaning bathrooms than boys.
• Sydney is a girl.
• Therefore, Sydney should clean the bathroom.

Harrison’s argument here is a form of deductive reasoning, specifically a syllogism. We will consider syllogisms in a few minutes. For our purposes here, let’s just focus on why Harrison’s argument fails to persuade Sydney. Assuming for the moment that we agree with Harrison’s first two premises, then it would seem that his argument makes sense. We know that Sydney is a girl, so the second premise is true. This leaves the first premise that girls are better at cleaning bathrooms than boys. This is the exact point where Harrison’s argument goes astray. The only way his entire argument will work is if we agree with the assumption girls are better at cleaning bathrooms than boys.

Let’s now look at Sydney’s argument and why it works. Her argument can be summarized as follows:

1. The bathroom responsibilities alternate weekly according to the work chart.

2. Sydney cleaned the bathroom last week.

3. The chart indicates it is Harrison’s turn to clean the bathroom this week.

4. Therefore, Harrison should clean the bathroom.

“Decorative toilet seat” by Bartux~commonswikiv. Public domain.

Sydney’s argument here is a form of inductive reasoning. We will look at inductive reasoning in depth below. For now, let’s look at why Sydney’s argument succeeds where Harrison’s fails. Unlike Harrison’s argument, which rests on assumption for its truth claims, Sydney’s argument rests on evidence. We can define evidence as anything used to support the validity of an assertion. Evidence includes: testimony, scientific findings, statistics, physical objects, and many others. Sydney uses two primary pieces of evidence: the work chart and her statement that she cleaned the bathroom last week. Because Harrison has no contradictory evidence, he can’t logically refute Sydney’s assertion and is therefore stuck with scrubbing the toilet.

Defining Deduction

Deductive reasoning refers to an argument in which the truth of its premises guarantees the truth of its conclusions. Think back to Harrison’s argument for Sydney cleaning the bathroom. In order for his final claim to be valid, we must accept the truth of his claims that girls are better at cleaning bathrooms than boys. The key focus in deductive arguments is that it must be impossible for the premises to be true and the conclusion to be false. The classic example is:

All men are mortal. Socrates is a man. Therefore, Socrates is mortal.

We can look at each of these statements individually and see each is true in its own right. It is virtually impossible for the first two propositions to be true and the conclusion to be false. Any argument which fails to meet this standard commits a logical error or fallacy. Even if we might accept the arguments as good and the conclusion as possible, the argument fails as a form of deductive reasoning.

A few observations and much reasoning lead to error; many observations and a little reasoning to truth. ~ Alexis Carrel

Another way to think of deductive reasoning is to think of it as moving from a general premise to a specific premise. The basic line of reasoning looks like this:

“Deductive Reasoning” CC-BY-NC-ND .

This form of deductive reasoning is called a syllogism. A syllogism need not have only three components to its argument, but it must have at least three. We have Aristotle to thank for identifying the syllogism and making the study of logic much easier. The focus on syllogisms dominated the field of philosophy for thousands of years. In fact, it wasn’t until the early nineteenth century that we began to see the discussion of other types of logic and other forms of logical reasoning.

It is easy to fall prey to missteps in reasoning when we focus on syllogisms and deductive reasoning. Let’s return to Harrison’s argument and see what happens.

Logic: the art of thinking and reasoning in strict accordance with the limitations and incapacities of the human misunderstanding. ~ Ambrose Bierce

“Applied Deductive Reasoning” CC-BY-NC-ND .

Considered in this manner, it should be clear how the strength of the conclusion depends upon us accepting as true the first two statements. This need for truth sets up deductive reasoning as a very rigid form of reasoning. If either one of the first two premises isn’t true, then the entire argument fails.

Let’s turn to recent world events for another example.

“US Invasion Deductive Reasoning Example” CC-BY-NC-ND .

In the debates over whether the United States should take military action in Iraq, this was the basic line of reasoning used to justify an invasion. This logic was sufficient for the United States to invade Iraq; however, as we have since learned, this line of reasoning also shows how quickly logic can go bad. We subsequently learned that the “experts” weren’t quite so confident, and their “evidence” wasn’t quite as concrete as originally represented.

Defining Induction

Inductive reasoning is often though of as the opposite of deductive reasoning; however, this approach is not wholly accurate. Inductive reasoning does move from the specific to the general. However, this fact alone does not make it the opposite of deductive reasoning. An argument which fails in its deductive reasoning may still stand inductively.

Unlike deductive reasoning, there is no standard format inductive arguments must take, making them more flexible. We can define an inductive argument as one in which the truth of its propositions lends support to the conclusion. The difference here in deduction is the truth of the propositions establishes with absolute certainty the truth of the conclusion. When we analyze an inductive argument, we do not focus on the truth of its premises. Instead we analyze inductive arguments for their strength or soundness.

“Inductive Reasoning Model” CC-BY-NC-ND .

Another significant difference between deduction and induction is inductive arguments do not have a standard format. Let’s return to Sydney’s argument to see how induction develops in action:

• Bathroom cleaning responsibilities alternate weekly according to the work chart.
• Sydney cleaned the bathroom last week.
• The chart indicates it is Harrison’s turn to clean the bathroom this week.
• Therefore, Harrison should clean the bathroom.

What Sydney does here is build to her conclusion that Harrison should clean the bathroom. She begins by stating the general house rule of alternate weeks for cleaning. She then adds in evidence before concluding her argument. While her argument is strong, we don’t know if it is true. There could be other factors Sydney has left out. Sydney may have agreed to take Harrison’s week of bathroom cleaning in exchange for him doing another one of her chores. Or there may be some extenuating circumstances preventing Harrison from bathroom cleaning this week.

You should carefully study the Art of Reasoning, as it is what most people are very deficient in, and I know few things more disagreeable than to argue, or even converse with a man who has no idea of inductive and deductive philosophy. ~ William John Wills

Let’s return to the world stage for another example. After the 9/11 attacks on the World Trade Center, we heard variations of the following arguments:

• The terrorists were Muslim (or Arab or Middle Eastern)
• The terrorists hated America.
• Therefore, all Muslims (or Arabs or Middle Easterners) hate America.

“1993 Word Trade Center bombing” by Bureau of ATF 1993 Explosives Incident Report. Public domain.

Clearly, we can see the problem in this line of reasoning. Beyond being a scary example of hyperbolic rhetoric, we can all probably think of at least one counter example to disprove the conclusion. However, individual passions and biases caused many otherwise rational people to say these things in the weeks following the attacks. This example also clearly illustrates how easy it is to get tripped up in your use of logic and the importance of practicing self-regulation.

• Adapted from Facione, P. A. (1990). Critical Thinking: A Statement of Expert Consensus for Purposes of Educational Assessment and Instruction, The Delphi Report (Executive Summary) . Millbrae, CA: California Academic Press. ↵
• Adapted from Facione, P. A. (1990). ↵
• Aristotle. (1989). Prior Analytics (Trans. Robin Smith). Cambridge, MA: Hackett Publishing. ↵
• Image of man and woman arguing. Authored by : mzacha. Provided by : MorgueFile. Located at : http://mrg.bz/ynkIUa . License : All Rights Reserved . License Terms : Free to remix, commercial use, no attribution required. http://www.morguefile.com/license/morguefile
• Chapter 6 Logic and the Role of Arguments. Authored by : Terri Russ, J.D., Ph.D.. Provided by : Saint Mary's College, Notre Dame, IN. Located at : http://publicspeakingproject.org/psvirtualtext.html . Project : The Public Speaking Project. License : CC BY-NC-ND: Attribution-NonCommercial-NoDerivatives
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