relationship between critical thinking and problem solving skills

Campus Life
...a student.
...a veteran.
...an alum.
...a parent.
...faculty or staff.
Class Schedule
Crisis Resources
People Finder
Change Password

UTC RAVE Alert

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

Teaching Strategies to Help Promote Critical Thinking Skills

References and Resources

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

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

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

Back

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

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

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

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

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

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

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

Teaching Strategies to Help Promote Critical Thinking

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

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

On the Internet

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

Walker Center for Teaching and Learning

433 Library
Dept 4354
615 McCallie Ave
423-425-4188

An official website of the United States government

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

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

Publications
Account settings

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

Advanced Search
Journal List
CBE Life Sci Educ
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

	Minimum	Mean	Median	Maximum
Analysis	70	88.6	90	100
Interpretation	74	89.7	87	100
Inference	78	87.9	89	100
Evaluation	63	83.6	84	100
Explanation	61	84.4	87	100
Induction	74	87.4	87	97
Deduction	71	86.4	87	97
Overall	73	86	85	97

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)

Variable	Model 1	Model 2	Model 3
CCTST inference	0.536***		0.491**
Grade point average		0.176	0.092
Independent study courses		−0.087	0.001
Writing-intensive courses		0.131	0.021
Institution		0.329	0.115
Male		0.085	0.041
Underrepresented group		−0.114	−0.060
Adjusted	0.273	−0. 022	0.195

** 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.

American Association for the Advancement of Science. (2011). Vision and change in undergraduate biology education: A call to action . Washington, DC: Retrieved September 26, 2017, from https://visionandchange.org/files/2013/11/aaas-VISchange-web1113.pdf . [ Google Scholar ]
August D. (2016). California Critical Thinking Skills Test user manual and resource guide . San Jose: Insight Assessment/California Academic Press. [ Google Scholar ]
Beyer C. H., Taylor E., Gillmore G. M. (2013). Inside the undergraduate teaching experience: The University of Washington’s growth in faculty teaching study . Albany, NY: SUNY Press. [ Google Scholar ]
Bissell A. N., Lemons P. P. (2006). A new method for assessing critical thinking in the classroom . BioScience , ( 1 ), 66–72. https://doi.org/10.1641/0006-3568(2006)056[0066:ANMFAC]2.0.CO;2 . [ Google Scholar ]
Blattner N. H., Frazier C. L. (2002). Developing a performance-based assessment of students’ critical thinking skills . Assessing Writing , ( 1 ), 47–64. [ Google Scholar ]
Clase K. L., Gundlach E., Pelaez N. J. (2010). Calibrated peer review for computer-assisted learning of biological research competencies . Biochemistry and Molecular Biology Education , ( 5 ), 290–295. [ PubMed ] [ Google Scholar ]
Condon W., Kelly-Riley D. (2004). Assessing and teaching what we value: The relationship between college-level writing and critical thinking abilities . Assessing Writing , ( 1 ), 56–75. https://doi.org/10.1016/j.asw.2004.01.003 . [ Google Scholar ]
Ding L., Wei X., Liu X. (2016). Variations in university students’ scientific reasoning skills across majors, years, and types of institutions . Research in Science Education , ( 5 ), 613–632. https://doi.org/10.1007/s11165-015-9473-y . [ Google Scholar ]
Dowd J. E., Connolly M. P., Thompson R. J., Jr., Reynolds J. A. (2015a). Improved reasoning in undergraduate writing through structured workshops . Journal of Economic Education , ( 1 ), 14–27. https://doi.org/10.1080/00220485.2014.978924 . [ Google Scholar ]
Dowd J. E., Roy C. P., Thompson R. J., Jr., Reynolds J. A. (2015b). “On course” for supporting expanded participation and improving scientific reasoning in undergraduate thesis writing . Journal of Chemical Education , ( 1 ), 39–45. https://doi.org/10.1021/ed500298r . [ Google Scholar ]
Dowd J. E., Thompson R. J., Jr., Reynolds J. A. (2016). Quantitative genre analysis of undergraduate theses: Uncovering different ways of writing and thinking in science disciplines . WAC Journal , , 36–51. [ Google Scholar ]
Facione P. A. (1990). Critical thinking: a statement of expert consensus for purposes of educational assessment and instruction. Research findings and recommendations . Newark, DE: American Philosophical Association; Retrieved September 26, 2017, from https://philpapers.org/archive/FACCTA.pdf . [ Google Scholar ]
Gerdeman R. D., Russell A. A., Worden K. J., Gerdeman R. D., Russell A. A., Worden K. J. (2007). Web-based student writing and reviewing in a large biology lecture course . Journal of College Science Teaching , ( 5 ), 46–52. [ Google Scholar ]
Greenhoot A. F., Semb G., Colombo J., Schreiber T. (2004). Prior beliefs and methodological concepts in scientific reasoning . Applied Cognitive Psychology , ( 2 ), 203–221. https://doi.org/10.1002/acp.959 . [ Google Scholar ]
Haaga D. A. F. (1993). Peer review of term papers in graduate psychology courses . Teaching of Psychology , ( 1 ), 28–32. https://doi.org/10.1207/s15328023top2001_5 . [ Google Scholar ]
Halonen J. S., Bosack T., Clay S., McCarthy M., Dunn D. S., Hill G. W., Whitlock K. (2003). A rubric for learning, teaching, and assessing scientific inquiry in psychology . Teaching of Psychology , ( 3 ), 196–208. https://doi.org/10.1207/S15328023TOP3003_01 . [ Google Scholar ]
Hand B., Keys C. W. (1999). Inquiry investigation . Science Teacher , ( 4 ), 27–29. [ Google Scholar ]
Holm S. (1979). A simple sequentially rejective multiple test procedure . Scandinavian Journal of Statistics , ( 2 ), 65–70. [ Google Scholar ]
Holyoak K. J., Morrison R. G. (2005). The Cambridge handbook of thinking and reasoning . New York: Cambridge University Press. [ Google Scholar ]
Insight Assessment. (2016a). California Critical Thinking Skills Test (CCTST) Retrieved September 26, 2017, from www.insightassessment.com/Products/Products-Summary/Critical-Thinking-Skills-Tests/California-Critical-Thinking-Skills-Test-CCTST .
Insight Assessment. (2016b). Sample thinking skills questions. Retrieved September 26, 2017, from www.insightassessment.com/Resources/Teaching-Training-and-Learning-Tools/node_1487 .
Kelly G. J., Takao A. (2002). Epistemic levels in argument: An analysis of university oceanography students’ use of evidence in writing . Science Education , ( 3 ), 314–342. https://doi.org/10.1002/sce.10024 . [ Google Scholar ]
Kuhn D., Dean D., Jr. (2004). Connecting scientific reasoning and causal inference . Journal of Cognition and Development , ( 2 ), 261–288. https://doi.org/10.1207/s15327647jcd0502_5 . [ Google Scholar ]
Kuhn D., Iordanou K., Pease M., Wirkala C. (2008). Beyond control of variables: What needs to develop to achieve skilled scientific thinking? . Cognitive Development , ( 4 ), 435–451. https://doi.org/10.1016/j.cogdev.2008.09.006 . [ Google Scholar ]
Lawson A. E. (2010). Basic inferences of scientific reasoning, argumentation, and discovery . Science Education , ( 2 ), 336–364. https://doi.org/10.1002/sce.20357 . [ Google Scholar ]
Meizlish D., LaVaque-Manty D., Silver N., Kaplan M. (2013). Think like/write like: Metacognitive strategies to foster students’ development as disciplinary thinkers and writers . In Thompson R. J. (Ed.), Changing the conversation about higher education (pp. 53–73). Lanham, MD: Rowman & Littlefield. [ Google Scholar ]
Miri B., David B.-C., Uri Z. (2007). Purposely teaching for the promotion of higher-order thinking skills: A case of critical thinking . Research in Science Education , ( 4 ), 353–369. https://doi.org/10.1007/s11165-006-9029-2 . [ Google Scholar ]
Moshman D. (2015). Epistemic cognition and development: The psychology of justification and truth . New York: Psychology Press. [ Google Scholar ]
National Research Council. (2000). How people learn: Brain, mind, experience, and school . Expanded ed. Washington, DC: National Academies Press. [ Google Scholar ]
Pukkila P. J. (2004). Introducing student inquiry in large introductory genetics classes . Genetics , ( 1 ), 11–18. https://doi.org/10.1534/genetics.166.1.11 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
Quitadamo I. J., Faiola C. L., Johnson J. E., Kurtz M. J. (2008). Community-based inquiry improves critical thinking in general education biology . CBE—Life Sciences Education , ( 3 ), 327–337. https://doi.org/10.1187/cbe.07-11-0097 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
Quitadamo I. J., Kurtz M. J. (2007). Learning to improve: Using writing to increase critical thinking performance in general education biology . CBE—Life Sciences Education , ( 2 ), 140–154. https://doi.org/10.1187/cbe.06-11-0203 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
Reynolds J. A., Smith R., Moskovitz C., Sayle A. (2009). BioTAP: A systematic approach to teaching scientific writing and evaluating undergraduate theses . BioScience , ( 10 ), 896–903. https://doi.org/10.1525/bio.2009.59.10.11 . [ Google Scholar ]
Reynolds J. A., Thaiss C., Katkin W., Thompson R. J. (2012). Writing-to-learn in undergraduate science education: A community-based, conceptually driven approach . CBE—Life Sciences Education , ( 1 ), 17–25. https://doi.org/10.1187/cbe.11-08-0064 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
Reynolds J. A., Thompson R. J. (2011). Want to improve undergraduate thesis writing? Engage students and their faculty readers in scientific peer review . CBE—Life Sciences Education , ( 2 ), 209–215. https://doi.org/10.1187/cbe.10-10-0127 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
Rhemtulla M., Brosseau-Liard P. E., Savalei V. (2012). When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions . Psychological Methods , ( 3 ), 354–373. https://doi.org/10.1037/a0029315 . [ PubMed ] [ Google Scholar ]
Stephenson N. S., Sadler-McKnight N. P. (2016). Developing critical thinking skills using the science writing heuristic in the chemistry laboratory . Chemistry Education Research and Practice , ( 1 ), 72–79. https://doi.org/10.1039/C5RP00102A . [ Google Scholar ]
Tariq V. N., Stefani L. A. J., Butcher A. C., Heylings D. J. A. (1998). Developing a new approach to the assessment of project work . Assessment and Evaluation in Higher Education , ( 3 ), 221–240. https://doi.org/10.1080/0260293980230301 . [ Google Scholar ]
Timmerman B. E. C., Strickland D. C., Johnson R. L., Payne J. R. (2011). Development of a “universal” rubric for assessing undergraduates’ scientific reasoning skills using scientific writing . Assessment and Evaluation in Higher Education , ( 5 ), 509–547. https://doi.org/10.1080/02602930903540991 . [ Google Scholar ]
Topping K. J., Smith E. F., Swanson I., Elliot A. (2000). Formative peer assessment of academic writing between postgraduate students . Assessment and Evaluation in Higher Education , ( 2 ), 149–169. https://doi.org/10.1080/713611428 . [ Google Scholar ]
Willison J., O’Regan K. (2007). Commonly known, commonly not known, totally unknown: A framework for students becoming researchers . Higher Education Research and Development , ( 4 ), 393–409. https://doi.org/10.1080/07294360701658609 . [ Google Scholar ]
Woodin T., Carter V. C., Fletcher L. (2010). Vision and Change in Biology Undergraduate Education: A Call for Action—Initial responses . CBE—Life Sciences Education , ( 2 ), 71–73. https://doi.org/10.1187/cbe.10-03-0044 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
Zeineddin A., Abd-El-Khalick F. (2010). Scientific reasoning and epistemological commitments: Coordination of theory and evidence among college science students . Journal of Research in Science Teaching , ( 9 ), 1064–1093. https://doi.org/10.1002/tea.20368 . [ Google Scholar ]
Zimmerman C. (2000). The development of scientific reasoning skills . Developmental Review , ( 1 ), 99–149. https://doi.org/10.1006/drev.1999.0497 . [ Google Scholar ]
Zimmerman C. (2007). The development of scientific thinking skills in elementary and middle school . Developmental Review , ( 2 ), 172–223. https://doi.org/10.1016/j.dr.2006.12.001 . [ Google Scholar ]

Get started with computers
Learn Microsoft Office
Apply for a job
Improve my work skills
Design nice-looking docs
Getting Started
Smartphones & Tablets
Typing Tutorial
Online Learning
Basic Internet Skills
Online Safety
Social Media
Zoom Basics
Google Docs
Google Sheets
Career Planning
Resume Writing
Cover Letters
Job Search and Networking
Business Communication
Entrepreneurship 101
Careers without College
Job Hunt for Today
3D Printing
Freelancing 101
Personal Finance
Sharing Economy
Decision-Making
Graphic Design
Photography
Image Editing
Learning WordPress
Language Learning
Critical Thinking
For Educators
Translations
Staff Picks
English expand_more expand_less

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

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

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

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

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

Watch the video below to learn more about critical thinking.

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

illustration of the terms logic, reasoning, and creativity

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

The process

illustration of "thoughts" inside a human brain, with several being connected and "analyzed"

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

Improving your critical thinking

illustration of the questions "What do I currently know?" and "How do I know this?"

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

Real-world applications

illustration of a hand holding a smartphone displaying an article that reads, "Study: Cats are better than dogs"

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

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

illustration of "Super Cat Blog" and "According to survery of cat owners" being highlighted from an article on a smartphone

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

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

illustration of a lightbulb, a briefcase, and the world

/en/problem-solving-and-decision-making/why-is-it-so-hard-to-make-decisions/content/

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

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

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

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

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

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

7.1. Different kinds of thought

7.2. Reasoning and Judgment

7.3. Problem Solving

READING WITH PURPOSE

Remember and understand.

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

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

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

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

Analyze, Evaluate, and Create

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

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

7.1. Different kinds of thought and knowledge

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

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

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

Factual and conceptual knowledge

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

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

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

Procedural knowledge

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

Metacognitive knowledge

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

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

The Dunning-Kruger Effect

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

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

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

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

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

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

Critical thinking

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

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

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

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

A Critical Thinker’s Toolkit

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

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

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

Here are some common sources of biases:

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

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

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

relationship between critical thinking and problem solving skills

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

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

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

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

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

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

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

bias : an inclination, tendency, leaning, or prejudice

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

7.2 Reasoning and Judgment

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

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

Deductive reasoning

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

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

Statement 2: You get an A on the final exam

Conclusion: You will get an A for the course

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

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

therefore q

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

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

I won’t have pizza (not p)

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

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

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

if p, then q

therefore, not p

Concrete version:

If I eat dinner, then I will have dessert

I did not have dessert

Therefore, I did not eat dinner

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

Students who like school study a lot

Students who study a lot get good grades

Jane does not like school

Therefore, Jane does not get good grades

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

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

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

You are not eleven feet tall

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

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

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

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

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

Inductive reasoning and judgment

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

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

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

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

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

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

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

Statement #1: Psychology is not my best subject

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

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

Judgment: The next exam will probably be very difficult.

Decision: I will study tonight instead of watching Netflix.

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

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

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

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

Statement #1: It is late at night.

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

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

Judgment: Albert will have no difficulty walking home.

Decision: He walks home alone.

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

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

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

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

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

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

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

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

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

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

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

Judgment: Breast cancer is the most common type.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

What percentage of workplace homicides are co-worker violence?

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

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

7.3 Problem Solving

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

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

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

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

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

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

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

Defining and Mentally Representing Problems in Order to Solve Them

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

insight : a sudden realization of a solution to a problem

Solving Problems by Trial and Error

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

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

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

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

Solving Problems with Algorithms and Heuristics

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

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

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

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

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

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

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

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

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

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

An Effective Problem-Solving Sequence

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

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

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

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

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

a mental representation of a category of things in the world

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

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

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

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

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

an inclination, tendency, leaning, or prejudice

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

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

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

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

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

fast, automatic, and emotional thinking

slow, effortful, and logical thinking

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

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

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

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

noticing, comprehending and forming a mental conception of a problem

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

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

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

a sudden realization of a solution to a problem

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

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

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

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

Share This Book

The Peak Performance Center

The pursuit of performance excellence, critical thinking.

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

Critical Thinkers

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

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

“What information supports that?”

“How was this information obtained?”

“Who obtained the information?”

“How do we know the information is valid?”

“Why is it that way?”

“What makes it do that?”

“How do we know that?”

“Are there other possibilities?”

Combination of Analytical and Creative Thinking

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

Elements of Critical Thinking

Critical thinking involves:

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

Developing Critical Thinking Skills

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

Interpreting : understanding the significance or meaning of information

Analyzing : breaking information down into its parts

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

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

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

Reasoning : creating an argument through logical steps

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

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

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

Blooms Taxonomy

Bloom’s Taxonomy Revised

Mind Mapping

Chunking Information

Brainstorming

career support

support to get a great job

Career Development

Critical Thinking vs Problem Solving: Understanding the Key Differences

Critical thinking and problem solving are two related but distinct skills that are crucial for success in work and life. While they both involve analytical thinking to evaluate situations, there are some key differences between the two. In this article, I’ll explain what critical thinking and problem solving are, break down the major differences between them, and provide examples of how to use each skill effectively.

What is Critical Thinking?

Critical thinking is the disciplined process of actively analyzing, synthesizing, interpreting, and evaluating information gathered from observation, reasoning, communication, or experience. It requires meticulously scrutinizing assumptions, discerning hidden values, assessing evidence, and interpreting facts to come to an objective, reasoned judgment.

The key characteristics of critical thinking include

Asking pertinent questions
Examining relevant evidence
Discerning between facts and opinions
Considering multiple perspectives
Acknowledging biases and assumptions
Identifying trends and patterns
Drawing well-reasoned conclusions
Testing hypotheses and inferences

Critical thinking isn’t about criticizing or finding fault Its purpose is to methodically analyze information to reach an impartial, logical determination of validity and value

What is Problem Solving?

Problem solving is the process of identifying a problem, discovering the underlying issue, developing potential solutions, evaluating the best option, implementing it, and reviewing the results to prevent the problem from recurring. It is a purposeful, structured approach to identifying obstacles and devising ways to surmount them.

The key aspects of effective problem solving include

Defining the problem clearly
Analyzing root causes
Brainstorming creative solutions
Evaluating pros and cons of options
Selecting optimal responses
Executing a solution successfully
Following up to assess resolution

Problem solving involves both analytics to understand causes and creativity to generate solutions. It seeks to find practical remedies to concrete issues that stand in the way of desired goals.

Key Differences Between Critical Thinking and Problem Solving

While critical thinking and problem solving certainly overlap, there are several key ways in which they differ:

Goal – Critical thinking aims to form a reasoned judgment or conclusion. Problem solving seeks to develop solutions.
Scope – Critical thinking deals with intangible concepts and ideas. Problem solving tackles tangible obstacles.
Approach – Critical thinking analyzes rationality and logic. Problem solving uses creative ideation and analysis.
Output – Critical thinking results in a hypothesis or inference. Problem solving results in an action plan and implementation.
Bias – Critical thinking requires removing bias. Problem solving includes personal/cultural context.
Application – Critical thinking applies to any scenario. Problem solving targets defined issues.

In short, critical thinking goes as far as understanding and evaluating a situation while problem solving goes beyond to identify, select, and carry out solutions.

Examples of Critical Thinking vs Problem Solving

Here are some examples that illustrate the key distinctions between critical thinking skills and problem solving skills in practice:

A manager critically analyzing the root causes of steadily declining sales would be demonstrating critical thinking. Developing and rolling out a promotion to turn sales around would demonstrate problem solving.

A student carefully evaluating the arguments on both sides of a controversial issue would be applying critical thinking. Coming up with an informed position or plan to address the controversy would be problem solving.

A scientist interpreting complex data to draw conclusions about the effectiveness of a new medical treatment would be utilizing critical thinking. Figuring out how to apply the findings to improve future treatments would be problem solving.

An engineer weighing the pros and cons of different building materials for a construction project would be critical thinking. Determining the right materials to meet durability, cost, and sustainability needs would be problem solving.

As you can see, critical thinking focuses on understanding the what and why of a situation, while problem solving focuses on how to address the situation pragmatically.

How to Improve Your Critical Thinking and Problem Solving Skills

Here are some tips to help develop stronger critical thinking and problem solving abilities:

For critical thinking:

Ask probing questions
Thoroughly research topics from multiple sources
Recognize biases and faulty logic
Consider context, cultural influences, and implicit values
Practice analyzing perspectives that differ from your own
Question assumptions and test inferences

For problem solving:

Take time to clearly define the problem – don’t make assumptions
Break large problems into smaller, manageable pieces
Research solutions that have worked for similar issues
Brainstorm creative solutions without judging initial ideas
Use logic and analysis to evaluate options thoroughly
Commit to a solution, implement, review, and recalibrate as needed

Getting in the habit of using critical thinking and problem solving in your daily life will help build proficiency. Seek out opportunities to flex these mental muscles and you’ll become a sharper, more nimble thinker.

Why Critical Thinking and Problem Solving Matter

In today’s fast-paced, complex world, being able to think critically and solve problems efficiently is more important than ever. These skills are invaluable for:

Making sound decisions – Critical analysis leads to more informed choices while problem solving enables executing the best option.

Achieving goals – Problem solving clears away obstacles standing in the way of accomplishments.

Innovation – New inventions, processes, and methods are born from keen critical thinking combined with creative problem solving.

Learning and growth – Strong analytic and problem solving skills allow for continuously expanding understanding and improvement.

Career advancement – Employers highly value and reward workers who demonstrate strong critical thinking and problem solving capabilities.

Personal success – Sharper thinking yields greater achievement, flexibility, self-sufficiency, and resilience in life.

In work and in life, being able to understand complex dynamics, evaluate information, and devise effective solutions provides a tremendous advantage.

While critical thinking and problem solving certainly intersect, they are distinct skills that serve different primary purposes. Critical thinking aims to assess rationality and form impartial evaluations while problem solving focuses on overcoming barriers to achieve goals.

By sharpening your skills in analysis, inference, creative ideation, logic, and objective reasoning, you can become an exceptional critical thinker and problem solver. These capabilities will supercharge your decision making, productivity, and ability to navigate challenges.

Make a point to practice critical thinking and problem solving regularly. Never stop questioning, examining, and striving to understand the deeper why and how of the world around you and your own mind. Keep these muscles strong and you’ll perform at your peak mentally.

Looking deeper: what skills are involved in critical thinking?

Weâve looked up definitions for critical thinking and problem solving, but these definitions donât tell us anything about the skills that are involved in each. For instance, what exactly do my kids need to be able to do in order to think critically? Critical thinking skills are habits of mind that help us be more thoughtful, rational, creative, and curious. Critical thinking can involve collecting information, organizing what we collect, analyzing and evaluating the information we have, making connections between different ideas, understanding whatâs relevant and what isnât, and so much more. All of this gives us a basis on which an informed decision can be made.

But when do we make decisions? When weâre confronted with a task, challenge, or problem. Indeed, we apply critical thinking when we are faced with a problem that demands we apply some of those skills. Critical thinking skills are general plans of attack, applicable to a wide array of problems!

Critical thinking vs. problem solving: the definitions

I was recently chatting with a colleague about the kinds of skills kids need to develop to be successful on the job, and in life. I started running down a list, and she said something along the lines of, âWell, critical thinking and problem solvingâ¦ theyâre the same thing right?â Thatâs a really interesting question! For my colleague, âcritical thinkingâ and âproblem solvingâ are just phrases that are out there, somehow related to learning. And just like with anything else in life, when you havenât had a reason to investigate them deeply, they might just be ideas that seem to mean something vaguely similarâ¦ but what do these ideas really mean?

First, letâs start with some basic definitions. Critical thinking, according to dictionary.com, is âdisciplined thinking that is clear, rational, open-minded and informed by evidence.â Well, that certainly sounds like something I want my kids to be proficient in! According to Merriam-Webster, problem solving is âthe process or act of finding a solution to a problemâ, and thereâs another no-brainer, definitely something I want to instill in my children. Can we move from these definitions to a real understanding of the differences between these two skill sets?

What is the difference between critical thinking and problem-solving?

Critical thinking and problem-solving can both help you resolve challenges, but the two practices have distinct purposes and strategies. Here are some differences between the two skills: This is a mode of thinking, compared to problem-solving, which is a set of solution-oriented strategies.

Is problem solving a critical thinking skill?

Problem solving uses many of the same skills required for critical thinking; e.g., observation, analysis, evaluation, interpretation, and reflection. Critical thinking is an important ingredient of problem solving. Not every problem-solving skill is a critical thinking skill. That is because not every problem requires thinking.

Why is critical thinking important?

Since critical thinking strengthens your reasoning, it makes it easier to learn new skills, including problem-solving. Working on your critical thinking can also help you understand yourself better, including your value system, learning style and strongest skills. Critical thinking comprises five steps, which are :

How can I improve my critical thinking and problem solving skills?

The first step to enhancing your critical thinking and problem solving skills is to think about them, become aware of them, then you can actively practice to improve them. Critical thinking and problem-solving are two important “soft” or essential skills hiring managers are looking for.

What Is Treasury Management? (With Definition and Benefits)
RASCI: What It Is and How To Use It for Project Management
Interview Question: “What’s the Most Difficult Decision You’ve Had to Make?”
Blog : Is there a dress code for the modern paralegal?

How to calculate percentile rank step-by-step, i want to be a lawyer: a step-by-step guide to becoming an attorney, leave a reply cancel reply.

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

How It Works

Link copied to clipboard

A Discrete Geometry Drawing Challenge

Kids Learn “New Math” for Good Reasons

Look out big ideas are hiding in your arithmetic, how can you prove something true by proving something else can't be true, the value of mathematical simplicity, making math relevant, pictures help us remember math, puzzling with your kids, seven questions (and one strategy) to build critical thinking skills, dissections in science, math, and reasoning, why learn math you might never actually use, how do you grow a critical thinker, trouble with an sat-style math question plug in numbers, yes, you'll enjoy this puzzling mathematical paradox, math should be complex, not complicated, help your kids become stronger problem solvers with one question, how to teach your child persistence, sometimes a jigsaw puzzle is more than just a puzzle, napoleon... the mathematician, sat-style geometry trick: make the “best” picture, 5 tips for helping your child with math homework, sports build your kids' mathematics skills, where is the math in bubbles, what would you decide a probability puzzle, algebra is useful... right, help your child work through frustration in math, all games build math and critical thinking skills, teach kids how to respond to mistakes, there is awesome math in your kitchen, experiment, and grow a little problem-solving in your garden, help your child build a problem-solving strategy toolbox, 6 strategies for building a positive math mindset, the math of dice and fair games, the importance of out-of-the-box thinking, the benefits of taking a break in problem solving, 5 tips to help kids get unstuck in math, what is graph theory, and why does it matter so much, talking about mental math with kids is meaningful, teach kids to make mistakes, why should kids learn to generalize in math, being good at math does not depend on how "smart" we are, 5 reasons your family should play more games, homer simpson and... the pythagorean theorem, help your kids learn to jump in and experiment, one easy way to do more math with your kids, what happens when you can't build something to help solve a problem, not sure how to start a problem choose a path… and then maybe another path, what’s the difference between critical thinking skills and problem-solving skills, are you smarter than the smart-bots, word problems don't have to be scary, help your child learn more by saying less, help your kids to flex their focus, the power of geometry vocabulary, getting the pythagorean theorem (really) right, confident parents build confident problem solvers, using math models: can you see all the sets, playing cards: the most amazing learning tool, help your child to become a better problem solver, why is understanding patterns so important, did you know there's math hiding in your spreadsheet, if you like magic squares, this puzzle is for you, we have to teach our kids how to struggle, wondering why, with your child, is worthwhile, your favorite mathematician should be euler, the number line contains all your favorite books, the importance of frames of reference in learning, geometry is not boring, kids can learn so much through tangram paradoxes, it's not magic, it's number sense, division is not boring, teaching through mystery, the joy of discovering mathematics… for yourself, the power of notation in math, building your child's problem solving tools: drawing, the value of labeling things in math, how can a problem that feels incomplete be finished, we are all natural (math) problem solvers, how well do you really know pi, how exstemsions is different, a single picture can explain the pythagorean theorem.

Critical thinking vs. problem solving: the definitions

I was recently chatting with a colleague about the kinds of skills kids need to develop to be successful on the job, and in life. I started running down a list, and she said something along the lines of, “Well, critical thinking and problem solving… they’re the same thing right?” That’s a really interesting question! For my colleague, “critical thinking” and “problem solving” are just phrases that are out there, somehow related to learning. And just like with anything else in life, when you haven’t had a reason to investigate them deeply, they might just be ideas that seem to mean something vaguely similar… but what do these ideas really mean?

First, let’s start with some basic definitions. Critical thinking, according to dictionary.com, is “disciplined thinking that is clear, rational, open-minded and informed by evidence.” Well, that certainly sounds like something I want my kids to be proficient in! According to Merriam-Webster, problem solving is “the process or act of finding a solution to a problem”, and there’s another no-brainer, definitely something I want to instill in my children. Can we move from these definitions to a real understanding of the differences between these two skill sets?

Looking deeper: what skills are involved in critical thinking?

We’ve looked up definitions for critical thinking and problem solving, but these definitions don’t tell us anything about the skills that are involved in each. For instance, what exactly do my kids need to be able to do in order to think critically? Critical thinking skills are habits of mind that help us be more thoughtful, rational, creative, and curious. Critical thinking can involve collecting information, organizing what we collect, analyzing and evaluating the information we have, making connections between different ideas, understanding what’s relevant and what isn’t, and so much more. All of this gives us a basis on which an informed decision can be made.

But when do we make decisions? When we’re confronted with a task, challenge, or problem . Indeed, we apply critical thinking when we are faced with a problem that demands we apply some of those skills. Critical thinking skills are general plans of attack, applicable to a wide array of problems!

Looking deeper: what skills are involved in problem solving?

So now we’ve discovered something interesting: critical thinking skills are problem solving skills! And if you think about it, any critical thinking skill could conceivably be applied to finding the solution to some kind of problem. (In fact, it's hard to define critical thinking skills and not make them about problem solving in some way!) So, every critical thinking skill is a problem-solving skill.

Does that mean that every problem-solving skill is also a critical thinking skill? Actually, no. For starters, there are lots of skills that help us solve problems, but are not thinking skills! For example, brute strength is a body skill that is also a problem-solving skill. (But probably much of the time, you need to figure out how to use that strength, say, so you don't unnecessarily break your best friend’s TV when helping her move to a new home; critical thinking skills to the rescue!)

There are also problem-solving skills that are thinking skills, but just not critical thinking skills. For example, people with “emotional intelligence” can soothe tempers, read other people, and help move ideas forward in contexts that have nothing to do with problem solving. Skills of persuasion and oration are thinking skills, but they don't necessarily have to be critical thinking skills.

There are even problem-solving skills that are the complete opposite of critical thinking, like following directions, and mechanical and rote thinking. For example, learning the steps for solving a linear equation allows you to solve linear equations like a machine, no critical thinking required. However, rote thinking without critical thinking can be dangerous; you don't necessarily want to follow rules without checking that those rules make sense!

Critical thinking and problem solving: sometimes different, sometimes the same

We know that critical thinking skills are fundamental to problem-solving. And we know that there are other skills that help us solve problems, skills that aren’t critical thinking skills. Problem solving involves a wide array of techniques and attacks, some of which fall under critical thinking, and some which don’t. Aspects of critical thinking and problem solving can be different, or the same, but both sets of skills are incredibly important for all kids to have. There isn’t a skill we’ve talked about here where I think “Well, my kiddo could probably live without being able to do that….” Critical thinking is the foundation that allows us to tackle challenges of all kinds, supplemented by other problem-solving skills as needed. We want our kids to have all of these skills at their fingertips, so they can solve problems effectively, using strong evidence, logical thinking, and clear reasoning. All are vital ingredients to a successful and happy grown-up life!

Find this post useful? Follow the blog using the link at the top of the page to get notified when new posts appear!

Looking for tasks that require BOTH critical thinking, and problem solving? Check out our Teachers Pay Teachers store !

Want awesome tips and a mini-challenge, all designed to help you build vital problem-solving and critical thinking skills in your child? Click here to sign up for our monthly newsletter!

Collaborative Learning and Critical Thinking

Reference work entry
Cite this reference work entry

Anu A. Gokhale 2

2987 Accesses

28 Citations

Cooperative learning ; Creative thinking ; Problem-solving

The term “collaborative learning” refers to an instruction method in which students at various performance levels work together in small groups toward a common goal. Collaborative learning is a relationship among learners that fosters positive interdependence, individual accountability, and interpersonal skills. “Critical thinking” involves asking appropriate questions, gathering and creatively sorting through relevant information, relating new information to existing knowledge, reexamining beliefs, reasoning logically, and drawing reliable and trustworthy conclusions.

Theoretical Background

The advent of revolutionary information and communication technologies has effected changes in the organizational infrastructure and altered the characteristics of the workplace putting an increased emphasis on teamwork and processes that require individuals to pool their resources and integrate specializations. The...

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

Access this chapter

Subscribe and save.

Get 10 units per month
Download Article/Chapter or eBook
1 Unit = 1 Article or 1 Chapter
Cancel anytime
Available as PDF
Read on any device
Instant download
Own it forever
Available as EPUB and PDF
Durable hardcover edition
Dispatched in 3 to 5 business days
Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

American Philosophical Association. (1990). Critical thinking: A statement of expert consensus for purposes of educational assessment and instruction. ERIC document ED (pp. 315–423).

Google Scholar

Cooper, J., Prescott, S., Cook, L., Smith, L., Mueck, R., & Cuseo, J. (1990). Cooperative learning and college instruction: Effective use of student learning teams . Long Beach: California State University Foundation.

Gokhale, A. A. (1995). Collaborative learning enhances critical thinking. Journal of Technology Education, 7 (1), 22–30.

Johnson, D. W., & Johnson, R. T. (1989). Cooperation and competition: Theory and research . Edina: Interaction Book Company.

Kollar, I., Fischer, F., & Hesse, F. (2006). Collaboration scripts – A conceptual analysis. Educational Psychology Review, 18 (2), 159–185.

Slavin, R. E. (1995). Cooperative learning: Theory, research, and practice (2nd ed.). Boston: Allyn & Bacon.

Download references

Author information

Authors and affiliations.

Department of Technology, Illinois State University, Campus Box 5100, Normal, IL, 61790-5110, USA

Dr. Anu A. Gokhale

You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anu A. Gokhale .

Editor information

Editors and affiliations.

Faculty of Economics and Behavioral Sciences, Department of Education, University of Freiburg, 79085, Freiburg, Germany

Norbert M. Seel

Rights and permissions

Reprints and permissions

Copyright information

About this entry

Cite this entry.

Gokhale, A.A. (2012). Collaborative Learning and Critical Thinking. In: Seel, N.M. (eds) Encyclopedia of the Sciences of Learning. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1428-6_910

Download citation

DOI : https://doi.org/10.1007/978-1-4419-1428-6_910

Publisher Name : Springer, Boston, MA

Print ISBN : 978-1-4419-1427-9

Online ISBN : 978-1-4419-1428-6

eBook Packages : Humanities, Social Sciences and Law

Share this entry

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

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

Provided by the Springer Nature SharedIt content-sharing initiative

Publish with us

Policies and ethics

Find a journal
Track your research

Not For Profit Charity
Early Childhood Language Delays
Language & Literacy Development
Professionals
Our Thought Leaders
Our Global Reach
It Takes Two To Talk
More Than Words
TalkAbility
Target Word
Learning Language and Loving It
ABC and Beyond
Teacher Talk Training Series
Program Search
Hanen 4 “I”s to Socialize
SPARK Communication
Workshop Schedule
Academic Presentation
Workshop Notification
It Takes Two to Talk
Make Play R.O.C.K.™ Booklet Series
You Make The Difference
Teacher Talk Workbooks
It Takes Two to Talk Parent Workbook - member only
Healthcare Professionals
When You Are Concerned
Parent Tips
Language and Literacy Tips
Fun Activities
Autism Corner
Literacy at Home
Literacy in the Classroom
Technology Corner
Hanen Newsletter
Speech-Language Pathologists

Critical Thinking: Building a Key Foundation for Language and Literacy Success

Did you know that school curriculums around the world are increasing their focus on critical thinking skills? Experts on early childhood development agree that the basic skills of reading, writing and math are no longer enough – children also need to learn to think critically if they’re going to be successful in today’s complex world.

What Is Critical Thinking?

Critical thinking happens when children draw on their existing knowledge and experience, as well as on their problem-solving skills, to do things like:

Compare and contrast
Explain why things happen
Evaluate ideas and form opinions
Understand the perspectives of others
Predict what will happen in the future
Think of creative solutions

Why is critical thinking so important?

Critical thinking is a fundamental skills for both language and literacy success.

Language − Language and critical thinking grow together and nurture each other’s development. As children engage in critical thinking, their language skills expand because they’re encouraged to develop and use more complex language with words like “because”, phrases with “if” and “then” and different verb tenses. Conversely, as children’s language development progresses, their ability to think critically grows as well.
Literacy − To truly understand the meaning of a book, children must be able to do more than recognize and sound out letters and words. They must also “read between the lines” to figure things out that are not actually stated in the book. To do this, they must use critical thinking skills like problem-solving, predicting and explaining. Encouraging this kind of thinking early in a child’s life prepares her for understanding the books she’ll read on her own later on.

When and How Does Critical Thinking Develop?

Research shows that children begin to think critically at a very young age. These skills develop during the natural, back and forth conversations children have with the important adults in their lives.

As soon as children are able to speak in sentences, they’re ready for you − the parent, caregiver or educator − to nurture the critical thinking skills that will prepare them for success in school. Whether you’re reading a book or taking a walk in the park, any time is a good time to build critical thinking.

Tips for Building Critical Thinking – It’s all about the E’s and P’s!

Use the arrows to scroll through the E’s and P’s and get a fun tip from the 2016 Calendar for promoting each one!

Tip for parents	Tip for educators
While pretending with stuffed animals, join in with your own animal and have your animal ask the other a question that could have many fun explanations. For example, "Why is your fur purple?" or "Why do you have such big teeth?"	Have the children pretend they're going on a trip to the desert and tell them they have only one suitcase to bring with them. Ask each child to name an item they'd put in the suitcase and explain why they think it will be important in the desert.

Tip for parents	Tip for educators
Using plastic food items, pretend you are judges in a food competition. Start by offering your own opinion with an explanation. For example, "I don't like this pasta because it's too salty" or "I like this soup because it has lots of carrots and they're my favourite." Encourage your child to offer his own opinions along with his reasons for them.	Show the children the Sports section of a newspaper and point out the different sports that are mentioned. Ask the children which sport they think is the hardest to play, and ask them to explain their reasoning.

Tip for parents	Tip for educators
When finished reading a book, encourage your child to think about what might happen next if the story continued. For example, "What do you think will happen tomorrow night when it is time for Mortimer to go to sleep again?" Ask your child to explain why he thinks that.	When introducing a new book, talk about the title and the illustrations on the cover, and ask the children what they think might happen in the story. Make sure to include a follow-up question like, "What makes you think that?"

Tip for parents	Tip for educators
During pretend activities, take on a role and make comments that show your child that you're thinking about how your pretend character feels. For example, "I'm just a little teddy bear in this big department store all by myself. I feel really scared."	Encourage the children to take on pretend roles and think about how their pretend character feels and what they might do. For example, "Oh no, Little Bear, your chair is broken! How does that make you feel?"

Tip for parents	Tip for educators
Draw your child's attention to problems as they arise and provide her with opportunities to think of solutions. For example, "Uh-oh. Your lunch bag is missing. What else can we use to carry your lunch?"	While on a walk, point out a problem and encourage the children to think of a solution. For example, "There's a lot of litter on the grass around here. What do you think could be done to stop people from littering here?"

Helpful articles on critical thinking

More Than ABCs: Building the Critical Thinking Skills Your Child Needs for Literacy Success Get more fun tips on building children’s E’s and P’s during book reading. Read article

Teaching Children to Think: Meeting the Demands of the 21st Century Learn more about the evolving role of early childhood educators and what governments around the world are doing to increase the focus on critical thinking. Read article

Share This Page

Contact Us |
Copyright |
Privacy Policy |
Accessibility Policy |
Terms of Use

Critical thinking definition

Critical thinking, as described by Oxford Languages, is the objective analysis and evaluation of an issue in order to form a judgement.

Active and skillful approach, evaluation, assessment, synthesis, and/or evaluation of information obtained from, or made by, observation, knowledge, reflection, acumen or conversation, as a guide to belief and action, requires the critical thinking process, which is why it's often used in education and academics.

Some even may view it as a backbone of modern thought.

However, it's a skill, and skills must be trained and encouraged to be used at its full potential.

People turn up to various approaches in improving their critical thinking, like:

Developing technical and problem-solving skills
Engaging in more active listening
Actively questioning their assumptions and beliefs
Seeking out more diversity of thought
Opening up their curiosity in an intellectual way etc.

Is critical thinking useful in writing?

Critical thinking can help in planning your paper and making it more concise, but it's not obvious at first. We carefully pinpointed some the questions you should ask yourself when boosting critical thinking in writing:

What information should be included?
Which information resources should the author look to?
What degree of technical knowledge should the report assume its audience has?
What is the most effective way to show information?
How should the report be organized?
How should it be designed?
What tone and level of language difficulty should the document have?

Usage of critical thinking comes down not only to the outline of your paper, it also begs the question: How can we use critical thinking solving problems in our writing's topic?

Let's say, you have a Powerpoint on how critical thinking can reduce poverty in the United States. You'll primarily have to define critical thinking for the viewers, as well as use a lot of critical thinking questions and synonyms to get them to be familiar with your methods and start the thinking process behind it.

Are there any services that can help me use more critical thinking?

We understand that it's difficult to learn how to use critical thinking more effectively in just one article, but our service is here to help.

We are a team specializing in writing essays and other assignments for college students and all other types of customers who need a helping hand in its making. We cover a great range of topics, offer perfect quality work, always deliver on time and aim to leave our customers completely satisfied with what they ordered.

The ordering process is fully online, and it goes as follows:

Select the topic and the deadline of your essay.
Provide us with any details, requirements, statements that should be emphasized or particular parts of the essay writing process you struggle with.
Leave the email address, where your completed order will be sent to.
Select your prefered payment type, sit back and relax!

With lots of experience on the market, professionally degreed essay writers , online 24/7 customer support and incredibly low prices, you won't find a service offering a better deal than ours.

Resilience is the process and outcome of successfully adapting to difficult or challenging life experiences, especially through mental, emotional, and behavioral flexibility and adjustment to external and internal demands.

A number of factors contribute to how well people adapt to adversities, including the ways in which individuals view and engage with the world, the availability and quality of social resources, and specific coping strategies.

Psychological research demonstrates that the resources and skills associated with resilience can be cultivated and practiced.

Adapted from the APA Dictionary of Psychology

Resources from APA

Building your resilience

Resilience for teens: 10 tips to build skills on bouncing back from rough times

Resilience guide for parents and teachers

Nature Meets Nurture

Motivation Myth Busters

Building Psychological Resilience in Military Personnel

The Pain Survival Guide, Rev. Ed.

Magination Press children’s books

The Hugging Tree

Lucy's Light

New Kid, New Scene

Out of the Fires

Baxter and Danny Stand Up to Bullying

Journal special issues

Trauma, Aging, and Well-Being

Resilience and Perseverance for Human Flourishing

Collaborative and Participatory Research to Promote Engagement, Empowerment, and Resilience for Immigrant and Refugee Youth, Families, and Communities

Psychiatric Rehabilitation for Veterans

IMAGES

Critical Thinking Skills
What is Critical Thinking and Problem Solving?
Critical Thinking and Problem Solving Skills by Heba Mansour on Prezi
6 Main Types of Critical Thinking Skills (With Examples)
[Outline] Critical Thinking & Problem Solving
How to promote Critical Thinking Skills

VIDEO

Problem solving and critical thinking
Core Critical thinking Skills
How ‘Flight Takes A Break Mid-Video’ Became His Biggest Meme
Top Critical Thinking Skills
Creative Thinking VS Critical Thinking
5 Examples of Critical Thinking Skills (to Become a Pro Problem Solver)

COMMENTS

Critical Thinking vs. Problem-Solving: What's the Difference?
Critical thinking vs. problem-solving Critical thinking and problem-solving can both help you resolve challenges, but the two practices have distinct purposes and strategies. Here are some differences between the two skills: Critical thinking This is a mode of thinking, compared to problem-solving, which is a set of solution-oriented strategies.
Critical Thinking versus Problem Solving
The first step to enhancing your critical thinking and problem solving skills is to think about them, become aware of them, then you can actively practice to improve them. Critical thinking and problem-solving are two important "soft" or essential skills hiring managers are looking for. According to a Linkedin survey, 57% of business ...
Critical Thinking and Problem-Solving
Critical thinking involves asking questions, defining a problem, examining evidence, analyzing assumptions and biases, avoiding emotional reasoning, avoiding oversimplification, considering other interpretations, and tolerating ambiguity. Dealing with ambiguity is also seen by Strohm & Baukus (1995) as an essential part of critical thinking ...
Understanding the Complex Relationship between Critical Thinking and
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 ...
5.3: Using Critical Thinking Skills- Decision Making and Problem Solving
Using Critical Thinking Skills in Problem Solving. Think of problem solving as a process with four Ps: Define the problem, generate possibilities,. create a plan, and perform your plan.. Step 1: Define the problem. To define a problem effectively, understand what a problem is—a mismatch between what you want and what you have.
Critical Thinking and Problem-Solving Skills
Critical thinking is a type of systematic thinking that is used to solve problems using logic. The first step is to gather the information needed to help you solve your problem. You start by analyzing and evaluating sources for authority to give you the best shot at finding something truthful and unbiased.
PDF Investigating The Relationship Between Critical Thinking Skills and
investigating the relationship between critical thinking and problem solving skills that includes overcoming the problems of daily life in different educational grades and professional groups (Koray et al., 2007; Cantürk, Günhan & Başer, 2009; Beşer & Kıssal, 2009; Choi, Lindquist & Song, 2014). A similar relationship is also considered to ...
Critical Thinking
Critical thinking is the discipline of rigorously and skillfully using information, experience, observation, and reasoning to guide your decisions, actions, and beliefs. You'll need to actively question every step of your thinking process to do it well. Collecting, analyzing and evaluating information is an important skill in life, and a highly ...
Critical Thinking and Decision-Making
Definition. Simply put, critical thinking is the act of deliberately analyzing information so that you can make better judgements and decisions. It involves using things like logic, reasoning, and creativity, to draw conclusions and generally understand things better. This may sound like a pretty broad definition, and that's because critical ...
7 Module 7: Thinking, Reasoning, and Problem-Solving
Module 7: Thinking, Reasoning, and Problem-Solving. This module is about how a solid working knowledge of psychological principles can help you to think more effectively, so you can succeed in school and life. You might be inclined to believe that—because you have been thinking for as long as you can remember, because you are able to figure ...
PDF Problem Solving and Critical Thinking
problems is one of the skills that employers look for in employees. Employers say they need a workforce fully equipped with skills beyond the basics of reading, writing, and arithmetic to grow their businesses. These skills include critical thinking and problem solving, according to a 2010 Critical Skills Survey by the American
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 ...
Critical Thinking vs Problem Solving: Understanding the Key Differences
Examples of Critical Thinking vs Problem Solving. Here are some examples that illustrate the key distinctions between critical thinking skills and problem solving skills in practice: A manager critically analyzing the root causes of steadily declining sales would be demonstrating critical thinking. Developing and rolling out a promotion to turn ...
What's the Difference Between Critical Thinking Skills and…
Critical thinking skills are habits of mind that help us be more thoughtful, rational, creative, and curious. Critical thinking can involve collecting information, organizing what we collect, analyzing and evaluating the information we have, making connections between different ideas, understanding what's relevant and what isn't, and so ...
Critical Thinking and Problem Solving Skills: How these Skills are
Pearson correlation test results (r) between the critical thinking skills and problem solving ability of students did not show a strong relationship even contradictory (-.05). based on the results ...
Collaborative Learning and Critical Thinking
Collaborative learning is a relationship among learners that fosters positive interdependence, individual accountability, and interpersonal skills. "Critical thinking" involves asking appropriate questions, gathering and creatively sorting through relevant information, relating new information to existing knowledge, reexamining beliefs ...
Relationship between Problem Solving and Critical Thinking (adapted
According to Rahmat (2020), writing improves problem solving and critical thinking skills. This is because learners are forced to use their thought processes to writeeven more so for creative ...
Critical Thinking: A Key Foundation for Language and Literacy ...
Critical thinking happens when children draw on their existing knowledge and experience, as well as on their problem-solving skills, to do things like: Compare and contrast. Explain why things happen. Evaluate ideas and form opinions. Understand the perspectives of others. Predict what will happen in the future. Think of creative solutions.
Determine the Relationship Between the Disposition of Critical Thinking
Key words: Critical thinking, problem solving skills, music teacher, correlational model 1. ... Tumkaya, Albek and Aldag (2009) aimed to determine whether there was a significant relationship between disposition of critical thinking and problem solving skills, and whether university students' disposition of critical thinking and problem solving ...
PDF The Relationship between Critical Thinking Disposition and Problem
Objective : The aim of the study was to investigate the relationship between critical thinking disposition and problem solving skills in nurses. Material and method: The research was a descriptive and correlation type. The research was carried out at a private hospital in the city of İstanbul in Turkey between April and July 2018.
Relationship between problem solving and critical thinking skills
Riyadi. Siswanto. Critical thinking skills are important in solving geometric problems. The intelligence aspect also influences problem-solving. Therefore, this study aimed to describe students ...
Using Critical Thinking in Essays and other Assignments
Critical thinking, as described by Oxford Languages, is the objective analysis and evaluation of an issue in order to form a judgement. Active and skillful approach, evaluation, assessment, synthesis, and/or evaluation of information obtained from, or made by, observation, knowledge, reflection, acumen or conversation, as a guide to belief and ...
Explained: Importance of critical thinking, problem-solving skills in
Critical thinking and problem-solving skills are two of the most sought-after skills. Hence, schools should emphasise the upskilling of students as a part of the academic curriculum.
Resilience
Resilience is the process and outcome of successfully adapting to difficult or challenging life experiences, especially through mental, emotional, and behavioral flexibility and adjustment to external and internal demands.

UTC RAVE Alert

References and Resources

Teaching Strategies to Help Promote Critical Thinking

Other Reading

On the Internet

Walker Center for Teaching and Learning

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

Robert J. Thompson, Jr.

Leslie A. Schiff

Julie A. Reynolds

INTRODUCTION

Critical Thinking

Scientific Reasoning

Scientific Reasoning in Students’ Thesis Writing

Research Question and Study Design

Study Sample

Scientific Reasoning in Writing

Statistical Analyses

Supplementary Material

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

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

The process

Improving your critical thinking

Real-world applications

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

READING WITH PURPOSE

Analyze, Evaluate, and Create

7.1. Different kinds of thought and knowledge

Factual and conceptual knowledge

Procedural knowledge

Metacognitive knowledge

The Dunning-Kruger Effect

Critical thinking

A Critical Thinker’s Toolkit

7.2 Reasoning and Judgment

Deductive reasoning

Inductive reasoning and judgment

7.3 Problem Solving

Defining and Mentally Representing Problems in Order to Solve Them

Solving Problems by Trial and Error

Solving Problems with Algorithms and Heuristics

An Effective Problem-Solving Sequence

Share This Book

The Peak Performance Center

Critical Thinkers

Combination of Analytical and Creative Thinking

Elements of Critical Thinking

Developing Critical Thinking Skills

Critical Thinking vs Problem Solving: Understanding the Key Differences

What is Critical Thinking?

What is Problem Solving?

Key Differences Between Critical Thinking and Problem Solving

Examples of Critical Thinking vs Problem Solving

How to Improve Your Critical Thinking and Problem Solving Skills

Why Critical Thinking and Problem Solving Matter

Looking deeper: what skills are involved in critical thinking?

Critical thinking vs. problem solving: the definitions

Related posts:

Related Posts

A Discrete Geometry Drawing Challenge

Kids Learn “New Math” for Good Reasons

Critical thinking vs. problem solving: the definitions

Looking deeper: what skills are involved in critical thinking?

Looking deeper: what skills are involved in problem solving?

Critical thinking and problem solving: sometimes different, sometimes the same

Collaborative Learning and Critical Thinking

Theoretical Background

Access this chapter

Author information

Corresponding author

Editor information

Rights and permissions

Copyright information

About this entry

Download citation

Share this entry

Critical Thinking: Building a Key Foundation for Language and Literacy Success

What Is Critical Thinking?

Why is critical thinking so important?

When and How Does Critical Thinking Develop?