scientific thinking and critical thinking

Advertisement

Scientific Thinking and Critical Thinking in Science Education 

Two Distinct but Symbiotically Related Intellectual Processes

• Open access
• Published: 05 September 2023

Cite this article

You have full access to this open access article

• Antonio García-Carmona   ORCID: orcid.org/0000-0001-5952-0340 1  

5038 Accesses

Explore all metrics

Scientific thinking and critical thinking are two intellectual processes that are considered keys in the basic and comprehensive education of citizens. For this reason, their development is also contemplated as among the main objectives of science education. However, in the literature about the two types of thinking in the context of science education, there are quite frequent allusions to one or the other indistinctly to refer to the same cognitive and metacognitive skills, usually leaving unclear what are their differences and what are their common aspects. The present work therefore was aimed at elucidating what the differences and relationships between these two types of thinking are. The conclusion reached was that, while they differ in regard to the purposes of their application and some skills or processes, they also share others and are related symbiotically in a metaphorical sense; i.e., each one makes sense or develops appropriately when it is nourished or enriched by the other. Finally, an orientative proposal is presented for an integrated development of the two types of thinking in science classes.

Similar content being viewed by others

Philosophical Inquiry and Critical Thinking in Primary and Secondary Science Education

Fostering scientific literacy and critical thinking in elementary science education.

Enhancing Scientific Thinking Through the Development of Critical Thinking in Higher Education

Avoid common mistakes on your manuscript.

Education is not the learning of facts, but the training of the mind to think. Albert Einstein

1 Introduction

In consulting technical reports, theoretical frameworks, research, and curricular reforms related to science education, one commonly finds appeals to scientific thinking and critical thinking as essential educational processes or objectives. This is confirmed in some studies that include exhaustive reviews of the literature in this regard such as those of Bailin ( 2002 ), Costa et al. ( 2020 ), and Santos ( 2017 ) on critical thinking, and of Klarh et al. ( 2019 ) and Lehrer and Schauble ( 2006 ) on scientific thinking. However, conceptualizing and differentiating between both types of thinking based on the above-mentioned documents of science education are generally difficult. In many cases, they are referred to without defining them, or they are used interchangeably to represent virtually the same thing. Thus, for example, the document A Framework for K-12 Science Education points out that “Critical thinking is required, whether in developing and refining an idea (an explanation or design) or in conducting an investigation” (National Research Council (NRC), 2012 , p. 46). The same document also refers to scientific thinking when it suggests that basic scientific education should “provide students with opportunities for a range of scientific activities and scientific thinking , including, but not limited to inquiry and investigation, collection and analysis of evidence, logical reasoning, and communication and application of information” (NRC, 2012 , p. 251).

A few years earlier, the report Science Teaching in Schools in Europe: Policies and Research (European Commission/Eurydice, 2006 ) included the dimension “scientific thinking” as part of standardized national science tests in European countries. This dimension consisted of three basic abilities: (i) to solve problems formulated in theoretical terms , (ii) to frame a problem in scientific terms , and (iii) to formulate scientific hypotheses . In contrast, critical thinking was not even mentioned in such a report. However, in subsequent similar reports by the European Commission/Eurydice ( 2011 , 2022 ), there are some references to the fact that the development of critical thinking should be a basic objective of science teaching, although these reports do not define it at any point.

The ENCIENDE report on early-year science education in Spain also includes an explicit allusion to critical thinking among its recommendations: “Providing students with learning tools means helping them to develop critical thinking , to form their own opinions, to distinguish between knowledge founded on the evidence available at a certain moment (evidence which can change) and unfounded beliefs” (Confederation of Scientific Societies in Spain (COSCE), 2011 , p. 62). However, the report makes no explicit mention to scientific thinking. More recently, the document “ Enseñando ciencia con ciencia ” (Teaching science with science) (Couso et al., 2020 ), sponsored by Spain’s Ministry of Education, also addresses critical thinking:

(…) with the teaching approach through guided inquiry students learn scientific content, learn to do science (procedures), learn what science is and how it is built, and this (...) helps to develop critical thinking , that is, to question any statement that is not supported by evidence. (Couso et al., 2020 , p. 54)

On the other hand, in referring to what is practically the same thing, the European report Science Education for Responsible Citizenship speaks of scientific thinking when it establishes that one of the challenges of scientific education should be: “To promote a culture of scientific thinking and inspire citizens to use evidence-based reasoning for decision making” (European Commission, 2015 , p. 14). However, the Pisa 2024 Strategic Vision and Direction for Science report does not mention scientific thinking but does mention critical thinking in noting that “More generally, (students) should be able to recognize the limitations of scientific inquiry and apply critical thinking when engaging with its results” (Organization for Economic Co-operation and Development (OECD), 2020 , p. 9).

The new Spanish science curriculum for basic education (Royal Decree 217/ 2022 ) does make explicit reference to scientific thinking. For example, one of the STEM (Science, Technology, Engineering, and Mathematics) competency descriptors for compulsory secondary education reads:

Use scientific thinking to understand and explain the phenomena that occur around them, trusting in knowledge as a motor for development, asking questions and checking hypotheses through experimentation and inquiry (...) showing a critical attitude about the scope and limitations of science. (p. 41,599)

Furthermore, when developing the curriculum for the subjects of physics and chemistry, the same provision clarifies that “The essence of scientific thinking is to understand what are the reasons for the phenomena that occur in the natural environment to then try to explain them through the appropriate laws of physics and chemistry” (Royal Decree 217/ 2022 , p. 41,659). However, within the science subjects (i.e., Biology and Geology, and Physics and Chemistry), critical thinking is not mentioned as such. Footnote 1 It is only more or less directly alluded to with such expressions as “critical analysis”, “critical assessment”, “critical reflection”, “critical attitude”, and “critical spirit”, with no attempt to conceptualize it as is done with regard to scientific thinking.

The above is just a small sample of the concepts of scientific thinking and critical thinking only being differentiated in some cases, while in others they are presented as interchangeable, using one or the other indistinctly to talk about the same cognitive/metacognitive processes or practices. In fairness, however, it has to be acknowledged—as said at the beginning—that it is far from easy to conceptualize these two types of thinking (Bailin, 2002 ; Dwyer et al., 2014 ; Ennis, 2018 ; Lehrer & Schauble, 2006 ; Kuhn, 1993 , 1999 ) since they feed back on each other, partially overlap, and share certain features (Cáceres et al., 2020 ; Vázquez-Alonso & Manassero-Mas, 2018 ). Neither is there unanimity in the literature on how to characterize each of them, and rarely have they been analyzed comparatively (e.g., Hyytinen et al., 2019 ). For these reasons, I believed it necessary to address this issue with the present work in order to offer some guidelines for science teachers interested in deepening into these two intellectual processes to promote them in their classes.

2 An Attempt to Delimit Scientific Thinking in Science Education

For many years, cognitive science has been interested in studying what scientific thinking is and how it can be taught in order to improve students’ science learning (Klarh et al., 2019 ; Zimmerman & Klarh, 2018 ). To this end, Kuhn et al. propose taking a characterization of science as argument (Kuhn, 1993 ; Kuhn et al., 2008 ). They argue that this is a suitable way of linking the activity of how scientists think with that of the students and of the public in general, since science is a social activity which is subject to ongoing debate, in which the construction of arguments plays a key role. Lehrer and Schauble ( 2006 ) link scientific thinking with scientific literacy, paying especial attention to the different images of science. According to those authors, these images would guide the development of the said literacy in class. The images of science that Leherer and Schauble highlight as characterizing scientific thinking are: (i) science-as-logical reasoning (role of domain-general forms of scientific reasoning, including formal logic, heuristic, and strategies applied in different fields of science), (ii) science-as-theory change (science is subject to permanent revision and change), and (iii) science-as-practice (scientific knowledge and reasoning are components of a larger set of activities that include rules of participation, procedural skills, epistemological knowledge, etc.).

Based on a literature review, Jirout ( 2020 ) defines scientific thinking as an intellectual process whose purpose is the intentional search for information about a phenomenon or facts by formulating questions, checking hypotheses, carrying out observations, recognizing patterns, and making inferences (a detailed description of all these scientific practices or competencies can be found, for example, in NRC, 2012 ; OECD, 2019 ). Therefore, for Jirout, the development of scientific thinking would involve bringing into play the basic science skills/practices common to the inquiry-based approach to learning science (García-Carmona, 2020 ; Harlen, 2014 ). For other authors, scientific thinking would include a whole spectrum of scientific reasoning competencies (Krell et al., 2022 ; Moore, 2019 ; Tytler & Peterson, 2004 ). However, these competences usually cover the same science skills/practices mentioned above. Indeed, a conceptual overlap between scientific thinking, scientific reasoning, and scientific inquiry is often found in science education goals (Krell et al., 2022 ). Although, according to Leherer and Schauble ( 2006 ), scientific thinking is a broader construct that encompasses the other two.

It could be said that scientific thinking is a particular way of searching for information using science practices Footnote 2 (Klarh et al., 2019 ; Zimmerman & Klarh, 2018 ; Vázquez-Alonso & Manassero-Mas, 2018 ). This intellectual process provides the individual with the ability to evaluate the robustness of evidence for or against a certain idea, in order to explain a phenomenon (Clouse, 2017 ). But the development of scientific thinking also requires metacognition processes. According to what Kuhn ( 2022 ) argues, metacognition is fundamental to the permanent control or revision of what an individual thinks and knows, as well as that of the other individuals with whom it interacts, when engaging in scientific practices. In short, scientific thinking demands a good connection between reasoning and metacognition (Kuhn, 2022 ). Footnote 3

From that perspective, Zimmerman and Klarh ( 2018 ) have synthesized a taxonomy categorizing scientific thinking, relating cognitive processes with the corresponding science practices (Table 1 ). It has to be noted that this taxonomy was prepared in line with the categorization of scientific practices proposed in the document A Framework for K-12 Science Education (NRC, 2012 ). This is why one needs to understand that, for example, the cognitive process of elaboration and refinement of hypotheses is not explicitly associated with the scientific practice of hypothesizing but only with the formulation of questions. Indeed, the K-12 Framework document does not establish hypothesis formulation as a basic scientific practice. Lederman et al. ( 2014 ) justify it by arguing that not all scientific research necessarily allows or requires the verification of hypotheses, for example, in cases of exploratory or descriptive research. However, the aforementioned document (NRC, 2012 , p. 50) does refer to hypotheses when describing the practice of developing and using models , appealing to the fact that they facilitate the testing of hypothetical explanations .

In the literature, there are also other interesting taxonomies characterizing scientific thinking for educational purposes. One of them is that of Vázquez-Alonso and Manassero-Mas ( 2018 ) who, instead of science practices, refer to skills associated with scientific thinking . Their characterization basically consists of breaking down into greater detail the content of those science practices that would be related to the different cognitive and metacognitive processes of scientific thinking. Also, unlike Zimmerman and Klarh’s ( 2018 ) proposal, Vázquez-Alonso and Manassero-Mas’s ( 2018 ) proposal explicitly mentions metacognition as one of the aspects of scientific thinking, which they call meta-process . In my opinion, the proposal of the latter authors, which shells out scientific thinking into a broader range of skills/practices, can be more conducive in order to favor its approach in science classes, as teachers would have more options to choose from to address components of this intellectual process depending on their teaching interests, the educational needs of their students and/or the learning objectives pursued. Table 2 presents an adapted characterization of the Vázquez-Alonso and Manassero-Mas’s ( 2018 ) proposal to address scientific thinking in science education.

3 Contextualization of Critical Thinking in Science Education

Theorization and research about critical thinking also has a long tradition in the field of the psychology of learning (Ennis, 2018 ; Kuhn, 1999 ), and its application extends far beyond science education (Dwyer et al., 2014 ). Indeed, the development of critical thinking is commonly accepted as being an essential goal of people’s overall education (Ennis, 2018 ; Hitchcock, 2017 ; Kuhn, 1999 ; Willingham, 2008 ). However, its conceptualization is not simple and there is no unanimous position taken on it in the literature (Costa et al., 2020 ; Dwyer et al., 2014 ); especially when trying to relate it to scientific thinking. Thus, while Tena-Sánchez and León-Medina ( 2022 ) Footnote 4 and McBain et al. ( 2020 ) consider critical thinking to be the basis of or forms part of scientific thinking, Dowd et al. ( 2018 ) understand scientific thinking to be just a subset of critical thinking. However, Vázquez-Alonso and Manassero-Mas ( 2018 ) do not seek to determine whether critical thinking encompasses scientific thinking or vice versa. They consider that both types of knowledge share numerous skills/practices and the progressive development of one fosters the development of the other as a virtuous circle of improvement. Other authors, such as Schafersman ( 1991 ), even go so far as to say that critical thinking and scientific thinking are the same thing. In addition, some views on the relationship between critical thinking and scientific thinking seem to be context-dependent. For example, Hyytine et al. ( 2019 ) point out that in the perspective of scientific thinking as a component of critical thinking, the former is often used to designate evidence-based thinking in the sciences, although this view tends to dominate in Europe but not in the USA context. Perhaps because of this lack of consensus, the two types of thinking are often confused, overlapping, or conceived as interchangeable in education.

Even with such a lack of unanimous or consensus vision, there are some interesting theoretical frameworks and definitions for the development of critical thinking in education. One of the most popular definitions of critical thinking is that proposed by The National Council for Excellence in Critical Thinking (1987, cited in Inter-American Teacher Education Network, 2015 , p. 6). This conceives of it as “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”. In other words, critical thinking can be regarded as a reflective and reasonable class of thinking that provides people with the ability to evaluate multiple statements or positions that are defensible to then decide which is the most defensible (Clouse, 2017 ; Ennis, 2018 ). It thus requires, in addition to a basic scientific competency, notions about epistemology (Kuhn, 1999 ) to understand how knowledge is constructed. Similarly, it requires skills for metacognition (Hyytine et al., 2019 ; Kuhn, 1999 ; Magno, 2010 ) since critical thinking “entails awareness of one’s own thinking and reflection on the thinking of self and others as objects of cognition” (Dean & Kuhn, 2003 , p. 3).

In science education, one of the most suitable scenarios or resources, but not the only one, Footnote 5 to address all these aspects of critical thinking is through the analysis of socioscientific issues (SSI) (Taylor et al., 2006 ; Zeidler & Nichols, 2009 ). Without wishing to expand on this here, I will only say that interesting works can be found in the literature that have analyzed how the discussion of SSIs can favor the development of critical thinking skills (see, e.g., López-Fernández et al., 2022 ; Solbes et al., 2018 ). For example, López-Fernández et al. ( 2022 ) focused their teaching-learning sequence on the following critical thinking skills: information analysis, argumentation, decision making, and communication of decisions. Even some authors add the nature of science (NOS) to this framework (i.e., SSI-NOS-critical thinking), as, for example, Yacoubian and Khishfe ( 2018 ) in order to develop critical thinking and how this can also favor the understanding of NOS (Yacoubian, 2020 ). In effect, as I argued in another work on the COVID-19 pandemic as an SSI, in which special emphasis was placed on critical thinking, an informed understanding of how science works would have helped the public understand why scientists were changing their criteria to face the pandemic in the light of new data and its reinterpretations, or that it was not possible to go faster to get an effective and secure medical treatment for the disease (García-Carmona, 2021b ).

In the recent literature, there have also been some proposals intended to characterize critical thinking in the context of science education. Table 3 presents two of these by way of example. As can be seen, both proposals share various components for the development of critical thinking (respect for evidence, critically analyzing/assessing the validity/reliability of information, adoption of independent opinions/decisions, participation, etc.), but that of Blanco et al. ( 2017 ) is more clearly contextualized in science education. Likewise, that of these authors includes some more aspects (or at least does so more explicitly), such as developing epistemological Footnote 6 knowledge of science (vision of science…) and on its interactions with technology, society, and environment (STSA relationships), and communication skills. Therefore, it offers a wider range of options for choosing critical thinking skills/processes to promote it in science classes. However, neither proposal refers to metacognitive skills, which are also essential for developing critical thinking (Kuhn, 1999 ).

3.1 Critical thinking vs. scientific thinking in science education: differences and similarities

In accordance with the above, it could be said that scientific thinking is nourished by critical thinking, especially when deciding between several possible interpretations and explanations of the same phenomenon since this generally takes place in a context of debate in the scientific community (Acevedo-Díaz & García-Carmona, 2017 ). Thus, the scientific attitude that is perhaps most clearly linked to critical thinking is the skepticism with which scientists tend to welcome new ideas (Normand, 2008 ; Sagan, 1987 ; Tena-Sánchez and León-Medina, 2022 ), especially if they are contrary to well-established scientific knowledge (Bell, 2009 ). A good example of this was the OPERA experiment (García-Carmona & Acevedo-Díaz, 2016a ), which initially seemed to find that neutrinos could move faster than the speed of light. This finding was supposed to invalidate Albert Einstein’s theory of relativity (the finding was later proved wrong). In response, Nobel laureate in physics Sheldon L. Glashow went so far as to state that:

the result obtained by the OPERA collaboration cannot be correct. If it were, we would have to give up so many things, it would be such a huge sacrifice... But if it is, I am officially announcing it: I will shout to Mother Nature: I’m giving up! And I will give up Physics. (BBVA Foundation, 2011 )

Indeed, scientific thinking is ultimately focused on getting evidence that may support an idea or explanation about a phenomenon, and consequently allow others that are less convincing or precise to be discarded. Therefore when, with the evidence available, science has more than one equally defensible position with respect to a problem, the investigation is considered inconclusive (Clouse, 2017 ). In certain cases, this gives rise to scientific controversies (Acevedo-Díaz & García-Carmona, 2017 ) which are not always resolved based exclusively on epistemic or rational factors (Elliott & McKaughan, 2014 ; Vallverdú, 2005 ). Hence, it is also necessary to integrate non-epistemic practices into the framework of scientific thinking (García-Carmona, 2021a ; García-Carmona & Acevedo-Díaz, 2018 ), practices that transcend the purely rational or cognitive processes, including, for example, those related to emotional or affective issues (Sinatra & Hofer, 2021 ). From an educational point of view, this suggests that for students to become more authentically immersed in the way of working or thinking scientifically, they should also learn to feel as scientists do when they carry out their work (Davidson et al., 2020 ). Davidson et al. ( 2020 ) call it epistemic affect , and they suggest that it could be approach in science classes by teaching students to manage their frustrations when they fail to achieve the expected results; Footnote 7 or, for example, to moderate their enthusiasm with favorable results in a scientific inquiry by activating a certain skepticism that encourages them to do more testing. And, as mentioned above, for some authors, having a skeptical attitude is one of the actions that best visualize the application of critical thinking in the framework of scientific thinking (Normand, 2008 ; Sagan, 1987 ; Tena-Sánchez and León-Medina, 2022 ).

On the other hand, critical thinking also draws on many of the skills or practices of scientific thinking, as discussed above. However, in contrast to scientific thinking, the coexistence of two or more defensible ideas is not, in principle, a problem for critical thinking since its purpose is not so much to invalidate some ideas or explanations with respect to others, but rather to provide the individual with the foundations on which to position themself with the idea/argument they find most defensible among several that are possible (Ennis, 2018 ). For example, science with its methods has managed to explain the greenhouse effect, the phenomenon of the tides, or the transmission mechanism of the coronavirus. For this, it had to discard other possible explanations as they were less valid in the investigations carried out. These are therefore issues resolved by the scientific community which create hardly any discussion at the present time. However, taking a position for or against the production of energy in nuclear power plants transcends the scope of scientific thinking since both positions are, in principle, equally defensible. Indeed, within the scientific community itself there are supporters and detractors of the two positions, based on the same scientific knowledge. Consequently, it is critical thinking, which requires the management of knowledge and scientific skills, a basic understanding of epistemic (rational or cognitive) and non-epistemic (social, ethical/moral, economic, psychological, cultural, ...) aspects of the nature of science, as well as metacognitive skills, which helps the individual forge a personal foundation on which to position themself in one place or another, or maintain an uncertain, undecided opinion.

In view of the above, one can summarize that scientific thinking and critical thinking are two different intellectual processes in terms of purpose, but are related symbiotically (i.e., one would make no sense without the other or both feed on each other) and that, in their performance, they share a fair number of features, actions, or mental skills. According to Cáceres et al. ( 2020 ) and Hyytine et al. ( 2019 ), the intellectual skills that are most clearly common to both types of thinking would be searching for relationships between evidence and explanations , as well as investigating and logical thinking to make inferences . To this common space, I would also add skills for metacognition in accordance with what has been discussed about both types of knowledge (Khun, 1999 , 2022 ).

In order to compile in a compact way all that has been argued so far, in Table 4 , I present my overview of the relationship between scientific thinking and critical thinking. I would like to point out that I do not intend to be extremely extensive in the compilation, in the sense that possibly more elements could be added in the different sections, but rather to represent above all the aspects that distinguish and share them, as well as the mutual enrichment (or symbiosis) between them.

4 A Proposal for the Integrated Development of Critical Thinking and Scientific Thinking in Science Classes

Once the differences, common aspects, and relationships between critical thinking and scientific thinking have been discussed, it would be relevant to establish some type of specific proposal to foster them in science classes. Table 5 includes a possible script to address various skills or processes of both types of thinking in an integrated manner. However, before giving guidance on how such skills/processes could be approached, I would like to clarify that while all of them could be dealt within the context of a single school activity, I will not do so in this way. First, because I think that it can give the impression that the proposal is only valid if it is applied all at once in a specific learning situation, which can also discourage science teachers from implementing it in class due to lack of time or training to do so. Second, I think it can be more interesting to conceive the proposal as a set of thinking skills or actions that can be dealt with throughout the different science contents, selecting only (if so decided) some of them, according to educational needs or characteristics of the learning situation posed in each case. Therefore, in the orientations for each point of the script or grouping of these, I will use different examples and/or contexts. Likewise, these orientations in the form of comments, although founded in the literature, should be considered only as possibilities to do so, among many others possible.

Motivation and predisposition to reflect and discuss (point i ) demands, on the one hand, that issues are chosen which are attractive for the students. This can be achieved, for example, by asking the students directly what current issues, related to science and its impact or repercussions, they would like to learn about, and then decide on which issue to focus on (García-Carmona, 2008 ). Or the teacher puts forward the issue directly in class, trying for it be current, to be present in the media, social networks, etc., or what they think may be of interest to their students based on their teaching experience. In this way, each student is encouraged to feel questioned or concerned as a citizen because of the issue that is going to be addressed (García-Carmona, 2008 ). Also of possible interest is the analysis of contemporary, as yet unresolved socioscientific affairs (Solbes et al., 2018 ), such as climate change, science and social justice, transgenic foods, homeopathy, and alcohol and drug use in society. But also, everyday questions can be investigated which demand a decision to be made, such as “What car to buy?” (Moreno-Fontiveros et al., 2022 ), or “How can we prevent the arrival of another pandemic?” (Ushola & Puig, 2023 ).

On the other hand, it is essential that the discussion about the chosen issue is planned through an instructional process that generates an environment conducive to reflection and debate, with a view to engaging the students’ participation in it. This can be achieved, for example, by setting up a role-play game (Blanco-López et al., 2017 ), especially if the issue is socioscientific, or by critical and reflective reading of advertisements with scientific content (Campanario et al., 2001 ) or of science-related news in the daily media (García-Carmona, 2014 , 2021a ; Guerrero-Márquez & García-Carmona, 2020 ; Oliveras et al., 2013 ), etc., for subsequent discussion—all this, in a collaborative learning setting and with a clear democratic spirit.

Respect for scientific evidence (point ii ) should be the indispensable condition in any analysis and discussion from the prisms of scientific and of critical thinking (Erduran, 2021 ). Although scientific knowledge may be impregnated with subjectivity during its construction and is revisable in the light of new evidence ( tentativeness of scientific knowledge), when it is accepted by the scientific community it is as objective as possible (García-Carmona & Acevedo-Díaz, 2016b ). Therefore, promoting trust and respect for scientific evidence should be one of the primary educational challenges to combating pseudoscientists and science deniers (Díaz & Cabrera, 2022 ), whose arguments are based on false beliefs and assumptions, anecdotes, and conspiracy theories (Normand, 2008 ). Nevertheless, it is no simple task to achieve the promotion or respect for scientific evidence (Fackler, 2021 ) since science deniers, for example, consider that science is unreliable because it is imperfect (McIntyre, 2021 ). Hence the need to promote a basic understanding of NOS (point iii ) as a fundamental pillar for the development of both scientific thinking and critical thinking. A good way to do this would be through explicit and reflective discussion about controversies from the history of science (Acevedo-Díaz & García-Carmona, 2017 ) or contemporary controversies (García-Carmona, 2021b ; García-Carmona & Acevedo-Díaz, 2016a ).

Also, with respect to point iii of the proposal, it is necessary to manage basic scientific knowledge in the development of scientific and critical thinking skills (Willingham, 2008 ). Without this, it will be impossible to develop a minimally serious and convincing argument on the issue being analyzed. For example, if one does not know the transmission mechanism of a certain disease, it is likely to be very difficult to understand or justify certain patterns of social behavior when faced with it. In general, possessing appropriate scientific knowledge on the issue in question helps to make the best interpretation of the data and evidence available on this issue (OECD, 2019 ).

The search for information from reliable sources, together with its analysis and interpretation (points iv to vi ), are essential practices both in purely scientific contexts (e.g., learning about the behavior of a given physical phenomenon from literature or through enquiry) and in the application of critical thinking (e.g., when one wishes to take a personal, but informed, position on a particular socio-scientific issue). With regard to determining the credibility of information with scientific content on the Internet, Osborne et al. ( 2022 ) propose, among other strategies, to check whether the source is free of conflicts of interest, i.e., whether or not it is biased by ideological, political or economic motives. Also, it should be checked whether the source and the author(s) of the information are sufficiently reputable.

Regarding the interpretation of data and evidence, several studies have shown the difficulties that students often have with this practice in the context of enquiry activities (e.g., Gobert et al., 2018 ; Kanari & Millar, 2004 ; Pols et al., 2021 ), or when analyzing science news in the press (Norris et al., 2003 ). It is also found that they have significant difficulties in choosing the most appropriate data to support their arguments in causal analyses (Kuhn & Modrek, 2022 ). However, it must be recognized that making interpretations or inferences from data is not a simple task; among other reasons, because their construction is influenced by multiple factors, both epistemic (prior knowledge, experimental designs, etc.) and non-epistemic (personal expectations, ideology, sociopolitical context, etc.), which means that such interpretations are not always the same for all scientists (García-Carmona, 2021a ; García-Carmona & Acevedo-Díaz, 2018 ). For this reason, the performance of this scientific practice constitutes one of the phases or processes that generate the most debate or discussion in a scientific community, as long as no consensus is reached. In order to improve the practice of making inferences among students, Kuhn and Lerman ( 2021 ) propose activities that help them develop their own epistemological norms to connect causally their statements with the available evidence.

Point vii refers, on the one hand, to an essential scientific practice: the elaboration of evidence-based scientific explanations which generally, in a reasoned way, account for the causality, properties, and/or behavior of the phenomena (Brigandt, 2016 ). In addition, point vii concerns the practice of argumentation . Unlike scientific explanations, argumentation tries to justify an idea, explanation, or position with the clear purpose of persuading those who defend other different ones (Osborne & Patterson, 2011 ). As noted above, the complexity of most socioscientific issues implies that they have no unique valid solution or response. Therefore, the content of the arguments used to defend one position or another are not always based solely on purely rational factors such as data and scientific evidence. Some authors defend the need to also deal with non-epistemic aspects of the nature of science when teaching it (García-Carmona, 2021a ; García-Carmona & Acevedo-Díaz, 2018 ) since many scientific and socioscientific controversies are resolved by different factors or go beyond just the epistemic (Vallverdú, 2005 ).

To defend an idea or position taken on an issue, it is not enough to have scientific evidence that supports it. It is also essential to have skills for the communication and discussion of ideas (point viii ). The history of science shows how the difficulties some scientists had in communicating their ideas scientifically led to those ideas not being accepted at the time. A good example for students to become aware of this is the historical case of Semmelweis and puerperal fever (Aragón-Méndez et al., 2019 ). Its reflective reading makes it possible to conclude that the proposal of this doctor that gynecologists disinfect their hands, when passing from one parturient to another to avoid contagions that provoked the fever, was rejected by the medical community not only for epistemic reasons, but also for the difficulties that he had to communicate his idea. The history of science also reveals that some scientific interpretations were imposed on others at certain historical moments due to the rhetorical skills of their proponents although none of the explanations would convincingly explain the phenomenon studied. An example is the case of the controversy between Pasteur and Liebig about the phenomenon of fermentation (García-Carmona & Acevedo-Díaz, 2017 ), whose reading and discussion in science class would also be recommended in this context of this critical and scientific thinking skill. With the COVID-19 pandemic, for example, the arguments of some charlatans in the media and on social networks managed to gain a certain influence in the population, even though scientifically they were muddled nonsense (García-Carmona, 2021b ). Therefore, the reflective reading of news on current SSIs such as this also constitutes a good resource for the same educational purpose. In general, according to Spektor-Levy et al. ( 2009 ), scientific communication skills should be addressed explicitly in class, in a progressive and continuous manner, including tasks of information seeking, reading, scientific writing, representation of information, and representation of the knowledge acquired.

Finally (point ix ), a good scientific/critical thinker must be aware of what they know, of what they have doubts about or do not know, to this end continuously practicing metacognitive exercises (Dean & Kuhn, 2003 ; Hyytine et al., 2019 ; Magno, 2010 ; Willingham, 2008 ). At the same time, they must recognize the weaknesses and strengths of the arguments of their peers in the debate in order to be self-critical if necessary, as well as to revising their own ideas and arguments to improve and reorient them, etc. ( self-regulation ). I see one of the keys of both scientific and critical thinking being the capacity or willingness to change one’s mind, without it being frowned upon. Indeed, quite the opposite since one assumes it to occur thanks to the arguments being enriched and more solidly founded. In other words, scientific and critical thinking and arrogance or haughtiness towards the rectification of ideas or opinions do not stick well together.

5 Final Remarks

For decades, scientific thinking and critical thinking have received particular attention from different disciplines such as psychology, philosophy, pedagogy, and specific areas of this last such as science education. The two types of knowledge represent intellectual processes whose development in students, and in society in general, is considered indispensable for the exercise of responsible citizenship in accord with the demands of today’s society (European Commission, 2006 , 2015 ; NRC, 2012 ; OECD, 2020 ). As has been shown however, the task of their conceptualization is complex, and teaching students to think scientifically and critically is a difficult educational challenge (Willingham, 2008 ).

Aware of this, and after many years dedicated to science education, I felt the need to organize my ideas regarding the aforementioned two types of thinking. In consulting the literature about these, I found that, in many publications, scientific thinking and critical thinking are presented or perceived as being interchangeable or indistinguishable; a conclusion also shared by Hyytine et al. ( 2019 ). Rarely have their differences, relationships, or common features been explicitly studied. So, I considered that it was a matter needing to be addressed because, in science education, the development of scientific thinking is an inherent objective, but, when critical thinking is added to the learning objectives, there arise more than reasonable doubts about when one or the other would be used, or both at the same time. The present work came about motivated by this, with the intention of making a particular contribution, but based on the relevant literature, to advance in the question raised. This converges in conceiving scientific thinking and critical thinking as two intellectual processes that overlap and feed into each other in many aspects but are different with respect to certain cognitive skills and in terms of their purpose. Thus, in the case of scientific thinking, the aim is to choose the best possible explanation of a phenomenon based on the available evidence, and it therefore involves the rejection of alternative explanatory proposals that are shown to be less coherent or convincing. Whereas, from the perspective of critical thinking, the purpose is to choose the most defensible idea/option among others that are also defensible, using both scientific and extra-scientific (i.e., moral, ethical, political, etc.) arguments. With this in mind, I have described a proposal to guide their development in the classroom, integrating them under a conception that I have called, metaphorically, a symbiotic relationship between two modes of thinking.

Critical thinking is mentioned literally in other of the curricular provisions’ subjects such as in Education in Civics and Ethical Values or in Geography and History (Royal Decree 217/2022).

García-Carmona ( 2021a ) conceives of them as activities that require the comprehensive application of procedural skills, cognitive and metacognitive processes, and both scientific knowledge and knowledge of the nature of scientific practice .

Kuhn ( 2021 ) argues that the relationship between scientific reasoning and metacognition is especially fostered by what she calls inhibitory control , which basically consists of breaking down the whole of a thought into parts in such a way that attention is inhibited on some of those parts to allow a focused examination of the intended mental content.

Specifically, Tena-Sánchez and León-Medina (2020) assume that critical thinking is at the basis of rational or scientific skepticism that leads to questioning any claim that does not have empirical support.

As discussed in the introduction, the inquiry-based approach is also considered conducive to addressing critical thinking in science education (Couso et al., 2020 ; NRC, 2012 ).

Epistemic skills should not be confused with epistemological knowledge (García-Carmona, 2021a ). The former refers to skills to construct, evaluate, and use knowledge, and the latter to understanding about the origin, nature, scope, and limits of scientific knowledge.

For this purpose, it can be very useful to address in class, with the help of the history and philosophy of science, that scientists get more wrong than right in their research, and that error is always an opportunity to learn (García-Carmona & Acevedo-Díaz, 2018 ).

Acevedo-Díaz, J. A., & García-Carmona, A. (2017). Controversias en la historia de la ciencia y cultura científica [Controversies in the history of science and scientific culture]. Los Libros de la Catarata.

Aragón-Méndez, M. D. M., Acevedo-Díaz, J. A., & García-Carmona, A. (2019). Prospective biology teachers’ understanding of the nature of science through an analysis of the historical case of Semmelweis and childbed fever. Cultural Studies of Science Education , 14 (3), 525–555. https://doi.org/10.1007/s11422-018-9868-y

Bailin, S. (2002). Critical thinking and science education. Science & Education, 11 (4), 361–375. https://doi.org/10.1023/A:1016042608621

Article   Google Scholar  

BBVA Foundation (2011). El Nobel de Física Sheldon L. Glashow no cree que los neutrinos viajen más rápido que la luz [Physics Nobel laureate Sheldon L. Glashow does not believe neutrinos travel faster than light.]. https://www.fbbva.es/noticias/nobel-fisica-sheldon-l-glashow-no-cree-los-neutrinos-viajen-mas-rapido-la-luz/ . Accessed 5 Februray 2023.

Bell, R. L. (2009). Teaching the nature of science: Three critical questions. In Best Practices in Science Education . National Geographic School Publishing.

Google Scholar  

Blanco-López, A., España-Ramos, E., & Franco-Mariscal, A. J. (2017). Estrategias didácticas para el desarrollo del pensamiento crítico en el aula de ciencias [Teaching strategies for the development of critical thinking in the teaching of science]. Ápice. Revista de Educación Científica, 1 (1), 107–115. https://doi.org/10.17979/arec.2017.1.1.2004

Brigandt, I. (2016). Why the difference between explanation and argument matters to science education. Science & Education, 25 (3-4), 251–275. https://doi.org/10.1007/s11191-016-9826-6

Cáceres, M., Nussbaum, M., & Ortiz, J. (2020). Integrating critical thinking into the classroom: A teacher’s perspective. Thinking Skills and Creativity, 37 , 100674. https://doi.org/10.1016/j.tsc.2020.100674

Campanario, J. M., Moya, A., & Otero, J. (2001). Invocaciones y usos inadecuados de la ciencia en la publicidad [Invocations and misuses of science in advertising]. Enseñanza de las Ciencias, 19 (1), 45–56. https://doi.org/10.5565/rev/ensciencias.4013

Clouse, S. (2017). Scientific thinking is not critical thinking. https://medium.com/extra-extra/scientific-thinking-is-not-critical-thinking-b1ea9ebd8b31

Confederacion de Sociedades Cientificas de Espana [COSCE]. (2011). Informe ENCIENDE: Enseñanza de las ciencias en la didáctica escolar para edades tempranas en España [ENCIENDE report: Science education for early-year in Spain] . COSCE.

Costa, S. L. R., Obara, C. E., & Broietti, F. C. D. (2020). Critical thinking in science education publications: the research contexts. International Journal of Development Research, 10 (8), 39438. https://doi.org/10.37118/ijdr.19437.08.2020

Couso, D., Jiménez-Liso, M.R., Refojo, C. & Sacristán, J.A. (coords.) (2020). Enseñando ciencia con ciencia [Teaching science with science]. FECYT & Fundacion Lilly / Penguin Random House

Davidson, S. G., Jaber, L. Z., & Southerland, S. A. (2020). Emotions in the doing of science: Exploring epistemic affect in elementary teachers' science research experiences. Science Education, 104 (6), 1008–1040. https://doi.org/10.1002/sce.21596

Dean, D., & Kuhn, D. (2003). Metacognition and critical thinking. ERIC document. Reproduction No. ED477930 . https://files.eric.ed.gov/fulltext/ED477930.pdf

Díaz, C., & Cabrera, C. (2022). Desinformación científica en España . FECYT/IBERIFIER https://www.fecyt.es/es/publicacion/desinformacion-cientifica-en-espana

Dowd, J. E., Thompson, R. J., Jr., Schiff, L. A., & Reynolds, J. A. (2018). Understanding the complex relationship between critical thinking and science reasoning among undergraduate thesis writers. CBE—Life Sciences . Education, 17 (1), ar4. https://doi.org/10.1187/cbe.17-03-0052

Dwyer, C. P., Hogan, M. J., & Stewart, I. (2014). An integrated critical thinking framework for the 21st century. Thinking Skills and Creativity, 12 , 43–52. https://doi.org/10.1016/j.tsc.2013.12.004

Elliott, K. C., & McKaughan, D. J. (2014). Non-epistemic values and the multiple goals of science. Philosophy of Science, 81 (1), 1–21. https://doi.org/10.1086/674345

Ennis, R. H. (2018). Critical thinking across the curriculum: A vision. Topoi, 37 (1), 165–184. https://doi.org/10.1007/s11245-016-9401-4

Erduran, S. (2021). Respect for evidence: Can science education deliver it? Science & Education, 30 (3), 441–444. https://doi.org/10.1007/s11191-021-00245-8

European Commission. (2015). Science education for responsible citizenship . Publications Office https://op.europa.eu/en/publication-detail/-/publication/a1d14fa0-8dbe-11e5-b8b7-01aa75ed71a1

European Commission / Eurydice. (2011). Science education in Europe: National policies, practices and research . Publications Office. https://op.europa.eu/en/publication-detail/-/publication/bae53054-c26c-4c9f-8366-5f95e2187634

European Commission / Eurydice. (2022). Increasing achievement and motivation in mathematics and science learning in schools . Publications Office. https://eurydice.eacea.ec.europa.eu/publications/mathematics-and-science-learning-schools-2022

European Commission/Eurydice. (2006). Science teaching in schools in Europe. Policies and research . Publications Office. https://op.europa.eu/en/publication-detail/-/publication/1dc3df34-acdf-479e-bbbf-c404fa3bee8b

Fackler, A. (2021). When science denial meets epistemic understanding. Science & Education, 30 (3), 445–461. https://doi.org/10.1007/s11191-021-00198-y

García-Carmona, A. (2008). Relaciones CTS en la educación científica básica. II. Investigando los problemas del mundo [STS relationships in basic science education II. Researching the world problems]. Enseñanza de las Ciencias, 26 (3), 389–402. https://doi.org/10.5565/rev/ensciencias.3750

García-Carmona, A. (2014). Naturaleza de la ciencia en noticias científicas de la prensa: Análisis del contenido y potencialidades didácticas [Nature of science in press articles about science: Content analysis and pedagogical potential]. Enseñanza de las Ciencias, 32 (3), 493–509. https://doi.org/10.5565/rev/ensciencias.1307

García-Carmona, A., & Acevedo-Díaz, J. A. (2016). Learning about the nature of science using newspaper articles with scientific content. Science & Education, 25 (5–6), 523–546. https://doi.org/10.1007/s11191-016-9831-9

García-Carmona, A., & Acevedo-Díaz, J. A. (2016b). Concepciones de estudiantes de profesorado de Educación Primaria sobre la naturaleza de la ciencia: Una evaluación diagnóstica a partir de reflexiones en equipo [Preservice elementary teachers' conceptions of the nature of science: a diagnostic evaluation based on team reflections]. Revista Mexicana de Investigación Educativa, 21 (69), 583–610. https://www.redalyc.org/articulo.oa?id=14045395010

García-Carmona, A., & Acevedo-Díaz, J. A. (2017). Understanding the nature of science through a critical and reflective analysis of the controversy between Pasteur and Liebig on fermentation. Science & Education, 26 (1–2), 65–91. https://doi.org/10.1007/s11191-017-9876-4

García-Carmona, A., & Acevedo-Díaz, J. A. (2018). The nature of scientific practice and science education. Science & Education, 27 (5–6), 435–455. https://doi.org/10.1007/s11191-018-9984-9

García-Carmona, A. (2020). From inquiry-based science education to the approach based on scientific practices. Science & Education, 29 (2), 443–463. https://doi.org/10.1007/s11191-020-00108-8

García-Carmona, A. (2021a). Prácticas no-epistémicas: ampliando la mirada en el enfoque didáctico basado en prácticas científicas [Non-epistemic practices: extending the view in the didactic approach based on scientific practices]. Revista Eureka sobre Enseñanza y Divulgación de las Ciencias, 18 (1), 1108. https://doi.org/10.25267/Rev_Eureka_ensen_divulg_cienc.2021.v18.i1.1108

García-Carmona, A. (2021b). Learning about the nature of science through the critical and reflective reading of news on the COVID-19 pandemic. Cultural Studies of Science Education, 16 (4), 1015–1028. https://doi.org/10.1007/s11422-021-10092-2

Guerrero-Márquez, I., & García-Carmona, A. (2020). La energía y su impacto socioambiental en la prensa digital: temáticas y potencialidades didácticas para una educación CTS [Energy and its socio-environmental impact in the digital press: issues and didactic potentialities for STS education]. Revista Eureka sobre Enseñanza y Divulgación de las Ciencias, 17(3), 3301. https://doi.org/10.25267/Rev_Eureka_ensen_divulg_cienc.2020.v17.i3.3301

Gobert, J. D., Moussavi, R., Li, H., Sao Pedro, M., & Dickler, R. (2018). Real-time scaffolding of students’ online data interpretation during inquiry with Inq-ITS using educational data mining. In M. E. Auer, A. K. M. Azad, A. Edwards, & T. de Jong (Eds.), Cyber-physical laboratories in engineering and science education (pp. 191–217). Springer.

Chapter   Google Scholar  

Harlen, W. (2014). Helping children’s development of inquiry skills. Inquiry in Primary Science Education, 1 (1), 5–19. https://ipsejournal.files.wordpress.com/2015/03/3-ipse-volume-1-no-1-wynne-harlen-p-5-19.pdf

Hitchcock, D. (2017). Critical thinking as an educational ideal. In On reasoning and argument (pp. 477–497). Springer.

Hyytinen, H., Toom, A., & Shavelson, R. J. (2019). Enhancing scientific thinking through the development of critical thinking in higher education. In M. Murtonen & K. Balloo (Eds.), Redefining scientific thinking for higher education . Palgrave Macmillan.

Jiménez-Aleixandre, M. P., & Puig, B. (2022). Educating critical citizens to face post-truth: the time is now. In B. Puig & M. P. Jiménez-Aleixandre (Eds.), Critical thinking in biology and environmental education, Contributions from biology education research (pp. 3–19). Springer.

Jirout, J. J. (2020). Supporting early scientific thinking through curiosity. Frontiers in Psychology, 11 , 1717. https://doi.org/10.3389/fpsyg.2020.01717

Kanari, Z., & Millar, R. (2004). Reasoning from data: How students collect and interpret data in science investigations. Journal of Research in Science Teaching, 41 (7), 748–769. https://doi.org/10.1002/tea.20020

Klahr, D., Zimmerman, C., & Matlen, B. J. (2019). Improving students’ scientific thinking. In J. Dunlosky & K. A. Rawson (Eds.), The Cambridge handbook of cognition and education (pp. 67–99). Cambridge University Press.

Krell, M., Vorholzer, A., & Nehring, A. (2022). Scientific reasoning in science education: from global measures to fine-grained descriptions of students’ competencies. Education Sciences, 12 , 97. https://doi.org/10.3390/educsci12020097

Kuhn, D. (1993). Science as argument: Implications for teaching and learning scientific thinking. Science education, 77 (3), 319–337. https://doi.org/10.1002/sce.3730770306

Kuhn, D. (1999). A developmental model of critical thinking. Educational Researcher, 28 (2), 16–46. https://doi.org/10.3102/0013189X028002016

Kuhn, D. (2022). Metacognition matters in many ways. Educational Psychologist, 57 (2), 73–86. https://doi.org/10.1080/00461520.2021.1988603

Kuhn, D., Iordanou, K., Pease, M., & Wirkala, C. (2008). Beyond control of variables: What needs to develop to achieve skilled scientific thinking? Cognitive Development, 23 (4), 435–451. https://doi.org/10.1016/j.cogdev.2008.09.006

Kuhn, D., & Lerman, D. (2021). Yes but: Developing a critical stance toward evidence. International Journal of Science Education, 43 (7), 1036–1053. https://doi.org/10.1080/09500693.2021.1897897

Kuhn, D., & Modrek, A. S. (2022). Choose your evidence: Scientific thinking where it may most count. Science & Education, 31 (1), 21–31. https://doi.org/10.1007/s11191-021-00209-y

Lederman, J. S., Lederman, N. G., Bartos, S. A., Bartels, S. L., Meyer, A. A., & Schwartz, R. S. (2014). Meaningful assessment of learners' understandings about scientific inquiry—The views about scientific inquiry (VASI) questionnaire. Journal of Research in Science Teaching, 51 (1), 65–83. https://doi.org/10.1002/tea.21125

Lehrer, R., & Schauble, L. (2006). Scientific thinking and science literacy. In K. A. Renninger, I. E. Sigel, W. Damon, & R. M. Lerner (Eds.), Handbook of child psychology: Child psychology in practice (pp. 153–196). John Wiley & Sons, Inc.

López-Fernández, M. D. M., González-García, F., & Franco-Mariscal, A. J. (2022). How can socio-scientific issues help develop critical thinking in chemistry education? A reflection on the problem of plastics. Journal of Chemical Education, 99 (10), 3435–3442. https://doi.org/10.1021/acs.jchemed.2c00223

Magno, C. (2010). The role of metacognitive skills in developing critical thinking. Metacognition and Learning, 5 , 137–156. https://doi.org/10.1007/s11409-010-9054-4

McBain, B., Yardy, A., Martin, F., Phelan, L., van Altena, I., McKeowen, J., Pembertond, C., Tosec, H., Fratuse, L., & Bowyer, M. (2020). Teaching science students how to think. International Journal of Innovation in Science and Mathematics Education, 28 (2), 28–35. https://openjournals.library.sydney.edu.au/CAL/article/view/14809/13480

McIntyre, L. (2021). Talking to science deniers and sceptics is not hopeless. Nature, 596 (7871), 165–165. https://doi.org/10.1038/d41586-021-02152-y

Moore, C. (2019). Teaching science thinking. Using scientific reasoning in the classroom . Routledge.

Moreno-Fontiveros, G., Cebrián-Robles, D., Blanco-López, A., & y España-Ramos, E. (2022). Decisiones de estudiantes de 14/15 años en una propuesta didáctica sobre la compra de un coche [Fourteen/fifteen-year-old students’ decisions in a teaching proposal on the buying of a car]. Enseñanza de las Ciencias, 40 (1), 199–219. https://doi.org/10.5565/rev/ensciencias.3292

National Research Council [NRC]. (2012). A framework for K-12 science education . National Academies Press.

Network, I.-A. T. E. (2015). Critical thinking toolkit . OAS/ITEN.

Normand, M. P. (2008). Science, skepticism, and applied behavior analysis. Behavior Analysis in Practice, 1 (2), 42–49. https://doi.org/10.1007/BF03391727

Norris, S. P., Phillips, L. M., & Korpan, C. A. (2003). University students’ interpretation of media reports of science and its relationship to background knowledge, interest, and reading difficulty. Public Understanding of Science, 12 (2), 123–145. https://doi.org/10.1177/09636625030122001

Oliveras, B., Márquez, C., & Sanmartí, N. (2013). The use of newspaper articles as a tool to develop critical thinking in science classes. International Journal of Science Education, 35 (6), 885–905. https://doi.org/10.1080/09500693.2011.586736

Organisation for Economic Co-operation and Development [OECD]. (2019). PISA 2018. Assessment and Analytical Framework . OECD Publishing. https://doi.org/10.1787/b25efab8-en

Book   Google Scholar  

Organisation for Economic Co-operation and Development [OECD]. (2020). PISA 2024: Strategic Vision and Direction for Science. https://www.oecd.org/pisa/publications/PISA-2024-Science-Strategic-Vision-Proposal.pdf

Osborne, J., Pimentel, D., Alberts, B., Allchin, D., Barzilai, S., Bergstrom, C., Coffey, J., Donovan, B., Kivinen, K., Kozyreva, A., & Wineburg, S. (2022). Science Education in an Age of Misinformation . Stanford University.

Osborne, J. F., & Patterson, A. (2011). Scientific argument and explanation: A necessary distinction? Science Education, 95 (4), 627–638. https://doi.org/10.1002/sce.20438

Pols, C. F. J., Dekkers, P. J. J. M., & De Vries, M. J. (2021). What do they know? Investigating students’ ability to analyse experimental data in secondary physics education. International Journal of Science Education, 43 (2), 274–297. https://doi.org/10.1080/09500693.2020.1865588

Royal Decree 217/2022. (2022). of 29 March, which establishes the organisation and minimum teaching of Compulsory Secondary Education (Vol. 76 , pp. 41571–41789). Spanish Official State Gazette. https://www.boe.es/eli/es/rd/2022/03/29/217

Sagan, C. (1987). The burden of skepticism. Skeptical Inquirer, 12 (1), 38–46. https://skepticalinquirer.org/1987/10/the-burden-of-skepticism/

Santos, L. F. (2017). The role of critical thinking in science education. Journal of Education and Practice, 8 (20), 160–173. https://eric.ed.gov/?id=ED575667

Schafersman, S. D. (1991). An introduction to critical thinking. https://facultycenter.ischool.syr.edu/wp-content/uploads/2012/02/Critical-Thinking.pdf . Accessed 10 May 2023.

Sinatra, G. M., & Hofer, B. K. (2021). How do emotions and attitudes influence science understanding? In Science denial: why it happens and what to do about it (pp. 142–180). Oxford Academic.

Solbes, J., Torres, N., & Traver, M. (2018). Use of socio-scientific issues in order to improve critical thinking competences. Asia-Pacific Forum on Science Learning & Teaching, 19 (1), 1–22. https://www.eduhk.hk/apfslt/

Spektor-Levy, O., Eylon, B. S., & Scherz, Z. (2009). Teaching scientific communication skills in science studies: Does it make a difference? International Journal of Science and Mathematics Education, 7 (5), 875–903. https://doi.org/10.1007/s10763-009-9150-6

Taylor, P., Lee, S. H., & Tal, T. (2006). Toward socio-scientific participation: changing culture in the science classroom and much more: Setting the stage. Cultural Studies of Science Education, 1 (4), 645–656. https://doi.org/10.1007/s11422-006-9028-7

Tena-Sánchez, J., & León-Medina, F. J. (2022). Y aún más al fondo del “bullshit”: El papel de la falsificación de preferencias en la difusión del oscurantismo en la teoría social y en la sociedad [And even deeper into “bullshit”: The role of preference falsification in the difussion of obscurantism in social theory and in society]. Scio, 22 , 209–233. https://doi.org/10.46583/scio_2022.22.949

Tytler, R., & Peterson, S. (2004). From “try it and see” to strategic exploration: Characterizing young children's scientific reasoning. Journal of Research in Science Teaching, 41 (1), 94–118. https://doi.org/10.1002/tea.10126

Uskola, A., & Puig, B. (2023). Development of systems and futures thinking skills by primary pre-service teachers for addressing epidemics. Research in Science Education , 1–17. https://doi.org/10.1007/s11165-023-10097-7

Vallverdú, J. (2005). ¿Cómo finalizan las controversias? Un nuevo modelo de análisis: la controvertida historia de la sacarina [How does controversies finish? A new model of analysis: the controversial history of saccharin]. Revista Iberoamericana de Ciencia, Tecnología y Sociedad, 2 (5), 19–50. http://www.revistacts.net/wp-content/uploads/2020/01/vol2-nro5-art01.pdf

Vázquez-Alonso, A., & Manassero-Mas, M. A. (2018). Más allá de la comprensión científica: educación científica para desarrollar el pensamiento [Beyond understanding of science: science education for teaching fair thinking]. Revista Electrónica de Enseñanza de las Ciencias, 17 (2), 309–336. http://reec.uvigo.es/volumenes/volumen17/REEC_17_2_02_ex1065.pdf

Willingham, D. T. (2008). Critical thinking: Why is it so hard to teach? Arts Education Policy Review, 109 (4), 21–32. https://doi.org/10.3200/AEPR.109.4.21-32

Yacoubian, H. A. (2020). Teaching nature of science through a critical thinking approach. In W. F. McComas (Ed.), Nature of Science in Science Instruction (pp. 199–212). Springer.

Yacoubian, H. A., & Khishfe, R. (2018). Argumentation, critical thinking, nature of science and socioscientific issues: a dialogue between two researchers. International Journal of Science Education, 40 (7), 796–807. https://doi.org/10.1080/09500693.2018.1449986

Zeidler, D. L., & Nichols, B. H. (2009). Socioscientific issues: Theory and practice. Journal of elementary science education, 21 (2), 49–58. https://doi.org/10.1007/BF03173684

Zimmerman, C., & Klahr, D. (2018). Development of scientific thinking. In J. T. Wixted (Ed.), Stevens’ handbook of experimental psychology and cognitive neuroscience (Vol. 4 , pp. 1–25). John Wiley & Sons, Inc..

Download references

Conflict of Interest

The author declares no conflict of interest.

Funding for open access publishing: Universidad de Sevilla/CBUA

Author information

Authors and affiliations.

Departamento de Didáctica de las Ciencias Experimentales y Sociales, Universidad de Sevilla, Seville, Spain

Antonio García-Carmona

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Antonio García-Carmona .

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

García-Carmona, A. Scientific Thinking and Critical Thinking in Science Education . Sci & Educ (2023). https://doi.org/10.1007/s11191-023-00460-5

Download citation

Accepted : 30 July 2023

Published : 05 September 2023

DOI : https://doi.org/10.1007/s11191-023-00460-5

Share this article

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

• Cognitive skills
• Critical thinking
• Metacognitive skills
• Science education
• Scientific thinking
• Find a journal
• Publish with us
• Track your research

• Search Search Search …
• Search Search …

What’s the Difference Between Critical Thinking and Scientific Thinking?

Thinking deeply about things is a defining feature of what it means to be human, but, surprising as it may seem, there isn’t just one way to ‘think’ about something; instead, humans have been developing organized and varied schools of thought for thousands of years.

Discussions about morality, religion, and the meaning of life often drive knowledge-seeking inquiry, leading people to wonder what the difference is between critical thinking and Scientific Thinking.

Critical thinkers prioritize objectivity to analyze a problem, deduce logical solutions, and examine what the ramifications of those solutions are.

While scientific thinking often relies heavily on critical thinking, scientific inquiry is more dedicated to acquiring knowledge rather than mere abstraction.

There are a lot of nuances between critical thinking and scientific thinking, and most of us probably utilize these skills in our everyday lives. The rest of this article will thoroughly define the two terms and relate how they are similar and different.

What Is Critical Thinking?

Critical thinking is a mindset ― a lens, if you will, through which one may view the world. Critical thinkers rely on a lot of introspection, constantly self-evaluating how they came to a conclusion, and what that conclusion naturally entails.

A critical thinker may discern what they already know about a subject, what that information suggests, why that information is relevant, and how that information could be linked to further lines of inquiry. Critical thinking is, therefore, simply the ability to think clearly and logically.

Systematic reasoning is prized over gut instinct, and determining relevance is crucial to parsing out useful data from extraneous information.

Naturally, the ability to think critically is highly prized in an academic setting, and most educators seek to enable their students to think critically.

What is the link between the styles and motivations of these two Romantic era poets? How can your current understanding of algebra be applied to geometry? How does our understanding of this historical figure influence our understanding of social life at the time?

So much information can be interlinked to develop our understanding of the world, and critical thinking is the basis for using objectivity to not only establish likely outcomes to a scenario, but also inquire on the repercussions of that outcome and reflect on the process by which one came to that conclusion.

What Is Scientific Thinking?

The objective of scientific thinking is the acquisition of knowledge. The more we know, the more we can hope to know.

Scientific thinking begins by imagining what the outcome of a problem may be, observing the situation, and then making notes and changing the initial hypothesis.

The commonly used scientific method is as follows:

• Define the purpose of the experiment
• Formulate a hypothesis
• Study the phenomenon and collect data
• Draw results

As you might imagine, this process can be repeated ad infinitum. So, you draw a conclusion that’s scientifically verifiable? Great! Now you can take that conclusion and use it as a basis for a new experiment. Of course, the scientific method has limits.

It’s hard to apply the scientific method when it comes to morality or religious beliefs. A revelation of a prophet cannot be empirically verified.

We can’t go inside said prophet’s mind and see exactly what neurons were firing to recreate the conditions under which the vision was made, and even if we could, the nature of such a revelation is spiritual and immaterial.

It’s impossible to influence the supernatural in the material world, and as such, creating a test that relies on changing something to see the outcome is impossible. Where scientific thinking does excel is in the fields of math and, well, science.

Physics is known as the perfect science because the forces that comprise our world are well understood and don’t tend to exhibit anomalies, making the empirically verified scientific method perfect for improving our understanding of the natural world.

How Are Critical Thinking and Scientific Thinking Similar and Different?

Both critical and scientific thinking rely on the use of empirical, objective evidence. Thinking scientifically or critically relies on using the data available and following it to its likely conclusion.

Scientific thinking can be seen as a stricter, more regulated version of critical thinking. It takes the tenets of critically thinking and narrows the focus.

Both fields of study eschew personal bias and gut instinct as both unreliable and unhelpful.

The main difference between the two, however, is the goal of each discipline.

While both prioritize learning and using data to make hypotheses, critical thinking is prone to much more abstraction and self-reflection.

With little variation in the scientific method, there’s not really any need to reflect on how those conclusions were drawn or if those conclusions are a result of any kind of bias. It’s just not useful information.

For a critical thinker, however, self-reflection is key to identifying inconsistencies and refining one’s argument.

Both scientific thinking and critical thinking tend to draw links between concepts, evaluating how they are related and what knowledge may be gleaned from that connection.

While critical thinking can be applied to most concepts, even those of morality and anthropology, scientific thinking is often problem oriented. If a problem exists, scientific inquiry attempts to gain the necessary information to solve it, overcoming obstacles along the way.

Both critical thinkers and scientific thinkers may very well end up at the same conclusion― they will just draw those conclusions differently. Critical thinkers are concerned with logic, order, and rational thinking.

Establishing already-understood information, applying that information to a query, and then establishing a defensible argument on the accuracy and relevance of the conclusion is the trademark of a critical thinker. Scientific thinkers, on the other hand, work towards solving knowledge almost exclusively through the acquisition of knowledge through the scientific method.

Scientific thinkers develop a hypothesis, test it, and then rinse and repeat until the phenomenon is understood. As such, scientific thinkers are obsessed with why questions. Why does this phenomenon happen?

Why does matter behave like this? In the end, both schools are thought have a lot of interesting ideas guiding them, and most of us probably use them throughout our daily lives.

https://www.vwaust.com/resource/what-is-scientific-thinking/

https://www.skillsyouneed.com/learn/critical-thinking.html#:~:text=Critical%20thinking%20is%20thinking%20about%20things%20in%20certain,to%20the%20best%20possible%20conclusion.%20Critical%20Thinking%20is%3A

https://psycnet.apa.org/record/2010-22950-019

You may also like

Critical thinking: Stop Overthinking and Make Faster Decisions

Overthinking isn’t actually thinking: it’s obsessing over a particular moment, idea, outcome, or fear. Unfortunately, this behavior traps you in your thoughts, […]

Critical Thinking in Healthcare and Medicine: A Crucial Skill for Improved Outcomes

Critical thinking is a crucial skill for individuals working in various healthcare domains, such as doctors, nurses, lab assistants, and patients. It […]

Critical thinking and Cyber security (How to protect your personal information online)

Whenever a job vacancy in cyber security is posted, you will always see one of the job requirements as ‘critical thinking’. Honestly, […]

Critical Thinking vs. Strategic Thinking (Strategy As a Critical Thinker)

When it comes to critical thinking vs. strategic thinking, the best way to explain it is to say that one is something […]

• Table of Contents
• Random Entry
• Chronological
• Editorial Information
• About the SEP
• Editorial Board
• How to Cite the SEP
• Special Characters
• Advanced Tools
• Support the SEP
• PDFs for SEP Friends
• Make a Donation
• SEPIA for Libraries
• Entry Contents

Bibliography

Academic tools.

• Friends PDF Preview
• Author and Citation Info
• Back to Top

Critical Thinking

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

2.1 Dewey’s Three Main Examples

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

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

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

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

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

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

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

2. Examples and Non-Examples

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

8. Critical Thinking Dispositions

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

12. Controversies

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

• Abrami, Philip C., Robert M. Bernard, Eugene Borokhovski, David I. Waddington, C. Anne Wade, and Tonje Person, 2015, “Strategies for Teaching Students to Think Critically: A Meta-analysis”, Review of Educational Research , 85(2): 275–314. doi:10.3102/0034654314551063
• Aikin, Wilford M., 1942, The Story of the Eight-year Study, with Conclusions and Recommendations , Volume I of Adventure in American Education , New York and London: Harper & Brothers. [ Aikin 1942 available online ]
• Alston, Kal, 1995, “Begging the Question: Is Critical Thinking Biased?”, Educational Theory , 45(2): 225–233. doi:10.1111/j.1741-5446.1995.00225.x
• –––, 2001, “Re/Thinking Critical Thinking: The Seductions of Everyday Life”, Studies in Philosophy and Education , 20(1): 27–40. doi:10.1023/A:1005247128053
• American Educational Research Association, 2014, Standards for Educational and Psychological Testing / American Educational Research Association, American Psychological Association, National Council on Measurement in Education , Washington, DC: American Educational Research Association.
• Anderson, Lorin W., David R. Krathwohl, Peter W. Airiasian, Kathleen A. Cruikshank, Richard E. Mayer, Paul R. Pintrich, James Raths, and Merlin C. Wittrock, 2001, A Taxonomy for Learning, Teaching and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives , New York: Longman, complete edition.
• Bailin, Sharon, 1987, “Critical and Creative Thinking”, Informal Logic , 9(1): 23–30. [ Bailin 1987 available online ]
• –––, 1988, Achieving Extraordinary Ends: An Essay on Creativity , Dordrecht: Kluwer. doi:10.1007/978-94-009-2780-3
• –––, 1995, “Is Critical Thinking Biased? Clarifications and Implications”, Educational Theory , 45(2): 191–197. doi:10.1111/j.1741-5446.1995.00191.x
• Bailin, Sharon and Mark Battersby, 2009, “Inquiry: A Dialectical Approach to Teaching Critical Thinking”, in Juho Ritola (ed.), Argument Cultures: Proceedings of OSSA 09 , CD-ROM (pp. 1–10), Windsor, ON: OSSA. [ Bailin & Battersby 2009 available online ]
• –––, 2016a, “Fostering the Virtues of Inquiry”, Topoi , 35(2): 367–374. doi:10.1007/s11245-015-9307-6
• –––, 2016b, Reason in the Balance: An Inquiry Approach to Critical Thinking , Indianapolis: Hackett, 2nd edition.
• –––, 2021, “Inquiry: Teaching for Reasoned Judgment”, in Daniel Fasko, Jr. and Frank Fair (eds.), Critical Thinking and Reasoning: Theory, Development, Instruction, and Assessment , Leiden: Brill, pp. 31–46. doi: 10.1163/9789004444591_003
• Bailin, Sharon, Roland Case, Jerrold R. Coombs, and Leroi B. Daniels, 1999a, “Common Misconceptions of Critical Thinking”, Journal of Curriculum Studies , 31(3): 269–283. doi:10.1080/002202799183124
• –––, 1999b, “Conceptualizing Critical Thinking”, Journal of Curriculum Studies , 31(3): 285–302. doi:10.1080/002202799183133
• Blair, J. Anthony, 2021, Studies in Critical Thinking , Windsor, ON: Windsor Studies in Argumentation, 2nd edition. [Available online at https://windsor.scholarsportal.info/omp/index.php/wsia/catalog/book/106]
• Berman, Alan M., Seth J. Schwartz, William M. Kurtines, and Steven L. Berman, 2001, “The Process of Exploration in Identity Formation: The Role of Style and Competence”, Journal of Adolescence , 24(4): 513–528. doi:10.1006/jado.2001.0386
• Black, Beth (ed.), 2012, An A to Z of Critical Thinking , London: Continuum International Publishing Group.
• Bloom, Benjamin Samuel, Max D. Engelhart, Edward J. Furst, Walter H. Hill, and David R. Krathwohl, 1956, Taxonomy of Educational Objectives. Handbook I: Cognitive Domain , New York: David McKay.
• Boardman, Frank, Nancy M. Cavender, and Howard Kahane, 2018, Logic and Contemporary Rhetoric: The Use of Reason in Everyday Life , Boston: Cengage, 13th edition.
• Browne, M. Neil and Stuart M. Keeley, 2018, Asking the Right Questions: A Guide to Critical Thinking , Hoboken, NJ: Pearson, 12th edition.
• Center for Assessment & Improvement of Learning, 2017, Critical Thinking Assessment Test , Cookeville, TN: Tennessee Technological University.
• Cleghorn, Paul. 2021. “Critical Thinking in the Elementary School: Practical Guidance for Building a Culture of Thinking”, in Daniel Fasko, Jr. and Frank Fair (eds.), Critical Thinking and Reasoning: Theory, Development, Instruction, and Assessmen t, Leiden: Brill, pp. 150–167. doi: 10.1163/9789004444591_010
• Cohen, Jacob, 1988, Statistical Power Analysis for the Behavioral Sciences , Hillsdale, NJ: Lawrence Erlbaum Associates, 2nd edition.
• College Board, 1983, Academic Preparation for College. What Students Need to Know and Be Able to Do , New York: College Entrance Examination Board, ERIC document ED232517.
• Commission on the Relation of School and College of the Progressive Education Association, 1943, Thirty Schools Tell Their Story , Volume V of Adventure in American Education , New York and London: Harper & Brothers.
• Council for Aid to Education, 2017, CLA+ Student Guide . Available at http://cae.org/images/uploads/pdf/CLA_Student_Guide_Institution.pdf ; last accessed 2022 07 16.
• Dalgleish, Adam, Patrick Girard, and Maree Davies, 2017, “Critical Thinking, Bias and Feminist Philosophy: Building a Better Framework through Collaboration”, Informal Logic , 37(4): 351–369. [ Dalgleish et al. available online ]
• Dewey, John, 1910, How We Think , Boston: D.C. Heath. [ Dewey 1910 available online ]
• –––, 1916, Democracy and Education: An Introduction to the Philosophy of Education , New York: Macmillan.
• –––, 1933, How We Think: A Restatement of the Relation of Reflective Thinking to the Educative Process , Lexington, MA: D.C. Heath.
• –––, 1936, “The Theory of the Chicago Experiment”, Appendix II of Mayhew & Edwards 1936: 463–477.
• –––, 1938, Logic: The Theory of Inquiry , New York: Henry Holt and Company.
• Dominguez, Caroline (coord.), 2018a, A European Collection of the Critical Thinking Skills and Dispositions Needed in Different Professional Fields for the 21st Century , Vila Real, Portugal: UTAD. Available at http://bit.ly/CRITHINKEDUO1 ; last accessed 2022 07 16.
• ––– (coord.), 2018b, A European Review on Critical Thinking Educational Practices in Higher Education Institutions , Vila Real: UTAD. Available at http://bit.ly/CRITHINKEDUO2 ; last accessed 2022 07 16.
• ––– (coord.), 2018c, The CRITHINKEDU European Course on Critical Thinking Education for University Teachers: From Conception to Delivery , Vila Real: UTAD. Available at http:/bit.ly/CRITHINKEDU03; last accessed 2022 07 16.
• Dominguez Caroline and Rita Payan-Carreira (eds.), 2019, Promoting Critical Thinking in European Higher Education Institutions: Towards an Educational Protocol , Vila Real: UTAD. Available at http:/bit.ly/CRITHINKEDU04; last accessed 2022 07 16.
• Ennis, Robert H., 1958, “An Appraisal of the Watson-Glaser Critical Thinking Appraisal”, The Journal of Educational Research , 52(4): 155–158. doi:10.1080/00220671.1958.10882558
• –––, 1962, “A Concept of Critical Thinking: A Proposed Basis for Research on the Teaching and Evaluation of Critical Thinking Ability”, Harvard Educational Review , 32(1): 81–111.
• –––, 1981a, “A Conception of Deductive Logical Competence”, Teaching Philosophy , 4(3/4): 337–385. doi:10.5840/teachphil198143/429
• –––, 1981b, “Eight Fallacies in Bloom’s Taxonomy”, in C. J. B. Macmillan (ed.), Philosophy of Education 1980: Proceedings of the Thirty-seventh Annual Meeting of the Philosophy of Education Society , Bloomington, IL: Philosophy of Education Society, pp. 269–273.
• –––, 1984, “Problems in Testing Informal Logic, Critical Thinking, Reasoning Ability”, Informal Logic , 6(1): 3–9. [ Ennis 1984 available online ]
• –––, 1987, “A Taxonomy of Critical Thinking Dispositions and Abilities”, in Joan Boykoff Baron and Robert J. Sternberg (eds.), Teaching Thinking Skills: Theory and Practice , New York: W. H. Freeman, pp. 9–26.
• –––, 1989, “Critical Thinking and Subject Specificity: Clarification and Needed Research”, Educational Researcher , 18(3): 4–10. doi:10.3102/0013189X018003004
• –––, 1991, “Critical Thinking: A Streamlined Conception”, Teaching Philosophy , 14(1): 5–24. doi:10.5840/teachphil19911412
• –––, 1996, “Critical Thinking Dispositions: Their Nature and Assessability”, Informal Logic , 18(2–3): 165–182. [ Ennis 1996 available online ]
• –––, 1998, “Is Critical Thinking Culturally Biased?”, Teaching Philosophy , 21(1): 15–33. doi:10.5840/teachphil19982113
• –––, 2011, “Critical Thinking: Reflection and Perspective Part I”, Inquiry: Critical Thinking across the Disciplines , 26(1): 4–18. doi:10.5840/inquiryctnews20112613
• –––, 2013, “Critical Thinking across the Curriculum: The Wisdom CTAC Program”, Inquiry: Critical Thinking across the Disciplines , 28(2): 25–45. doi:10.5840/inquiryct20132828
• –––, 2016, “Definition: A Three-Dimensional Analysis with Bearing on Key Concepts”, in Patrick Bondy and Laura Benacquista (eds.), Argumentation, Objectivity, and Bias: Proceedings of the 11th International Conference of the Ontario Society for the Study of Argumentation (OSSA), 18–21 May 2016 , Windsor, ON: OSSA, pp. 1–19. Available at http://scholar.uwindsor.ca/ossaarchive/OSSA11/papersandcommentaries/105 ; last accessed 2022 07 16.
• –––, 2018, “Critical Thinking Across the Curriculum: A Vision”, Topoi , 37(1): 165–184. doi:10.1007/s11245-016-9401-4
• Ennis, Robert H., and Jason Millman, 1971, Manual for Cornell Critical Thinking Test, Level X, and Cornell Critical Thinking Test, Level Z , Urbana, IL: Critical Thinking Project, University of Illinois.
• Ennis, Robert H., Jason Millman, and Thomas Norbert Tomko, 1985, Cornell Critical Thinking Tests Level X & Level Z: Manual , Pacific Grove, CA: Midwest Publication, 3rd edition.
• –––, 2005, Cornell Critical Thinking Tests Level X & Level Z: Manual , Seaside, CA: Critical Thinking Company, 5th edition.
• Ennis, Robert H. and Eric Weir, 1985, The Ennis-Weir Critical Thinking Essay Test: Test, Manual, Criteria, Scoring Sheet: An Instrument for Teaching and Testing , Pacific Grove, CA: Midwest Publications.
• Facione, Peter A., 1990a, Critical Thinking: A Statement of Expert Consensus for Purposes of Educational Assessment and Instruction , Research Findings and Recommendations Prepared for the Committee on Pre-College Philosophy of the American Philosophical Association, ERIC Document ED315423.
• –––, 1990b, California Critical Thinking Skills Test, CCTST – Form A , Millbrae, CA: The California Academic Press.
• –––, 1990c, The California Critical Thinking Skills Test--College Level. Technical Report #3. Gender, Ethnicity, Major, CT Self-Esteem, and the CCTST , ERIC Document ED326584.
• –––, 1992, California Critical Thinking Skills Test: CCTST – Form B, Millbrae, CA: The California Academic Press.
• –––, 2000, “The Disposition Toward Critical Thinking: Its Character, Measurement, and Relationship to Critical Thinking Skill”, Informal Logic , 20(1): 61–84. [ Facione 2000 available online ]
• Facione, Peter A. and Noreen C. Facione, 1992, CCTDI: A Disposition Inventory , Millbrae, CA: The California Academic Press.
• Facione, Peter A., Noreen C. Facione, and Carol Ann F. Giancarlo, 2001, California Critical Thinking Disposition Inventory: CCTDI: Inventory Manual , Millbrae, CA: The California Academic Press.
• Facione, Peter A., Carol A. Sánchez, and Noreen C. Facione, 1994, Are College Students Disposed to Think? , Millbrae, CA: The California Academic Press. ERIC Document ED368311.
• Fisher, Alec, and Michael Scriven, 1997, Critical Thinking: Its Definition and Assessment , Norwich: Centre for Research in Critical Thinking, University of East Anglia.
• Freire, Paulo, 1968 [1970], Pedagogia do Oprimido . Translated as Pedagogy of the Oppressed , Myra Bergman Ramos (trans.), New York: Continuum, 1970.
• Gigerenzer, Gerd, 2001, “The Adaptive Toolbox”, in Gerd Gigerenzer and Reinhard Selten (eds.), Bounded Rationality: The Adaptive Toolbox , Cambridge, MA: MIT Press, pp. 37–50.
• Glaser, Edward Maynard, 1941, An Experiment in the Development of Critical Thinking , New York: Bureau of Publications, Teachers College, Columbia University.
• Groarke, Leo A. and Christopher W. Tindale, 2012, Good Reasoning Matters! A Constructive Approach to Critical Thinking , Don Mills, ON: Oxford University Press, 5th edition.
• Halpern, Diane F., 1998, “Teaching Critical Thinking for Transfer Across Domains: Disposition, Skills, Structure Training, and Metacognitive Monitoring”, American Psychologist , 53(4): 449–455. doi:10.1037/0003-066X.53.4.449
• –––, 2016, Manual: Halpern Critical Thinking Assessment , Mödling, Austria: Schuhfried. Available at https://pdfcoffee.com/hcta-test-manual-pdf-free.html; last accessed 2022 07 16.
• Hamby, Benjamin, 2014, The Virtues of Critical Thinkers , Doctoral dissertation, Philosophy, McMaster University. [ Hamby 2014 available online ]
• –––, 2015, “Willingness to Inquire: The Cardinal Critical Thinking Virtue”, in Martin Davies and Ronald Barnett (eds.), The Palgrave Handbook of Critical Thinking in Higher Education , New York: Palgrave Macmillan, pp. 77–87.
• Haran, Uriel, Ilana Ritov, and Barbara A. Mellers, 2013, “The Role of Actively Open-minded Thinking in Information Acquisition, Accuracy, and Calibration”, Judgment and Decision Making , 8(3): 188–201.
• Hatcher, Donald and Kevin Possin, 2021, “Commentary: Thinking Critically about Critical Thinking Assessment”, in Daniel Fasko, Jr. and Frank Fair (eds.), Critical Thinking and Reasoning: Theory, Development, Instruction, and Assessment , Leiden: Brill, pp. 298–322. doi: 10.1163/9789004444591_017
• Haynes, Ada, Elizabeth Lisic, Kevin Harris, Katie Leming, Kyle Shanks, and Barry Stein, 2015, “Using the Critical Thinking Assessment Test (CAT) as a Model for Designing Within-Course Assessments: Changing How Faculty Assess Student Learning”, Inquiry: Critical Thinking Across the Disciplines , 30(3): 38–48. doi:10.5840/inquiryct201530316
• Haynes, Ada and Barry Stein, 2021, “Observations from a Long-Term Effort to Assess and Improve Critical Thinking”, in Daniel Fasko, Jr. and Frank Fair (eds.), Critical Thinking and Reasoning: Theory, Development, Instruction, and Assessment , Leiden: Brill, pp. 231–254. doi: 10.1163/9789004444591_014
• Hiner, Amanda L. 2021. “Equipping Students for Success in College and Beyond: Placing Critical Thinking Instruction at the Heart of a General Education Program”, in Daniel Fasko, Jr. and Frank Fair (eds.), Critical Thinking and Reasoning: Theory, Development, Instruction, and Assessment , Leiden: Brill, pp. 188–208. doi: 10.1163/9789004444591_012
• Hitchcock, David, 2017, “Critical Thinking as an Educational Ideal”, in his On Reasoning and Argument: Essays in Informal Logic and on Critical Thinking , Dordrecht: Springer, pp. 477–497. doi:10.1007/978-3-319-53562-3_30
• –––, 2021, “Seven Philosophical Implications of Critical Thinking: Themes, Variations, Implications”, in Daniel Fasko, Jr. and Frank Fair (eds.), Critical Thinking and Reasoning: Theory, Development, Instruction, and Assessment , Leiden: Brill, pp. 9–30. doi: 10.1163/9789004444591_002
• hooks, bell, 1994, Teaching to Transgress: Education as the Practice of Freedom , New York and London: Routledge.
• –––, 2010, Teaching Critical Thinking: Practical Wisdom , New York and London: Routledge.
• Johnson, Ralph H., 1992, “The Problem of Defining Critical Thinking”, in Stephen P, Norris (ed.), The Generalizability of Critical Thinking , New York: Teachers College Press, pp. 38–53.
• Kahane, Howard, 1971, Logic and Contemporary Rhetoric: The Use of Reason in Everyday Life , Belmont, CA: Wadsworth.
• Kahneman, Daniel, 2011, Thinking, Fast and Slow , New York: Farrar, Straus and Giroux.
• Kahneman, Daniel, Olivier Sibony, & Cass R. Sunstein, 2021, Noise: A Flaw in Human Judgment , New York: Little, Brown Spark.
• Kenyon, Tim, and Guillaume Beaulac, 2014, “Critical Thinking Education and Debasing”, Informal Logic , 34(4): 341–363. [ Kenyon & Beaulac 2014 available online ]
• Krathwohl, David R., Benjamin S. Bloom, and Bertram B. Masia, 1964, Taxonomy of Educational Objectives, Handbook II: Affective Domain , New York: David McKay.
• Kuhn, Deanna, 1991, The Skills of Argument , New York: Cambridge University Press. doi:10.1017/CBO9780511571350
• –––, 2019, “Critical Thinking as Discourse”, Human Development, 62 (3): 146–164. doi:10.1159/000500171
• Lipman, Matthew, 1987, “Critical Thinking–What Can It Be?”, Analytic Teaching , 8(1): 5–12. [ Lipman 1987 available online ]
• –––, 2003, Thinking in Education , Cambridge: Cambridge University Press, 2nd edition.
• Loftus, Elizabeth F., 2017, “Eavesdropping on Memory”, Annual Review of Psychology , 68: 1–18. doi:10.1146/annurev-psych-010416-044138
• Makaiau, Amber Strong, 2021, “The Good Thinker’s Tool Kit: How to Engage Critical Thinking and Reasoning in Secondary Education”, in Daniel Fasko, Jr. and Frank Fair (eds.), Critical Thinking and Reasoning: Theory, Development, Instruction, and Assessment , Leiden: Brill, pp. 168–187. doi: 10.1163/9789004444591_011
• Martin, Jane Roland, 1992, “Critical Thinking for a Humane World”, in Stephen P. Norris (ed.), The Generalizability of Critical Thinking , New York: Teachers College Press, pp. 163–180.
• Mayhew, Katherine Camp, and Anna Camp Edwards, 1936, The Dewey School: The Laboratory School of the University of Chicago, 1896–1903 , New York: Appleton-Century. [ Mayhew & Edwards 1936 available online ]
• McPeck, John E., 1981, Critical Thinking and Education , New York: St. Martin’s Press.
• Moore, Brooke Noel and Richard Parker, 2020, Critical Thinking , New York: McGraw-Hill, 13th edition.
• Nickerson, Raymond S., 1998, “Confirmation Bias: A Ubiquitous Phenomenon in Many Guises”, Review of General Psychology , 2(2): 175–220. doi:10.1037/1089-2680.2.2.175
• Nieto, Ana Maria, and Jorge Valenzuela, 2012, “A Study of the Internal Structure of Critical Thinking Dispositions”, Inquiry: Critical Thinking across the Disciplines , 27(1): 31–38. doi:10.5840/inquiryct20122713
• Norris, Stephen P., 1985, “Controlling for Background Beliefs When Developing Multiple-choice Critical Thinking Tests”, Educational Measurement: Issues and Practice , 7(3): 5–11. doi:10.1111/j.1745-3992.1988.tb00437.x
• Norris, Stephen P. and Robert H. Ennis, 1989, Evaluating Critical Thinking (The Practitioners’ Guide to Teaching Thinking Series), Pacific Grove, CA: Midwest Publications.
• Norris, Stephen P. and Ruth Elizabeth King, 1983, Test on Appraising Observations , St. John’s, NL: Institute for Educational Research and Development, Memorial University of Newfoundland.
• –––, 1984, The Design of a Critical Thinking Test on Appraising Observations , St. John’s, NL: Institute for Educational Research and Development, Memorial University of Newfoundland. ERIC Document ED260083.
• –––, 1985, Test on Appraising Observations: Manual , St. John’s, NL: Institute for Educational Research and Development, Memorial University of Newfoundland.
• –––, 1990a, Test on Appraising Observations , St. John’s, NL: Institute for Educational Research and Development, Memorial University of Newfoundland, 2nd edition.
• –––, 1990b, Test on Appraising Observations: Manual , St. John’s, NL: Institute for Educational Research and Development, Memorial University of Newfoundland, 2nd edition.
• OCR [Oxford, Cambridge and RSA Examinations], 2011, AS/A Level GCE: Critical Thinking – H052, H452 , Cambridge: OCR. Past papers available at https://pastpapers.co/ocr/?dir=A-Level/Critical-Thinking-H052-H452; last accessed 2022 07 16.
• Ontario Ministry of Education, 2013, The Ontario Curriculum Grades 9 to 12: Social Sciences and Humanities . Available at http://www.edu.gov.on.ca/eng/curriculum/secondary/ssciences9to122013.pdf ; last accessed 2022 07 16.
• Passmore, John Arthur, 1980, The Philosophy of Teaching , London: Duckworth.
• Paul, Richard W., 1981, “Teaching Critical Thinking in the ‘Strong’ Sense: A Focus on Self-Deception, World Views, and a Dialectical Mode of Analysis”, Informal Logic , 4(2): 2–7. [ Paul 1981 available online ]
• –––, 1984, “Critical Thinking: Fundamental to Education for a Free Society”, Educational Leadership , 42(1): 4–14.
• –––, 1985, “McPeck’s Mistakes”, Informal Logic , 7(1): 35–43. [ Paul 1985 available online ]
• Paul, Richard W. and Linda Elder, 2006, The Miniature Guide to Critical Thinking: Concepts and Tools , Dillon Beach, CA: Foundation for Critical Thinking, 4th edition.
• Payette, Patricia, and Edna Ross, 2016, “Making a Campus-Wide Commitment to Critical Thinking: Insights and Promising Practices Utilizing the Paul-Elder Approach at the University of Louisville”, Inquiry: Critical Thinking Across the Disciplines , 31(1): 98–110. doi:10.5840/inquiryct20163118
• Possin, Kevin, 2008, “A Field Guide to Critical-Thinking Assessment”, Teaching Philosophy , 31(3): 201–228. doi:10.5840/teachphil200831324
• –––, 2013a, “Some Problems with the Halpern Critical Thinking Assessment (HCTA) Test”, Inquiry: Critical Thinking across the Disciplines , 28(3): 4–12. doi:10.5840/inquiryct201328313
• –––, 2013b, “A Serious Flaw in the Collegiate Learning Assessment (CLA) Test”, Informal Logic , 33(3): 390–405. [ Possin 2013b available online ]
• –––, 2013c, “A Fatal Flaw in the Collegiate Learning Assessment Test”, Assessment Update , 25 (1): 8–12.
• –––, 2014, “Critique of the Watson-Glaser Critical Thinking Appraisal Test: The More You Know, the Lower Your Score”, Informal Logic , 34(4): 393–416. [ Possin 2014 available online ]
• –––, 2020, “CAT Scan: A Critical Review of the Critical-Thinking Assessment Test”, Informal Logic , 40 (3): 489–508. [Available online at https://informallogic.ca/index.php/informal_logic/article/view/6243]
• Rawls, John, 1971, A Theory of Justice , Cambridge, MA: Harvard University Press.
• Rear, David, 2019, “One Size Fits All? The Limitations of Standardised Assessment in Critical Thinking”, Assessment & Evaluation in Higher Education , 44(5): 664–675. doi: 10.1080/02602938.2018.1526255
• Rousseau, Jean-Jacques, 1762, Émile , Amsterdam: Jean Néaulme.
• Scheffler, Israel, 1960, The Language of Education , Springfield, IL: Charles C. Thomas.
• Scriven, Michael, and Richard W. Paul, 1987, Defining Critical Thinking , Draft statement written for the National Council for Excellence in Critical Thinking Instruction. Available at http://www.criticalthinking.org/pages/defining-critical-thinking/766 ; last accessed 2022 07 16.
• Sheffield, Clarence Burton Jr., 2018, “Promoting Critical Thinking in Higher Education: My Experiences as the Inaugural Eugene H. Fram Chair in Applied Critical Thinking at Rochester Institute of Technology”, Topoi , 37(1): 155–163. doi:10.1007/s11245-016-9392-1
• Siegel, Harvey, 1985, “McPeck, Informal Logic and the Nature of Critical Thinking”, in David Nyberg (ed.), Philosophy of Education 1985: Proceedings of the Forty-First Annual Meeting of the Philosophy of Education Society , Normal, IL: Philosophy of Education Society, pp. 61–72.
• –––, 1988, Educating Reason: Rationality, Critical Thinking, and Education , New York: Routledge.
• –––, 1999, “What (Good) Are Thinking Dispositions?”, Educational Theory , 49(2): 207–221. doi:10.1111/j.1741-5446.1999.00207.x
• Simon, Herbert A., 1956, “Rational Choice and the Structure of the Environment”, Psychological Review , 63(2): 129–138. doi: 10.1037/h0042769
• Simpson, Elizabeth, 1966–67, “The Classification of Educational Objectives: Psychomotor Domain”, Illinois Teacher of Home Economics , 10(4): 110–144, ERIC document ED0103613. [ Simpson 1966–67 available online ]
• Skolverket, 2018, Curriculum for the Compulsory School, Preschool Class and School-age Educare , Stockholm: Skolverket, revised 2018. Available at https://www.skolverket.se/download/18.31c292d516e7445866a218f/1576654682907/pdf3984.pdf; last accessed 2022 07 15.
• Smith, B. Othanel, 1953, “The Improvement of Critical Thinking”, Progressive Education , 30(5): 129–134.
• Smith, Eugene Randolph, Ralph Winfred Tyler, and the Evaluation Staff, 1942, Appraising and Recording Student Progress , Volume III of Adventure in American Education , New York and London: Harper & Brothers.
• Splitter, Laurance J., 1987, “Educational Reform through Philosophy for Children”, Thinking: The Journal of Philosophy for Children , 7(2): 32–39. doi:10.5840/thinking1987729
• Stanovich Keith E., and Paula J. Stanovich, 2010, “A Framework for Critical Thinking, Rational Thinking, and Intelligence”, in David D. Preiss and Robert J. Sternberg (eds), Innovations in Educational Psychology: Perspectives on Learning, Teaching and Human Development , New York: Springer Publishing, pp 195–237.
• Stanovich Keith E., Richard F. West, and Maggie E. Toplak, 2011, “Intelligence and Rationality”, in Robert J. Sternberg and Scott Barry Kaufman (eds.), Cambridge Handbook of Intelligence , Cambridge: Cambridge University Press, 3rd edition, pp. 784–826. doi:10.1017/CBO9780511977244.040
• Tankersley, Karen, 2005, Literacy Strategies for Grades 4–12: Reinforcing the Threads of Reading , Alexandria, VA: Association for Supervision and Curriculum Development.
• Thayer-Bacon, Barbara J., 1992, “Is Modern Critical Thinking Theory Sexist?”, Inquiry: Critical Thinking Across the Disciplines , 10(1): 3–7. doi:10.5840/inquiryctnews199210123
• –––, 1993, “Caring and Its Relationship to Critical Thinking”, Educational Theory , 43(3): 323–340. doi:10.1111/j.1741-5446.1993.00323.x
• –––, 1995a, “Constructive Thinking: Personal Voice”, Journal of Thought , 30(1): 55–70.
• –––, 1995b, “Doubting and Believing: Both are Important for Critical Thinking”, Inquiry: Critical Thinking across the Disciplines , 15(2): 59–66. doi:10.5840/inquiryctnews199515226
• –––, 2000, Transforming Critical Thinking: Thinking Constructively , New York: Teachers College Press.
• Toulmin, Stephen Edelston, 1958, The Uses of Argument , Cambridge: Cambridge University Press.
• Turri, John, Mark Alfano, and John Greco, 2017, “Virtue Epistemology”, in Edward N. Zalta (ed.), The Stanford Encyclopedia of Philosophy (Winter 2017 Edition). URL = < https://plato.stanford.edu/archives/win2017/entries/epistemology-virtue/ >
• Vincent-Lancrin, Stéphan, Carlos González-Sancho, Mathias Bouckaert, Federico de Luca, Meritxell Fernández-Barrerra, Gwénaël Jacotin, Joaquin Urgel, and Quentin Vidal, 2019, Fostering Students’ Creativity and Critical Thinking: What It Means in School. Educational Research and Innovation , Paris: OECD Publishing.
• Warren, Karen J. 1988. “Critical Thinking and Feminism”, Informal Logic , 10(1): 31–44. [ Warren 1988 available online ]
• Watson, Goodwin, and Edward M. Glaser, 1980a, Watson-Glaser Critical Thinking Appraisal, Form A , San Antonio, TX: Psychological Corporation.
• –––, 1980b, Watson-Glaser Critical Thinking Appraisal: Forms A and B; Manual , San Antonio, TX: Psychological Corporation,
• –––, 1994, Watson-Glaser Critical Thinking Appraisal, Form B , San Antonio, TX: Psychological Corporation.
• Weinstein, Mark, 1990, “Towards a Research Agenda for Informal Logic and Critical Thinking”, Informal Logic , 12(3): 121–143. [ Weinstein 1990 available online ]
• –––, 2013, Logic, Truth and Inquiry , London: College Publications.
• Willingham, Daniel T., 2019, “How to Teach Critical Thinking”, Education: Future Frontiers , 1: 1–17. [Available online at https://prod65.education.nsw.gov.au/content/dam/main-education/teaching-and-learning/education-for-a-changing-world/media/documents/How-to-teach-critical-thinking-Willingham.pdf.]
• Zagzebski, Linda Trinkaus, 1996, Virtues of the Mind: An Inquiry into the Nature of Virtue and the Ethical Foundations of Knowledge , Cambridge: Cambridge University Press. doi:10.1017/CBO9781139174763

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

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

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

Copyright © 2022 by David Hitchcock < hitchckd @ mcmaster . ca >

• Accessibility

Support SEP

Mirror sites.

View this site from another server:

• Info about mirror sites

The Stanford Encyclopedia of Philosophy is copyright © 2024 by The Metaphysics Research Lab , Department of Philosophy, Stanford University

Library of Congress Catalog Data: ISSN 1095-5054

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

• < Previous chapter
• Next chapter >

35 Scientific Thinking and Reasoning

Kevin N. Dunbar, Department of Human Development and Quantitative Methodology, University of Maryland, College Park, MD

David Klahr, Department of Psychology, Carnegie Mellon University, Pittsburgh, PA

• Published: 21 November 2012
• Cite Icon Cite
• Permissions Icon Permissions

Scientific thinking refers to both thinking about the content of science and the set of reasoning processes that permeate the field of science: induction, deduction, experimental design, causal reasoning, concept formation, hypothesis testing, and so on. Here we cover both the history of research on scientific thinking and the different approaches that have been used, highlighting common themes that have emerged over the past 50 years of research. Future research will focus on the collaborative aspects of scientific thinking, on effective methods for teaching science, and on the neural underpinnings of the scientific mind.

There is no unitary activity called “scientific discovery”; there are activities of designing experiments, gathering data, inventing and developing observational instruments, formulating and modifying theories, deducing consequences from theories, making predictions from theories, testing theories, inducing regularities and invariants from data, discovering theoretical constructs, and others. — Simon, Langley, & Bradshaw, 1981 , p. 2

What Is Scientific Thinking and Reasoning?

There are two kinds of thinking we call “scientific.” The first, and most obvious, is thinking about the content of science. People are engaged in scientific thinking when they are reasoning about such entities and processes as force, mass, energy, equilibrium, magnetism, atoms, photosynthesis, radiation, geology, or astrophysics (and, of course, cognitive psychology!). The second kind of scientific thinking includes the set of reasoning processes that permeate the field of science: induction, deduction, experimental design, causal reasoning, concept formation, hypothesis testing, and so on. However, these reasoning processes are not unique to scientific thinking: They are the very same processes involved in everyday thinking. As Einstein put it:

The scientific way of forming concepts differs from that which we use in our daily life, not basically, but merely in the more precise definition of concepts and conclusions; more painstaking and systematic choice of experimental material, and greater logical economy. (The Common Language of Science, 1941, reprinted in Einstein, 1950 , p. 98)

Nearly 40 years after Einstein's remarkably insightful statement, Francis Crick offered a similar perspective: that great discoveries in science result not from extraordinary mental processes, but rather from rather common ones. The greatness of the discovery lies in the thing discovered.

I think what needs to be emphasized about the discovery of the double helix is that the path to it was, scientifically speaking, fairly commonplace. What was important was not the way it was discovered , but the object discovered—the structure of DNA itself. (Crick, 1988 , p. 67; emphasis added)

Under this view, scientific thinking involves the same general-purpose cognitive processes—such as induction, deduction, analogy, problem solving, and causal reasoning—that humans apply in nonscientific domains. These processes are covered in several different chapters of this handbook: Rips, Smith, & Medin, Chapter 11 on induction; Evans, Chapter 8 on deduction; Holyoak, Chapter 13 on analogy; Bassok & Novick, Chapter 21 on problem solving; and Cheng & Buehner, Chapter 12 on causality. One might question the claim that the highly specialized procedures associated with doing science in the “real world” can be understood by investigating the thinking processes used in laboratory studies of the sort described in this volume. However, when the focus is on major scientific breakthroughs, rather than on the more routine, incremental progress in a field, the psychology of problem solving provides a rich source of ideas about how such discoveries might occur. As Simon and his colleagues put it:

It is understandable, if ironic, that ‘normal’ science fits … the description of expert problem solving, while ‘revolutionary’ science fits the description of problem solving by novices. It is understandable because scientific activity, particularly at the revolutionary end of the continuum, is concerned with the discovery of new truths, not with the application of truths that are already well-known … it is basically a journey into unmapped terrain. Consequently, it is mainly characterized, as is novice problem solving, by trial-and-error search. The search may be highly selective—but it reaches its goal only after many halts, turnings, and back-trackings. (Simon, Langley, & Bradshaw, 1981 , p. 5)

The research literature on scientific thinking can be roughly categorized according to the two types of scientific thinking listed in the opening paragraph of this chapter: (1) One category focuses on thinking that directly involves scientific content . Such research ranges from studies of young children reasoning about the sun-moon-earth system (Vosniadou & Brewer, 1992 ) to college students reasoning about chemical equilibrium (Davenport, Yaron, Klahr, & Koedinger, 2008 ), to research that investigates collaborative problem solving by world-class researchers in real-world molecular biology labs (Dunbar, 1995 ). (2) The other category focuses on “general” cognitive processes, but it tends to do so by analyzing people's problem-solving behavior when they are presented with relatively complex situations that involve the integration and coordination of several different types of processes, and that are designed to capture some essential features of “real-world” science in the psychology laboratory (Bruner, Goodnow, & Austin, 1956 ; Klahr & Dunbar, 1988 ; Mynatt, Doherty, & Tweney, 1977 ).

There are a number of overlapping research traditions that have been used to investigate scientific thinking. We will cover both the history of research on scientific thinking and the different approaches that have been used, highlighting common themes that have emerged over the past 50 years of research.

A Brief History of Research on Scientific Thinking

Science is often considered one of the hallmarks of the human species, along with art and literature. Illuminating the thought processes used in science thus reveal key aspects of the human mind. The thought processes underlying scientific thinking have fascinated both scientists and nonscientists because the products of science have transformed our world and because the process of discovery is shrouded in mystery. Scientists talk of the chance discovery, the flash of insight, the years of perspiration, and the voyage of discovery. These images of science have helped make the mental processes underlying the discovery process intriguing to cognitive scientists as they attempt to uncover what really goes on inside the scientific mind and how scientists really think. Furthermore, the possibilities that scientists can be taught to think better by avoiding mistakes that have been clearly identified in research on scientific thinking, and that their scientific process could be partially automated, makes scientific thinking a topic of enduring interest.

The cognitive processes underlying scientific discovery and day-to-day scientific thinking have been a topic of intense scrutiny and speculation for almost 400 years (e.g., Bacon, 1620 ; Galilei 1638 ; Klahr 2000 ; Tweney, Doherty, & Mynatt, 1981 ). Understanding the nature of scientific thinking has been a central issue not only for our understanding of science but also for our understating of what it is to be human. Bacon's Novumm Organum in 1620 sketched out some of the key features of the ways that experiments are designed and data interpreted. Over the ensuing 400 years philosophers and scientists vigorously debated about the appropriate methods that scientists should use (see Giere, 1993 ). These debates over the appropriate methods for science typically resulted in the espousal of a particular type of reasoning method, such as induction or deduction. It was not until the Gestalt psychologists began working on the nature of human problem solving, during the 1940s, that experimental psychologists began to investigate the cognitive processes underlying scientific thinking and reasoning.

The Gestalt psychologist Max Wertheimer pioneered the investigation of scientific thinking (of the first type described earlier: thinking about scientific content ) in his landmark book Productive Thinking (Wertheimer, 1945 ). Wertheimer spent a considerable amount of time corresponding with Albert Einstein, attempting to discover how Einstein generated the concept of relativity. Wertheimer argued that Einstein had to overcome the structure of Newtonian physics at each step in his theorizing, and the ways that Einstein actually achieved this restructuring were articulated in terms of Gestalt theories. (For a recent and different account of how Einstein made his discovery, see Galison, 2003 .) We will see later how this process of overcoming alternative theories is an obstacle that both scientists and nonscientists need to deal with when evaluating and theorizing about the world.

One of the first investigations of scientific thinking of the second type (i.e., collections of general-purpose processes operating on complex, abstract, components of scientific thought) was carried out by Jerome Bruner and his colleagues at Harvard (Bruner et al., 1956 ). They argued that a key activity engaged in by scientists is to determine whether a particular instance is a member of a category. For example, a scientist might want to discover which substances undergo fission when bombarded by neutrons and which substances do not. Here, scientists have to discover the attributes that make a substance undergo fission. Bruner et al. saw scientific thinking as the testing of hypotheses and the collecting of data with the end goal of determining whether something is a member of a category. They invented a paradigm where people were required to formulate hypotheses and collect data that test their hypotheses. In one type of experiment, the participants were shown a card such as one with two borders and three green triangles. The participants were asked to determine the concept that this card represented by choosing other cards and getting feedback from the experimenter as to whether the chosen card was an example of the concept. In this case the participant may have thought that the concept was green and chosen a card with two green squares and one border. If the underlying concept was green, then the experimenter would say that the card was an example of the concept. In terms of scientific thinking, choosing a new card is akin to conducting an experiment, and the feedback from the experimenter is similar to knowing whether a hypothesis is confirmed or disconfirmed. Using this approach, Bruner et al. identified a number of strategies that people use to formulate and test hypotheses. They found that a key factor determining which hypothesis-testing strategy that people use is the amount of memory capacity that the strategy takes up (see also Morrison & Knowlton, Chapter 6 ; Medin et al., Chapter 11 ). Another key factor that they discovered was that it was much more difficult for people to discover negative concepts (e.g., not blue) than positive concepts (e.g., blue). Although Bruner et al.'s research is most commonly viewed as work on concepts, they saw their work as uncovering a key component of scientific thinking.

A second early line of research on scientific thinking was developed by Peter Wason and his colleagues (Wason, 1968 ). Like Bruner et al., Wason saw a key component of scientific thinking as being the testing of hypotheses. Whereas Bruner et al. focused on the different types of strategies that people use to formulate hypotheses, Wason focused on whether people adopt a strategy of trying to confirm or disconfirm their hypotheses. Using Popper's ( 1959 ) theory that scientists should try and falsify rather than confirm their hypotheses, Wason devised a deceptively simple task in which participants were given three numbers, such as 2-4-6, and were asked to discover the rule underlying the three numbers. Participants were asked to generate other triads of numbers and the experimenter would tell the participant whether the triad was consistent or inconsistent with the rule. They were told that when they were sure they knew what the rule was they should state it. Most participants began the experiment by thinking that the rule was even numbers increasing by 2. They then attempted to confirm their hypothesis by generating a triad like 8-10-12, then 14-16-18. These triads are consistent with the rule and the participants were told yes, that the triads were indeed consistent with the rule. However, when they proposed the rule—even numbers increasing by 2—they were told that the rule was incorrect. The correct rule was numbers of increasing magnitude! From this research, Wason concluded that people try to confirm their hypotheses, whereas normatively speaking, they should try to disconfirm their hypotheses. One implication of this research is that confirmation bias is not just restricted to scientists but is a general human tendency.

It was not until the 1970s that a general account of scientific reasoning was proposed. Herbert Simon, often in collaboration with Allan Newell, proposed that scientific thinking is a form of problem solving. He proposed that problem solving is a search in a problem space. Newell and Simon's theory of problem solving is discussed in many places in this handbook, usually in the context of specific problems (see especially Bassok & Novick, Chapter 21 ). Herbert Simon, however, devoted considerable time to understanding many different scientific discoveries and scientific reasoning processes. The common thread in his research was that scientific thinking and discovery is not a mysterious magical process but a process of problem solving in which clear heuristics are used. Simon's goal was to articulate the heuristics that scientists use in their research at a fine-grained level. By constructing computer programs that simulated the process of several major scientific discoveries, Simon and colleagues were able to articulate the specific computations that scientists could have used in making those discoveries (Langley, Simon, Bradshaw, & Zytkow, 1987 ; see section on “Computational Approaches to Scientific Thinking”). Particularly influential was Simon and Lea's ( 1974 ) work demonstrating that concept formation and induction consist of a search in two problem spaces: a space of instances and a space of rules. This idea has influenced problem-solving accounts of scientific thinking that will be discussed in the next section.

Overall, the work of Bruner, Wason, and Simon laid the foundations for contemporary research on scientific thinking. Early research on scientific thinking is summarized in Tweney, Doherty and Mynatt's 1981 book On Scientific Thinking , where they sketched out many of the themes that have dominated research on scientific thinking over the past few decades. Other more recent books such as Cognitive Models of Science (Giere, 1993 ), Exploring Science (Klahr, 2000 ), Cognitive Basis of Science (Carruthers, Stich, & Siegal, 2002 ), and New Directions in Scientific and Technical Thinking (Gorman, Kincannon, Gooding, & Tweney, 2004 ) provide detailed analyses of different aspects of scientific discovery. Another important collection is Vosnadiau's handbook on conceptual change research (Vosniadou, 2008 ). In this chapter, we discuss the main approaches that have been used to investigate scientific thinking.

How does one go about investigating the many different aspects of scientific thinking? One common approach to the study of the scientific mind has been to investigate several key aspects of scientific thinking using abstract tasks designed to mimic some essential characteristics of “real-world” science. There have been numerous methodologies that have been used to analyze the genesis of scientific concepts, theories, hypotheses, and experiments. Researchers have used experiments, verbal protocols, computer programs, and analyzed particular scientific discoveries. A more recent development has been to increase the ecological validity of such research by investigating scientists as they reason “live” (in vivo studies of scientific thinking) in their own laboratories (Dunbar, 1995 , 2002 ). From a “Thinking and Reasoning” standpoint the major aspects of scientific thinking that have been most actively investigated are problem solving, analogical reasoning, hypothesis testing, conceptual change, collaborative reasoning, inductive reasoning, and deductive reasoning.

Scientific Thinking as Problem Solving

One of the primary goals of accounts of scientific thinking has been to provide an overarching framework to understand the scientific mind. One framework that has had a great influence in cognitive science is that scientific thinking and scientific discovery can be conceived as a form of problem solving. As noted in the opening section of this chapter, Simon ( 1977 ; Simon, Langley, & Bradshaw, 1981 ) argued that both scientific thinking in general and problem solving in particular could be thought of as a search in a problem space. A problem space consists of all the possible states of a problem and all the operations that a problem solver can use to get from one state to the next. According to this view, by characterizing the types of representations and procedures that people use to get from one state to another it is possible to understand scientific thinking. Thus, scientific thinking can be characterized as a search in various problem spaces (Simon, 1977 ). Simon investigated a number of scientific discoveries by bringing participants into the laboratory, providing the participants with the data that a scientist had access to, and getting the participants to reason about the data and rediscover a scientific concept. He then analyzed the verbal protocols that participants generated and mapped out the types of problem spaces that the participants search in (e.g., Qin & Simon, 1990 ). Kulkarni and Simon ( 1988 ) used a more historical approach to uncover the problem-solving heuristics that Krebs used in his discovery of the urea cycle. Kulkarni and Simon analyzed Krebs's diaries and proposed a set of problem-solving heuristics that he used in his research. They then built a computer program incorporating the heuristics and biological knowledge that Krebs had before he made his discoveries. Of particular importance are the search heuristics that the program uses, which include experimental proposal heuristics and data interpretation heuristics. A key heuristic was an unusualness heuristic that focused on unusual findings, which guided search through a space of theories and a space of experiments.

Klahr and Dunbar ( 1988 ) extended the search in a problem space approach and proposed that scientific thinking can be thought of as a search through two related spaces: an hypothesis space and an experiment space. Each problem space that a scientist uses will have its own types of representations and operators used to change the representations. Search in the hypothesis space constrains search in the experiment space. Klahr and Dunbar found that some participants move from the hypothesis space to the experiment space, whereas others move from the experiment space to the hypothesis space. These different types of searches lead to the proposal of different types of hypotheses and experiments. More recent work has extended the dual-space approach to include alternative problem-solving spaces, including those for data, instrumentation, and domain-specific knowledge (Klahr & Simon, 1999 ; Schunn & Klahr, 1995 , 1996 ).

Scientific Thinking as Hypothesis Testing

Many researchers have regarded testing specific hypotheses predicted by theories as one of the key attributes of scientific thinking. Hypothesis testing is the process of evaluating a proposition by collecting evidence regarding its truth. Experimental cognitive research on scientific thinking that specifically examines this issue has tended to fall into two broad classes of investigations. The first class is concerned with the types of reasoning that lead scientists astray, thus blocking scientific ingenuity. A large amount of research has been conducted on the potentially faulty reasoning strategies that both participants in experiments and scientists use, such as considering only one favored hypothesis at a time and how this prevents the scientists from making discoveries. The second class is concerned with uncovering the mental processes underlying the generation of new scientific hypotheses and concepts. This research has tended to focus on the use of analogy and imagery in science, as well as the use of specific types of problem-solving heuristics.

Turning first to investigations of what diminishes scientific creativity, philosophers, historians, and experimental psychologists have devoted a considerable amount of research to “confirmation bias.” This occurs when scientists only consider one hypothesis (typically the favored hypothesis) and ignore other alternative hypotheses or potentially relevant hypotheses. This important phenomenon can distort the design of experiments, formulation of theories, and interpretation of data. Beginning with the work of Wason ( 1968 ) and as discussed earlier, researchers have repeatedly shown that when participants are asked to design an experiment to test a hypothesis they will predominantly design experiments that they think will yield results consistent with the hypothesis. Using the 2-4-6 task mentioned earlier, Klayman and Ha ( 1987 ) showed that in situations where one's hypothesis is likely to be confirmed, seeking confirmation is a normatively incorrect strategy, whereas when the probability of confirming one's hypothesis is low, then attempting to confirm one's hypothesis can be an appropriate strategy. Historical analyses by Tweney ( 1989 ), concerning the way that Faraday made his discoveries, and experiments investigating people testing hypotheses, have revealed that people use a confirm early, disconfirm late strategy: When people initially generate or are given hypotheses, they try and gather evidence that is consistent with the hypothesis. Once enough evidence has been gathered, then people attempt to find the boundaries of their hypothesis and often try to disconfirm their hypotheses.

In an interesting variant on the confirmation bias paradigm, Gorman ( 1989 ) showed that when participants are told that there is the possibility of error in the data that they receive, participants assume that any data that are inconsistent with their favored hypothesis are due to error. Thus, the possibility of error “insulates” hypotheses against disconfirmation. This intriguing hypothesis has not been confirmed by other researchers (Penner & Klahr, 1996 ), but it is an intriguing hypothesis that warrants further investigation.

Confirmation bias is very difficult to overcome. Even when participants are asked to consider alternate hypotheses, they will often fail to conduct experiments that could potentially disconfirm their hypothesis. Tweney and his colleagues provide an excellent overview of this phenomenon in their classic monograph On Scientific Thinking (1981). The precise reasons for this type of block are still widely debated. Researchers such as Michael Doherty have argued that working memory limitations make it difficult for people to consider more than one hypothesis. Consistent with this view, Dunbar and Sussman ( 1995 ) have shown that when participants are asked to hold irrelevant items in working memory while testing hypotheses, the participants will be unable to switch hypotheses in the face of inconsistent evidence. While working memory limitations are involved in the phenomenon of confirmation bias, even groups of scientists can also display confirmation bias. For example, the controversy over cold fusion is an example of confirmation bias. Here, large groups of scientists had other hypotheses available to explain their data yet maintained their hypotheses in the face of other more standard alternative hypotheses. Mitroff ( 1974 ) provides some interesting examples of NASA scientists demonstrating confirmation bias, which highlight the roles of commitment and motivation in this process. See also MacPherson and Stanovich ( 2007 ) for specific strategies that can be used to overcome confirmation bias.

Causal Thinking in Science

Much of scientific thinking and scientific theory building pertains to the development of causal models between variables of interest. For example, do vaccines cause illnesses? Do carbon dioxide emissions cause global warming? Does water on a planet indicate that there is life on the planet? Scientists and nonscientists alike are constantly bombarded with statements regarding the causal relationship between such variables. How does one evaluate the status of such claims? What kinds of data are informative? How do scientists and nonscientists deal with data that are inconsistent with their theory?

A central issue in the causal reasoning literature, one that is directly relevant to scientific thinking, is the extent to which scientists and nonscientists alike are governed by the search for causal mechanisms (i.e., how a variable works) versus the search for statistical data (i.e., how often variables co-occur). This dichotomy can be boiled down to the search for qualitative versus quantitative information about the paradigm the scientist is investigating. Researchers from a number of cognitive psychology laboratories have found that people prefer to gather more information about an underlying mechanism than covariation between a cause and an effect (e.g., Ahn, Kalish, Medin, & Gelman, 1995 ). That is, the predominant strategy that students in simulations of scientific thinking use is to gather as much information as possible about how the objects under investigation work, rather than collecting large amounts of quantitative data to determine whether the observations hold across multiple samples. These findings suggest that a central component of scientific thinking may be to formulate explicit mechanistic causal models of scientific events.

One type of situation in which causal reasoning has been observed extensively is when scientists obtain unexpected findings. Both historical and naturalistic research has revealed that reasoning causally about unexpected findings plays a central role in science. Indeed, scientists themselves frequently state that a finding was due to chance or was unexpected. Given that claims of unexpected findings are such a frequent component of scientists' autobiographies and interviews in the media, Dunbar ( 1995 , 1997 , 1999 ; Dunbar & Fugelsang, 2005 ; Fugelsang, Stein, Green, & Dunbar, 2004 ) decided to investigate the ways that scientists deal with unexpected findings. In 1991–1992 Dunbar spent 1 year in three molecular biology laboratories and one immunology laboratory at a prestigious U.S. university. He used the weekly laboratory meeting as a source of data on scientific discovery and scientific reasoning. (He termed this type of study “in vivo” cognition.) When he looked at the types of findings that the scientists made, he found that over 50% of the findings were unexpected and that these scientists had evolved a number of effective strategies for dealing with such findings. One clear strategy was to reason causally about the findings: Scientists attempted to build causal models of their unexpected findings. This causal model building results in the extensive use of collaborative reasoning, analogical reasoning, and problem-solving heuristics (Dunbar, 1997 , 2001 ).

Many of the key unexpected findings that scientists reasoned about in the in vivo studies of scientific thinking were inconsistent with the scientists' preexisting causal models. A laboratory equivalent of the biology labs involved creating a situation in which students obtained unexpected findings that were inconsistent with their preexisting theories. Dunbar and Fugelsang ( 2005 ) examined this issue by creating a scientific causal thinking simulation where experimental outcomes were either expected or unexpected. Dunbar ( 1995 ) has called the study of people reasoning in a cognitive laboratory “in vitro” cognition. These investigators found that students spent considerably more time reasoning about unexpected findings than expected findings. In addition, when assessing the overall degree to which their hypothesis was supported or refuted, participants spent the majority of their time considering unexpected findings. An analysis of participants' verbal protocols indicates that much of this extra time was spent formulating causal models for the unexpected findings. Similarly, scientists spend more time considering unexpected than expected findings, and this time is devoted to building causal models (Dunbar & Fugelsang, 2004 ).

Scientists know that unexpected findings occur often, and they have developed many strategies to take advantage of their unexpected findings. One of the most important places that they anticipate the unexpected is in designing experiments (Baker & Dunbar, 2000 ). They build different causal models of their experiments incorporating many conditions and controls. These multiple conditions and controls allow unknown mechanisms to manifest themselves. Thus, rather than being the victims of the unexpected, they create opportunities for unexpected events to occur, and once these events do occur, they have causal models that allow them to determine exactly where in the causal chain their unexpected finding arose. The results of these in vivo and in vitro studies all point to a more complex and nuanced account of how scientists and nonscientists alike test and evaluate hypotheses about theories.

The Roles of Inductive, Abductive, and Deductive Thinking in Science

One of the most basic characteristics of science is that scientists assume that the universe that we live in follows predictable rules. Scientists reason using a variety of different strategies to make new scientific discoveries. Three frequently used types of reasoning strategies that scientists use are inductive, abductive, and deductive reasoning. In the case of inductive reasoning, a scientist may observe a series of events and try to discover a rule that governs the event. Once a rule is discovered, scientists can extrapolate from the rule to formulate theories of observed and yet-to-be-observed phenomena. One example is the discovery using inductive reasoning that a certain type of bacterium is a cause of many ulcers (Thagard, 1999 ). In a fascinating series of articles, Thagard documented the reasoning processes that Marshall and Warren went through in proposing this novel hypothesis. One key reasoning process was the use of induction by generalization. Marshall and Warren noted that almost all patients with gastric entritis had a spiral bacterium in their stomachs, and he formed the generalization that this bacterium is the cause of stomach ulcers. There are numerous other examples of induction by generalization in science, such as Tycho De Brea's induction about the motion of planets from his observations, Dalton's use of induction in chemistry, and the discovery of prions as the source of mad cow disease. Many theories of induction have used scientific discovery and reasoning as examples of this important reasoning process.

Another common type of inductive reasoning is to map a feature of one member of a category to another member of a category. This is called categorical induction. This type of induction is a way of projecting a known property of one item onto another item that is from the same category. Thus, knowing that the Rous Sarcoma virus is a retrovirus that uses RNA rather than DNA, a biologist might assume that another virus that is thought to be a retrovirus also uses RNA rather than DNA. While research on this type of induction typically has not been discussed in accounts of scientific thinking, this type of induction is common in science. For an influential contribution to this literature, see Smith, Shafir, and Osherson ( 1993 ), and for reviews of this literature see Heit ( 2000 ) and Medin et al. (Chapter 11 ).

While less commonly mentioned than inductive reasoning, abductive reasoning is an important form of reasoning that scientists use when they are seeking to propose explanations for events such as unexpected findings (see Lombrozo, Chapter 14 ; Magnani, et al., 2010 ). In Figure 35.1 , taken from King ( 2011 ), the differences between inductive, abductive, and deductive thinking are highlighted. In the case of abduction, the reasoner attempts to generate explanations of the form “if situation X had occurred, could it have produced the current evidence I am attempting to interpret?” (For an interesting of analysis of abductive reasoning see the brief paper by Klahr & Masnick, 2001 ). Of course, as in classical induction, such reasoning may produce a plausible account that is still not the correct one. However, abduction does involve the generation of new knowledge, and is thus also related to research on creativity.

The different processes underlying inductive, abductive, and deductive reasoning in science. (Figure reproduced from King 2011 ).)

Turning now to deductive thinking, many thinking processes that scientists adhere to follow traditional rules of deductive logic. These processes correspond to those conditions in which a hypothesis may lead to, or is deducible to, a conclusion. Though they are not always phrased in syllogistic form, deductive arguments can be phrased as “syllogisms,” or as brief, mathematical statements in which the premises lead to the conclusion. Deductive reasoning is an extremely important aspect of scientific thinking because it underlies a large component of how scientists conduct their research. By looking at many scientific discoveries, we can often see that deductive reasoning is at work. Deductive reasoning statements all contain information or rules that state an assumption about how the world works, as well as a conclusion that would necessarily follow from the rule. Numerous discoveries in physics such as the discovery of dark matter by Vera Rubin are based on deductions. In the dark matter case, Rubin measured galactic rotation curves and based on the differences between the predicted and observed angular motions of galaxies she deduced that the structure of the universe was uneven. This led her to propose that dark matter existed. In contemporary physics the CERN Large Hadron Collider is being used to search for the Higgs Boson. The Higgs Boson is a deductive prediction from contemporary physics. If the Higgs Boson is not found, it may lead to a radical revision of the nature of physics and a new understanding of mass (Hecht, 2011 ).

The Roles of Analogy in Scientific Thinking

One of the most widely mentioned reasoning processes used in science is analogy. Scientists use analogies to form a bridge between what they already know and what they are trying to explain, understand, or discover. In fact, many scientists have claimed that the making of certain analogies was instrumental in their making a scientific discovery, and almost all scientific autobiographies and biographies feature one particular analogy that is discussed in depth. Coupled with the fact that there has been an enormous research program on analogical thinking and reasoning (see Holyoak, Chapter 13 ), we now have a number of models and theories of analogical reasoning that suggest how analogy can play a role in scientific discovery (see Gentner, Holyoak, & Kokinov, 2001 ). By analyzing several major discoveries in the history of science, Thagard and Croft ( 1999 ), Nersessian ( 1999 , 2008 ), and Gentner and Jeziorski ( 1993 ) have all shown that analogical reasoning is a key aspect of scientific discovery.

Traditional accounts of analogy distinguish between two components of analogical reasoning: the target and the source (Holyoak, Chapter 13 ; Gentner 2010 ). The target is the concept or problem that a scientist is attempting to explain or solve. The source is another piece of knowledge that the scientist uses to understand the target or to explain the target to others. What the scientist does when he or she makes an analogy is to map features of the source onto features of the target. By mapping the features of the source onto the target, new features of the target may be discovered, or the features of the target may be rearranged so that a new concept is invented and a scientific discovery is made. For example, a common analogy that is used with computers is to describe a harmful piece of software as a computer virus. Once a piece of software is called a virus, people can map features of biological viruses, such as that it is small, spreads easily, self-replicates using a host, and causes damage. People not only map individual features of the source onto the target but also the systems of relations. For example, if a computer virus is similar to a biological virus, then an immune system can be created on computers that can protect computers from future variants of a virus. One of the reasons that scientific analogy is so powerful is that it can generate new knowledge, such as the creation of a computational immune system having many of the features of a real biological immune system. This analogy also leads to predictions that there will be newer computer viruses that are the computational equivalent of retroviruses, lacking DNA, or standard instructions, that will elude the computational immune system.

The process of making an analogy involves a number of key steps: retrieval of a source from memory, aligning the features of the source with those of the target, mapping features of the source onto those of the target, and possibly making new inferences about the target. Scientific discoveries are made when the source highlights a hitherto unknown feature of the target or restructures the target into a new set of relations. Interestingly, research on analogy has shown that participants do not easily use remote analogies (see Gentner et al., 1997 ; Holyoak & Thagard 1995 ). Participants in experiments tend to focus on the sharing of a superficial feature between the source and the target, rather than the relations among features. In his in vivo studies of science, Dunbar ( 1995 , 2001 , 2002 ) investigated the ways that scientists use analogies while they are conducting their research and found that scientists use both relational and superficial features when they make analogies. Whether they use superficial or relational features depends on their goals. If their goal is to fix a problem in an experiment, their analogies are based upon superficial features. However, if their goal is to formulate hypotheses, they focus on analogies based upon sets of relations. One important difference between scientists and participants in experiments is that the scientists have deep relational knowledge of the processes that they are investigating and can hence use this relational knowledge to make analogies (see Holyoak, Chapter 13 for a thorough review of analogical reasoning).

Are scientific analogies always useful? Sometimes analogies can lead scientists and students astray. For example, Evelyn Fox-Keller ( 1985 ) shows how an analogy between the pulsing of a lighthouse and the activity of the slime mold dictyostelium led researchers astray for a number of years. Likewise, the analogy between the solar system (the source) and the structure of the atom (the target) has been shown to be potentially misleading to students taking more advanced courses in physics or chemistry. The solar system analogy has a number of misalignments to the structure of the atom, such as electrons being repelled from each other rather than attracted; moreover, electrons do not have individual orbits like planets but have orbit clouds of electron density. Furthermore, students have serious misconceptions about the nature of the solar system, which can compound their misunderstanding of the nature of the atom (Fischler & Lichtfeld, 1992 ). While analogy is a powerful tool in science, like all forms of induction, incorrect conclusions can be reached.

Conceptual Change in Science

Scientific knowledge continually accumulates as scientists gather evidence about the natural world. Over extended time, this knowledge accumulation leads to major revisions, extensions, and new organizational forms for expressing what is known about nature. Indeed, these changes are so substantial that philosophers of science speak of “revolutions” in a variety of scientific domains (Kuhn, 1962 ). The psychological literature that explores the idea of revolutionary conceptual change can be roughly divided into (a) investigations of how scientists actually make discoveries and integrate those discoveries into existing scientific contexts, and (b) investigations of nonscientists ranging from infants, to children, to students in science classes. In this section we summarize the adult studies of conceptual change, and in the next section we look at its developmental aspects.

Scientific concepts, like all concepts, can be characterized as containing a variety of “knowledge elements”: representations of words, thoughts, actions, objects, and processes. At certain points in the history of science, the accumulated evidence has demanded major shifts in the way these collections of knowledge elements are organized. This “radical conceptual change” process (see Keil, 1999 ; Nersessian 1998 , 2002 ; Thagard, 1992 ; Vosniadou 1998, for reviews) requires the formation of a new conceptual system that organizes knowledge in new ways, adds new knowledge, and results in a very different conceptual structure. For more recent research on conceptual change, The International Handbook of Research on Conceptual Change (Vosniadou, 2008 ) provides a detailed compendium of theories and controversies within the field.

While conceptual change in science is usually characterized by large-scale changes in concepts that occur over extensive periods of time, it has been possible to observe conceptual change using in vivo methodologies. Dunbar ( 1995 ) reported a major conceptual shift that occurred in immunologists, where they obtained a series of unexpected findings that forced the scientists to propose a new concept in immunology that in turn forced the change in other concepts. The drive behind this conceptual change was the discovery of a series of different unexpected findings or anomalies that required the scientists to both revise and reorganize their conceptual knowledge. Interestingly, this conceptual change was achieved by a group of scientists reasoning collaboratively, rather than by a scientist working alone. Different scientists tend to work on different aspects of concepts, and also different concepts, that when put together lead to a rapid change in entire conceptual structures.

Overall, accounts of conceptual change in individuals indicate that it is indeed similar to that of conceptual change in entire scientific fields. Individuals need to be confronted with anomalies that their preexisting theories cannot explain before entire conceptual structures are overthrown. However, replacement conceptual structures have to be generated before the old conceptual structure can be discarded. Sometimes, people do not overthrow their original conceptual theories and through their lives maintain their original views of many fundamental scientific concepts. Whether people actively possess naive theories, or whether they appear to have a naive theory because of the demand characteristics of the testing context, is a lively source of debate within the science education community (see Gupta, Hammer, & Redish, 2010 ).

Scientific Thinking in Children

Well before their first birthday, children appear to know several fundamental facts about the physical world. For example, studies with infants show that they behave as if they understand that solid objects endure over time (e.g., they don't just disappear and reappear, they cannot move through each other, and they move as a result of collisions with other solid objects or the force of gravity (Baillargeon, 2004 ; Carey 1985 ; Cohen & Cashon, 2006 ; Duschl, Schweingruber, & Shouse, 2007 ; Gelman & Baillargeon, 1983 ; Gelman & Kalish, 2006 ; Mandler, 2004 ; Metz 1995 ; Munakata, Casey, & Diamond, 2004 ). And even 6-month-olds are able to predict the future location of a moving object that they are attempting to grasp (Von Hofsten, 1980 ; Von Hofsten, Feng, & Spelke, 2000 ). In addition, they appear to be able to make nontrivial inferences about causes and their effects (Gopnik et al., 2004 ).

The similarities between children's thinking and scientists' thinking have an inherent allure and an internal contradiction. The allure resides in the enthusiastic wonder and openness with which both children and scientists approach the world around them. The paradox comes from the fact that different investigators of children's thinking have reached diametrically opposing conclusions about just how “scientific” children's thinking really is. Some claim support for the “child as a scientist” position (Brewer & Samarapungavan, 1991 ; Gelman & Wellman, 1991 ; Gopnik, Meltzoff, & Kuhl, 1999 ; Karmiloff-Smith 1988 ; Sodian, Zaitchik, & Carey, 1991 ; Samarapungavan 1992 ), while others offer serious challenges to the view (Fay & Klahr, 1996 ; Kern, Mirels, & Hinshaw, 1983 ; Kuhn, Amsel, & O'Laughlin, 1988 ; Schauble & Glaser, 1990 ; Siegler & Liebert, 1975 .) Such fundamentally incommensurate conclusions suggest that this very field—children's scientific thinking—is ripe for a conceptual revolution!

A recent comprehensive review (Duschl, Schweingruber, & Shouse, 2007 ) of what children bring to their science classes offers the following concise summary of the extensive developmental and educational research literature on children's scientific thinking:

Children entering school already have substantial knowledge of the natural world, much of which is implicit.

What children are capable of at a particular age is the result of a complex interplay among maturation, experience, and instruction. What is developmentally appropriate is not a simple function of age or grade, but rather is largely contingent on children's prior opportunities to learn.

Students' knowledge and experience play a critical role in their science learning, influencing four aspects of science understanding, including (a) knowing, using, and interpreting scientific explanations of the natural world; (b) generating and evaluating scientific evidence and explanations, (c) understanding how scientific knowledge is developed in the scientific community, and (d) participating in scientific practices and discourse.

Students learn science by actively engaging in the practices of science.

In the previous section of this article we discussed conceptual change with respect to scientific fields and undergraduate science students. However, the idea that children undergo radical conceptual change in which old “theories” need to be overthrown and reorganized has been a central topic in understanding changes in scientific thinking in both children and across the life span. This radical conceptual change is thought to be necessary for acquiring many new concepts in physics and is regarded as the major source of difficulty for students. The factors that are at the root of this conceptual shift view have been difficult to determine, although there have been a number of studies in cognitive development (Carey, 1985 ; Chi 1992 ; Chi & Roscoe, 2002 ), in the history of science (Thagard, 1992 ), and in physics education (Clement, 1982 ; Mestre 1991 ) that give detailed accounts of the changes in knowledge representation that occur while people switch from one way of representing scientific knowledge to another.

One area where students show great difficulty in understanding scientific concepts is physics. Analyses of students' changing conceptions, using interviews, verbal protocols, and behavioral outcome measures, indicate that large-scale changes in students' concepts occur in physics education (see McDermott & Redish, 1999 , for a review of this literature). Following Kuhn ( 1962 ), many researchers, but not all, have noted that students' changing conceptions resemble the sequences of conceptual changes in physics that have occurred in the history of science. These notions of radical paradigm shifts and ensuing incompatibility with past knowledge-states have called attention to interesting parallels between the development of particular scientific concepts in children and in the history of physics. Investigations of nonphysicists' understanding of motion indicate that students have extensive misunderstandings of motion. Some researchers have interpreted these findings as an indication that many people hold erroneous beliefs about motion similar to a medieval “impetus” theory (McCloskey, Caramazza, & Green, 1980 ). Furthermore, students appear to maintain “impetus” notions even after one or two courses in physics. In fact, some authors have noted that students who have taken one or two courses in physics can perform worse on physics problems than naive students (Mestre, 1991 ). Thus, it is only after extensive learning that we see a conceptual shift from impetus theories of motion to Newtonian scientific theories.

How one's conceptual representation shifts from “naive” to Newtonian is a matter of contention, as some have argued that the shift involves a radical conceptual change, whereas others have argued that the conceptual change is not really complete. For example, Kozhevnikov and Hegarty ( 2001 ) argue that much of the naive impetus notions of motion are maintained at the expense of Newtonian principles even with extensive training in physics. However, they argue that such impetus principles are maintained at an implicit level. Thus, although students can give the correct Newtonian answer to problems, their reaction times to respond indicate that they are also using impetus theories when they respond. An alternative view of conceptual change focuses on whether there are real conceptual changes at all. Gupta, Hammer and Redish ( 2010 ) and Disessa ( 2004 ) have conducted detailed investigations of changes in physics students' accounts of phenomena covered in elementary physics courses. They have found that rather than students possessing a naive theory that is replaced by the standard theory, many introductory physics students have no stable physical theory but rather construct their explanations from elementary pieces of knowledge of the physical world.

Computational Approaches to Scientific Thinking

Computational approaches have provided a more complete account of the scientific mind. Computational models provide specific detailed accounts of the cognitive processes underlying scientific thinking. Early computational work consisted of taking a scientific discovery and building computational models of the reasoning processes involved in the discovery. Langley, Simon, Bradshaw, and Zytkow ( 1987 ) built a series of programs that simulated discoveries such as those of Copernicus, Bacon, and Stahl. These programs had various inductive reasoning algorithms built into them, and when given the data that the scientists used, they were able to propose the same rules. Computational models make it possible to propose detailed models of the cognitive subcomponents of scientific thinking that specify exactly how scientific theories are generated, tested, and amended (see Darden, 1997 , and Shrager & Langley, 1990 , for accounts of this branch of research). More recently, the incorporation of scientific knowledge into computer programs has resulted in a shift in emphasis from using programs to simulate discoveries to building programs that are used to help scientists make discoveries. A number of these computer programs have made novel discoveries. For example, Valdes-Perez ( 1994 ) has built systems for discoveries in chemistry, and Fajtlowicz has done this in mathematics (Erdos, Fajtlowicz, & Staton, 1991 ).

These advances in the fields of computer discovery have led to new fields, conferences, journals, and even departments that specialize in the development of programs devised to search large databases in the hope of making new scientific discoveries (Langley, 2000 , 2002 ). This process is commonly known as “data mining.” This approach has only proved viable relatively recently, due to advances in computer technology. Biswal et al. ( 2010 ), Mitchell ( 2009 ), and Yang ( 2009 ) provide recent reviews of data mining in different scientific fields. Data mining is at the core of drug discovery, our understanding of the human genome, and our understanding of the universe for a number of reasons. First, vast databases concerning drug actions, biological processes, the genome, the proteome, and the universe itself now exist. Second, the development of high throughput data-mining algorithms makes it possible to search for new drug targets, novel biological mechanisms, and new astronomical phenomena in relatively short periods of time. Research programs that took decades, such as the development of penicillin, can now be done in days (Yang, 2009 ).

Another recent shift in the use of computers in scientific discovery has been to have both computers and people make discoveries together, rather than expecting that computers make an entire scientific discovery. Now instead of using computers to mimic the entire scientific discovery process as used by humans, computers can use powerful algorithms that search for patterns on large databases and provide the patterns to humans who can then use the output of these computers to make discoveries, ranging from the human genome to the structure of the universe. However, there are some robots such as ADAM, developed by King ( 2011 ), that can actually perform the entire scientific process, from the generation of hypotheses, to the conduct of experiments and the interpretation of results, with little human intervention. The ongoing development of scientific robots by some scientists (King et al., 2009 ) thus continues the tradition started by Herbert Simon in the 1960s. However, many of the controversies as to whether the robot is a “real scientist” or not continue to the present (Evans & Rzhetsky, 2010 , Gianfelici, 2010 ; Haufe, Elliott, Burian, & O' Malley, 2010 ; O'Malley 2011 ).

Scientific Thinking and Science Education

Accounts of the nature of science and research on scientific thinking have had profound effects on science education along many levels, particularly in recent years. Science education from the 1900s until the 1970s was primarily concerned with teaching students both the content of science (such as Newton's laws of motion) or the methods that scientists need to use in their research (such as using experimental and control groups). Beginning in the 1980s, a number of reports (e.g., American Association for the Advancement of Science, 1993; National Commission on Excellence in Education, 1983; Rutherford & Ahlgren, 1991 ) stressed the need for teaching scientific thinking skills rather than just methods and content. The addition of scientific thinking skills to the science curriculum from kindergarten through adulthood was a major shift in focus. Many of the particular scientific thinking skills that have been emphasized are skills covered in previous sections of this chapter, such as teaching deductive and inductive thinking strategies. However, rather than focusing on one particular skill, such as induction, researchers in education have focused on how the different components of scientific thinking are put together in science. Furthermore, science educators have focused upon situations where science is conducted collaboratively, rather than being the product of one person thinking alone. These changes in science education parallel changes in methodologies used to investigate science, such as analyzing the ways that scientists think and reason in their laboratories.

By looking at science as a complex multilayered and group activity, many researchers in science education have adopted a constructivist approach. This approach sees learning as an active rather than a passive process, and it suggests that students learn through constructing their scientific knowledge. We will first describe a few examples of the constructivist approach to science education. Following that, we will address several lines of work that challenge some of the assumptions of the constructivist approach to science education.

Often the goal of constructivist science education is to produce conceptual change through guided instruction where the teacher or professor acts as a guide to discovery, rather than the keeper of all the facts. One recent and influential approach to science education is the inquiry-based learning approach. Inquiry-based learning focuses on posing a problem or a puzzling event to students and asking them to propose a hypothesis that could explain the event. Next, the student is asked to collect data that test the hypothesis, make conclusions, and then reflect upon both the original problem and the thought processes that they used to solve the problem. Often students use computers that aid in their construction of new knowledge. The computers allow students to learn many of the different components of scientific thinking. For example, Reiser and his colleagues have developed a learning environment for biology, where students are encouraged to develop hypotheses in groups, codify the hypotheses, and search databases to test these hypotheses (Reiser et al., 2001 ).

One of the myths of science is the lone scientist suddenly shouting “Eureka, I have made a discovery!” Instead, in vivo studies of scientists (e.g., Dunbar, 1995 , 2002 ), historical analyses of scientific discoveries (Nersessian, 1999 ), and studies of children learning science at museums have all pointed to collaborative scientific discovery mechanisms as being one of the driving forces of science (Atkins et al., 2009 ; Azmitia & Crowley, 2001 ). What happens during collaborative scientific thinking is that there is usually a triggering event, such as an unexpected result or situation that a student does not understand. This results in other members of the group adding new information to the person's representation of knowledge, often adding new inductions and deductions that both challenge and transform the reasoner's old representations of knowledge (Chi & Roscoe, 2002 ; Dunbar 1998 ). Social mechanisms play a key component in fostering changes in concepts that have been ignored in traditional cognitive research but are crucial for both science and science education. In science education there has been a shift to collaborative learning, particularly at the elementary level; however, in university education, the emphasis is still on the individual scientist. As many domains of science now involve collaborations across scientific disciplines, we expect the explicit teaching of heuristics for collaborative science to increase.

What is the best way to teach and learn science? Surprisingly, the answer to this question has been difficult to uncover. For example, toward the end of the last century, influenced by several thinkers who advocated a constructivist approach to learning, ranging from Piaget (Beilin, 1994 ) to Papert ( 1980 ), many schools answered this question by adopting a philosophy dubbed “discovery learning.” Although a clear operational definition of this approach has yet to be articulated, the general idea is that children are expected to learn science by reconstructing the processes of scientific discovery—in a range of areas from computer programming to chemistry to mathematics. The premise is that letting students discover principles on their own, set their own goals, and collaboratively explore the natural world produces deeper knowledge that transfers widely.

The research literature on science education is far from consistent in its use of terminology. However, our reading suggests that “discovery learning” differs from “inquiry-based learning” in that few, if any, guidelines are given to students in discovery learning contexts, whereas in inquiry learning, students are given hypotheses and specific goals to achieve (see the second paragraph of this section for a definition of inquiry-based learning). Even though thousands of schools have adopted discovery learning as an alternative to more didactic approaches to teaching and learning, the evidence showing that it is more effective than traditional, direct, teacher-controlled instructional approaches is mixed, at best (Lorch et al., 2010 ; Minner, Levy, & Century, 2010 ). In several cases where the distinctions between direct instruction and more open-ended constructivist instruction have been clearly articulated, implemented, and assessed, direct instruction has proven to be superior to the alternatives (Chen & Klahr, 1999 ; Toth, Klahr, & Chen, 2000 ). For example, in a study of third- and fourth-grade children learning about experimental design, Klahr and Nigam ( 2004 ) found that many more children learned from direct instruction than from discovery learning. Furthermore, they found that among the few children who did manage to learn from a discovery method, there was no better performance on a far transfer test of scientific reasoning than that observed for the many children who learned from direct instruction.

The idea of children learning most of their science through a process of self-directed discovery has some romantic appeal, and it may accurately describe the personal experience of a handful of world-class scientists. However, the claim has generated some contentious disagreements (Kirschner, Sweller, & Clark, 2006 ; Klahr, 2010 ; Taber 2009 ; Tobias & Duffy, 2009 ), and the jury remains out on the extent to which most children can learn science that way.

Conclusions and Future Directions

The field of scientific thinking is now a thriving area of research with strong underpinnings in cognitive psychology and cognitive science. In recent years, a new professional society has been formed that aims to facilitate this integrative and interdisciplinary approach to the psychology of science, with its own journal and regular professional meetings. 1 Clearly the relations between these different aspects of scientific thinking need to be combined in order to produce a truly comprehensive picture of the scientific mind.

While much is known about certain aspects of scientific thinking, much more remains to be discovered. In particular, there has been little contact between cognitive, neuroscience, social, personality, and motivational accounts of scientific thinking. Research in thinking and reasoning has been expanded to use the methods and theories of cognitive neuroscience (see Morrison & Knowlton, Chapter 6 ). A similar approach can be taken in exploring scientific thinking (see Dunbar et al., 2007 ). There are two main reasons for taking a neuroscience approach to scientific thinking. First, functional neuroimaging allows the researcher to look at the entire human brain, making it possible to see the many different sites that are involved in scientific thinking and gain a more complete understanding of the entire range of mechanisms involved in this type of thought. Second, these brain-imaging approaches allow researchers to address fundamental questions in research on scientific thinking, such as the extent to which ordinary thinking in nonscientific contexts and scientific thinking recruit similar versus disparate neural structures of the brain.

Dunbar ( 2009 ) has used some novel methods to explore Simon's assertion, cited at the beginning of this chapter, that scientific thinking uses the same cognitive mechanisms that all human beings possess (rather than being an entirely different type of thinking) but combines them in ways that are specific to a particular aspect of science or a specific discipline of science. For example, Fugelsang and Dunbar ( 2009 ) compared causal reasoning when two colliding circular objects were labeled balls or labeled subatomic particles. They obtained different brain activation patterns depending on whether the stimuli were labeled balls or subatomic particles. In another series of experiments, Dunbar and colleagues used functional magnetic resonance imaging (fMRI) to study patterns of activation in the brains of students who have and who have not undergone conceptual change in physics. For example, Fugelsang and Dunbar ( 2005 ) and Dunbar et al. ( 2007 ) have found differences in the activation of specific brain sites (such as the anterior cingulate) for students when they encounter evidence that is inconsistent with their current conceptual understandings. These initial cognitive neuroscience investigations have the potential to reveal the ways that knowledge is organized in the scientific brain and provide detailed accounts of the nature of the representation of scientific knowledge. Petitto and Dunbar ( 2004 ) proposed the term “educational neuroscience” for the integration of research on education, including science education, with research on neuroscience. However, see Fitzpatrick (in press) for a very different perspective on whether neuroscience approaches are relevant to education. Clearly, research on the scientific brain is just beginning. We as scientists are beginning to get a reasonable grasp of the inner workings of the subcomponents of the scientific mind (i.e., problem solving, analogy, induction). However, great advances remain to be made concerning how these processes interact so that scientific discoveries can be made. Future research will focus on both the collaborative aspects of scientific thinking and the neural underpinnings of the scientific mind.

The International Society for the Psychology of Science and Technology (ISPST). Available at http://www.ispstonline.org/

Ahn, W., Kalish, C. W., Medin, D. L., & Gelman, S. A. ( 1995 ). The role of covariation versus mechanism information in causal attribution.   Cognition , 54 , 299–352.

American Association for the Advancement of Science. ( 1993 ). Benchmarks for scientific literacy . New York: Oxford University Press.

Google Scholar

Google Preview

Atkins, L. J., Velez, L., Goudy, D., & Dunbar, K. N. ( 2009 ). The unintended effects of interactive objects and labels in the science museum.   Science Education , 54 , 161–184.

Azmitia, M. A., & Crowley, K. ( 2001 ). The rhythms of scientific thinking: A study of collaboration in an earthquake microworld. In K. Crowley, C. Schunn, & T. Okada (Eds.), Designing for science: Implications from everyday, classroom, and professional settings (pp. 45–72). Mahwah, NJ: Erlbaum.

Bacon, F. ( 1620 /1854). Novum organum (B. Monatgue, Trans.). Philadelphia, P A: Parry & McMillan.

Baillargeon, R. ( 2004 ). Infants' reasoning about hidden objects: Evidence for event-general and event-specific expectations (article with peer commentaries and response, listed below).   Developmental Science , 54 , 391–424.

Baker, L. M., & Dunbar, K. ( 2000 ). Experimental design heuristics for scientific discovery: The use of baseline and known controls.   International Journal of Human Computer Studies , 54 , 335–349.

Beilin, H. ( 1994 ). Jean Piaget's enduring contribution to developmental psychology. In R. D. Parke, P. A. Ornstein, J. J. Rieser, & C. Zahn-Waxler (Eds.), A century of developmental psychology (pp. 257–290). Washington, DC US: American Psychological Association.

Biswal, B. B., Mennes, M., Zuo, X.-N., Gohel, S., Kelly, C., Smith, S.M., et al. ( 2010 ). Toward discovery science of human brain function.   Proceedings of the National Academy of Sciences of the United States of America , 107, 4734–4739.

Brewer, W. F., & Samarapungavan, A. ( 1991 ). Children's theories vs. scientific theories: Differences in reasoning or differences in knowledge? In R. R. Hoffman & D. S. Palermo (Eds.), Cognition and the symbolic processes: Applied and ecological perspectives (pp. 209–232). Hillsdale, NJ: Erlbaum.

Bruner, J. S., Goodnow, J. J., & Austin, G. A. ( 1956 ). A study of thinking . New York: NY Science Editions.

Carey, S. ( 1985 ). Conceptual change in childhood . Cambridge, MA: MIT Press.

Carruthers, P., Stich, S., & Siegal, M. ( 2002 ). The cognitive basis of science . New York: Cambridge University Press.

Chi, M. ( 1992 ). Conceptual change within and across ontological categories: Examples from learning and discovery in science. In R. Giere (Ed.), Cognitive models of science (pp. 129–186). Minneapolis: University of Minnesota Press.

Chi, M. T. H., & Roscoe, R. D. ( 2002 ). The processes and challenges of conceptual change. In M. Limon & L. Mason (Eds.), Reconsidering conceptual change: Issues in theory and practice (pp 3–27). Amsterdam, Netherlands: Kluwer Academic Publishers.

Chen, Z., & Klahr, D. ( 1999 ). All other things being equal: Children's acquisition of the control of variables strategy.   Child Development , 54 (5), 1098–1120.

Clement, J. ( 1982 ). Students' preconceptions in introductory mechanics.   American Journal of Physics , 54 , 66–71.

Cohen, L. B., & Cashon, C. H. ( 2006 ). Infant cognition. In W. Damon & R. M. Lerner (Series Eds.) & D. Kuhn & R. S. Siegler (Vol. Eds.), Handbook of child psychology. Vol. 2: Cognition, perception, and language (6th ed., pp. 214–251). New York: Wiley.

National Commission on Excellence in Education. ( 1983 ). A nation at risk: The imperative for educational reform . Washington, DC: US Department of Education.

Crick, F. H. C. ( 1988 ). What mad pursuit: A personal view of science . New York: Basic Books.

Darden, L. ( 2002 ). Strategies for discovering mechanisms: Schema instantiation, modular subassembly, forward chaining/backtracking.   Philosophy of Science , 69, S354–S365.

Davenport, J. L., Yaron, D., Klahr, D., & Koedinger, K. ( 2008 ). Development of conceptual understanding and problem solving expertise in chemistry. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 751–756). Austin, TX: Cognitive Science Society.

diSessa, A. A. ( 2004 ). Contextuality and coordination in conceptual change. In E. Redish & M. Vicentini (Eds.), Proceedings of the International School of Physics “Enrico Fermi:” Research on physics education (pp. 137–156). Amsterdam, Netherlands: ISO Press/Italian Physics Society

Dunbar, K. ( 1995 ). How scientists really reason: Scientific reasoning in real-world laboratories. In R. J. Sternberg, & J. Davidson (Eds.), Mechanisms of insight (pp. 365–395). Cambridge, MA: MIT press.

Dunbar, K. ( 1997 ). How scientists think: Online creativity and conceptual change in science. In T. B. Ward, S. M. Smith, & S. Vaid (Eds.), Conceptual structures and processes: Emergence, discovery and change (pp. 461–494). Washington, DC: American Psychological Association.

Dunbar, K. ( 1998 ). Problem solving. In W. Bechtel & G. Graham (Eds.), A companion to cognitive science (pp. 289–298). London: Blackwell

Dunbar, K. ( 1999 ). The scientist InVivo : How scientists think and reason in the laboratory. In L. Magnani, N. Nersessian, & P. Thagard (Eds.), Model-based reasoning in scientific discovery (pp. 85–100). New York: Plenum.

Dunbar, K. ( 2001 ). The analogical paradox: Why analogy is so easy in naturalistic settings, yet so difficult in the psychology laboratory. In D. Gentner, K. J. Holyoak, & B. Kokinov Analogy: Perspectives from cognitive science (pp. 313–334). Cambridge, MA: MIT press.

Dunbar, K. ( 2002 ). Science as category: Implications of InVivo science for theories of cognitive development, scientific discovery, and the nature of science. In P. Caruthers, S. Stich, & M. Siegel (Eds.) Cognitive models of science (pp. 154–170). New York: Cambridge University Press.

Dunbar, K. ( 2009 ). The biology of physics: What the brain reveals about our physical understanding of the world. In M. Sabella, C. Henderson, & C. Singh. (Eds.), Proceedings of the Physics Education Research Conference (pp. 15–18). Melville, NY: American Institute of Physics.

Dunbar, K., & Fugelsang, J. ( 2004 ). Causal thinking in science: How scientists and students interpret the unexpected. In M. E. Gorman, A. Kincannon, D. Gooding, & R. D. Tweney (Eds.), New directions in scientific and technical thinking (pp. 57–59). Mahway, NJ: Erlbaum.

Dunbar, K., Fugelsang, J., & Stein, C. ( 2007 ). Do naïve theories ever go away? In M. Lovett & P. Shah (Eds.), Thinking with Data: 33 rd Carnegie Symposium on Cognition (pp. 193–206). Mahwah, NJ: Erlbaum.

Dunbar, K., & Sussman, D. ( 1995 ). Toward a cognitive account of frontal lobe function: Simulating frontal lobe deficits in normal subjects.   Annals of the New York Academy of Sciences , 54 , 289–304.

Duschl, R. A., Schweingruber, H. A., & Shouse, A. W. (Eds.). ( 2007 ). Taking science to school: Learning and teaching science in grades K-8. Washington, DC: National Academies Press.

Einstein, A. ( 1950 ). Out of my later years . New York: Philosophical Library

Erdos, P., Fajtlowicz, S., & Staton, W. ( 1991 ). Degree sequences in the triangle-free graphs,   Discrete Mathematics , 54 (91), 85–88.

Evans, J., & Rzhetsky, A. ( 2010 ). Machine science.   Science , 54 , 399–400.

Fay, A., & Klahr, D. ( 1996 ). Knowing about guessing and guessing about knowing: Preschoolers' understanding of indeterminacy.   Child Development , 54 , 689–716.

Fischler, H., & Lichtfeldt, M. ( 1992 ). Modern physics and students conceptions.   International Journal of Science Education , 54 , 181–190.

Fitzpatrick, S. M. (in press). Functional brain imaging: Neuro-turn or wrong turn? In M. M., Littlefield & J.M., Johnson (Eds.), The neuroscientific turn: Transdisciplinarity in the age of the brain. Ann Arbor: University of Michigan Press.

Fox-Keller, E. ( 1985 ). Reflections on gender and science . New Haven, CT: Yale University Press.

Fugelsang, J., & Dunbar, K. ( 2005 ). Brain-based mechanisms underlying complex causal thinking.   Neuropsychologia , 54 , 1204–1213.

Fugelsang, J., & Dunbar, K. ( 2009 ). Brain-based mechanisms underlying causal reasoning. In E. Kraft (Ed.), Neural correlates of thinking (pp. 269–279). Berlin, Germany: Springer

Fugelsang, J., Stein, C., Green, A., & Dunbar, K. ( 2004 ). Theory and data interactions of the scientific mind: Evidence from the molecular and the cognitive laboratory.   Canadian Journal of Experimental Psychology , 54 , 132–141

Galilei, G. ( 1638 /1991). Dialogues concerning two new sciences (A. de Salvio & H. Crew, Trans.). Amherst, NY: Prometheus Books.

Galison, P. ( 2003 ). Einstein's clocks, Poincaré's maps: Empires of time . New York: W. W. Norton.

Gelman, R., & Baillargeon, R. ( 1983 ). A review of Piagetian concepts. In P. H. Mussen (Series Ed.) & J. H. Flavell & E. M. Markman (Vol. Eds.), Handbook of child psychology (4th ed., Vol. 3, pp. 167–230). New York: Wiley.

Gelman, S. A., & Kalish, C. W. ( 2006 ). Conceptual development. In D. Kuhn & R. Siegler (Eds.), Handbook of child psychology. Vol. 2: Cognition, perception and language (pp. 687–733). New York: Wiley.

Gelman, S., & Wellman, H. ( 1991 ). Insides and essences.   Cognition , 54 , 214–244.

Gentner, D. ( 2010 ). Bootstrapping the mind: Analogical processes and symbol systems.   Cognitive Science , 54 , 752–775.

Gentner, D., Brem, S., Ferguson, R. W., Markman, A. B., Levidow, B. B., Wolff, P., & Forbus, K. D. ( 1997 ). Analogical reasoning and conceptual change: A case study of Johannes Kepler.   The Journal of the Learning Sciences , 54 (1), 3–40.

Gentner, D., Holyoak, K. J., & Kokinov, B. ( 2001 ). The analogical mind: Perspectives from cognitive science . Cambridge, MA: MIT Press.

Gentner, D., & Jeziorski, M. ( 1993 ). The shift from metaphor to analogy in western science. In A. Ortony (Ed.), Metaphor and thought (2nd ed., pp. 447–480). Cambridge, England: Cambridge University Press.

Gianfelici, F. ( 2010 ). Machine science: Truly machine-aided science.   Science , 54 , 317–319.

Giere, R. ( 1993 ). Cognitive models of science . Minneapolis: University of Minnesota Press.

Gopnik, A. N., Meltzoff, A. N., & Kuhl, P. K. ( 1999 ). The scientist in the crib: Minds, brains and how children learn . New York: Harper Collins

Gorman, M. E. ( 1989 ). Error, falsification and scientific inference: An experimental investigation.   Quarterly Journal of Experimental Psychology: Human Experimental Psychology , 41A , 385–412

Gorman, M. E., Kincannon, A., Gooding, D., & Tweney, R. D. ( 2004 ). New directions in scientific and technical thinking . Mahwah, NJ: Erlbaum.

Gupta, A., Hammer, D., & Redish, E. F. ( 2010 ). The case for dynamic models of learners' ontologies in physics.   Journal of the Learning Sciences , 54 (3), 285–321.

Haufe, C., Elliott, K. C., Burian, R., & O'Malley, M. A. ( 2010 ). Machine science: What's missing.   Science , 54 , 318–320.

Hecht, E. ( 2011 ). On defining mass.   The Physics Teacher , 54 , 40–43.

Heit, E. ( 2000 ). Properties of inductive reasoning.   Psychonomic Bulletin and Review , 54 , 569–592.

Holyoak, K. J., & Thagard, P. ( 1995 ). Mental leaps . Cambridge, MA: MIT Press.

Karmiloff-Smith, A. ( 1988 ) The child is a theoretician, not an inductivist.   Mind and Language , 54 , 183–195.

Keil, F. C. ( 1999 ). Conceptual change. In R. Wilson & F. Keil (Eds.), The MIT encyclopedia of cognitive science . (pp. 179–182) Cambridge, MA: MIT press.

Kern, L. H., Mirels, H. L., & Hinshaw, V. G. ( 1983 ). Scientists' understanding of propositional logic: An experimental investigation.   Social Studies of Science , 54 , 131–146.

King, R. D. ( 2011 ). Rise of the robo scientists.   Scientific American , 54 (1), 73–77.

King, R. D., Rowland, J., Oliver, S. G., Young, M., Aubrey, W., Byrne, E., et al. ( 2009 ). The automation of science.   Science , 54 , 85–89.

Kirschner, P. A., Sweller, J., & Clark, R. ( 2006 ) Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching.   Educational Psychologist , 54 , 75–86

Klahr, D. ( 2000 ). Exploring science: The cognition and development of discovery processes . Cambridge, MA: MIT Press.

Klahr, D. ( 2010 ). Coming up for air: But is it oxygen or phlogiston? A response to Taber's review of constructivist instruction: Success or failure?   Education Review , 54 (13), 1–6.

Klahr, D., & Dunbar, K. ( 1988 ). Dual space search during scientific reasoning.   Cognitive Science , 54 , 1–48.

Klahr, D., & Nigam, M. ( 2004 ). The equivalence of learning paths in early science instruction: effects of direct instruction and discovery learning.   Psychological Science , 54 (10), 661–667.

Klahr, D. & Masnick, A. M. ( 2002 ). Explaining, but not discovering, abduction. Review of L. Magnani (2001) abduction, reason, and science: Processes of discovery and explanation.   Contemporary Psychology , 47, 740–741.

Klahr, D., & Simon, H. ( 1999 ). Studies of scientific discovery: Complementary approaches and convergent findings.   Psychological Bulletin , 54 , 524–543.

Klayman, J., & Ha, Y. ( 1987 ). Confirmation, disconfirmation, and information in hypothesis testing.   Psychological Review , 54 , 211–228.

Kozhevnikov, M., & Hegarty, M. ( 2001 ). Impetus beliefs as default heuristic: Dissociation between explicit and implicit knowledge about motion.   Psychonomic Bulletin and Review , 54 , 439–453.

Kuhn, T. ( 1962 ). The structure of scientific revolutions . Chicago, IL: University of Chicago Press.

Kuhn, D., Amsel, E., & O'Laughlin, M. ( 1988 ). The development of scientific thinking skills . Orlando, FL: Academic Press.

Kulkarni, D., & Simon, H. A. ( 1988 ). The processes of scientific discovery: The strategy of experimentation.   Cognitive Science , 54 , 139–176.

Langley, P. ( 2000 ). Computational support of scientific discovery.   International Journal of Human-Computer Studies , 54 , 393–410.

Langley, P. ( 2002 ). Lessons for the computational discovery of scientific knowledge. In Proceedings of the First International Workshop on Data Mining Lessons Learned (pp. 9–12).

Langley, P., Simon, H. A., Bradshaw, G. L., & Zytkow, J. M. ( 1987 ). Scientific discovery: Computational explorations of the creative processes . Cambridge, MA: MIT Press.

Lorch, R. F., Jr., Lorch, E. P., Calderhead, W. J., Dunlap, E. E., Hodell, E. C., & Freer, B. D. ( 2010 ). Learning the control of variables strategy in higher and lower achieving classrooms: Contributions of explicit instruction and experimentation.   Journal of Educational Psychology , 54 (1), 90–101.

Magnani, L., Carnielli, W., & Pizzi, C., (Eds.) ( 2010 ). Model-based reasoning in science and technology: Abduction, logic,and computational discovery. Series Studies in Computational Intelligence (Vol. 314). Heidelberg/Berlin: Springer.

Mandler, J.M. ( 2004 ). The foundations of mind: Origins of conceptual thought . Oxford, England: Oxford University Press.

Macpherson, R., & Stanovich, K. E. ( 2007 ). Cognitive ability, thinking dispositions, and instructional set as predictors of critical thinking.   Learning and Individual Differences , 54 , 115–127.

McCloskey, M., Caramazza, A., & Green, B. ( 1980 ). Curvilinear motion in the absence of external forces: Naive beliefs about the motion of objects.   Science , 54 , 1139–1141.

McDermott, L. C., & Redish, L. ( 1999 ). Research letter on physics education research.   American Journal of Psychics , 54 , 755.

Mestre, J. P. ( 1991 ). Learning and instruction in pre-college physical science.   Physics Today , 54 , 56–62.

Metz, K. E. ( 1995 ). Reassessment of developmental constraints on children's science instruction.   Review of Educational Research , 54 (2), 93–127.

Minner, D. D., Levy, A. J., & Century, J. ( 2010 ). Inquiry-based science instruction—what is it and does it matter? Results from a research synthesis years 1984 to 2002.   Journal of Research in Science Teaching , 54 (4), 474–496.

Mitchell, T. M. ( 2009 ). Mining our reality.   Science , 54 , 1644–1645.

Mitroff, I. ( 1974 ). The subjective side of science . Amsterdam, Netherlands: Elsevier.

Munakata, Y., Casey, B. J., & Diamond, A. ( 2004 ). Developmental cognitive neuroscience: Progress and potential.   Trends in Cognitive Sciences , 54 , 122–128.

Mynatt, C. R., Doherty, M. E., & Tweney, R. D. ( 1977 ) Confirmation bias in a simulated research environment: An experimental study of scientific inference.   Quarterly Journal of Experimental Psychology , 54 , 89–95.

Nersessian, N. ( 1998 ). Conceptual change. In W. Bechtel, & G. Graham (Eds.), A companion to cognitive science (pp. 157–166). London, England: Blackwell.

Nersessian, N. ( 1999 ). Models, mental models, and representations: Model-based reasoning in conceptual change. In L. Magnani, N. Nersessian, & P. Thagard (Eds.), Model-based reasoning in scientific discovery (pp. 5–22). New York: Plenum.

Nersessian, N. J. ( 2002 ). The cognitive basis of model-based reasoning in science In. P. Carruthers, S. Stich, & M. Siegal (Eds.), The cognitive basis of science (pp. 133–152). New York: Cambridge University Press.

Nersessian, N. J. ( 2008 ) Creating scientific concepts . Cambridge, MA: MIT Press.

O' Malley, M. A. ( 2011 ). Exploration, iterativity and kludging in synthetic biology.   Comptes Rendus Chimie , 54 (4), 406–412 .

Papert, S. ( 1980 ) Mindstorms: Children computers and powerful ideas. New York: Basic Books.

Penner, D. E., & Klahr, D. ( 1996 ). When to trust the data: Further investigations of system error in a scientific reasoning task.   Memory and Cognition , 54 (5), 655–668.

Petitto, L. A., & Dunbar, K. ( 2004 ). New findings from educational neuroscience on bilingual brains, scientific brains, and the educated mind. In K. Fischer & T. Katzir (Eds.), Building usable knowledge in mind, brain, and education Cambridge, England: Cambridge University Press.

Popper, K. R. ( 1959 ). The logic of scientific discovery . London, England: Hutchinson.

Qin, Y., & Simon, H.A. ( 1990 ). Laboratory replication of scientific discovery processes.   Cognitive Science , 54 , 281–312.

Reiser, B. J., Tabak, I., Sandoval, W. A., Smith, B., Steinmuller, F., & Leone, T. J., ( 2001 ). BGuILE: Stategic and conceptual scaffolds for scientific inquiry in biology classrooms. In S. M. Carver & D. Klahr (Eds.), Cognition and instruction: Twenty-five years of progress (pp. 263–306). Mahwah, NJ: Erlbaum

Riordan, M., Rowson, P. C., & Wu, S. L. ( 2001 ). The search for the higgs boson.   Science , 54 , 259–260.

Rutherford, F. J., & Ahlgren, A. ( 1991 ). Science for all Americans. New York: Oxford University Press.

Samarapungavan, A. ( 1992 ). Children's judgments in theory choice tasks: Scientifc rationality in childhood.   Cognition , 54 , 1–32.

Schauble, L., & Glaser, R. ( 1990 ). Scientific thinking in children and adults. In D. Kuhn (Ed.), Developmental perspectives on teaching and learning thinking skills. Contributions to Human Development , (Vol. 21, pp. 9–26). Basel, Switzerland: Karger.

Schunn, C. D., & Klahr, D. ( 1995 ). A 4-space model of scientific discovery. In Proceedings of the 17th Annual Conference of the Cognitive Science Society (pp. 106–111). Mahwah, NJ: Erlbaum.

Schunn, C. D., & Klahr, D. ( 1996 ). The problem of problem spaces: When and how to go beyond a 2-space model of scientific discovery. Part of symposium on Building a theory of problem solving and scientific discovery: How big is N in N-space search? In Proceedings of the 18th Annual Conference of the Cognitive Science Society (pp. 25–26). Mahwah, NJ: Erlbaum.

Shrager, J., & Langley, P. ( 1990 ). Computational models of scientific discovery and theory formation . San Mateo, CA: Morgan Kaufmann.

Siegler, R. S., & Liebert, R. M. ( 1975 ). Acquisition of formal scientific reasoning by 10- and 13-year-olds: Designing a factorial experiment.   Developmental Psychology , 54 , 401–412.

Simon, H. A. ( 1977 ). Models of discovery . Dordrecht, Netherlands: D. Reidel Publishing.

Simon, H. A., Langley, P., & Bradshaw, G. L. ( 1981 ). Scientific discovery as problem solving.   Synthese , 54 , 1–27.

Simon, H. A., & Lea, G. ( 1974 ). Problem solving and rule induction. In H. Simon (Ed.), Models of thought (pp. 329–346). New Haven, CT: Yale University Press.

Smith, E. E., Shafir, E., & Osherson, D. ( 1993 ). Similarity, plausibility, and judgments of probability.   Cognition. Special Issue: Reasoning and decision making , 54 , 67–96.

Sodian, B., Zaitchik, D., & Carey, S. ( 1991 ). Young children's differentiation of hypothetical beliefs from evidence.   Child Development , 54 , 753–766.

Taber, K. S. ( 2009 ). Constructivism and the crisis in U.S. science education: An essay review.   Education Review , 54 (12), 1–26.

Thagard, P. ( 1992 ). Conceptual revolutions . Cambridge, MA: MIT Press.

Thagard, P. ( 1999 ). How scientists explain disease . Princeton, NJ: Princeton University Press.

Thagard, P., & Croft, D. ( 1999 ). Scientific discovery and technological innovation: Ulcers, dinosaur extinction, and the programming language Java. In L. Magnani, N. Nersessian, & P. Thagard (Eds.), Model-based reasoning in scientific discovery (pp. 125–138). New York: Plenum.

Tobias, S., & Duffy, T. M. (Eds.). ( 2009 ). Constructivist instruction: Success or failure? New York: Routledge.

Toth, E. E., Klahr, D., & Chen, Z. ( 2000 ) Bridging research and practice: A cognitively-based classroom intervention for teaching experimentation skills to elementary school children.   Cognition and Instruction , 54 (4), 423–459.

Tweney, R. D. ( 1989 ). A framework for the cognitive psychology of science. In B. Gholson, A. Houts, R. A. Neimeyer, & W. Shadish (Eds.), Psychology of science: Contributions to metascience (pp. 342–366). Cambridge, England: Cambridge University Press.

Tweney, R. D., Doherty, M. E., & Mynatt, C. R. ( 1981 ). On scientific thinking . New York: Columbia University Press.

Valdes-Perez, R. E. ( 1994 ). Conjecturing hidden entities via simplicity and conservation laws: Machine discovery in chemistry.   Artificial Intelligence , 54 (2), 247–280.

Von Hofsten, C. ( 1980 ). Predictive reaching for moving objects by human infants.   Journal of Experimental Child Psychology , 54 , 369–382.

Von Hofsten, C., Feng, Q., & Spelke, E. S. ( 2000 ). Object representation and predictive action in infancy.   Developmental Science , 54 , 193–205.

Vosnaidou, S. (Ed.). ( 2008 ). International handbook of research on conceptual change . New York: Taylor & Francis.

Vosniadou, S., & Brewer, W. F. ( 1992 ). Mental models of the earth: A study of conceptual change in childhood.   Cognitive Psychology , 54 , 535–585.

Wason, P. C. ( 1968 ). Reasoning about a rule.   Quarterly Journal of Experimental Psychology , 54 , 273–281.

Wertheimer, M. ( 1945 ). Productive thinking . New York: Harper.

Yang, Y. ( 2009 ). Target discovery from data mining approaches.   Drug Discovery Today , 54 (3–4), 147–154.

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

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

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

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

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

Thinking critically on critical thinking: why scientists’ skills need to spread

Lecturer in Psychology, University of Tasmania

Disclosure statement

Rachel Grieve does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

University of Tasmania provides funding as a member of The Conversation AU.

View all partners

MATHS AND SCIENCE EDUCATION: We’ve asked our authors about the state of maths and science education in Australia and its future direction. Today, Rachel Grieve discusses why we need to spread science-specific skills into the wider curriculum.

When we think of science and maths, stereotypical visions of lab coats, test-tubes, and formulae often spring to mind.

But more important than these stereotypes are the methods that underpin the work scientists do – namely generating and systematically testing hypotheses. A key part of this is critical thinking.

It’s a skill that often feels in short supply these days, but you don’t necessarily need to study science or maths in order gain it. It’s time to take critical thinking out of the realm of maths and science and broaden it into students’ general education.

What is critical thinking?

Critical thinking is a reflective and analytical style of thinking, with its basis in logic, rationality, and synthesis. It means delving deeper and asking questions like: why is that so? Where is the evidence? How good is that evidence? Is this a good argument? Is it biased? Is it verifiable? What are the alternative explanations?

Critical thinking moves us beyond mere description and into the realms of scientific inference and reasoning. This is what enables discoveries to be made and innovations to be fostered.

For many scientists, critical thinking becomes (seemingly) intuitive, but like any skill set, critical thinking needs to be taught and cultivated. Unfortunately, educators are unable to deposit this information directly into their students’ heads. While the theory of critical thinking can be taught, critical thinking itself needs to be experienced first-hand.

So what does this mean for educators trying to incorporate critical thinking within their curricula? We can teach students the theoretical elements of critical thinking. Take for example working through [statistical problems](http://wdeneys.org/data/COGNIT_1695.pdf](http://wdeneys.org/data/COGNIT_1695.pdf) like this one:

In a 1,000-person study, four people said their favourite series was Star Trek and 996 said Days of Our Lives. Jeremy is a randomly chosen participant in this study, is 26, and is doing graduate studies in physics. He stays at home most of the time and likes to play videogames. What is most likely? a. Jeremy’s favourite series is Star Trek b. Jeremy’s favourite series is Days of Our Lives

Some critical thought applied to this problem allows us to know that Jeremy is most likely to prefer Days of Our Lives.

Can you teach it?

It’s well established that statistical training is associated with improved decision-making. But the idea of “teaching” critical thinking is itself an oxymoron: critical thinking can really only be learned through practice. Thus, it is not surprising that student engagement with the critical thinking process itself is what pays the dividends for students.

As such, educators try to connect students with the subject matter outside the lecture theatre or classroom. For example, problem based learning is now widely used in the health sciences, whereby students must figure out the key issues related to a case and direct their own learning to solve that problem. Problem based learning has clear parallels with real life practice for health professionals.

Critical thinking goes beyond what might be on the final exam and life-long learning becomes the key. This is a good thing, as practice helps to improve our ability to think critically over time .

Just for scientists?

For those engaging with science, learning the skills needed to be a critical consumer of information is invaluable. But should these skills remain in the domain of scientists? Clearly not: for those engaging with life, being a critical consumer of information is also invaluable, allowing informed judgement.

Being able to actively consider and evaluate information, identify biases, examine the logic of arguments, and tolerate ambiguity until the evidence is in would allow many people from all backgrounds to make better decisions. While these decisions can be trivial (does that miracle anti-wrinkle cream really do what it claims?), in many cases, reasoning and decision-making can have a substantial impact, with some decisions have life-altering effects. A timely case-in-point is immunisation.

Pushing critical thinking from the realms of science and maths into the broader curriculum may lead to far-reaching outcomes. With increasing access to information on the internet, giving individuals the skills to critically think about that information may have widespread benefit, both personally and socially.

The value of science education might not always be in the facts, but in the thinking.

This is the sixth part of our series Maths and Science Education .

• Maths and science education

Associate Professor, Occupational Therapy

Operations Manager

Senior Lecturer, Occupational Therapy

Lecturer, Occupational Therapy 

Events and Communications Coordinator

• MISSION / VISION
• DIVERSITY STATEMENT
• CAREER OPPORTUNITIES
• Kide Science
• STEMscopes Science
• Collaborate Science
• STEMscopes Math
• Math Nation
• STEMscopes Coding
• Mastery Coding
• DIVE-in Engineering
• STEMscopes Streaming
• Tuva Data Literacy
• NATIONAL INSTITUTE FOR STEM EDUCATION
• STEMSCOPES PROFESSIONAL LEARNING
• RESEARCH & EFFICACY STUDIES
• STEM EDUCATION WEBINARS
• LEARNING EQUITY
• DISTANCE LEARNING
• PRODUCT UPDATES
• LMS INTEGRATIONS
• STEMSCOPES BLOG
• FREE RESOURCES
• TESTIMONIALS

Critical Thinking in Science: Fostering Scientific Reasoning Skills in Students

ALI Staff | Published  July 13, 2023

Thinking like a scientist is a central goal of all science curricula.

As students learn facts, methodologies, and methods, what matters most is that all their learning happens through the lens of scientific reasoning what matters most is that it’s all through the lens of scientific reasoning.

That way, when it comes time for them to take on a little science themselves, either in the lab or by theoretically thinking through a solution, they understand how to do it in the right context.

One component of this type of thinking is being critical. Based on facts and evidence, critical thinking in science isn’t exactly the same as critical thinking in other subjects.

Students have to doubt the information they’re given until they can prove it’s right.

They have to truly understand what’s true and what’s hearsay. It’s complex, but with the right tools and plenty of practice, students can get it right.

What is critical thinking?

This particular style of thinking stands out because it requires reflection and analysis. Based on what's logical and rational, thinking critically is all about digging deep and going beyond the surface of a question to establish the quality of the question itself.

It ensures students put their brains to work when confronted with a question rather than taking every piece of information they’re given at face value.

It’s engaged, higher-level thinking that will serve them well in school and throughout their lives.

Why is critical thinking important?

Critical thinking is important when it comes to making good decisions.

It gives us the tools to think through a choice rather than quickly picking an option — and probably guessing wrong. Think of it as the all-important ‘why.’

Why is that true? Why is that right? Why is this the only option?

Finding answers to questions like these requires critical thinking. They require you to really analyze both the question itself and the possible solutions to establish validity.

Will that choice work for me? Does this feel right based on the evidence?

How does critical thinking in science impact students?

Critical thinking is essential in science.

It’s what naturally takes students in the direction of scientific reasoning since evidence is a key component of this style of thought.

It’s not just about whether evidence is available to support a particular answer but how valid that evidence is.

It’s about whether the information the student has fits together to create a strong argument and how to use verifiable facts to get a proper response.

Critical thinking in science helps students:

• Actively evaluate information
• Identify bias
• Separate the logic within arguments
• Analyze evidence

4 Ways to promote critical thinking

Figuring out how to develop critical thinking skills in science means looking at multiple strategies and deciding what will work best at your school and in your class.

Based on your student population, their needs and abilities, not every option will be a home run.

These particular examples are all based on the idea that for students to really learn how to think critically, they have to practice doing it. 

Each focuses on engaging students with science in a way that will motivate them to work independently as they hone their scientific reasoning skills.

Project-Based Learning

Project-based learning centers on critical thinking.

Teachers can shape a project around the thinking style to give students practice with evaluating evidence or other critical thinking skills.

Critical thinking also happens during collaboration, evidence-based thought, and reflection.

For example, setting students up for a research project is not only a great way to get them to think critically, but it also helps motivate them to learn.

Allowing them to pick the topic (that isn’t easy to look up online), develop their own research questions, and establish a process to collect data to find an answer lets students personally connect to science while using critical thinking at each stage of the assignment.

They’ll have to evaluate the quality of the research they find and make evidence-based decisions.

Self-Reflection

Adding a question or two to any lab practicum or activity requiring students to pause and reflect on what they did or learned also helps them practice critical thinking.

At this point in an assignment, they’ll pause and assess independently. 

You can ask students to reflect on the conclusions they came up with for a completed activity, which really makes them think about whether there's any bias in their answer.

Addressing Assumptions

One way critical thinking aligns so perfectly with scientific reasoning is that it encourages students to challenge all assumptions. 

Evidence is king in the science classroom, but even when students work with hard facts, there comes the risk of a little assumptive thinking.

Working with students to identify assumptions in existing research or asking them to address an issue where they suspend their own judgment and simply look at established facts polishes their that critical eye.

They’re getting practice without tossing out opinions, unproven hypotheses, and speculation in exchange for real data and real results, just like a scientist has to do.

Lab Activities With Trial-And-Error

Another component of critical thinking (as well as thinking like a scientist) is figuring out what to do when you get something wrong.

Backtracking can mean you have to rethink a process, redesign an experiment, or reevaluate data because the outcomes don’t make sense, but it’s okay.

The ability to get something wrong and recover is not only a valuable life skill, but it’s where most scientific breakthroughs start. Reminding students of this is always a valuable lesson.

Labs that include comparative activities are one way to increase critical thinking skills, especially when introducing new evidence that might cause students to change their conclusions once the lab has begun.

For example, you provide students with two distinct data sets and ask them to compare them.

With only two choices, there are a finite amount of conclusions to draw, but then what happens when you bring in a third data set? Will it void certain conclusions? Will it allow students to make new conclusions, ones even more deeply rooted in evidence?

Thinking like a scientist

When students get the opportunity to think critically, they’re learning to trust the data over their ‘gut,’ to approach problems systematically and make informed decisions using ‘good’ evidence.

When practiced enough, this ability will engage students in science in a whole new way, providing them with opportunities to dig deeper and learn more.

It can help enrich science and motivate students to approach the subject just like a professional would.

Share this post!

Related articles.

Play-based Learning in Preschool: Learning Through Play

Play is a natural part of early childhood development, making play-based learning a perfect fit for preschool...

Strategies For Building A Math Community In Your Classroom

At the start of the school year, teachers have the chance to create a math classroom where every student feels valued...

Math Manipulatives: How Can They Improve Student Learning in Math?

Math manipulatives are a great way to make math more accessible for your students, especially if you know they may...

STAY INFORMED ON THE LATEST IN STEM. SUBSCRIBE TODAY!

Which stem subjects are of interest to you.

STEMscopes Tech Specifications      STEMscopes Security Information & Compliance      Privacy Policy      Terms and Conditions

© 2024 Accelerate Learning  

Change Password

Your password must have 8 characters or more and contain 3 of the following:.

• a lower case character, 
• an upper case character, 
• a special character 

Password Changed Successfully

Your password has been changed

• Sign in / Register

Request Username

Can't sign in? Forgot your username?

Enter your email address below and we will send you your username

If the address matches an existing account you will receive an email with instructions to retrieve your username

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

• Jason E. Dowd
• Robert J. Thompson
• Leslie A. Schiff
• Julie A. Reynolds

*Address correspondence to: Jason E. Dowd ( E-mail Address: [email protected] ).

Department of Biology, Duke University, Durham, NC 27708

Search for more papers by this author

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

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

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 .

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.

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.

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.

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.

** 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.

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 , 56 (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 , 8 (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 , 38 (5), 290–295. Medline ,  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 , 9 (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 , 46 (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 , 46 (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 , 92 (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 , 27 , 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 , 36 (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 , 18 (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 , 20 (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 , 30 (3), 196–208. https://doi.org/10.1207/S15328023TOP3003_01 . Google Scholar
• Hand, B., & Keys, C. W. ( 1999 ). Inquiry investigation . Science Teacher , 66 (4), 27–29. Google Scholar
• Holm, S. ( 1979 ). A simple sequentially rejective multiple test procedure . Scandinavian Journal of Statistics , 6 (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 . Google Scholar
• Insight Assessment . ( 2016b ). Sample thinking skills questions. Retrieved September 26, 2017, from www.insightassessment.com/Resources/Teaching-Training-and-Learning-Tools/node_1487 . Google Scholar
• Kelly, G. J., & Takao, A. ( 2002 ). Epistemic levels in argument: An analysis of university oceanography students’ use of evidence in writing . Science Education , 86 (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 , 5 (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 , 23 (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 , 94 (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 , 37 (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 , 166 (1), 11–18. https://doi.org/10.1534/genetics.166.1.11 . Medline ,  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 , 7 (3), 327–337. https://doi.org/10.1187/cbe.07-11-0097 . Link ,  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 , 6 (2), 140–154. https://doi.org/10.1187/cbe.06-11-0203 . Link ,  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 , 59 (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 , 11 (1), 17–25. https://doi.org/10.1187/cbe.11-08-0064 . Link ,  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 , 10 (2), 209–215. https://doi.org/­10.1187/cbe.10-10-0127 . Link ,  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 , 17 (3), 354–373. https://doi.org/­10.1037/a0029315 . Medline ,  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 , 17 (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 , 23 (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 , 36 (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 , 25 (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 , 26 (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 , 9 (2), 71–73. https://doi.org/10.1187/cbe.10-03-0044 . Link ,  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 , 47 (9), 1064–1093. https://doi.org/10.1002/tea.20368 . Google Scholar
• Zimmerman, C. ( 2000 ). The development of scientific reasoning skills . Developmental Review , 20 (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 , 27 (2), 172–223. https://doi.org/10.1016/j.dr.2006.12.001 . Google Scholar
• Gender, Equity, and Science Writing: Examining Differences in Undergraduate Life Science Majors’ Attitudes toward Writing Lab Reports 6 March 2024 | Education Sciences, Vol. 14, No. 3
• Designing a framework to improve critical reflection writing in teacher education using action research 24 February 2022 | Educational Action Research, Vol. 32, No. 1
• Scientific Thinking and Critical Thinking in Science Education  5 September 2023 | Science & Education, Vol. 11
• Students Need More than Content Knowledge To Counter Vaccine Hesitancy Journal of Microbiology & Biology Education, Vol. 24, No. 2
• Critical thinking during science investigations: what do practicing teachers value and observe? 16 March 2023 | Teachers and Teaching, Vol. 29, No. 6
• Effect of Web-Based Collaborative Learning Method with Scratch on Critical Thinking Skills of 5th Grade Students 30 March 2023 | Participatory Educational Research, Vol. 10, No. 2
• Are We on the Way to Successfully Educating Future Citizens?—A Spotlight on Critical Thinking Skills and Beliefs about the Nature of Science among Pre-Service Biology Teachers in Germany 22 March 2023 | Behavioral Sciences, Vol. 13, No. 3
• A Systematic Review on Inquiry-Based Writing Instruction in Tertiary Settings 30 November 2022 | Written Communication, Vol. 40, No. 1
• An empirical analysis of the relationship between nature of science and critical thinking through science definitions and thinking skills 8 December 2022 | SN Social Sciences, Vol. 2, No. 12
• TEACHING OF CRITICAL THINKING SKILLS BY SCIENCE TEACHERS IN JAPANESE PRIMARY SCHOOLS 25 October 2022 | Journal of Baltic Science Education, Vol. 21, No. 5
• A Team-Based Activity to Support Knowledge Transfer and Experimental Design Skills of Undergraduate Science Students 4 May 2022 | Journal of Microbiology & Biology Education, Vol. 21
• Curriculum Design of College Students’ English Critical Ability in the Internet Age Wireless Communications and Mobile Computing, Vol. 2022
• Exploring the structure of students’ scientific higher order thinking in science education Thinking Skills and Creativity, Vol. 43
• The Asia-Pacific Education Researcher, Vol. 31, No. 4
• Conspiratorial Beliefs and Cognitive Styles: An Integrated Look on Analytic Thinking, Critical Thinking, and Scientific Reasoning in Relation to (Dis)trust in Conspiracy Theories 12 October 2021 | Frontiers in Psychology, Vol. 12
• Professional Knowledge and Self-Efficacy Expectations of Pre-Service Teachers Regarding Scientific Reasoning and Diagnostics 11 October 2021 | Education Sciences, Vol. 11, No. 10
• Developing textbook based on scientific approach, critical thinking, and science process skills Journal of Physics: Conference Series, Vol. 1839, No. 1
• Using Models of Cognitive Development to Design College Learning Experiences
• Thinking Skills and Creativity, Vol. 42
• Assessing students’ prior knowledge on critical thinking skills in the biology classroom: Has it already been good?
• Critical Thinking Level among Medical Sciences Students in Iran Education Research International, Vol. 2020
• Teaching during a pandemic: Using high‐impact writing assignments to balance rigor, engagement, flexibility, and workload 12 October 2020 | Ecology and Evolution, Vol. 10, No. 22
• Mini-Review - Teaching Writing in the Undergraduate Neuroscience Curriculum: Its Importance and Best Practices Neuroscience Letters, Vol. 737
• Developing critical thinking skills assessment for pre-service elementary school teacher about the basic concept of science: validity and reliability Journal of Physics: Conference Series, Vol. 1567, No. 2
• Challenging endocrinology students with a critical-thinking workbook Advances in Physiology Education, Vol. 44, No. 1
• Jason E. Dowd ,
• Robert J. Thompson ,
• Leslie Schiff ,
• Kelaine Haas ,
• Christine Hohmann ,
• Chris Roy ,
• Warren Meck ,
• John Bruno , and
• Rebecca Price, Monitoring Editor
• Kari L. Nelson ,
• Claudia M. Rauter , and
• Christine E. Cutucache
• Elisabeth Schussler, Monitoring Editor

Submitted: 17 March 2017 Revised: 19 October 2017 Accepted: 20 October 2017

© 2018 J. E. Dowd et al. CBE—Life Sciences Education © 2018 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

3. Critical Thinking in Science: How to Foster Scientific Reasoning Skills

Critical thinking in science is important largely because a lot of students have developed expectations about science that can prove to be counter-productive. 

After various experiences — both in school and out — students often perceive science to be primarily about learning “authoritative” content knowledge: this is how the solar system works; that is how diffusion works; this is the right answer and that is not. 

This perception allows little room for critical thinking in science, in spite of the fact that argument, reasoning, and critical thinking lie at the very core of scientific practice.

Argument, reasoning, and critical thinking lie at the very core of scientific practice.

In this article, we outline two of the best approaches to be most effective in fostering scientific reasoning. Both try to put students in a scientist’s frame of mind more than is typical in science education:

• First, we look at  small-group inquiry , where students formulate questions and investigate them in small groups. This approach is geared more toward younger students but has applications at higher levels too.
• We also look  science   labs . Too often, science labs too often involve students simply following recipes or replicating standard results. Here, we offer tips to turn labs into spaces for independent inquiry and scientific reasoning.

I. Critical Thinking in Science and Scientific Inquiry

Even very young students can “think scientifically” under the right instructional support. A series of experiments , for instance, established that preschoolers can make statistically valid inferences about unknown variables. Through observation they are also capable of distinguishing actions that cause certain outcomes from actions that don’t. These innate capacities, however, have to be developed for students to grow up into rigorous scientific critical thinkers. 

Even very young students can “think scientifically” under the right instructional support.

Although there are many techniques to get young children involved in scientific inquiry — encouraging them to ask and answer “why” questions, for instance — teachers can provide structured scientific inquiry experiences that are deeper than students can experience on their own. 

Goals for Teaching Critical Thinking Through Scientific Inquiry

When it comes to teaching critical thinking via science, the learning goals may vary, but students should learn that:

• Failure to agree is okay, as long as you have reasons for why you disagree about something.
• The logic of scientific inquiry is iterative. Scientists always have to consider how they might improve your methods next time. This includes addressing sources of uncertainty.
• Claims to knowledge usually require multiple lines of evidence and a “match” or “fit” between our explanations and the evidence we have.
• Collaboration, argument, and discussion are central features of scientific reasoning.
• Visualization, analysis, and presentation are central features of scientific reasoning.
• Overarching concepts in scientific practice — such as uncertainty, measurement, and meaningful experimental contrasts — manifest themselves somewhat differently in different scientific domains.

How to Teaching Critical Thinking in Science Via Inquiry

Sometimes we think of science education as being either a “direct” approach, where we tell students about a concept, or an “inquiry-based” approach, where students explore a concept themselves.  

But, especially, at the earliest grades, integrating both approaches can inform students of their options (i.e., generate and extend their ideas), while also letting students make decisions about what to do.

Like a lot of projects targeting critical thinking, limited classroom time is a challenge. Although the latest content standards, such as the Next Generation Science Standards , emphasize teaching scientific practices, many standardized tests still emphasize assessing scientific content knowledge.

The concept of uncertainty comes up in every scientific domain.

Creating a lesson that targets the right content is also an important aspect of developing authentic scientific experiences. It’s now more  widely acknowledged  that effective science instruction involves the interaction between domain-specific knowledge and domain-general knowledge, and that linking an inquiry experience to appropriate target content is vital.

For instance, the concept of uncertainty  comes up  in every scientific domain. But the sources of uncertainty coming from any given measurement vary tremendously by discipline. It requires content knowledge to know how to wisely apply the concept of uncertainty.

Tips and Challenges for teaching critical thinking in science

Teachers need to grapple with student misconceptions. Student intuition about how the world works — the way living things grow and behave, the way that objects fall and interact — often conflicts with scientific explanations. As part of the inquiry experience, teachers can help students to articulate these intuitions and revise them through argument and evidence.

Group composition is another challenge. Teachers will want to avoid situations where one member of the group will simply “take charge” of the decision-making, while other member(s) disengage. In some cases, grouping students by current ability level can make the group work more productive. 

Another approach is to establish group norms that help prevent unproductive group interactions. A third tactic is to have each group member learn an essential piece of the puzzle prior to the group work, so that each member is bringing something valuable to the table (which other group members don’t yet know).

It’s critical to ask students about how certain they are in their observations and explanations and what they could do better next time. When disagreements arise about what to do next or how to interpret evidence, the instructor should model good scientific practice by, for instance, getting students to think about what kind of evidence would help resolve the disagreement or whether there’s a compromise that might satisfy both groups.

The subjects of the inquiry experience and the tools at students’ disposal will depend upon the class and the grade level. Older students may be asked to create mathematical models, more sophisticated visualizations, and give fuller presentations of their results.

Lesson Plan Outline

This lesson plan takes a small-group inquiry approach to critical thinking in science. It asks students to collaboratively explore a scientific question, or perhaps a series of related questions, within a scientific domain.

Suppose students are exploring insect behavior. Groups may decide what questions to ask about insect behavior; how to observe, define, and record insect behavior; how to design an experiment that generates evidence related to their research questions; and how to interpret and present their results.

An in-depth inquiry experience usually takes place over the course of several classroom sessions, and includes classroom-wide instruction, small-group work, and potentially some individual work as well.

Students, especially younger students, will typically need some background knowledge that can inform more independent decision-making. So providing classroom-wide instruction and discussion before individual group work is a good idea.

For instance, Kathleen Metz had students observe insect behavior, explore the anatomy of insects, draw habitat maps, and collaboratively formulate (and categorize) research questions before students began to work more independently.

The subjects of a science inquiry experience can vary tremendously: local weather patterns, plant growth, pollution, bridge-building. The point is to engage students in multiple aspects of scientific practice: observing, formulating research questions, making predictions, gathering data, analyzing and interpreting data, refining and iterating the process.

As student groups take responsibility for their own investigation, teachers act as facilitators. They can circulate around the room, providing advice and guidance to individual groups. If classroom-wide misconceptions arise, they can pause group work to address those misconceptions directly and re-orient the class toward a more productive way of thinking.

Throughout the process, teachers can also ask questions like:

• What are your assumptions about what’s going on? How can you check your assumptions?
• Suppose that your results show X, what would you conclude?
• If you had to do the process over again, what would you change? Why?

II. Rethinking Science Labs

Beyond changing how students approach scientific inquiry, we also need to rethink science labs. After all, science lab activities are ubiquitous in science classrooms and they are a great opportunity to teach critical thinking skills.

Often, however, science labs are merely recipes that students follow to verify standard values (such as the force of acceleration due to gravity) or relationships between variables (such as the relationship between force, mass, and acceleration) known to the students beforehand. 

This approach does not usually involve critical thinking: students are not making many decisions during the process, and they do not reflect on what they’ve done except to see whether their experimental data matches the expected values.

With some small tweaks, however, science labs can involve more critical thinking. Science lab activities that give students not only the opportunity to design, analyze, and interpret the experiment, but re -design, re -analyze, and re -interpret the experiment provides ample opportunity for grappling with evidence and evidence-model relationships, particularly if students don’t know what answer they should be expecting beforehand.

Such activities improve scientific reasoning skills, such as: 

• Evaluating quantitative data
• Plausible scientific explanations for observed patterns

And also broader critical thinking skills, like:

• Comparing models to data, and comparing models to each other
• Thinking about what kind of evidence supports one model or another
• Being open to changing your beliefs based on evidence

Traditional science lab experiences bear little resemblance to actual scientific practice. Actual practice  involves  decision-making under uncertainty, trial-and-error, tweaking experimental methods over time, testing instruments, and resolving conflicts among different kinds of evidence. Traditional in-school science labs rarely involve these things.

Traditional science lab experiences bear little resemblance to actual scientific practice.

When teachers use science labs as opportunities to engage students in the kinds of dilemmas that scientists actually face during research, students make more decisions and exhibit more sophisticated reasoning.

In the lesson plan below, students are asked to evaluate two models of drag forces on a falling object. One model assumes that drag increases linearly with the velocity of the falling object. Another model assumes that drag increases quadratically (e.g., with the square of the velocity).  Students use a motion detector and computer software to create a plot of the position of a disposable paper coffee filter as it falls to the ground. Among other variables, students can vary the number of coffee filters they drop at once, the height at which they drop them, how they drop  them, and how they clean their data. This is an approach to scaffolding critical thinking: a way to get students to ask the right kinds of questions and think in the way that scientists tend to think.

Design an experiment to test which model best characterizes the motion of the coffee filters. 

Things to think about in your design:

• What are the relevant variables to control and which ones do you need to explore?
• What are some logistical issues associated with the data collection that may cause unnecessary variability (either random or systematic) or mistakes?
• How can you control or measure these?
• What ways can you graph your data and which ones will help you figure out which model better describes your data?

Discuss your design with other groups and modify as you see fit.

Initial data collection

Conduct a quick trial-run of your experiment so that you can evaluate your methods.

• Do your graphs provide evidence of which model is the best?
• What ways can you improve your methods, data, or graphs to make your case more convincing?
• Do you need to change how you’re collecting data?
• Do you need to take data at different regions?
• Do you just need more data?
• Do you need to reduce your uncertainty?

After this initial evaluation of your data and methods, conduct the desired improvements, changes, or additions and re-evaluate at the end.

In your lab notes, make sure to keep track of your progress and process as you go. As always, your final product is less important than how you get there.

How to Make Science Labs Run Smoothly

Managing student expectations . As with many other lesson plans that incorporate critical thinking, students are not used to having so much freedom. As with the example lesson plan above, it’s important to scaffold student decision-making by pointing out what decisions have to be made, especially as students are transitioning to this approach.

Supporting student reasoning . Another challenge is to provide guidance to student groups without telling them how to do something. Too much “telling” diminishes student decision-making, but not enough support may leave students simply not knowing what to do. 

There are several key strategies teachers can try out here: 

• Point out an issue with their data collection process without specifying exactly how to solve it.
• Ask a lab group how they would improve their approach.
• Ask two groups with conflicting results to compare their results, methods, and analyses.

Download our Teachers’ Guide

(please click here)

Sources and Resources

Lehrer, R., & Schauble, L. (2007). Scientific thinking and scientific literacy . Handbook of child psychology , Vol. 4. Wiley. A review of research on scientific thinking and experiments on teaching scientific thinking in the classroom.

Metz, K. (2004). Children’s understanding of scientific inquiry: Their conceptualizations of uncertainty in investigations of their own design . Cognition and Instruction 22(2). An example of a scientific inquiry experience for elementary school students.

The Next Generation Science Standards . The latest U.S. science content standards.

Concepts of Evidence A collection of important concepts related to evidence that cut across scientific disciplines.

Scienceblind A book about children’s science misconceptions and how to correct them.

Holmes, N. G., Keep, B., & Wieman, C. E. (2020). Developing scientific decision making by structuring and supporting student agency. Physical Review Physics Education Research , 16 (1), 010109. A research study on minimally altering traditional lab approaches to incorporate more critical thinking. The drag example was taken from this piece.

ISLE , led by E. Etkina.  A platform that helps teachers incorporate more critical thinking in physics labs.

Holmes, N. G., Wieman, C. E., & Bonn, D. A. (2015). Teaching critical thinking . Proceedings of the National Academy of Sciences , 112 (36), 11199-11204. An approach to improving critical thinking and reflection in science labs. Walker, J. P., Sampson, V., Grooms, J., Anderson, B., & Zimmerman, C. O. (2012). Argument-driven inquiry in undergraduate chemistry labs: The impact on students’ conceptual understanding, argument skills, and attitudes toward science . Journal of College Science Teaching , 41 (4), 74-81. A large-scale research study on transforming chemistry labs to be more inquiry-based.

Privacy Overview

• Thinker's Guides

The Thinker's Guide to Scientific Thinking - Based on Critical Thinking Concepts and Principles

Fourth edition richard paul and linda elder, order from rowman & littlefield here., contact info for rowman & littlefield:.

• Toll free: (800) 462-6420 ext. 3024
• Fax: (800) 338-4550
• Orders to [email protected]
• Queries to [email protected]

This guide focuses on developing the intellectual skills inherent in the well-cultivated scientific thinker. It helps students and practicing scientists come to reason within the logic of science and to see the field as a cohesive whole. From astronomers to zoologists and physicists to chemists, skilled scientists use careful analysis to question data, test theories, draw logical conclusions, and propose feasible solutions. Students in science courses, and scientists themselves will find their analytical abilities enhanced by the engaging framework of inquiry set forth by Richard Paul and Linda Elder in this guide. As part of the Thinker’s Guide Library, this book advances the mission of the Foundation for Critical Thinking to promote fairminded critical societies through cultivating essential intellectual abilities and virtues across every field of study across world.

Rowman & littlefield publishers / the foundation for critical thinking pages: 66 • trim: 5 1/2 x 8 978-0-9857544-2-6 • paperback • january 2015 • $21.99 • (£14.95) 978-1-5381-3384-2 • ebook • june 2019 • $20.50 • (£13.95) series: thinker's guide library, additional information about: the thinker's guide to scientific thinking - based on critical thinking concepts and principles.

Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4

A critical approach to learning science is concerned less with accumulating undigested facts and scientific definitions and procedures, than with learning to think scientifically . As we learn to think scientifically, we inevitably organize and internalize facts, learn terminology, and use scientific procedures. But we learn them deeply, because they are tied into ideas we have thought through, and hence do not have to “re-learn” later. A critical approach to learning science requires us to ponder questions, propose solutions, and think through possible experiments.  

A well cultivated scientific thinker:

• raises vital scientific questions and problems, formulating them clearly and precisely;

• gathers and assesses relevant scientific data and information, using abstract ideas to interpret them effectively;

• comes to well-reasoned scientific conclusions and solutions, testing them against relevant criteria and standards;

• thinks openmindedly within convergent systems of scientific thought, recognizing and assessing scientific assumptions, implications, and practical consequences; and

• communicates effectively with others in proposing solutions to complex scientific problems.

Scientific thinking is, in short, self-directed, self-disciplined, self-monitored, and self-corrective. It presupposes assent to rigorous standards of excellence and mindful command of their use. It entails effective communication and problem solving abilities as well as a commitment to developing scientific skills, abilities, and dispositions.

This guide is designed for students and faculty. It consists of the essence of scientific thinking concepts and tools. For faculty it provides a shared concept of scientific thinking. For students it is a scientific thinking supplement to any textbook for any science course. Faculty can use it to design science instruction, assignments, and tests. Students can use it to improve their perspective in any domain of science.

Contents include:

• Why Scientific Thinking
• The Elements of Scientific Thought
• A Checklist for Scientific Reasoning
• Questions Using the Elements of Scientific Thought
• Scientific Thinking Seeks to Quantify, Explain, and Predict Relationships in Nature
• Scientific Thinking Requires Precision
• Experimental Thinking Requires Experimental Controls
• Universal Intellectual Standards in Scientific Thinking
• Analyzing the Logic of Scientific Articles
• Analyzing the Logic of Science Textbooks
• Two Kinds of Scientific Questions
• Analyzing the Logic of An Experiment
• Criteria for Evaluating Scientific Reasoning
• Scientific Reasoning Abilities
• Intellectual Dispositions Essential to Scientific Thinking
• What Scientific Thinkers Routinely Do
• Stages of Scientific Thinking Development
• The Questioning Mind in Science (Newton, Darwin, and Einstein)
• The Logic of Science
• The Logic of Physics
• The Logic of Chemistry
• The Logic of Geology
• The Logic of Astronomy
• The Logic of Biology
• The Logic of Zoology
• The Logic of Botany
• The Logic of Biochemistry
• The Logic of Paleontology
• The Logic of Animal Physiology
• The Logic of Archaeology
• The Logic of Ecology
• The Problem of Unscientific Thinking
• A Pseudo-Science: Why Astrology is Not a Science

May 1, 2024

18 min read

Can Scientific Thinking Save the World?

A physicist, a philosopher and a psychologist are working together to bring better, smarter decision-making to the masses

By Lee Billings

Kislev/Getty Images

A physicist, a philosopher and a psychologist walk into a classroom.

Although it sounds like a premise for a joke, this was actually the origin of a unique collaboration between Nobel Prize–winning physicist Saul Perlmutter, philosopher John Campbell and the psychologist Rob MacCoun. Spurred by what they saw as a perilously rising tide of irrationality, misinformation and sociopolitical polarization, they teamed up in 2011 to create a multidisciplinary course at the University of California, Berkeley, with the modest goal of teaching undergraduate students how to think—more specifically, how to think like a scientist . That is, they wished to show students how to use scientific tools and techniques for solving problems, making decisions and distinguishing reality from fantasy . The course proved popular, drawing enough interest to run for more than a decade (and counting) while sparking multiple spin-offs at other universities and institutions.

Now the three researchers are bringing their message to the masses with a new book, Third Millennium Thinking: Creating Sense in a World of Nonsense . And their timing is impeccable: Our world seems to have only become more uncertain and complex since their course began, with cognitive biases and information overload all too easily clouding debates over high-stakes issues such as climate change , global pandemics , and the development and regulation of artificial intelligence . But one need not be an academic expert or policymaker to find value in this book’s pages. From parsing the daily news to treating a medical condition, talking with opposite-minded relatives at Thanksgiving or even choosing how to vote in an election, Third Millennium Thinking offers lessons that anyone can use—individually and collectively—to make smarter, better decisions in everyday life.

On supporting science journalism

If you're enjoying this article, consider supporting our award-winning journalism by subscribing . By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.

Scientific American spoke with Perlmutter, Campbell and MacCoun about their work—and whether it’s wishful thinking to believe logic and evidence can save the world.

[ An edited transcript of the interview follows .]

How did all of this begin, and what motivated each of you to take on such an ambitious project?

PERLMUTTER: In 2011 I was looking at our society making big decisions: “Should we raise the debt ceiling?”—things like that. And surprisingly enough, we were not doing it in a very sensible way. The conversations I was hearing about these political decisions weren’t like those I’d have over lunch with a bunch of scientists at the lab—not because of politics, but rather because of the style of how scientists tend to think about solving problems. And I thought, “Well, where did scientists learn this stuff? And is it possible for us to articulate what these concepts are and teach them in a way that people would apply them in their whole lives, not just in a lab? And can we empower them to think for themselves using the best available cognitive tools rather than teaching them to ‘just trust scientists?’”

So that was the starting point of it. But that’s not the whole story. If you put a bunch of physicists together in a faculty meeting, they don’t necessarily act much more rational than any other faculty members, right? So it was clear we really needed expertise from other fields, too, such as John’s expertise in philosophy and Rob’s expertise in social psychology. We actually put a little sign up looking for people who’d want to help develop the course. It said something like, “Are you embarrassed watching our society make decisions? Come help invent our course; come help save the world.”

MacCOUN: When Saul approached me about the course, I was delighted to work with him. Even back in 2011 I was filled with angst about the inefficacy of policy debates; I had spent years working on two big hot-button issues: drug legalization and open military service for gay and lesbian individuals. I worked with policymakers and advocates on both sides, just trying to be an honest broker in these debates to help clarify the truth—you know, “What do we actually know, and what don’t we know?” And the quality of debate for both of those issues was so bad, with so much distortion of research findings. So when Saul mentioned the course to me, I just jumped at the chance to work on this.

CAMPBELL: It was obvious to me that this was philosophically very interesting. I mean, we’re talking about how science inputs into decision-making. And in decision-making, there are always questions of value, as well as questions of fact; questions about where you want to go, as well as questions about how do we get there; and questions about what “the science” can answer. And it’s very interesting to ask, “Can we tease apart facts and values in decision-making? Does the science have anything to tell us about values?” Well, likely not. Scientists always shy away from telling us about values. So we need to know something about how broader effective concerns can be woven in with scientific results in decision-making.

Some of this is about how science is embedded in the life of a community. You take a village—you have the pub, you have the church, you know clearly what they are for and how they function in the whole community. But then the science, what is that? Is it just this kind of shimmering thing that produces telephones, TVs and stuff? How does it fit into the life of the community? How does it embed in our civilization? Classically, it’s been regarded as a “high church” kind of thing. The scientists are literally in an ivory tower and do as they please. And then occasionally, they produce these gadgets, and we’re not sure if we should like them or not. But we really need a more healthy, grounded conception of how science plays into our broader society.

I’m glad you brought up the distinction between facts and values. To me, that overlaps with the distinction between groups and individuals—“values” feel more personal and subjective and thus more directly applicable to a reader, in a way. And the book is ultimately about how individuals can empower themselves with so-called scientific thinking—presumably to live their best lives based on their personal values. But how does that accord with this other assertion you’ve just made, saying science likely doesn’t have anything to tell us about values in the first place?

PERLMUTTER: Well, I think what John was getting at is: even once we develop all these ways to think through facts, we don’t want to stop thinking through values, right? One point here is that we’ve actually made progress together thinking about values over centuries. And we have to keep talking to each other. But it’s still very helpful to separate the values and the facts because each requires a slightly different style of thinking, and you want people to be able to do both.

MacCOUN: That’s right. Scientists can’t tell us and shouldn’t tell us, in fact, what values to hold. Scientists get in trouble when they try that. We talk in the book about “pathologies” of science that sometimes happen and how those can be driven by values-based thinking. Regarding values, where science excels is in clarifying where and how they conflict so that in public policy analysis, you can inform the trade-offs to make sure that the stakeholders in a debate empirically understand how its various outcomes advance certain values while impeding others. Usually what happens next is finding solutions that minimize those trade-offs and reduce the friction between conflicting values.

And let’s be clear: when we talk about values, we sometimes talk as if people are either one thing or another. You know, someone may ask, “Are you for or against ‘freedom?’” But in reality, everyone values freedom. It’s just a question of how much, of how we differ in our rankings of such things. And we’re all looking for some way to pursue more than one value at a time, and we need other people to help us get there.

PERLMUTTER: And let’s remember that we’re not even consistent within our own selves about our individual rankings of values, which tend to fluctuate a lot based on the situation.

I love how our discussion is now reflecting the style of the book: breezy and approachable but also unflinching in talking about complexity and uncertainty. And in it, you’re trying to give readers a “tool kit” for navigating such things. That’s great, yet it can be challenging for readers who might assume it’s, say, a science-infused self-help book offering them a few simple rules about how to improve their rational thinking. This makes me wonder: If you did have to somehow reduce the book’s message to something like a series of bullet points on a note card, what would that be? What are the most essential tools in the kit?

CAMPBELL: This may be a bit ironic, but I was reading somewhere recently that where AI programs such as ChatGPT really go wrong is in not giving sources. Most of these tools don’t tell you what evidence they’re using for their outputs. And you’d think, of course, we should always show what evidence we have for anything we’re gonna say. But really, we can’t do that. Most of us can’t remember the evidence for half of what we know. What we can usually recall is how likely we thought some assertion was to be true, how probable we thought it was. And keeping track of this is a worthwhile habit of mind: if you’re going to act on any belief you might have, you need to know the strength with which you can hold that belief.

PERLMUTTER: We spend a fair amount of time on this in the book because it allows you to see that the world doesn’t come to us with certainty in almost anything. Even when we’re pretty sure of something, we’re only pretty sure, and there’s real utility in having a sense of the possibility for something contradicting what we think or expect. Many people do this naturally all the time, thinking about the odds for placing a bet on their favorite sports team or about the chance of a rain shower spoiling a picnic. Acknowledging uncertainty puts your ego in the right place. Your ego should, in the end, be attached to being pretty good at knowing how strong or weak your trust is in some fact rather than in being always right. Needing to always be right is a very problematic way to approach the world. In the book, we compare it to skiing down a mountain with all your weight rigid on both legs; if you don’t ever shift your stance to turn and slow down, you might go very fast, but you usually don’t get very far before toppling over! So instead you need to be able to maneuver and adjust to keep track of what it is that you really do know versus what you don’t. That’s how to actually get wherever you’re trying to go, and it’s also how to have useful conversations with other people who may not agree with you.

MacCOUN: And that sense of working together is important because these habits of mind we’re discussing aren’t just about your personal decision-making; they’re also about how science works in a democracy. You know, scientists end up having to work with people they disagree with all the time. And they cultivate certain communal ways of doing that—because it’s not enough to just be a “better” thinker; even people well-trained in these methods make mistakes. So you also need these habits at a communal level for other people to keep you honest. That means it’s okay, and necessary even, to interact with people who disagree with you—because that’s how you find out when you’re making mistakes. And it doesn’t necessarily mean you’ll change your mind. But it’ll improve your thinking about your own views.

So in summary:

Try to rank your confidence in your beliefs.

Try to update your beliefs based on new evidence and don’t fear being (temporarily) wrong.

Try to productively engage with others who have different beliefs than you.

That’s a pretty good “top three” list, I think! But, pardon my cynicism, do you worry that some of this might come off as rather quaint? We mentioned at the outset how this project really began in 2011, not much more than a decade ago. Yet some would probably argue that social and technological changes across that time have now effectively placed us in a different situation, a different world. It seems—to me at least—on average much harder now than it was 10 years ago for people with divergent beliefs and values to have a pleasant, productive conversation. Are the challenges we face today really things that can be solved by everyone just getting together and talking?

CAMPBELL: I agree with you that this sort of cynicism is now widespread. Across the past few decades we seem to have forgotten how to have a conversation across a fundamental divide, so now we take for granted that it’s pointless to try to convert those holding different views. But the alternative is to run society by coercion. And just beating people down with violent subjugation is not a long-term tenable solution. If you’re going to coerce, you have to at least show your work. You have to engage with other people and explain why you think your policies are good.

MacCOUN: You can think of cynicism as this god-awful corrosive mix of skepticism and pessimism. At the other extreme, you have gullibility, which, combined with optimism, leads to wishful thinking. And that’s really not helpful either. In the book we talk about an insight Saul had, which is that scientists tend to combine skepticism with optimism—a combo I’d say is not generally cultivated in our society. Scientists are skeptical, not gullible, but they’re optimistic, not pessimistic: they tend to assume that problems have a solution. So scientists sitting around the table are more likely to be trying to figure out fixes for a problem rather than bemoaning how terrible it is.

PERLMUTTER: This is something we’ve grappled with, and there are a couple of elements, I think, that are important to transmit about it. One is that there are good reasons to be disappointed when you look at the leaders of our society. They’ve structurally now gotten themselves into a fix, where they seem unable to even publicly say what they believe, let alone find real compromises on divisive issues. Meanwhile you can find lots of examples of “citizen assembly” events where a random selection of average people who completely disagree and support the opposite sides of the political spectrum sit down together and are much more able to have a civil, thoughtful conversation than their sociopolitical leaders can. That makes me think most of the [people in the] country (but not all!) could have a very reasonable conversation with each other. So clearly there’s an opportunity that we haven’t taken advantage of to structurally find ways to empower those conversations, not just the leaders trying to act for us. That’s something to be optimistic about. Another is that the daily news portrays the world as a very scary and negative place—but we know the daily news is not offering a very good representative take on the true state of the world, especially regarding the huge improvements in human well-being that have occurred over the past few decades.

So it feels to me that many people are living in “crisis” mode because they’re always consuming news that’s presenting us crises every moment and driving us apart with wedge issues. And I think there’s optimism to be found in looking for ways to talk together again. As John says, that’s the only game in town: to try to work with people until you learn something together, as opposed to just trying to win and then having half your population being unhappy.

CAMPBELL: We are maybe the most tribal species on the planet, but we are also perhaps the most amazingly flexible and cooperative species on the planet. And as Saul said, in these almost town-hall-style deliberative citizen assemblies you see this capacity for cooperation coming out, even among people who’d be bitterly divided and [belong to] opposite tribes otherwise—so there must be ways to amplify that and to escape being locked into these tribal schisms.

MacCOUN: And it’s important to remember that research on cooperation suggests you don’t need to have everybody cooperating to get the benefits. You do need a critical mass, but you’re never going to get everyone, so you shouldn’t waste your time trying to reach 100 percent. [Political scientist] Robert Axelrod and others studying the evolution of cooperation have shown that if cooperators can find each other, they can start to thrive and begin attracting other cooperators, and they can become more robust in the face of those who are uncooperative or trying to undermine cooperation. So somehow getting that critical mass is probably the best you can hope for.

I’m sure it hasn’t escaped anyone’s notice that as we discuss large-scale social cooperation, we’re also in an election year in the U.S., ostensibly the world’s most powerful democracy. And sure, part of the equation here is breaking down walls with basic acts of kindness and humility: love thy neighbor, find common ground, and so on. But what about voting? Does scientific decision-making give us some guidance on “best practices” there?

PERLMUTTER: Well, clearly we want this to be something that transcends election years. But in general, you should avoid making decisions—voting included—purely based on fear. This is not a time in the world where fear should be the dominant thing driving our individual or collective actions. Most of our fears divide us, yet most of our strength is found in working together to solve problems. So one basic thing is not to let yourself be flustered into voting for anyone or anything out of fear. But another is to look for leaders who use and reflect the scientific style of thinking, in which you’re open to being wrong, you’re bound by evidence, and you’re able to change your mind if it turns out that you were pursuing a bad plan. And that’s something that unfortunately we very rarely see.

CAMPBELL: At the moment we have an abundance of free speech—everyone can get on to some kind of social media and explain their views to the entire country. But we seem to have forgotten that the whole point of free speech was the testing of ideas. That was why it seemed like such a good thing: through free speech, new ideas can be generated and discussed and tested. But that idea of testing the ideas you freely express has just dropped out of the culture. We really need to tune back in to that in how we teach and talk about free speech and its value. It’s not just an end in itself, you know?

MacCOUN: And let’s be mindful of some lessons from history, too. For a lot of these issues that are so polarizing and divisive, it’s probably going to turn out that neither side was completely right, and there was some third possibility that didn’t occur to most, if any, of us. This happens in science all the time, with each victorious insight usually being provisional until the next, better theory or piece of evidence comes along. And in the same way, if we can’t move past arguing about our current conception of these problems, we’re trapping ourselves in this one little region of conceptual space when the solution might lie somewhere outside. This is one of very many cognitive traps we talk about in the book. Rather than staking out our hill to die on, we should be more open to uncertainty and experimentation: we test some policy solution to a problem, and if it doesn’t work, we’re ready to rapidly make adjustments and try something else.

Maybe we can practice what we preach here, this idea of performing evidence-based testing and course correction and escaping various sorts of cognitive traps. While you were working on this book, did you find and reflect on any irrational habits of mind you might have? And was there a case where you chose a hill to die on, and you were wrong, and you begrudgingly adjusted?

MacCOUN: Yeah, in the book we give examples of our own personal mistakes. One from my own research involves the replicability crisis and people engaging in confirmation bias. I had written a review paper summarizing evidence that seemed to show that decriminalizing drugs—that is, removing criminal penalties for them—did not lead to higher levels of use. After writing it, I had a new opportunity to test that hypothesis, looking at data from Italy, where in the 1970s they’d basically decriminalized personal possession of small quantities of all drugs. And then they recriminalized them in 1990. And then they redecriminalized in 1993. So it was like a perfect opportunity. And the data showed drug related deaths actually went down when they reinstituted penalties and went back up again when the penalties were removed. And this was completely opposite of what I had already staked my reputation on! And so, well, I had a personal bias, right? And that’s really the only reason I went and did more research, digging deeper on this Italian thing, because I didn’t like the findings. So across the same span of time I looked at Spain (a country that had decriminalized without recriminalizing) and at Germany (a country that never decriminalized during that time), and all three showed the same death pattern. This suggests that the suspicious pattern of deaths in fact had nothing to do with penalties. Now, I think that leads to the correct conclusion—my original conclusion, of course! But the point is: I’m embarrassed to admit I had fallen into the trap of confirmation bias—or, really, of its close cousin called disconfirmation bias, where you’re much tougher on evidence that seems to run counter to your beliefs. It’s a teachable moment, for sure.

CAMPBELL: It takes a lot of courage to admit these sorts of things and make the necessary transitions. One cognitive trap that affects many of us is what’s called the implicit bias blind spot, where you can be really subtle and perceptive in spotting other people’s biases but not your own. You can often see a bias of some sort in an instant in other people. But what happens when you look at yourself? The reaction is usually, “Na, I don't do that stuff!” You know, I must have been through hundreds and hundreds of student applications for admission or searches for faculty members, and I never spotted myself being biased at all, not once. “I just look at the applications straight,” right? But that can’t always be true because the person easiest to fool is yourself! Realizing that can be such a revelation.

PERLMUTTER: And this really informs one of the book’s key points: that we need to find better ways to work with people with whom we disagree—because one of the very best ways to get at your own biases is to find somebody who disagrees with you and is strongly motivated to prove you wrong. It’s hard, but you really do need the loyal opposition. Thinking back, for instance, to the big race for measuring the cosmological expansion of the universe that led to the discovery of dark energy, it was between my team and another team. Sometimes my colleagues and I would see members of the other team showing up to do their observations at the telescopes just as we were leaving from doing ours, and it was uncomfortable knowing both teams were chasing the same thing. On the other hand, that competition ensured we’d each try to figure out if the other team was making mistakes, and it greatly improved the confidence we collectively had in our results. But it’s not good enough just to have two opposing sides—you also need ways for them to engage with each other.

I realize I’ve inadvertently left probably the most basic question for last. What exactly is “third millennium thinking?”

PERLMUTTER: That’s okay, we actually leave explaining this to the book’s last chapter, too!

MacCOUN: Third millennium thinking is about recognizing a big shift that’s underway. We all have a sense of what the long millennia predating science must have been like, and we all know the tremendous advances that gradually came about as the modern scientific era emerged—from the practices of various ancient civilizations to the Renaissance and the Enlightenment, all those shifts in thinking that led to the amazing scientific revolution that has so profoundly changed our world here in what, until the end of the 20th century, was the second millennium. But there’s also been disenchantment with science, especially recently. And there’s validity to concerns that science was sometimes just a handmaiden of the powerful and that scientists sometimes wield more authority than they deserve to advance their own personal projects and politics. And sometimes science can become pathological; sometimes it can fail.

A big part of third millennium thinking is acknowledging science’s historic faults but also its capacity for self-correction, some of which we’re seeing today. We think this is leading us into a new era in which science is becoming less hierarchical. It’s becoming more interdisciplinary and team-based and, in some cases, more approachable for everyday people to be meaningfully involved—think of so-called citizen science projects. Science is also becoming more open, where researchers must show their work by making their data and methods more readily available so that others can independently check it. And we hope these sorts of changes are making scientists more humble: This attitude of “yeah, I’ve got the Ph.D., so you listen to me,” that doesn’t necessarily work anymore for big, divisive policy issues. You need a more deliberative consultation in which everyday people can be involved. Scientists do need to stay in their lane to some extent and not claim authority just based on their pedigree—the authority comes from the method used, not from the pedigree.

We see these all connected in their potential to advance a new way of doing science and of being scientists, and that’s what third millennium thinking is about.

CAMPBELL: With the COVID pandemic, I think we’ve all sadly become very familiar with the idea that the freedom of the individual citizen is somehow opposed to the authority of the scientist. You know, “the scientist is a person who will boss you around, diminish your freedom and inject you with vaccines laced with mind-controlling nanobots” or whatever. And it’s such a shame. It’s so debilitating when people use or see science like that. Or alternatively, you might say, “Well, I’m no scientist, and I can’t do the math, so I’ll just believe and do whatever they tell me.” And that really is relinquishing your freedom. Science should be an enabler of individual power, not a threat to your freedom. Third millennium thinking is about achieving that, allowing as many people as possible to be empowered—to empower themselves—by using scientific thinking.

PERLMUTTER: Exactly. We're trying to help people see that this combination of trends we’re now seeing around the world is actually a very fertile opportunity for big, meaningful, positive change. And if we lean into this, it could set us in a very good position on the long-term path to a really great millennium. Even though there are all these other forces to worry about at the moment, by applying the tools, ideas and processes from the culture of science to other parts of our lives, we can have the wind at our back as we move toward a brighter, better future.

• Augsburg.edu
• Inside Augsburg

Search Strommen Center for Meaningful Work

• Faculty & Staff
• Graduate Students
• First Generation
• International
• Students With Disabilities
• Undocumented
• Business & Finance
• Culture and Language
• Environmental Sustainability
• Government, Law & Policy
• Health Professions
• Human & Social Services
• Information Technology & Data
• Marketing, Media & Communications
• Resumes and Cover Letters
• Expand Your Network / Mentor
• Explore Your Interests / Self Assessment
• Negotiate an Offer
• Prepare for an Interview
• Prepare for Graduate School
• Search for a Job / Internship
• Job Fair Preparation
• Start Your Internship
• Choosing a Major
• Career Collaborative
• Travelers EDGE
• Meet the Team

Critical Thinking: A Simple Guide and Why It’s Important

• Share This: Share Critical Thinking: A Simple Guide and Why It’s Important on Facebook Share Critical Thinking: A Simple Guide and Why It’s Important on LinkedIn Share Critical Thinking: A Simple Guide and Why It’s Important on X

Critical Thinking: A Simple Guide and Why It’s Important was originally published on Ivy Exec .

Strong critical thinking skills are crucial for career success, regardless of educational background. It embodies the ability to engage in astute and effective decision-making, lending invaluable dimensions to professional growth.

At its essence, critical thinking is the ability to analyze, evaluate, and synthesize information in a logical and reasoned manner. It’s not merely about accumulating knowledge but harnessing it effectively to make informed decisions and solve complex problems. In the dynamic landscape of modern careers, honing this skill is paramount.

The Impact of Critical Thinking on Your Career

☑ problem-solving mastery.

Visualize critical thinking as the Sherlock Holmes of your career journey. It facilitates swift problem resolution akin to a detective unraveling a mystery. By methodically analyzing situations and deconstructing complexities, critical thinkers emerge as adept problem solvers, rendering them invaluable assets in the workplace.

☑ Refined Decision-Making

Navigating dilemmas in your career path resembles traversing uncertain terrain. Critical thinking acts as a dependable GPS, steering you toward informed decisions. It involves weighing options, evaluating potential outcomes, and confidently choosing the most favorable path forward.

☑ Enhanced Teamwork Dynamics

Within collaborative settings, critical thinkers stand out as proactive contributors. They engage in scrutinizing ideas, proposing enhancements, and fostering meaningful contributions. Consequently, the team evolves into a dynamic hub of ideas, with the critical thinker recognized as the architect behind its success.

☑ Communication Prowess

Effective communication is the cornerstone of professional interactions. Critical thinking enriches communication skills, enabling the clear and logical articulation of ideas. Whether in emails, presentations, or casual conversations, individuals adept in critical thinking exude clarity, earning appreciation for their ability to convey thoughts seamlessly.

☑ Adaptability and Resilience

Perceptive individuals adept in critical thinking display resilience in the face of unforeseen challenges. Instead of succumbing to panic, they assess situations, recalibrate their approaches, and persist in moving forward despite adversity.

☑ Fostering Innovation

Innovation is the lifeblood of progressive organizations, and critical thinking serves as its catalyst. Proficient critical thinkers possess the ability to identify overlooked opportunities, propose inventive solutions, and streamline processes, thereby positioning their organizations at the forefront of innovation.

☑ Confidence Amplification

Critical thinkers exude confidence derived from honing their analytical skills. This self-assurance radiates during job interviews, presentations, and daily interactions, catching the attention of superiors and propelling career advancement.

So, how can one cultivate and harness this invaluable skill?

✅ developing curiosity and inquisitiveness:.

Embrace a curious mindset by questioning the status quo and exploring topics beyond your immediate scope. Cultivate an inquisitive approach to everyday situations. Encourage a habit of asking “why” and “how” to deepen understanding. Curiosity fuels the desire to seek information and alternative perspectives.

✅ Practice Reflection and Self-Awareness:

Engage in reflective thinking by assessing your thoughts, actions, and decisions. Regularly introspect to understand your biases, assumptions, and cognitive processes. Cultivate self-awareness to recognize personal prejudices or cognitive biases that might influence your thinking. This allows for a more objective analysis of situations.

✅ Strengthening Analytical Skills:

Practice breaking down complex problems into manageable components. Analyze each part systematically to understand the whole picture. Develop skills in data analysis, statistics, and logical reasoning. This includes understanding correlation versus causation, interpreting graphs, and evaluating statistical significance.

✅ Engaging in Active Listening and Observation:

Actively listen to diverse viewpoints without immediately forming judgments. Allow others to express their ideas fully before responding. Observe situations attentively, noticing details that others might overlook. This habit enhances your ability to analyze problems more comprehensively.

✅ Encouraging Intellectual Humility and Open-Mindedness:

Foster intellectual humility by acknowledging that you don’t know everything. Be open to learning from others, regardless of their position or expertise. Cultivate open-mindedness by actively seeking out perspectives different from your own. Engage in discussions with people holding diverse opinions to broaden your understanding.

✅ Practicing Problem-Solving and Decision-Making:

Engage in regular problem-solving exercises that challenge you to think creatively and analytically. This can include puzzles, riddles, or real-world scenarios. When making decisions, consciously evaluate available information, consider various alternatives, and anticipate potential outcomes before reaching a conclusion.

✅ Continuous Learning and Exposure to Varied Content:

Read extensively across diverse subjects and formats, exposing yourself to different viewpoints, cultures, and ways of thinking. Engage in courses, workshops, or seminars that stimulate critical thinking skills. Seek out opportunities for learning that challenge your existing beliefs.

✅ Engage in Constructive Disagreement and Debate:

Encourage healthy debates and discussions where differing opinions are respectfully debated.

This practice fosters the ability to defend your viewpoints logically while also being open to changing your perspective based on valid arguments. Embrace disagreement as an opportunity to learn rather than a conflict to win. Engaging in constructive debate sharpens your ability to evaluate and counter-arguments effectively.

✅ Utilize Problem-Based Learning and Real-World Applications:

Engage in problem-based learning activities that simulate real-world challenges. Work on projects or scenarios that require critical thinking skills to develop practical problem-solving approaches. Apply critical thinking in real-life situations whenever possible.

This could involve analyzing news articles, evaluating product reviews, or dissecting marketing strategies to understand their underlying rationale.

In conclusion, critical thinking is the linchpin of a successful career journey. It empowers individuals to navigate complexities, make informed decisions, and innovate in their respective domains. Embracing and honing this skill isn’t just an advantage; it’s a necessity in a world where adaptability and sound judgment reign supreme.

So, as you traverse your career path, remember that the ability to think critically is not just an asset but the differentiator that propels you toward excellence.

Can Scientific Thinking Save the World?

A physicist, a philosopher and a psychologist walk into a classroom.

Although it sounds like a premise for a joke, this was actually the origin of a unique collaboration between Nobel Prize–winning physicist Saul Perlmutter, philosopher John Campbell and the psychologist Rob MacCoun. Spurred by what they saw as a perilously rising tide of irrationality, misinformation and sociopolitical polarization, they teamed up in 2011 to create a multidisciplinary course at the University of California, Berkeley, with the modest goal of teaching undergraduate students how to think—more specifically,  how to think like a scientist . That is, they wished to show students how to use scientific tools and techniques for solving problems, making decisions and  distinguishing reality from fantasy . The course proved popular, drawing enough interest to run for more than a decade (and counting) while sparking multiple spin-offs at other universities and institutions.

Psychology and Everyday Life: Psychology and Real-World Experiences (Unabridged‪)‬

Publisher description.

Everyday Life demonstrates how a scientific and critical thinking approach can be successful in resolving psychological concerns, and it also examines other questions that defy categorization as either scientific or non-scientific. This textbook offers a guide for how to differentiate between fact and conjecture, as well as between factual statements and misconceptions and misinformation.  While scientific and critical thinking can be beneficial in tackling psychological concerns, this textbook addresses how to differentiate between the two. Are humans able to manipulate objects with their minds without the use of any physical means? In the event that one has an out-of-body experience, does the mind actually depart from the body? The fact that we are tantalizingly near to a scientific answer to this final question may come as a surprise to you.

Main navigation

• Our Articles
• Dr. Joe's Books
• Media and Press
• Our History
• Public Lectures
• Past Newsletters

Subscribe to the OSS Weekly Newsletter!

Register for the oss 25th anniversary event, no, eating french fries is not the same as smoking cigarettes.

• Add to calendar
• Tweet Widget

This article was first published in  The Montreal Gazette.

I had never heard of psychiatrist Dr. Paul Saladino, which is somewhat surprising because he is quite frisky in the duck pond. His TikTok videos in which he tries to convince his legions of followers that dietary fibre is unnecessary, that drinking beer leads to “man boobs,” that LDL cholesterol does not increase the risk of heart disease, that oatmeal is toxic and the key to health is eating red meat, are laughable.

Saladino’s pseudoscientific rants were brought to my attention by a former student who now teaches science in Germany. He was asked by one of his students about a video in which Saladino claims that eating a serving of McDonald’s fries is equivalent to smoking a pack of 25 cigarettes.

The stimulus for this video seems to be a paper that Saladino read but was unable to properly digest. It discussed similarities between the chemical content of french fries and tobacco smoke and noted that a serving of fries can contain some carcinogenic aldehydes in amounts comparable with that found in the smoke from 25 cigarettes. In no way did the authors suggest that the risks were comparable.

Let’s note right away that there is a big difference between inhaling or ingesting a substance. Inhalation leads to direct entry into the bloodstream, while the digestive tract contains numerous enzymes that metabolize food components.

Next, tobacco smoke contains thousands of compounds, with 62 of these listed by the International Agency for Research on Cancer (IARC) as carcinogenic to humans. The most significant carcinogens in tobacco smoke are not aldehydes, but N-nitrosamines, polyaromatic hydrocarbons, aromatic amines, 1,3-butadiene, benzene and ethylene oxide. While there is no question that carcinogenic aldehydes such as crotonaldehyde can form when fats are heated, the total number of carcinogens that invade a body from a pack of cigarettes are far, far greater than from a serving of french fries.

Of course, the only way to compare the health impact of a daily serving of fries with smoking a pack a day would be to run a long-term study comparing two groups of subjects with the only difference between them being smoking or eating french fries. Clearly, this is impossible to do, but if it were carried out, I would wager that the smoker group would have a far higher incidence of cancer than the french fry group.

Fearmongering has become an industry, and Saladino is a head honcho in this arena. The usual technique is to pick a scientific study that finds some risk and then exaggerate it without taking into account type and extent of exposure. Pesticides, fluoride, oxalates, gluten, lectins and vaccines have all been unrealistically portrayed as villains. This is not to say that there are no legitimate chemical risks. We live in a very complex world, with some 160 million known chemicals, both natural and synthetic. There certainly are issues with some of these. Perfluoroalkyl substances (PFAS), bisphenol A and phthalates are present in just about everyone’s bloodstream and may indeed be causing some serious mischief.

One way or another, we are in contact with thousands of chemicals on a regular basis, and teasing out individual effects is not possible. While french fries may indeed contain some carcinogens, it does not automatically follow that eating them causes cancer. As a classic analogy, coffee contains carcinogens such as furfural, caffeic acid and styrene, but we know that coffee doesn’t cause cancer.

None of this is to say that I am willing to absolve french fries from all blame. Excessive consumption of fried foods is a problem, and not only because of the extra calories provided by the fat. When fats are heated, particularly polyunsaturated seed oils, they form a slew of potentially carcinogenic compounds.

And then there is the issue of the “Maillard reaction,” named after Louis Camille Maillard, physician turned chemist, who in 1912 described the reaction between sugars and amino acids that produces a variety of “melanoidins” responsible for the browning of toast, doughnuts and french fries. In fried potatoes, glucose and the amino acid asparagine undergo a Maillard reaction to yield acrylamide, classified by IARC as a “probable human carcinogen.”

Although associations cannot prove a cause-and-effect relationship, a study by the highly reputable Fred Hutchinson Cancer Research Center in Seattle compared about 1,500 prostate cancer patients with the same number of controls and found that regular consumption, at least once a week, of fried chicken, fried fish, doughnuts or french fries increases the risk of developing the disease.

While carcinogens in fried foods cannot be totally eliminated, they can be significantly reduced. The secret is to do your “frying” in an “air fryer.” These devices have taken kitchens by storm, including mine. Basically, they are small convection ovens in which a current passing through an element heats air that is then circulated by a fan. The basket in which the food is placed has openings to ensure heating from all sides, so covering these with parchment paper or aluminum foil in pursuit of cleanliness is counterproductive.

Although the temperature to which the air is heated, about 180-190 degrees C, is comparable with the temperature of frying oil, air is far less efficient at transferring heat to food. While deep frying takes only five or six minutes, air frying can take three times as long. However, since no oil is being used, there is no worry about its carcinogenic breakdown products. Furthermore, hot air penetrates the food less effectively than hot oil, so the inside of the food doesn’t get as hot, which means significantly less acrylamide formation.

As far as crispiness goes, that is determined by the moisture content at the food’s surface. When food is placed in a deep fryer, the immediate bubbling seen is because of steam released from its surface. Hot air does not heat the surface quite as well, but still well enough to drive out moisture and produce crispiness. In the case of fries, this can be improved by first coating the potatoes with a thin layer of oil. If you really want to reduce oil-degradation products, the best choice is avocado oil because of its extremely high smoke point. I won’t say that my “air fries” are comparable with the best double-fried restaurant version, but they are very acceptable. And healthier.

Remember that the claim of french fries being as dangerous as smoking comes from someone who thinks that lamb testicles and raw liver are healthy, and cruciferous vegetables like broccoli, Brussels sprouts, chard and kale are “bulls–t.” These, Saladino says, should be avoided because “once chewed they produce sulforaphane, which is toxic to humans.”

Actually, sulforaphane has been shown to be an anti-carcinogen. So go for your broccoli and kale. If it is taste and crispiness you are after, put them in the air fryer. As far as Saladino’s TikTok videos go, after watching a bunch of them with their confusing message, I am led to conclude that this psychiatrist needs a psychiatrist.

@JoeSchwarcz

What to read next

Twisting facts about cancer 8 may 2024.

Taking a Bite Out of the Carnivore Diet 3 May 2024

Quandary About Fats in the Diet 1 May 2024

The Best Diet for You? Here It Is 26 Apr 2024

The Folly of Water-Fuelled Vehicles 26 Apr 2024

Is Nutmeg Really Hallucinogenic? 19 Apr 2024

Department and University Information

Office for science and society.