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  • Teaching for facts seems to be less and less satisfying for the XXI century society – or at least this is the image that many educational initiatives and educational institutions around the world have been promoting for some years.
  • There is a widespread acceptance of the idea that critical thinking is a valuable asset and that it should be part of the curriculum at various levels of education. Apparently, the institutional educational world has taken sides in favor of critical thinking. Critical thinking is one of the skills for the XXI century society, one of the objectives of the standards set by the American AAAS and Research Council for science education, and its success expands to domains well beyond science, such as teaching history or reading.  
  • It would seem that all we have to do is to implement critical thinking in our courses at different levels of education, probably. However, things are not that simple.First, in the opposite direction and simultaneously, we are invited to free our natural intuition, the so-called experiential wisdom, and even to trust our gut feelings in the face of scientific results (sometimes with terrible consequence, as described in Specter, 2009). Should/could we trust our “intuition”? The answer to this question is relevant for education.  However, and this is the second and major difficulty, there’s no consensus about how to teach it, whether it can be learnt, and even about what is it.
  • A report published in 1987 in the USA expresses the will and reveals the difficulties of educating higher skills such as critical thinking (Psychologists involved in the report include Jerome Bruner, Susan Carey, John Bransford and Ann Brown, authors of How people learn, Robert Ennis, one of the representatives of the literature on critical thinking), Carol Dweck, …: 
  • A paper published 20 years after, restates the same conclusions and adds the consideration that after all this time and efforts to teach students to think critically, one should admit that thinking critically cannot be taught – because it is not a skill that one can learn once and for all, but critically depends on contents and thus on domain-specific knowledge and practices.
  • The first difficulty concerns the definition of what is it to think critically. The first difficulties arise with the very question of what is meant by the term “higher order skills.” Many candidate definitions are available. Philosophers promote critical thinking and logical reasoning skills, developmental psychologists point to metacognition, and cognitive scientists study cognitive strategies and heuristics. Educators advocate training in study skills and problem solving.How should we make sense of these many labels? Do critical thinking, metacognition, cognitive strategies, and study skills refer to the same kinds of capabilities? And how are they related to the problem-solving abilities that mathematicians, scientists, and engineers try to teach their students? (Resnick 1987)Literature on critical thinking stems at least from three different traditions: philosophy cognitive psychologyeducation.
  • Critical thinking can be considered as part of higher order thinking. A definition of higher order thinkingcan be found in (Resnick 1987): Higher order thinking is nonalgorithmic. That is, the path of action is not fully specified in advance.Higher order thinking tends to be complex. The total path is not “visible” (mentally speaking) from any single vantage point.Higher order thinking often yields multiple solutions, each with costs and benefits, rather than unique solutions.Higher order thinking involves nuanced judgment and interpretation.Higher order thinking involves the application of multiple criteria, which sometimes conflict with one another.Higher order thinking often involves uncertainty. Not everything that bears on the task at hand is known.Higher order thinking involves self-regulation of the thinking process. We do not recognize higher order thinking in an individual when someone else “calls the plays” at every step.Higher order thinking involves imposing meaning, finding structure in apparent disorder.Higher order thinking is effortful. There is considerable mental work involved in the kinds of elaborations and judgments required. (Resnick 1987 p. 7)
  • Critical thinking can also be defined at minima, as the faculty of parting wheat from chaff, of distinguishing good arguments from bad ones (because they are ill-formed) and identifying beliefs that can be given away (because they are not justified). It is at the same time a general - because it does not say much - and a restrictive definition of critical thinking – because it equates critical thinking with skeptical thinking (they K is important and is not just a matter of US vs UK English). Late Carl Sagan used to describe science as a candle in the dark, and science education as a shield against pseudo-science and superstition. (Sagan 1996) includes a list of the tools one needs to master in order to appraise critically new ideas (the contents of knowledge behind the capacity of thinking critically): the Baloney Detection Kit (BDK). The BDK includes two kinds of tools: procedures for the evaluation of evidence and a list of fallacies that one should be able to identify in others’ and in one’s own arguments.  “If the new idea survives examination by the tools in our kit, we grant it warm, although tentative, acceptance.” (Sagan 1996, p. 210). “Like all tools, the baloney detection kit can be misused, applied out of context, or even employed as a rote alternative to thinking. But applied judiciously, it can make all the difference in the world – not least in evaluating our own arguments before we present them to others.” (Sagan 1996, p. 216). The kit is an inspiration for today’s skeptics, but Carl Sagan used to teach critical thinking at Cornell University, within the Department of Astronomy, and the BDK was part of it. The course is presently hold by YervantTerzian, physicist, but it is not bound to the domains of astronomy and physics.  « Students in Astronomy 490, a seminar on “critical thinking” originally taught by the late Carl Sagan and revived by astronomer YervantTerzian, ponder questions more typical of a philosophy course: “Can machines think?” “Is immortality around the corner?” “What is the debate between science and religion?” “The teaching of science or scientific thought is not the most important thing, nor the goal of the class,” says Terzian, the David Duncan Professor in the Physical Sciences. “[The goal] is the ability to critically think about various issues” » (http://www.astro.cornell.edu/academics/course-detail.php?course_instance_id=325&semester=&year=). 
  • - In 1990, Peter Facione publishes a Delphi Report with a statement of expert consensus (mostly philosophers, but also a meaningful amount of educators and social scientists, and a small amount of scientists) on critical thinking. The consensus presents the critical thinker as an ideal logical and scientifically-minded person that has good habits of mind independent from any context or domain. However it is recognized that, for thinking critically in specific domains, content knowledge is necessary, critical thinking is conceptualized in analogy with reading and writing: skills that apply in any areas of life and learning and do not depend on content. The education of critical thinking thus aims at producing the ideal thinker that thinks critically in every occasion of her life, because she possesses the right skills and has a disposition to use them. Skills without a disposition are not enough and the philosophical approach clearly distinguishes the ability to think critically from the disposition to do it.  We understand critical thinking to be 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. CT is essential as a tool of inquiry. As such, CT is a liberating force in education and a powerful resource in one's personal and civic life. While not synonymous with good thinking, CT is a pervasive and self-rectifying human phenomenon. The ideal critical thinker is habitually inquisitive, well-informed, trustful of reason, open-minded, flexible, fair-minded in evaluation, honest in facing personal biases, prudent in making judgments, willing to reconsider, clear about issues, orderly in complex matters, diligent in seeking relevant information, reasonable in the selection of criteria, focused in inquiry, and persistent in seeking results which are as precise as the subject and the circumstances of inquiry permit. Thus, educating good critical thinkers means working toward this ideal. It combines developing CT skills with nurturing those dispositions which consistently yield useful insights and which are the basis of a rational and democratic society. (Facione 1990) The ideal critical thinker is a bit of an ideal, and appears far from the reality of the human nature.
  • Let us briefly review the characteristics of the three main approaches to critical thinking – 1. the philosophical, normative approach, 2. the cognitive psychology, descriptive one, 3. the educational, pragmatic one – and then add an epistemological and moral dimension to critical thinking.The philosophical, normative approach to critical thinking This definition refers to both the development of rules of informal logic and of the scientific method. It is thus part of the philosophical tradition of reflection upon how to shape the mind, eventually the scientific mind, and obtain good thinking (a normative stance):  Critical thinking is at the heart of the logic of valid argumentation that has seen the light in the ancient Greece of Socrates (Socrates’ elenchus, as portrayed in Plato’s dialogues), Aristotle and the Skeptics, of Thomas Aquinas, of Descartes’ Rules for the direction of the mind, of the accent the Hobbes put on facts and reasoning. As opposed to idola, critical thinking is at the heart of the modern scientific thinking of Francis Bacon’s The advancement of learning, as well as of theScepticalChymist of Robert Boyle and of Galileo’s method (Paul, Elder, Bartell, 1997). In modern times, the philosophical approach is represented by Matthew Lipman, Richard Paul, Robert Ennis, John McPeck, and others (see Lai 2011). The approach includes norms for spotting fallacies in arguments, an ideal view of the critical thinker and the setting of standards of good thinking. It focuses on reasoning, informal logic, and argumentation.  Definitions of critical thinking emerging from the philosophical tradition include   “the propensity and skill to engage in an activity with reflective skepticism” (McPeck, 1981, p. 8);   “reflective and reasonable thinking that is focused on deciding what to believe or do” (Ennis, 1985, p. 45);   “skillful, responsible thinking that facilitates good judgment because it 1) relies upon criteria, 2) is self-correcting, and 3) is sensitive tocontext” (Lipman, 1988, p. 39);   “purposeful, self-regulatory judgment which results in interpretation, analysis, evaluation, and inference, as well as explanation of the evidential, conceptual, methodological, criteriological, or conceptual considerations upon which that judgment is based” (Facione, 1990, p. 3);   “disciplined, self-directed thinking that exemplifies the perfections of thinking appropriate to a particular mode or domain of thought” (Paul, 1992, p. 9);   thinking that is goal-directed and purposive, “thinking aimed at forming a judgment,” where the thinking itself meets standards of adequacy and accuracy (Bailin et al., 1999b, p. 287); and   “judging in a reflective way what to do or what to believe” (Facione, 2000, p. 61). (Lai 2011) - Matthew Lipman has promoted philosophy education for young children, by creating an Institute for the Advancement of Philosphy for Children (http://www.montclair.edu/cehs/academics/centers-and-institutes/iapc/index.html), as well as educational resources, such as the Harry Stottlemeier’s series of books (the first one published in 1974). It was during the contentious years of the Vietnam War that Matthew Lipman, a philosopher and educator, found that many Americans were having trouble presenting their views about the conflict cogently, and it distressed him. Professor Lipman, who was teaching at Columbia University at the time, concluded that many adults could simply not reason well for themselves, and he feared that it was too late for them to learn. So he responded with a radical idea: to teach children philosophy — or specifically “the cultivation of excellent thinking” — beginning in pre-kindergarten and continuing through high school. (http://www.nytimes.com/2011/01/15/education/15lipman.html?_r=0) There are two interesting considerations in Lipman’s work: the first is that critical thinking has a life well beyond the prep room or the lab; the other is that even children as young as six years old can have a grasp of abstract matter, contrarily to what affirmed by Jean Piaget, who was the dogma at the time. Initially, the focus of the Institute’s program was on logic, then it grew to include epistemological and moral notions like truth and justice. The method is nevertheless always the same, and resembles in a certain way to inquiry-based science education: children sit in a circle (community of inquiry) and read a work of fiction that prompts philosophical discussions; guided by the teacher and then on their own, they explore and debate the questions that arise from the text. - In 1990, Peter Facione publishes a Delphi Report with a statement of expert consensus (mostly philosophers, but also a meaningful amount of educators and social scientists, and a small amount of scientists) on critical thinking. The consensus presents the critical thinker as an ideal logical and scientifically-minded person that has good habits of mind independent from any context or domain. However it is recognized that, for thinking critically in specific domains, content knowledge is necessary, critical thinking is conceptualized in analogy with reading and writing: skills that apply in any areas of life and learning and do not depend on content. The education of critical thinking thus aims at producing the ideal thinker that thinks critically in every occasion of her life, because she possesses the right skills and has a disposition to use them. Skills without a disposition are not enough and the philosophical approach clearly distinguishes the ability to think critically from the disposition to do it.  We understand critical thinking to be 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. CT is essential as a tool of inquiry. As such, CT is a liberating force in education and a powerful resource in one's personal and civic life. While not synonymous with good thinking, CT is a pervasive and self-rectifying human phenomenon. The ideal critical thinker is habitually inquisitive, well-informed, trustful of reason, open-minded, flexible, fair-minded in evaluation, honest in facing personal biases, prudent in making judgments, willing to reconsider, clear about issues, orderly in complex matters, diligent in seeking relevant information, reasonable in the selection of criteria, focused in inquiry, and persistent in seeking results which are as precise as the subject and the circumstances of inquiry permit. Thus, educating good critical thinkers means working toward this ideal. It combines developing CT skills with nurturing those dispositions which consistently yield useful insights and which are the basis of a rational and democratic society. (Facione 1990) The ideal critical thinker is a bit of an ideal, and appears far from the reality of the human nature.
  • 1. The philosophical, normative approach to critical thinking  In modern times, the philosophical approach is represented by Matthew Lipman, Richard Paul, Robert Ennis, John McPeck, and others (see Lai 2011). The approach includes norms for spotting fallacies in arguments, an ideal view of the critical thinker and the setting of standards of good thinking. It focuses on reasoning, informal logic, and argumentation.  Definitions of critical thinking emerging from the philosophical tradition include   “the propensity and skill to engage in an activity with reflective skepticism” (McPeck, 1981, p. 8);   “reflective and reasonable thinking that is focused on deciding what to believe or do” (Ennis, 1985, p. 45);   “skillful, responsible thinking that facilitates good judgment because it 1) relies upon criteria, 2) is self-correcting, and 3) is sensitive tocontext” (Lipman, 1988, p. 39);   “purposeful, self-regulatory judgment which results in interpretation, analysis, evaluation, and inference, as well as explanation of the evidential, conceptual, methodological, criteriological, or conceptual considerations upon which that judgment is based” (Facione, 1990, p. 3);   “disciplined, self-directed thinking that exemplifies the perfections of thinking appropriate to a particular mode or domain of thought” (Paul, 1992, p. 9);   thinking that is goal-directed and purposive, “thinking aimed at forming a judgment,” where the thinking itself meets standards of adequacy and accuracy (Bailin et al., 1999b, p. 287); and   “judging in a reflective way what to do or what to believe” (Facione, 2000, p. 61). (Lai 2011) - Matthew Lipman has promoted philosophy education for young children, by creating an Institute for the Advancement of Philosphy for Children (http://www.montclair.edu/cehs/academics/centers-and-institutes/iapc/index.html), as well as educational resources, such as the Harry Stottlemeier’s series of books (the first one published in 1974). It was during the contentious years of the Vietnam War that Matthew Lipman, a philosopher and educator, found that many Americans were having trouble presenting their views about the conflict cogently, and it distressed him. Professor Lipman, who was teaching at Columbia University at the time, concluded that many adults could simply not reason well for themselves, and he feared that it was too late for them to learn. So he responded with a radical idea: to teach children philosophy — or specifically “the cultivation of excellent thinking” — beginning in pre-kindergarten and continuing through high school. (http://www.nytimes.com/2011/01/15/education/15lipman.html?_r=0) There are two interesting considerations in Lipman’s work: the first is that critical thinking has a life well beyond the prep room or the lab; the other is that even children as young as six years old can have a grasp of abstract matter, contrarily to what affirmed by Jean Piaget, who was the dogma at the time. Initially, the focus of the Institute’s program was on logic, then it grew to include epistemological and moral notions like truth and justice. The method is nevertheless always the same, and resembles in a certain way to inquiry-based science education: children sit in a circle (community of inquiry) and read a work of fiction that prompts philosophical discussions; guided by the teacher and then on their own, they explore and debate the questions that arise from the text. - In 1990, Peter Facione publishes a Delphi Report with a statement of expert consensus (mostly philosophers, but also a meaningful amount of educators and social scientists, and a small amount of scientists) on critical thinking. The consensus presents the critical thinker as an ideal logical and scientifically-minded person that has good habits of mind independent from any context or domain. However it is recognized that, for thinking critically in specific domains, content knowledge is necessary, critical thinking is conceptualized in analogy with reading and writing: skills that apply in any areas of life and learning and do not depend on content. The education of critical thinking thus aims at producing the ideal thinker that thinks critically in every occasion of her life, because she possesses the right skills and has a disposition to use them. Skills without a disposition are not enough and the philosophical approach clearly distinguishes the ability to think critically from the disposition to do it.  We understand critical thinking to be 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. CT is essential as a tool of inquiry. As such, CT is a liberating force in education and a powerful resource in one's personal and civic life. While not synonymous with good thinking, CT is a pervasive and self-rectifying human phenomenon. The ideal critical thinker is habitually inquisitive, well-informed, trustful of reason, open-minded, flexible, fair-minded in evaluation, honest in facing personal biases, prudent in making judgments, willing to reconsider, clear about issues, orderly in complex matters, diligent in seeking relevant information, reasonable in the selection of criteria, focused in inquiry, and persistent in seeking results which are as precise as the subject and the circumstances of inquiry permit. Thus, educating good critical thinkers means working toward this ideal. It combines developing CT skills with nurturing those dispositions which consistently yield useful insights and which are the basis of a rational and democratic society. (Facione 1990) The ideal critical thinker is a bit of an ideal, and appears far from the reality of the human nature.
  • 2. The cognitive psychology, descriptive approach to critical thinking The psychological approach has tended to focus on how people really think, namely on how experts think in their domain, and whether experts in different domains share skills and procedures that can be considered as general requirements for thinking critically. Skills and procedures are especially important in this view and definitions of critical thinking include lists of skills and procedures implemented by “good thinkers”. Among these, meta-cognitive skills and problem solving skills are pre-eminent (Bransford et al 1984; Resnick 1997). However, the cognitive approach tends to deal more with the kind of good thinking that experts show in their domain and share with other experts, with meta-cognition and with reading with understanding, with scientific thinking and its education, than with critical thinking in itself. In fact, apparently, and according to Tim van Gelder: cognitive scientists do not study critical thinking much, at least not as a topic in its own right. This is partly because the topic is too broad and open-ended to be captured by the cognitive scientist’s tightly focuses techniques. Partly, it is also because critical thinking in general is a neglected topic, despite its importance and broad relevance. Nevertheless, cognitive scientists have some contributions to make. They have developed some very general insights into how we think and how we learn, and these can be carried over to critical thinking. They also have studied many phenomena that are particular aspects or dimensions of critical thinking. (van Gelder 2005) Representatives of the cognitive psychology approach to critical thinking include Robert Sternberg (Sternberg, 1986; Sternberg, Roediger III, Halpern, 2007) and Diane Halpern (Halpern 1992, 2003; Halpern & Riggio, 2003); more recently Tim van Gelder and Daniel Willingham have contributed with two analyses of the difficulties and strategies for teaching critical thinking that include a cognitive view of it.  van Gelder’s approach to critical thinking strongly relies on the literature on expertise, but also on more general insights about learning and thinking; on these grounds, he proposes the following view: critical thinking is hard and it is a form of expertise based on deliberate practice.  Critical thinking is hard, for at least two reasons. The first is related to our nature: because of the brain we have inherited through evolution, we have intrinsic tendencies toward illusions and biases; van Gelder re-states that  humans are not naturally critical. Indeed, like ballet, critical thinking is a highly contrived activity. Running is natural; nightclub dancing is less so; but ballet is something people can only do well with many years of painful, expensive, dedicated training. Evolution did not intend us to walk on the ends of our toes, and whatever Aristotle might have said, we were not designed to be at all that critical either. Evolution foes not waste effort making things better than they need to be, and homo sapiens evolved to be just logical enough to survive, while competitors such as Neanderthals and mastodons died out. (van Gelder 2005) However, the difficulty at acquiring critical thinking habits and skills might also depend on the very nature of critical thinking as a higher-order cognitive capacity that builds upon simpler ones and uses them in a certain order: Even if humans were naturally inclined to think critically, it would still be difficult to master because it is what cognitive scientists call a “higher-order skill”. That is, critical thinking is a complex activity built up out of other skills that are simpler and easier to acquire. … Furthermore, even if the lower-level skills have been mastered, they have to be combined in the right way.. . Because critical thinking is so difficult, it tales a long tome to become good at it. As a rule of thumb my guess is that mastering critical thinking is about as difficult as becoming fluent in a second language. (van Gelder 2005) Critical thinking is a form of expertise: it does not happen overnight, it cannot be learnt by reading about critical thinking, but, as any other skilled action, it requires practice. Practice and expertise, or: becoming good at something, are the domain of Karl Anders Ericsson. Van Gelder proposes to import the lessons that Ericsson has extracted from his research on experts in the teaching of critical thinking. Namely, Ericcson has developed a view of the kind of practice that leads to expertise in domains as different as chess, violin playing, golf that he calls “deliberate practice” (e.g. Ericcson, Krampe, Tesch-Römer, 1993). The accent on practice should not make us forget the importance of theory and of teaching the theory of critical thinking: the same study of expertise shows that it won’t be simply picked up from practice.  Although Ericsson did not study critical thinking specifically, it is reasonable to assume that his conclusions will hold true for critical thinking. This means that our students will improve their critical thinking skills most effectively just to the extent they engage in lots of deliberate practice in critical thinking. (van Gelder 2005) However, deliberate practice does not suffice to warrant “general critical thinking” skills to develop. Transfer happens but it is more difficult than one expects, and this consideration applies to critical thinking as well. Indeed critical thinking is especially vulnerable to the problem of transfer because critical thinking is intrinsically general in nature. Critical thinking skills are, by definition, ones that apply in a very wide range of domains, contexts, and so on…The closest thing we have to a solution to the transfer problem is the recognition that there is a problem that must be confronted head-on. As psychologist Dianne Halpern put it (1998), we must teach for transfer.  As a practical tool for enhancing critical thinking, van Gelder suggests the use of argument mapping for simplifying the cognitive task of manipulating many arguments simultaneously.  Daniel Willingham, cognitive psychologist involved in education, has summarized the cognitive scientist’s point of view on critical thinking: the mental activities that are typically called critical thinking are actually a subset of three types of thinking: reasoning, making judgments and decisions, and problem solving. I say that critical thinking is a subset of these because we think in these ways all the time, but only sometimes in a critical way. Deciding to read this article, for example, is not critical thinking. But carefully weighing the evidence it presents in order to decide whether or not to believe what it says is. Critical reasoning, decision making, and problem solving—which, for brevity’s sake, I will refer to as critical thinking—have three key features: effectiveness, novelty, and self-direction. Critical thinking is effective in that it avoids common pitfalls, such as seeing only one side of an issue, discounting new evidence that disconfirms your ideas, reasoning from passion rather than logic, failing to support statements with evidence, and so on. Critical thinking is novel in that you don’t simply remember a solution or situation that is similar enough to guide you. For example, solving a complex but familiar physics problem by applying a multi-step algorithm isn’t critical thinking because you are really drawing on memory to solve the problem. But devising a new algorithm is critical thinking. Critical thinking is self-directed in that the thinker must be calling the shots: We wouldn’t give a student much credit for critical thinking if the teacher were prompting each step he took. (Willingham 2007)The ideas of novelty and self-direction are not explicit in van Gelder’s account and can be considered analogous to the philosopher’s idea of disposition, and an answer to the philosopher’s criticism that performing steps that lead to good thinking is not enough if it is done automatically and mechanically.  The dispositional dimension is often absent from the cognitive approach, thus raising the criticism, on the side of philosophers, that performing a number of steps (such as the ones suggested by van Gelder) automatically and uncritically cannot count as critical thinking. Bailin (2002) is exemplary of this type of criticism. However, Bailin is also critical towards the content-free domain-general view of critical thinking that belongs to the philosophical tradition.  For Bailin, conceptualizing critical thinking as mental processes is problematic because mental processes cannot be directly observed but only inferred from the behavior of someone who has accomplished a task which requires critical thinking. According to her the assumption that there is a mental process which corresponds to each kind of thinking task represents an unwarranted reification. (Bailin 2002). It is not that each thinking task has a corresponding mental process, and that each time that a certain mental act is accomplished that one and the same mental process is at stake, according to Bailin. On the other side, conceptualizing critical thinking in terms of a set of procedures that one carries on does not guarantee that one is thinking critically, and not just carelessly, superficially, unreflectively – uncritically – adopt a set of procedures. Moreover, these approaches are purely descriptive: they describe what the critical thinker does (her abilities, the procedures she puts in place) but lack a normative dimension. Critical thinking is, however, centrally a normative concept. It refers to good thinking. It is the quality of the thinking which  distinguishes critical from uncritical thinking, and this quality is determined by the degree to which the thinking meets the relevant standards and criteria. It is, then, the adherence to certain criteria which is the defining characteristic of critical thinking. An account of critical thinking in terms of processes omits what is most central to critical thinking. (Bailin 2002)According to Bailin, norms cannot be reduced to procedures because criteria cannot be completely proceduralized; seemingly, skills only can be taken as including norms when they are used as in the sentence “a skilled thinker”: someone who meets the criteria for good thinking. In fact, there can be different ways to attain a certain form of good thinking, not only one procedure fits all.  Such procedures are often really heuristics, i.e., useful suggestions which point to aspects to be attended to and which may be helpful but are not necessary to solving the problem. There are, after all, often different ways to solve a problem. There are however, some cases where some detailed procedure is necessary in order for thinking in that context to qualify as critical thinking, for instance, controlling an experiment or verifying a result in science. Such procedures do, however, have criteria built in to what it means to carry them on. (Bailin 2002) I have argued, then, that it is a mistake to conceptualize critical thinking in terms of skills or processes. Rather, a justifiable conception of critical thinking must be explicitly normative, focusing on the adherence to criteria and standards. Such a focus is central to all the main philosophical accounts of critical thinking (e.g., Ennis 1985; Siegel 1988; Lipman 1991). The pedagogical focus can then shift from issues relating to application of processes and the acquisition of skills, with all the attendant conceptual problems, to the question of what one needs to understand in order to meet the criteria of good thinking in particular contexts. Such understandings include criteria, concepts, and habits of mind as well as background knowledge (Bailin et al. 1999b). …Since the adherence to the criteria which govern quality thinking and judgment in the particular area is the defining characteristic of critical thinking, it follows that the most important intellectual resource is knowledge of these criteria. Some of the criteria which apply in science include accuracy of data, control of experimental variables, reliability of sources, and validity of inferences. Another key type of intellectual resource is constituted by the many concepts which mark certain distinctions in an area or pick out certain aspects which are central to the area. Such concepts as necessary and sufficient conditions, correlation and causation, and hypothesis and prediction provide invaluable tools for critical analysis and evaluation in science. Background knowledge in the relevant area is also an important determinant of the quality of thinking in the area and is thus central to the making of reasoned judgments. In addition, there may be some strategies or heuristics which, although not central to critical thinking, may be useful in the course of arriving at reasoned judgments. Finally, the mastery of the other intellectual resources is insufficient if an individual does not have a basic commitment to rational inquiry which disposes her to deploy the resources and the attitudes or habits of mind which characterize critical thinking. These include respect for reasons, an inquiring attitude, open-mindedness, and fair-mindedness, among others (Bailin et al. 1999b).  (Bailin 2002) In other words, Bailin proposes a philosophical, normative approach to educating critical thinking, but one that leads to rethink the generalizability and transferability of critical thinking and fits well, as we shall see, with considerations that arise from education and cognitive psychology: that the observation that generalization and transfer are overstated. Without being enough for good thinking in a certain discipline, background knowledge is necessary. For consequence, someone lacking background knowledge, but impregnated with knowledge of the criteria (that experiments must be controlled, inferences must be valid, experimental data must be accurate, and so on) will not necessarily produce good thinking. Not only, but even the criteria for good thinking are specific of certain areas, those for good reading or good thinking in history being eventually different from those for good thinking in a particular domain of science. There can be general heuristics that apply everywhere, but they are general, hence not central to good thinking, but only helpful. The idea behind this approach is that critical thinking is essentially captured by norms that are context and content specific, thus that cannot rest on general skills and procedures only but have also to do without knowledge as specific to a certain domain or content of thinking.
  • 2. The cognitive psychology, descriptive approach to critical thinking The psychological approach has tended to focus on how people really think, namely on how experts think in their domain, and whether experts in different domains share skills and procedures that can be considered as general requirements for thinking critically. Skills and procedures are especially important in this view and definitions of critical thinking include lists of skills and procedures implemented by “good thinkers”. Among these, meta-cognitive skills and problem solving skills are pre-eminent (Bransford et al 1984; Resnick 1997). However, the cognitive approach tends to deal more with the kind of good thinking that experts show in their domain and share with other experts, with meta-cognition and with reading with understanding, with scientific thinking and its education, than with critical thinking in itself. In fact, apparently, and according to Tim van Gelder: cognitive scientists do not study critical thinking much, at least not as a topic in its own right. This is partly because the topic is too broad and open-ended to be captured by the cognitive scientist’s tightly focuses techniques. Partly, it is also because critical thinking in general is a neglected topic, despite its importance and broad relevance. Nevertheless, cognitive scientists have some contributions to make. They have developed some very general insights into how we think and how we learn, and these can be carried over to critical thinking. They also have studied many phenomena that are particular aspects or dimensions of critical thinking. (van Gelder 2005) Representatives of the cognitive psychology approach to critical thinking include Robert Sternberg (Sternberg, 1986; Sternberg, Roediger III, Halpern, 2007) and Diane Halpern (Halpern 1992, 2003; Halpern & Riggio, 2003); more recently Tim van Gelder and Daniel Willingham have contributed with two analyses of the difficulties and strategies for teaching critical thinking that include a cognitive view of it.  van Gelder’s approach to critical thinking strongly relies on the literature on expertise, but also on more general insights about learning and thinking; on these grounds, he proposes the following view: critical thinking is hard and it is a form of expertise based on deliberate practice.  Critical thinking is hard, for at least two reasons. The first is related to our nature: because of the brain we have inherited through evolution, we have intrinsic tendencies toward illusions and biases; van Gelder re-states that  humans are not naturally critical. Indeed, like ballet, critical thinking is a highly contrived activity. Running is natural; nightclub dancing is less so; but ballet is something people can only do well with many years of painful, expensive, dedicated training. Evolution did not intend us to walk on the ends of our toes, and whatever Aristotle might have said, we were not designed to be at all that critical either. Evolution foes not waste effort making things better than they need to be, and homo sapiens evolved to be just logical enough to survive, while competitors such as Neanderthals and mastodons died out. (van Gelder 2005) However, the difficulty at acquiring critical thinking habits and skills might also depend on the very nature of critical thinking as a higher-order cognitive capacity that builds upon simpler ones and uses them in a certain order: Even if humans were naturally inclined to think critically, it would still be difficult to master because it is what cognitive scientists call a “higher-order skill”. That is, critical thinking is a complex activity built up out of other skills that are simpler and easier to acquire. … Furthermore, even if the lower-level skills have been mastered, they have to be combined in the right way.. . Because critical thinking is so difficult, it tales a long tome to become good at it. As a rule of thumb my guess is that mastering critical thinking is about as difficult as becoming fluent in a second language. (van Gelder 2005) Critical thinking is a form of expertise: it does not happen overnight, it cannot be learnt by reading about critical thinking, but, as any other skilled action, it requires practice. Practice and expertise, or: becoming good at something, are the domain of Karl Anders Ericsson. Van Gelder proposes to import the lessons that Ericsson has extracted from his research on experts in the teaching of critical thinking. Namely, Ericcson has developed a view of the kind of practice that leads to expertise in domains as different as chess, violin playing, golf that he calls “deliberate practice” (e.g. Ericcson, Krampe, Tesch-Römer, 1993). The accent on practice should not make us forget the importance of theory and of teaching the theory of critical thinking: the same study of expertise shows that it won’t be simply picked up from practice.  Although Ericsson did not study critical thinking specifically, it is reasonable to assume that his conclusions will hold true for critical thinking. This means that our students will improve their critical thinking skills most effectively just to the extent they engage in lots of deliberate practice in critical thinking. (van Gelder 2005) However, deliberate practice does not suffice to warrant “general critical thinking” skills to develop. Transfer happens but it is more difficult than one expects, and this consideration applies to critical thinking as well. Indeed critical thinking is especially vulnerable to the problem of transfer because critical thinking is intrinsically general in nature. Critical thinking skills are, by definition, ones that apply in a very wide range of domains, contexts, and so on…The closest thing we have to a solution to the transfer problem is the recognition that there is a problem that must be confronted head-on. As psychologist Dianne Halpern put it (1998), we must teach for transfer.  As a practical tool for enhancing critical thinking, van Gelder suggests the use of argument mapping for simplifying the cognitive task of manipulating many arguments simultaneously.  Daniel Willingham, cognitive psychologist involved in education, has summarized the cognitive scientist’s point of view on critical thinking: the mental activities that are typically called critical thinking are actually a subset of three types of thinking: reasoning, making judgments and decisions, and problem solving. I say that critical thinking is a subset of these because we think in these ways all the time, but only sometimes in a critical way. Deciding to read this article, for example, is not critical thinking. But carefully weighing the evidence it presents in order to decide whether or not to believe what it says is. Critical reasoning, decision making, and problem solving—which, for brevity’s sake, I will refer to as critical thinking—have three key features: effectiveness, novelty, and self-direction. Critical thinking is effective in that it avoids common pitfalls, such as seeing only one side of an issue, discounting new evidence that disconfirms your ideas, reasoning from passion rather than logic, failing to support statements with evidence, and so on. Critical thinking is novel in that you don’t simply remember a solution or situation that is similar enough to guide you. For example, solving a complex but familiar physics problem by applying a multi-step algorithm isn’t critical thinking because you are really drawing on memory to solve the problem. But devising a new algorithm is critical thinking. Critical thinking is self-directed in that the thinker must be calling the shots: We wouldn’t give a student much credit for critical thinking if the teacher were prompting each step he took. (Willingham 2007)The ideas of novelty and self-direction are not explicit in van Gelder’s account and can be considered analogous to the philosopher’s idea of disposition, and an answer to the philosopher’s criticism that performing steps that lead to good thinking is not enough if it is done automatically and mechanically.  The dispositional dimension is often absent from the cognitive approach, thus raising the criticism, on the side of philosophers, that performing a number of steps (such as the ones suggested by van Gelder) automatically and uncritically cannot count as critical thinking. Bailin (2002) is exemplary of this type of criticism. However, Bailin is also critical towards the content-free domain-general view of critical thinking that belongs to the philosophical tradition.  For Bailin, conceptualizing critical thinking as mental processes is problematic because mental processes cannot be directly observed but only inferred from the behavior of someone who has accomplished a task which requires critical thinking. According to her the assumption that there is a mental process which corresponds to each kind of thinking task represents an unwarranted reification. (Bailin 2002). It is not that each thinking task has a corresponding mental process, and that each time that a certain mental act is accomplished that one and the same mental process is at stake, according to Bailin. On the other side, conceptualizing critical thinking in terms of a set of procedures that one carries on does not guarantee that one is thinking critically, and not just carelessly, superficially, unreflectively – uncritically – adopt a set of procedures. Moreover, these approaches are purely descriptive: they describe what the critical thinker does (her abilities, the procedures she puts in place) but lack a normative dimension. Critical thinking is, however, centrally a normative concept. It refers to good thinking. It is the quality of the thinking which  distinguishes critical from uncritical thinking, and this quality is determined by the degree to which the thinking meets the relevant standards and criteria. It is, then, the adherence to certain criteria which is the defining characteristic of critical thinking. An account of critical thinking in terms of processes omits what is most central to critical thinking. (Bailin 2002)According to Bailin, norms cannot be reduced to procedures because criteria cannot be completely proceduralized; seemingly, skills only can be taken as including norms when they are used as in the sentence “a skilled thinker”: someone who meets the criteria for good thinking. In fact, there can be different ways to attain a certain form of good thinking, not only one procedure fits all.  Such procedures are often really heuristics, i.e., useful suggestions which point to aspects to be attended to and which may be helpful but are not necessary to solving the problem. There are, after all, often different ways to solve a problem. There are however, some cases where some detailed procedure is necessary in order for thinking in that context to qualify as critical thinking, for instance, controlling an experiment or verifying a result in science. Such procedures do, however, have criteria built in to what it means to carry them on. (Bailin 2002) I have argued, then, that it is a mistake to conceptualize critical thinking in terms of skills or processes. Rather, a justifiable conception of critical thinking must be explicitly normative, focusing on the adherence to criteria and standards. Such a focus is central to all the main philosophical accounts of critical thinking (e.g., Ennis 1985; Siegel 1988; Lipman 1991). The pedagogical focus can then shift from issues relating to application of processes and the acquisition of skills, with all the attendant conceptual problems, to the question of what one needs to understand in order to meet the criteria of good thinking in particular contexts. Such understandings include criteria, concepts, and habits of mind as well as background knowledge (Bailin et al. 1999b). …Since the adherence to the criteria which govern quality thinking and judgment in the particular area is the defining characteristic of critical thinking, it follows that the most important intellectual resource is knowledge of these criteria. Some of the criteria which apply in science include accuracy of data, control of experimental variables, reliability of sources, and validity of inferences. Another key type of intellectual resource is constituted by the many concepts which mark certain distinctions in an area or pick out certain aspects which are central to the area. Such concepts as necessary and sufficient conditions, correlation and causation, and hypothesis and prediction provide invaluable tools for critical analysis and evaluation in science. Background knowledge in the relevant area is also an important determinant of the quality of thinking in the area and is thus central to the making of reasoned judgments. In addition, there may be some strategies or heuristics which, although not central to critical thinking, may be useful in the course of arriving at reasoned judgments. Finally, the mastery of the other intellectual resources is insufficient if an individual does not have a basic commitment to rational inquiry which disposes her to deploy the resources and the attitudes or habits of mind which characterize critical thinking. These include respect for reasons, an inquiring attitude, open-mindedness, and fair-mindedness, among others (Bailin et al. 1999b).  (Bailin 2002) In other words, Bailin proposes a philosophical, normative approach to educating critical thinking, but one that leads to rethink the generalizability and transferability of critical thinking and fits well, as we shall see, with considerations that arise from education and cognitive psychology: that the observation that generalization and transfer are overstated. Without being enough for good thinking in a certain discipline, background knowledge is necessary. For consequence, someone lacking background knowledge, but impregnated with knowledge of the criteria (that experiments must be controlled, inferences must be valid, experimental data must be accurate, and so on) will not necessarily produce good thinking. Not only, but even the criteria for good thinking are specific of certain areas, those for good reading or good thinking in history being eventually different from those for good thinking in a particular domain of science. There can be general heuristics that apply everywhere, but they are general, hence not central to good thinking, but only helpful. The idea behind this approach is that critical thinking is essentially captured by norms that are context and content specific, thus that cannot rest on general skills and procedures only but have also to do without knowledge as specific to a certain domain or content of thinking.
  • This idea of teaching for critical thinking (in modern education) goes back at least to John Dewey’s idea of teaching for reflexive thought, that is, of a certain form of critical, reflexive thinking as the very objective of education. Reflexive thought consists in the activity of evaluating the degree of probability that a certain belief is true, and to accordingly accept it or refuse it, on the ground of the analysis of the facts and arguments. Reflexive thinking is composed of two movements: an act of investigation and research: study of the fact and examination and revision of evidence, definition of the different hypotheses and their implications, comparison between hypotheses and of the hypotheses with facts of observation adoption of a skeptical attitude: in order to investigate, one must doubt, hesitate, be perplexed; the skeptical attitude is opposed to the attitude that consists in accepting beliefs because of tradition, instruction, imitation (authority) or because of emotions and possible advantages.Unfortunately human beings are not natural “reflexive thinkers”, and our intelligence is not a protection against mistake and the accumulation of misconceptions.  «Dreams, the position of the stars, the lines of the hand, may be regarded as valuable signs, and the fall of cards as an inevitable omen, while natural events of the most crucial significance go disregarded. Beliefs in portents of various kinds, now mere nook and cranny superstitions, were once universal. A long discipline of exact science was required for their conquest. » (Dewey, 1910, p. 21) Humans tend to accept their first idea as being true: doubt is effortful and uncomfortable. Society tends to shape habits that are opposite to critical thinking. However, children are naturally curious and naturally form ideas and hypotheses. They are also perseverant. Curiosity, and the tendency to seek for explanations and form hypothesis, as well as doubt are the necessary conditions for reflexive thinking. The education of reflexive thinking can thus build upon these natural characteristics (luckily, because Dewey is a partisan of instruction as a form of empowerment that enhances the possibilities that are present in the human mind, as opposed to instruction as the filling-in of the mind with external concepts that do not resonate with the interests and predispositions of learners). Teaching reflexive thinking thus consists in a form of training that starts from natural skills and transforms them into habits. The aim of education is in fact the production of a disciplined mind: a mind that adopts reflexive thinking skillfully almost automatically. A disciplined mind is not only capable of identifying and defining difficulties, developing suggestions for their solution, reasoning on the consequences of the suggestions, conducing observations and experiments in order to accept or refute the suggestions; a disciplined mind is disposed to use these capacities and to adopt a logical attitude: « The whole object of intellectual education is formation of logical disposition » (Dewey, 1910, p. 57). Science, and in particular the experimental method, implements the different operations of reflexive thinking, systematically. It thus represents for Dewey the model of education, to be applied to any discipline and subject matter since primary school. The idea that science is the model of all education is different from the idea that scientific instruction is especially basic or formative. That is, that science as a specific matter should be privileged over other contents, or that the teaching of science will transfer its benefit upon other contents. Quite at the opposite, the scientific method should permeate any dimension of education, including manual, occupational, and graphical disciplines. Starting from concrete explorations of daily objects children develop the taste for science but the scientific method is the method for training disciplined minds, whatever the content.
  • Tim Van Gelder classifies ways of teaching critical thinking into 5 categories http://timvangelder.com/2010/10/20/how-are-critical-thinking-skills-acquired-five-perspectives/):formal teaching, e.g. working on some form of brain gym, such as chesstheoretical instruction, i.e. by learning the theorysituated cognition, from the extreme of denying general critical thinking skills to the idea of acquiring critical thinking skills through engaging in domain-specific activitiespractice, e.g. applying the skills to several domains, that varyevolutionary psychology, i.e. consolidating skills we are naturally endowed with.However, the main distinction concerns a. stand-alone and b. integrated teachings (eventually: c. mixed teachings). In fact, together with methods for teaching thinking skills within a discipline (e.g. Reif et al 1974 for physics; the work of Frederick Reif is extensive and he has dedicated as much attention to physics as to cognitive science and developing thinking skills in physics), we find methods for teaching thinking skills in general.  Both the philosophical (informal logic) and the psychological tradition include partisans of domain-general and of domain-specific methods: some programs focus largely on identifying and correctly variety of practice and labeling reasoning fallacies; others concentrate more on developing skills of argumentation in extended discourse, without extensive formal analysis. An important debate in the field exactly parallels psychologists' discussions of whether general cognitive skills or specific knowledge is most central to intellectual competence. Most informal logic philosophers believe that general reasoning capacity can be shaped and that it transcends specific knowledge domains (e.g., Ennis, 1980, 1985). In an even stronger claim, Paul (1982, in press) argues that we should seek to develop in students a broadly rational personality rather than any set of technical reasoning skills. This view usually, but not always, supports calls for independent critical thinking courses. However, a competing view, most strongly stated by McPeck (1981), argues that no general reasoning skill is possible and that all instruction in thinking should be situated in particular disciplines. (Resnick 1987, p. 31)
  • a. Stand-alone A classic example of general thinking teaching method is DeBono’sCoRT, which is as content-free as possible; another is the Productive Thinking Program – both are based on planning and meta-cognitive skills. Other diffused methods concern reading and studying from texts, but also the improvement of general intelligence (with no common definition, and no effort in this direction); the latter can include problem-solving techniques, memory strategies, informal logic and other tools that are present in critical thinking programs. As for what concerns programs explicitly aimed at critical thinking, some include activities for enhancing argumentation skills and logics that are inspired by the philosophical tradition and have a normative stance (one the most famous of these programs is Matthew Lipman’s philosophy teaching for children, e.g. Lipman 1974, largely evaluated and with apparently good results on discussion of philosophical texts, but also external goals such as reading capacities and even IQ tests):  they prescribe acceptable forms of thinking based on standards of logic. This contrasts with psychologists' efforts to discover and then to teach students the actual processes used by good thinkers. Philosophers promote an approach designed to discipline thinking and to guard against the propensities of humans to accept fallacious arguments and draw inappropriate conclusions. Indeed, the scholarly heart of the informal logic movement is the analysis of fallacies common in undisciplined reasoning. (Resnick 1987, p. 30) The philosophical approach to critical thinking has traditionally proposed courses for learning how to spot flawed arguments and deploy good argumentation and reasoning. It has also traditionally proposed general norms that would be independent from context and contents. But in the philosophical tradition, some, such as Bailin, have endorsed the normative view but criticized the attempt to define norms and educational that are independent from contents. Indeed the very notion of thinking processes which are separate from knowledge is highly questionable. For example, it makes no sense to refer to a process of interpreting which remains constant regardless of subject matter. Rather, what is involved in and even meant by interpreting varies with the context, and this difference is connected with the different kinds of knowledge and understanding necessary for successful completion of the particular task. Interpreting a graph is very different from interpreting the anomalous results of an experiment, and both differ significantly from interpreting a poem or interpreting the expression in someone’s voice. This is because the nature of the task indicated by the term ‘interpreting’ will vary with content.  (Bailin 2002) The cognitive approach has put the accent on skills. The processes (skills and procedures) that are typically pointed at are certain problem-solving routines and meta-cognitive skills. So both problem-solving and meta-cognitive skills (in fact: routines) have been both proposed as candidates for teaching. However, the same body of research that has helped identifying general skills has also demonstrated the importance of content knowledge: specific content knowledge plays a role both in thinking and in learning. The paradigmatic case is represented by Simon’s and Newell’s General Problem Solver (one and the same problem solving structure for many and different contents), with its successes (procedures that are useful independently form content) and deceptions (with its logical weapons, it can solve only some problems). Also, by the observation of reading and of scientific reasoning: in both cases, “skilled problem solvers” rely on their domain knowledge.  The reason that a single artificial intelligence program cannot solve a wide variety of problems is not that the fundamental processes it applies are widely different across domains, but rather that the program must apply these processes to very specific, organized bodies of knowledge. Each simulation must build in the relevant knowledge, and so it becomes specific to its knowledge base (see Dehn and Schank, 1982). (Resnick 1987, p. 28) 
  • b. integratedLilienfeld, Lohr and Morier (2001) have underlined the importance of introducing specific teachings of science and pseudo-science in the cursus of psychological studies, where myths abound. Since even students in psychology are susceptible of being seduced by jargon and images, and are sometimes the prey of pseudo-scientific beliefs, and because of the danger of entertaining pseudo-scientific beliefs in the framework of disciplines that have an applicative aspect (e.g. clinical psychology), it is important that they receive an appropriate training in critical thinking, at least in thinking critically about their own domain. Lilienfeld, Lohr and Morier (2001) have thus proposed to integrate general teaching about how to think skeptically (the baloney detection kit) with an analysis of mistakes, myths and pseudo-scientific claims that concern the mind and brain in particular. According to the authors, exposing false beliefs might also be useful in order to facilitate the acquisition of knowledge.  A second example of a disciplinary approach to critical thinking is represented by EBM (evidence-based medicine). EMB shares many common aims and tools with the idea of teaching and learning to think critically, including the aim of developing a critical appraisal of evidence and ideas received from tradition and authority. One could describe EBM as a truly scientific approach to medicine (Goldacre, 2008). David Sackett and colleagues (2000) have proposed to teach EBM by training students on real clinical cases: preparing them on how to ask the good questions, search for relevant evidence and appraise it critically, use evidence in order to propose diagnostics and therapies. In this way they can learn how to use evidence (the principle of EBM) directly on concrete examples. In the classroom, students and teachers simulate the reality of clinics. Ecological but rigorous evaluations are required in order to establish whether the program “works”, that is: whether students that participate to the program are “more critical” in their domain, and eventually in other, more or less close, domains.  
  • c. Mixed and enhancedWhile teaching critical thinking in one discipline, one can provide explicit instruction about rules and promote the use of metacognitive attitudes towards learning:anchor instruction on concrete cases, and propose variations (same inner structure, different superficial content), so as to favor flexibilitydo not bound instruction to implicit learning, but explicit both acquired knowledge and its contexts of applicationexplicit the processes that have produced knowledge acquisition, difficulties, strategies, that is: explicitly use and train metacognitive skills.Tim Van Gelder (2006), an expert in situated, distributed, embodied cognition preaches for a form of learning through deliberate practice, but he also praises the use of external tools for representing thinking processes: maps, diagrams, and in particular argument mapping. Argument mapping helps representing hierarchies, relations and the logical structure of arguments. In the “distributed cognition” view proposed by Van Gelder, by exploiting visuo-spatial capacities, these tools help reducing the cognitive charge (Hutchins, 1995 ; Kirsh & Maglio, 1995). It is a fact that scientists help themselves with diagrams and visual representations, the most famous of which are Feynman diagrams: not a simple graphic representation of mathematical relationships, but a tool for simplifying calculations. It is also a fact that humans produce external graphical representations since the stone age, that graphical representations possess the cognitive advantage of involving vision and more generally perception in the thinking process – and that we are plausibly better at seeing and perceiving than at thinking, and the further cognitive advantage of displaying diachronic information synchronically – so as to free short term memory (Spelke, 1991).
  • In 1987, the “experts” were very skeptical about the possibility of teaching thinking through content-free lessons, and suggest abandoning the idea that general thinking skills can be taught as such. Of course, to appreciate the dependence of general skills application on specific knowledge is not to deny that such general skills exist. Yet such an understanding raises questions about the wisdom of attempting to develop thinking skills outside the context of specific knowledge domains. It suggests that a more promising route may be to teach thinking skills within specific disciplines and perhaps hope for some transfer to other disciplines as relevant knowledge is acquired. (Resnick 1987, p. 29) However, they do not give up the idea that general skills for good thinking exist and turn to transfer mechanisms: If thinking skills cannot be taught as general skills, because they depend on domain-specific knowledge (too), can teaching thinking skills be taught in the framework of specific disciplines and then transferred elsewhere?  Over the decades, educators have espoused a recurring belief that certain school subject matters “discipline the mind” and therefore should be taught not so much for their inherent value as for their efficacy in facilitating other learning. Latin was defended for many years in these terms; mathematics and logic are often so defended today. Most recently, computer programming has been proposed as a way to develop general problem-solving and reasoning abilities (e.g., Papert, 1980). The view that we can expect strong transfer from learning in one area to improvements across the board has never been well supported empirically. At the turn of the century, Thorndike and Woodworth (1901) studied transfer among school subjects and found that it was more efficient to study the subject of interest (English vocabulary, for example) than to study some other subject (e.g., Latin) that “prepared” one's mind. Subsequent reviews of research on transfer of school subject matter generally have reconfirmed Thorndike and Woodworth's finding. (Resnick 1987, p. 29-30) Empirical evidence on the effects of programs for teaching higher order skills seems to confirm these sobering considerations – but the authors of the report leave the door open to hope in the learnability of learning and thinking skills, and even in their transferability. Both skepticism and hope are motivated by the fact that, although many methods exist (existed in 1987 and exist today) for teaching problem solving and reasoning, in general but also in the framework of a specific discipline, appropriate evaluations both of efficacy (better thinking in the framework of the discipline) and of transfer (to other disciplines) are scarce. Many assessments use self-evaluation; control groups are difficult to form. In general assessment address the specific skills and operations that are trained in the program, such as the capacity of generating questions, but not the effects on school results in general, or in a certain discipline, or in the real world (e.g. on the resistance to pseudo-scientific beliefs, on the capacity of appraising arguments and facts about relevant choices, on the capacity of practical problem solving). One measure is missing, that is: the measure of transfer from the course to reality, even within disciplinary knowledge and practice or a school context. In other words, usability and applicability of what has been learnt, with an effect on performances that are relevant for schooling and/or life.  The most common evaluation reported for the programs we have considered is mastery performance (Arbitman-Smith et al., 1984), that is, performance on exercises similar to those included in the program itself. In other words, evaluation provides evidence that students who have used a program learn to do the things the program teaches. This is a necessary first evaluation step, a minimal test that the program in question is worthwhile. Although necessary, such evidence is rarely sufficient to establish the program's educational value. If the program teaches skills that are in themselves considered valuable, then clear evidence that students learn and maintain those skills is adequate. But if a program is meant to teach skills that facilitate other learning but are not valued in themselves, then more is needed than merely tests of the performances directly taught. In these cases, assessments of transfer beyond the course or program itself must be included. (Resnick 1987, p. 32)Thinking and problem-solving programs within the academic disciplines seem to meet their internal goals and perhaps even boost performance more generally. It seems possible to raise reading competence by a variety of methods, ranging from study skill training through the reciprocal teaching methods of Brown and Palincsar to the discussions of philosophical texts in Lipman's program. On the other hand, general improvements in problem-solving, rhetoric, or other general thinking abilities have rarely been demonstrated, perhaps because few evaluators have included convincing assessments of these abilities in their studies. (Resnick 1987, p. 35) 
  • Twenty years after, Daniel Willingham has re-stated the same considerations. The evidence on the results of programs for teaching critical thinking is that these programs (many of which existed in 1987) achieve at most their internal goals: students learn to solve the kind of problems they encounter in the program but not to extend this skill to other problems.  A large number of programs designed to make students better thinkers are available, and they have some features in common. They are premised on the idea that there is a set of critical thinking skills that can be applied and practiced across content domains. They are designed to supplement regular curricula, not to replace them, and so they are not tied to particular content areas such as language arts, science, or social studies. Many programs are intended to last about three years, with several hours of instruction (delivered in one or two lessons) per week. The programs vary in how they deliver this instruction and practice. Some use abstract problems such as finding patterns in meaningless figures (Reuven Feuerstein’s Instrumental Enrichment), some use mystery stories (Martin Covington’s Productive Thinking), some use group discussion of interesting problems that one might encounter in daily life (Edward de Bono’s Cognitive Research Trust, or CoRT), and so on. However it is implemented, each program introduces students to examples of critical thinking and then requires that the students practice such thinking themselves. How well do these programs work? Many researchers have tried to answer that question, but their studies tend to have methodological problems. Four limitations of these studies are especially typical, and they make any effects suspect : 1) students are evaluated just once after the program, so it’s not known whether any observed effects are enduring; 2) there is not a control group, leaving it unclear whether gains are due to the thinking program, to other aspects of schooling, or to experiences outside the classroom; 3) the control group does not have a comparison intervention, so any positive effects found may be due, for example, to the teacher’s enthusiasm for something new, not the program itself; and 4) there is no measure of whether or not students can transfer their new thinking ability to materials that differ from those used in the program. In addition, only a small fraction of the studies have undergone peer review (meaning that they have been impartially evaluated by independent experts). Peer review is crucial because it is known that researchers unconsciously bias the design and analysis of their research to favor the conclusions they hope to see. (Willingham 2007)Willingham also reports a systematic review conducted on programs for teaching philosophy to children (Trickey & Topping 2004) conducted on eight studies evaluating academic outcomes; the main results is that evaluations are seldom conducted in a rigorous way and that they often take into account specific objectives, such as reading abilities; also, programs seem to fare better when the outcome measure matches the contents of the program (IQ scores are raised by programs that include training on the kind of puzzles that are included in IQ tests) and their efficacy seems to depend on the teacher’s skills. Willingham skepticism goes beyond evidence and existing programs and includes the very possibility that programs for improving critical thinking in general might ever be effective; this skepticism stems from knowledge about thinking processes, namely from the fact that (critical) thinking crucially depends on possessing content knowledge of the problem to solve. Thus, just like Bailin and the authors of the 1987 report on higher skills education, he relies the difficulty of teaching and learning to think critically to the fact that thinking is not a general capacity but a domain-specific one, and to difficulties related to transfer; this difficulty to the fact that critical thinking, just like any other kind of thinking and learning is not content-free but strongly depends on background knowledge. Can critical thinking actually be taught? Decades of cognitive research point to a disappointing answer: not really. People who have sought to teach critical thinking have assumed that it is a skill, like riding a bicycle, and that, like other skills, once you learn it, you can apply it in any situation. Research from cognitive science shows that thinking is not that sort of skill. The processes of thinking are intertwined with the content of thought (that is, domain knowledge). (Willingham 2007)
  • Failures at educating critical thinking and the apparent intractability of the limits of generalization and transfer Even without denying the existence of processes, or at least of procedures, that can work as universal tools, when one has to apply these procedures one is inevitably confronted with contents that are domain-specific. Here three things can happen:  first, content knowledge boosts performances, e.g. because it affects texts comprehension or because it helps recasting problems in more solvable configurations;second, the application of general procedures to specific knowledge might require adjustments, or even just raise the problem of understanding that that certain procedure applies: General skills such as breaking down a problem into simpler problems or checking to see whether one has captured the main idea of a passage may be impossible to apply if one does not have a store of knowledge about similar problems—or know enough about the topic to be able to recognize its central ideas. (Resnick 1987, p. 29)third, specific knowledge might trigger specific naïve ideas, biases and heuristics that hinder a good solution to the problem. Let us take the case of reading with understanding (Willingham 2010). Reading with understanding is predicted by both reading fluidity and knowledge relative to the contents of the textIn the absence of domain knowledge one cannot find the right way of setting an experiment, even if one has been instructed on the general rules of setting a good experiment (randomization, etc.); for example, one might not know how to choose the right control groupIn the absence of domain knowledge is difficult and maybe impossible to analyze a problem in several components and identify the core ideasPeople who know more are those who learn better because they understand, and understanding is one of the conditions for memorization and re-usePeople who know more are those who think better because:Possessing factual knowledge stored in long-term memory helps reducing the cognitive charge imposed to short term memory when manipulating multiple itemsit allows chunking, hence manipulating a greater number of contents in short-term memoryit reduces the necessity of thinking (one can directly use stored knowledge or automatized skills, e.g. when driving is automatized cognitive resources are set free for other tasks). Thinking is long and effortful, uncertain in the results and thus avoided as much as possible. Whenever possible, the brain will respond automatically or by using knowledge stored in memory. Factual knowledge is thus a condition for “functioning well” and reducing the necessity of thinking. Even metacognitive skills are not as general as they might seem: even metacognitive skills are enhanced by domain knowledge, and domain knowledge favors the skilled use of metacognitive capacities within the perimeter of that particular domain. In fact, it is a common experience that one is more skilled at estimating the time it will take to accomplish an action (acquire new knowledge) in a familiar than in a non familiar domain (Resnick, 1987).  (The relevance of content knowledge for the acquisition of critical thinking skills is not bound to the fact that thinking requires a content in order to operate: even the capacity of monitoring and directing one’s own learning depends on domain knowledge. The better one knows a domain, the better one thinks about it and about how to know more of it.) In 1987, the “experts” were very skeptical about the possibility of teaching thinking through content-free lessons, and suggest abandoning the idea that general thinking skills can be taught as such. Of course, to appreciate the dependence of general skills application on specific knowledge is not to deny that such general skills exist. Yet such an understanding raises questions about the wisdom of attempting to develop thinking skills outside the context of specific knowledge domains. It suggests that a more promising route may be to teach thinking skills within specific disciplines and perhaps hope for some transfer to other disciplines as relevant knowledge is acquired. (Resnick 1987, p. 29) However, they do not give up the idea that general skills for good thinking exist and turn to transfer mechanisms: If thinking skills cannot be taught as general skills, because they depend on domain-specific knowledge (too), can teaching thinking skills be taught in the framework of specific disciplines and then transferred elsewhere?  Over the decades, educators have espoused a recurring belief that certain school subject matters “discipline the mind” and therefore should be taught not so much for their inherent value as for their efficacy in facilitating other learning. Latin was defended for many years in these terms; mathematics and logic are often so defended today. Most recently, computer programming has been proposed as a way to develop general problem-solving and reasoning abilities (e.g., Papert, 1980). The view that we can expect strong transfer from learning in one area to improvements across the board has never been well supported empirically. At the turn of the century, Thorndike and Woodworth (1901) studied transfer among school subjects and found that it was more efficient to study the subject of interest (English vocabulary, for example) than to study some other subject (e.g., Latin) that “prepared” one's mind. Subsequent reviews of research on transfer of school subject matter generally have reconfirmed Thorndike and Woodworth's finding. (Resnick 1987, p. 29-30) Empirical evidence on the effects of programs for teaching higher order skills seems to confirm these sobering considerations – but the authors of the report leave the door open to hope in the learnability of learning and thinking skills, and even in their transferability. Both skepticism and hope are motivated by the fact that, although many methods exist (existed in 1987 and exist today) for teaching problem solving and reasoning, in general but also in the framework of a specific discipline, appropriate evaluations both of efficacy (better thinking in the framework of the discipline) and of transfer (to other disciplines) are scarce. Many assessments use self-evaluation; control groups are difficult to form. In general assessment address the specific skills and operations that are trained in the program, such as the capacity of generating questions, but not the effects on school results in general, or in a certain discipline, or in the real world (e.g. on the resistance to pseudo-scientific beliefs, on the capacity of appraising arguments and facts about relevant choices, on the capacity of practical problem solving). One measure is missing, that is: the measure of transfer from the course to reality, even within disciplinary knowledge and practice or a school context. In other words, usability and applicability of what has been learnt, with an effect on performances that are relevant for schooling and/or life.  The most common evaluation reported for the programs we have considered is mastery performance (Arbitman-Smith et al., 1984), that is, performance on exercises similar to those included in the program itself. In other words, evaluation provides evidence that students who have used a program learn to do the things the program teaches. This is a necessary first evaluation step, a minimal test that the program in question is worthwhile. Although necessary, such evidence is rarely sufficient to establish the program's educational value. If the program teaches skills that are in themselves considered valuable, then clear evidence that students learn and maintain those skills is adequate. But if a program is meant to teach skills that facilitate other learning but are not valued in themselves, then more is needed than merely tests of the performances directly taught. In these cases, assessments of transfer beyond the course or program itself must be included. (Resnick 1987, p. 32)Thinking and problem-solving programs within the academic disciplines seem to meet their internal goals and perhaps even boost performance more generally. It seems possible to raise reading competence by a variety of methods, ranging from study skill training through the reciprocal teaching methods of Brown and Palincsar to the discussions of philosophical texts in Lipman's program. On the other hand, general improvements in problem-solving, rhetoric, or other general thinking abilities have rarely been demonstrated, perhaps because few evaluators have included convincing assessments of these abilities in their studies. (Resnick 1987, p. 35) The suggestions that emerges from the report is that, on the grounds of the scarce evidence available and of the current knowledge provided by cognitive science, it seems reasonable to avoid domain-general approaches and to embed the teaching of thinking skills in each and every discipline, hence adopting a discipline-embedded approach. The discipline-embedded approach presents three types of advantage: it provides a knowledge base upon which thinking can be exerted; it facilitates evaluation, because it equates thinking skills with good thinking in a certain discipline; it brings something to the learner even if thinking skills are not really enhanced: This discipline-embedded approach has several advantages. First, it provides a natural knowledge base and environment in which to practice and develop higher order skills. As we have shown earlier, cognitive research has established the very important role of knowledge in reasoning and thinking. One cannot reason in the abstract; one must reason about something. Each school discipline provides extensive reasoning and problem-solving material by incorporating problem- solving or critical thinking training into the disciplines; the problem of “empty thinking”—thinking about nothing—is solved. As knowledge in the discipline develops, the base on which effective problem solving can operate is naturally available.Second, embedding higher order skill training within school disciplines provides criteria for what constitutes good thinking and reasoning within the disciplinary tradition. Each discipline has characteristic ways of reasoning, and a complete higher order education would seek to expose students to all of these. Reasoning and problem solving in the physical sciences, for example, are shaped by particular combinations of inductive and deductive reasoning, by appeal to mathematical tests, and by an extensive body of agreed upon fact for which new theories must account. In the social sciences, good reasoning and problem solving are much more heavily influenced by traditions of rhetorical argument, of weighing alternatives, and of “building a case” for a proposed solution. Mathematics insists on formal proofs—a criterion absent in most other disciplines. Each style of reasoning (and several others that could be elaborated) is worth learning. However, only if higher order skills are taught within each discipline are they likely to be learned.Finally, teaching higher order skills within the disciplines will ensure that something worthwhile will have been learned even if wide transfer proves unattainable. This point is profoundly important. It amounts to saying that no special, separate brief for teaching higher order skills need be made. Rather, it proposes that if a subject matter is worth teaching in school it is worth teaching at a high level—to everyone. A decision to pursue such an approach would transform the whole curriculum in fundamental ways. It would treat higher order skills development as the paramount goal of all schooling. Paradoxically, then, dropping the quest for general skills might, in the end, be the most powerful means of cultivating generally higher levels of cognitive functioning.(Resnick 1987, p. 35-36) Twenty years after, Daniel Willingham has re-stated the same considerations. The evidence on the results of programs for teaching critical thinking is that these programs (many of which existed in 1987) achieve at most their internal goals: students learn to solve the kind of problems they encounter in the program but not to extend this skill to other problems.  A large number of programs designed to make students better thinkers are available, and they have some features in common. They are premised on the idea that there is a set of critical thinking skills that can be applied and practiced across content domains. They are designed to supplement regular curricula, not to replace them, and so they are not tied to particular content areas such as language arts, science, or social studies. Many programs are intended to last about three years, with several hours of instruction (delivered in one or two lessons) per week. The programs vary in how they deliver this instruction and practice. Some use abstract problems such as finding patterns in meaningless figures (Reuven Feuerstein’s Instrumental Enrichment), some use mystery stories (Martin Covington’s Productive Thinking), some use group discussion of interesting problems that one might encounter in daily life (Edward de Bono’s Cognitive Research Trust, or CoRT), and so on. However it is implemented, each program introduces students to examples of critical thinking and then requires that the students practice such thinking themselves. How well do these programs work? Many researchers have tried to answer that question, but their studies tend to have methodological problems. Four limitations of these studies are especially typical, and they make any effects suspect : 1) students are evaluated just once after the program, so it’s not known whether any observed effects are enduring; 2) there is not a control group, leaving it unclear whether gains are due to the thinking program, to other aspects of schooling, or to experiences outside the classroom; 3) the control group does not have a comparison intervention, so any positive effects found may be due, for example, to the teacher’s enthusiasm for something new, not the program itself; and 4) there is no measure of whether or not students can transfer their new thinking ability to materials that differ from those used in the program. In addition, only a small fraction of the studies have undergone peer review (meaning that they have been impartially evaluated by independent experts). Peer review is crucial because it is known that researchers unconsciously bias the design and analysis of their research to favor the conclusions they hope to see. (Willingham 2007)Willingham also reports a systematic review conducted on programs for teaching philosophy to children (Trickey & Topping 2004) conducted on eight studies evaluating academic outcomes; the main results is that evaluations are seldom conducted in a rigorous way and that they often take into account specific objectives, such as reading abilities; also, programs seem to fare better when the outcome measure matches the contents of the program (IQ scores are raised by programs that include training on the kind of puzzles that are included in IQ tests) and their efficacy seems to depend on the teacher’s skills. Willingham skepticism goes beyond evidence and existing programs and includes the very possibility that programs for improving critical thinking in general might ever be effective; this skepticism stems from knowledge about thinking processes, namely from the fact that (critical) thinking crucially depends on possessing content knowledge of the problem to solve. Thus, just like Bailin and the authors of the 1987 report on higher skills education, he relies the difficulty of teaching and learning to think critically to the fact that thinking is not a general capacity but a domain-specific one, and to difficulties related to transfer; this difficulty to the fact that critical thinking, just like any other kind of thinking and learning is not content-free but strongly depends on background knowledge. Can critical thinking actually be taught? Decades of cognitive research point to a disappointing answer: not really. People who have sought to teach critical thinking have assumed that it is a skill, like riding a bicycle, and that, like other skills, once you learn it, you can apply it in any situation. Research from cognitive science shows that thinking is not that sort of skill. The processes of thinking are intertwined with the content of thought (that is, domain knowledge). (Willingham 2007) Learning and thinking require “facts”, in the sense that they operate on contents and not in the vacuum and that they are enhanced by the possession of domain knowledge.  (By the way, the importance of possessing knowledge for thinking better conflicts with the idea that all what students have to do is to learn how to access information, e.g. how to search for information in the Internet or in a library, and that there is no need for memorizing “facts”.) At the same time, Willingham states that teaching facts or teaching critical thinking as related with specific domain-knowledge and facts is not enough, for at least two reasons. The first reason, expressed at length by John Bransford and derived from the study of experts, is that experts possess domain knowledge – but not just “a lot of” domain knowledge: domain knowledge is also organized, retrievable, associated with meta-cognitive operations relative to the domain (monitoring of progress, etc.) So, facts are not enough and a diet of facts will not help.  The new science of learning does not deny that facts are important for thinking and problem solving. Research on expertisein areas such as chess, history, science, and mathematics demonstrate that experts' abilities to think and solve problems depend strongly on a rich body of knowledge about subject matter (e.g., Chase and Simon, 1973; Chi et al., 1981; deGroot, 1965). However, the research also shows clearly that "usable knowledge" is not the same as a mere list of disconnected facts. Experts' knowledge is connected and organized around important concepts (e.g., Newton's second law of motion); it is "conditionalized" to specify the contexts in which it is applicable; it supports understanding and transfer(to other contexts) rather than only the ability to remember.” (Bransford et al. 2000) The second one is that thinking tends to stick to the surface structure of a problem. Even when practical cases are presented, it is not certain that learners are capable of “seeing” the deep structure of problems with a different surface structure, or presented in different contexts (i.e. the fortress and the cancer problem; throwing darts under water: Bransford, Brown, & Cocking, 2000). Problems presented in a concrete context and specific content then tend to distract the learner from their deep structure, the one that is common to that problem and others. The student thus might be able to solve the problem at stake but still unable to recognize that a problem with a different surface structure presents indeed the same deep structure and then can be solved in a similar way.  When a student reads a word problem, her mind interprets the problem in light of her prior knowledge, as happened when you read the two sentences about copyrights and China. The difficulty is that the knowledge that seems relevant relates to the surface structure—in this problem, the reader dredges up knowledge about bands, high school, musicians, and so forth. The student is unlikely to read the problem and think of it in terms of its deep structure—using the least common multiple. The surface structure of the problem is overt, but the deep structure of the problem is not. Thus, people fail to use the first problem to help them solve the second… (Willingham 2007) Nonetheless, transfer occurs, even if not as easily and automatically at it could seem.  “If knowledge of how to solve a problem never transferred to problems with new surface structures, schooling would be inefficient or even futile—but of course, such transfer does occur. When and why is complex, but two factors are especially relevant for educators: familiarity with a problem’s deep structure and the knowledge that one should look for a deep structure.” (Willingham 2009) Willingham indicates that transfer requires two complementary operations:the multiplication of experience with a certain kind of problem and its deep structure, through repeated expositions to variations of the surface structure of the problem; apparently, it takes a lot of practice for the deep structure of a problem to “pop up” all by itself;look at the deep structure of problems. The step from surface to the deep structure can be made explicit by the teacher, by asking students to pay attention to the fact that the present problem shares the same solutions or analogies with a previously encountered one. Or, it can be directly implemented by the student, who can think about the nature of the problem, scan her memory in search for something similar, and in particular, use the general rule: always search for the deep structure of the problem (as she can adopt the rule: see both sides of an argument). These kinds of meta-cognitive skills and procedures are at the hearth of various cognitive-science inspired methods for teaching critical thinking, and have been considered as the key to critical thinking. Only, teaching maxims about how to think and providing the list of the right procedures to implement for regulating one’s own thinking does not seem to be enough. The problem is that the “thinker” might know that she has to look for the deep structure but fail to do it when it is appropriate or she might not know how to do it. According to Willingham, and on the grounds of the failure of instruction directly aimed at meta-cognitive skills, using meta-cognitive procedures still requires background knowledge and practice. So, meta-cognitive skills help but are not the solution to the problem of teaching and transferring critical thinking, but rather part of the problem. The same consideration applies to “scientific thinking”, even if in this case the existence of specific content provides cues about which meta-cognitive procedure they should use: students can learn metacognitive strategies that help them look past the surface structure of a problem and identify its deep structure, thereby get- ting them a step closer to figuring out a solution. Essentially the same thing can happen with scientific thinking. Students can learn certain metacognitive strategies that will cue them to think scientifically. But, as with problem solving, the metacognitive strategies only tell the students what they should do—they do not provide the knowledge that students need to actually do it. The good news is that within a content area like science, students have more context cues to help them figure out which metacognitive strategy to use, and teachers have a clearer idea of what domain knowledge they must teach to enable students to do what the strategy calls for. For example, two researchers taught second-, third-, and fourth-graders the scientific concept behind controlling variables; that is, of keeping everything in two comparison conditions the same, except for the one variable that is the focus of investigation. The experimenters gave explicit instruction about this strategy for conducting experiments and then had students practice with a set of materials (e.g., springs) to answer a specific question (e.g., which of these factors determine how far a spring will stretch: length, coil diameter, wire diameter, or weight?). The experiment- ers found that students not only understood the concept of controlling variables, they were able to apply it seven months later with different materials and a different experimenter, although the older children showed more robust transfer than the younger children. In this case, the students recognized that they were designing an experiment and that cued them to recall the metacognitive strategy, “When I design experiments, I should try to control variables.” Of course, succeeding in controlling all of the relevant variables is another matter—that depends on knowing which variables may matter and how they could vary. (Willingham 2005) In fact, even knowing that variables should be controlled or that control groups must be chosen does not help to devise which variables should be controlled and how control groups should be composed, unless one possesses content knowledge relative to the experiment. Content knowledge is also necessary in order to recognize experimental results as being anomalous.
  • Learning and thinking require “facts”, in the sense that they operate on contents and not in the vacuum and that they are enhanced by the possession of domain knowledge.  (By the way, the importance of possessing knowledge for thinking better conflicts with the idea that all what students have to do is to learn how to access information, e.g. how to search for information in the Internet or in a library, and that there is no need for memorizing “facts”.) At the same time, Willingham states that teaching facts or teaching critical thinking as related with specific domain-knowledge and facts is not enough, for at least two reasons. The first reason, expressed at length by John Bransford and derived from the study of experts, is that experts possess domain knowledge – but not just “a lot of” domain knowledge: domain knowledge is also organized, retrievable, associated with meta-cognitive operations relative to the domain (monitoring of progress, etc.) So, facts are not enough and a diet of facts will not help.  The new science of learning does not deny that facts are important for thinking and problem solving. Research on expertisein areas such as chess, history, science, and mathematics demonstrate that experts' abilities to think and solve problems depend strongly on a rich body of knowledge about subject matter (e.g., Chase and Simon, 1973; Chi et al., 1981; deGroot, 1965). However, the research also shows clearly that "usable knowledge" is not the same as a mere list of disconnected facts. Experts' knowledge is connected and organized around important concepts (e.g., Newton's second law of motion); it is "conditionalized" to specify the contexts in which it is applicable; it supports understanding and transfer(to other contexts) rather than only the ability to remember.” (Bransford et al. 2000) The second one is that thinking tends to stick to the surface structure of a problem. Even when practical cases are presented, it is not certain that learners are capable of “seeing” the deep structure of problems with a different surface structure, or presented in different contexts (i.e. the fortress and the cancer problem; throwing darts under water: Bransford, Brown, & Cocking, 2000). Problems presented in a concrete context and specific content then tend to distract the learner from their deep structure, the one that is common to that problem and others. The student thus might be able to solve the problem at stake but still unable to recognize that a problem with a different surface structure presents indeed the same deep structure and then can be solved in a similar way.  When a student reads a word problem, her mind interprets the problem in light of her prior knowledge, as happened when you read the two sentences about copyrights and China. The difficulty is that the knowledge that seems relevant relates to the surface structure—in this problem, the reader dredges up knowledge about bands, high school, musicians, and so forth. The student is unlikely to read the problem and think of it in terms of its deep structure—using the least common multiple. The surface structure of the problem is overt, but the deep structure of the problem is not. Thus, people fail to use the first problem to help them solve the second… (Willingham 2007) Nonetheless, transfer occurs, even if not as easily and automatically at it could seem.  “If knowledge of how to solve a problem never transferred to problems with new surface structures, schooling would be inefficient or even futile—but of course, such transfer does occur. When and why is complex, but two factors are especially relevant for educators: familiarity with a problem’s deep structure and the knowledge that one should look for a deep structure.” (Willingham 2009) Willingham indicates that transfer requires two complementary operations:the multiplication of experience with a certain kind of problem and its deep structure, through repeated expositions to variations of the surface structure of the problem; apparently, it takes a lot of practice for the deep structure of a problem to “pop up” all by itself;look at the deep structure of problems. The step from surface to the deep structure can be made explicit by the teacher, by asking students to pay attention to the fact that the present problem shares the same solutions or analogies with a previously encountered one. Or, it can be directly implemented by the student, who can think about the nature of the problem, scan her memory in search for something similar, and in particular, use the general rule: always search for the deep structure of the problem (as she can adopt the rule: see both sides of an argument). These kinds of meta-cognitive skills and procedures are at the hearth of various cognitive-science inspired methods for teaching critical thinking, and have been considered as the key to critical thinking. Only, teaching maxims about how to think and providing the list of the right procedures to implement for regulating one’s own thinking does not seem to be enough. The problem is that the “thinker” might know that she has to look for the deep structure but fail to do it when it is appropriate or she might not know how to do it. According to Willingham, and on the grounds of the failure of instruction directly aimed at meta-cognitive skills, using meta-cognitive procedures still requires background knowledge and practice. So, meta-cognitive skills help but are not the solution to the problem of teaching and transferring critical thinking, but rather part of the problem. The same consideration applies to “scientific thinking”, even if in this case the existence of specific content provides cues about which meta-cognitive procedure they should use: students can learn metacognitive strategies that help them look past the surface structure of a problem and identify its deep structure, thereby get- ting them a step closer to figuring out a solution. Essentially the same thing can happen with scientific thinking. Students can learn certain metacognitive strategies that will cue them to think scientifically. But, as with problem solving, the metacognitive strategies only tell the students what they should do—they do not provide the knowledge that students need to actually do it. The good news is that within a content area like science, students have more context cues to help them figure out which metacognitive strategy to use, and teachers have a clearer idea of what domain knowledge they must teach to enable students to do what the strategy calls for. For example, two researchers taught second-, third-, and fourth-graders the scientific concept behind controlling variables; that is, of keeping everything in two comparison conditions the same, except for the one variable that is the focus of investigation. The experimenters gave explicit instruction about this strategy for conducting experiments and then had students practice with a set of materials (e.g., springs) to answer a specific question (e.g., which of these factors determine how far a spring will stretch: length, coil diameter, wire diameter, or weight?). The experiment- ers found that students not only understood the concept of controlling variables, they were able to apply it seven months later with different materials and a different experimenter, although the older children showed more robust transfer than the younger children. In this case, the students recognized that they were designing an experiment and that cued them to recall the metacognitive strategy, “When I design experiments, I should try to control variables.” Of course, succeeding in controlling all of the relevant variables is another matter—that depends on knowing which variables may matter and how they could vary. (Willingham 2005) In fact, even knowing that variables should be controlled or that control groups must be chosen does not help to devise which variables should be controlled and how control groups should be composed, unless one possesses content knowledge relative to the experiment. Content knowledge is also necessary in order to recognize experimental results as being anomalous.
  • The idea that one can “learn to think”, that critical thinking is a general ability based on some trainable skills and the acquisition of procedural competences, this idea is now out of date. “As computers developed, there was an effort within psychology and cognitive science to produce models of mental processes in the form of computer programs. An early example was the General Problem Solver (Newell, Shaw, & Simon, 1958) … demonstrated that relatively few basic principles could be used to produce a program capable of proving a broad range of mathematical theorems. Many followers believed that the GPS simulation of the human mind indicated that humans needed to acquire only a few general principles to solve a wide range of complex problems. Instead, it was revealed that a great deal of information about the specific domain of application was needed for problem solution within that domain. When applied to humans, this view led to the concept of expertise based on a large amount of domain-specific learning, acquired with practice and stored in semantic memory (Chi, Glaser & Farr, 1988). Research on human chess masters led Herbert Simon (1969) to conclude that their skills were based entirely on knowledge about  chess and not on any general ability, either innate or learned. On the basis of his analyses on chess masters, Simon reasoned that up to 50000 hours of training was necessary to develop the semantic memory of chess that allowed the master to do so well… Perhaps, the most persuasive evidence of the power of expertise was in the training of several students to exhibit a memory span of up to 100 digits (Ericsson & Chase, 1982) … When they were switched to remembering letters, their memory span fell back to the usual seven…” (Posner & Rothbart 2007, p. 14-15) The alternative to critical thinking as a general ability is that skills and procedural competences are acquired locally (on specific contents) and then transferred - in the sense that there is something as a formative discipline that has the capacity of exerting general skills e.g.: mathematics, philosophy, logics, Latin, science. But at least this does not seem to be the case: « At the turn of the 20th century, … The basic idea was that the brain’s general capacity could be exercised like a healthy muscle, and that certain areas of learning, such as logic, mathematics, Latin, and Greek, were better sources of brain exercise than  were other areas.” (Posner & Rothbart 2007, p. 13-14) But the view of formal disciplines is not supported empirically.Over the decades, educators have espoused a recurring belief that certain school subject matters “discipline the mind” and therefore should be taught not so much for their inherent value as for their efficacy in facilitating other learning. Latin was defended for many years in these terms; mathematics and logic are often so defended today. Most recently, computer programming has been proposed as a way to develop general problem-solving and reasoning abilities (e.g., Papert, 1980). The view that we can expect strong transfer from learning in one area to improvements across the board has never been well supported empirically. (Resnick 1987)The idea of formal disciplines also clashes with the modular view of how the mind works, which dominates in cognitive science.What do all these studies boil down to? First, critical thinking (as well as scientific thinking and other domain-based thinking) is not a skill. There is not a set of critical thinking skills that can be acquired and deployed regardless of context. Second, there are metacognitive strategies that, once learned, make critical thinking more likely. Third, the ability to think critically (to actually do what the metacognitive strategies call for) depends on domain knowledge and practice. For teachers, the situation is not hopeless, but no one should underestimate the difficulty of teaching students to think critically. (Willingham 2005) 
  • Theoretical framework: Modularity to massive modularity (domain-specificity) of the mind – There’s not such a thing as a general ability We can be good at solving (certain) problems not because we possess a general problem solving machine that works on any content, but exactly at the opposite, because we know a lot of things (innately, by “instinct”) and we can use them to frame a problem, narrow it, find specific solutions that go well with the content of the problem (as we have “learnt” from evolution). According to the view introduced by Fodor (1983), in fact, the mind is modular, that is: lower functions (like perception and action) are encapsulated and domain-specific (plus 7 other characteristics). This idea has been hardened in the view proposed by evolutionary psychology, that sees the mind as being massively modular (Pinker 1997; Tooby & Cosmides 1992, 1994). The general idea is that “different neural circuits are specialized for solving different adaptive problems” “our modern skulls house a stone age mind.” In this view, instincts and heuristics are certainly not “bad reasoning”. At the opposite of what emerges from the Kahnemann-Tversy’s perspective “pure reason” is not necessarily desirable in itself, at least not without a lot of domain knowledge. Here lies, possibly, the BIG difference between evolutionary psychology and the Kahnemann-Tversy’s perspective: they both seem to acknowledge that solutions are pre-shaped by evolution, that they are useful in their original context, and can go very wrong when the world around changes, without the brain following it; but the evolutionary psychology perspective stresses the importance of domain-specific knowledge and content in reasoning and problem-solving. In this way, it seems to comply better with a problem that will be discussed further: the limits of transfer and the importance of domain-knowledge for good thinking, including critical thinking. More specifically:“Psychologists have long known that the human mind contains circuits that are specialized for different modes of perception, such as vision and hearing. But until recently, it was thought that perception and, perhaps, language were the only activities caused by cognitive processes that are specialized (e.g., Fodor, 1983). Other cognitive functions -- learning, reasoning, decision-making -- were thought to be accomplished by circuits that are very general purpose: jacks-of-all-trades, but masters of none. Prime candidates were "rational" algorithms: ones that implement formal methods for inductive and deductive reasoning, such as Bayes's rule or the propositional calculus (a formal logic). "General intelligence" -- a hypothetical faculty composed of simple reasoning circuits that are few in number, content-independent, and general purpose -- was thought to be the engine that generates solutions to reasoning problems. The flexibility of human reasoning -- that is, our ability to solve many different kinds of problems -- was thought to be evidence for the generality of the circuits that generate it.An evolutionary perspective suggests otherwise (Tooby & Cosmides, 1992). Biological machines are calibrated to the environments in which they evolved, and they embody information about the stably recurring properties of these ancestral worlds. (E.g., human color constancy mechanisms are calibrated to natural changes in terrestrial illumination; as a result, grass looks green at both high noon and sunset, even though the spectral properties of the light it reflects have changed dramatically.) Rational algorithms do not, because they are content-independent. Figure 2 shows two rules of inference from the propositional calculus, a system that allows one to deduce true conclusions from true premises, no matter what the subject matter of the premises is -- no mattter what P and Q refer to. Bayes's rule, an equation for computing the probability of a hypothesis given data, is also content-independent. It can be applied indiscriminately to medical diagnosis, card games, hunting success, or any other subject matter. It contains no domain-specific knowledge, so it cannot support inferences that would apply to mate choice, for example, but not to hunting. (That is the price of content-independence.) Evolved problem-solvers, however, are equipped with crib sheets: they come to a problem already "knowing" a lot about it. For example, a newborn's brain has response systems that "expect" faces to be present in the environment: babies less than 10 minutes old turn their eyes and head in response to face-like patterns, but not to scrambled versions of the same pattern with identical spatial frequencies (Johnson & Morton, 1991). Infants make strong ontological assumptions about how the world works and what kinds of things it contains -- even at 2 1/2 months (the point at which they can see well enough to be tested). They assume, for example, that it will contain rigid objects that are continuous in space and time, and they have perfered ways of parsing the world into separate objects (e.g., Baillergeon, 1986; Spelke, 1990). Ignoring shape, color, and texture, they treat any surface that is cohesive, bounded, and moves as a unit as a single object. When one solid object appears to pass through another, these infants are surprised. Yet a system with no "privileged" hypotheses -- a truly "open-minded" system -- would be undisturbed by such displays. In watching objects interact, babies less than a year old distinguish causal events from non-causal ones that have similar spatio-temporal properties; they distinguish objects that move only when acted upon from ones that are capable of self-generated motion (the inanimate/animate distinction); they assume that the self-propelled movement of animate objects is caused by invisible internal states -- goals and intentions -- whose presence must be inferred, since internal states cannot be seen (Baron-Cohen, 1995; Leslie, 1988; 1994). Toddlers have a well-developed "mind-reading" system, which uses eye direction and movement to infer what other people want, know, and believe (Baron-Cohen, 1995). (When this system is impaired, as in autism, the child cannot infer what others believe.) When an adult utters a word-like sound while pointing to a novel object, toddlers assume the word refers to the whole object, rather than one of its parts (Markman, 1989).Without these privileged hypotheses -- about faces, objects, physical causality, other minds, word meanings, and so on -- a developing child could learn very little about its environment. For example, a child with autism who has a normal IQ and intact perceptual systems is, nevertheless, unable to make simple inferences about mental states (Baron-Cohen, 1995). Children with Williams syndrome are profoundly retarded and have difficulty learning even very simple spatial tasks, yet they are good at inferring other people's mental states. Some of their reasoning mechanisms are damaged, but their mind-reading system is intact.Different problems require different crib sheets. For example, knowledge about intentions, beliefs, and desires, which allows one to infer the behavior of persons, will be misleading if applied to inanimate objects. Two machines are better than one when the crib sheet that helps solve problems in one domain is misleading in another. This suggests that many evolved computational mechanisms will be domain-specific: they will be activated in some domains but not others. Some of these will embody rational methods, but others will have special purpose inference procedures that respond not to logical form but to content-types -- procedures that work well within the stable ecological structure of a particular domain, even though they might lead to false or contradictory inferences if they were activated outside of that domain.The more crib sheets a system has, the more problems it can solve. A brain equipped with a multiplicity of specialized inference engines will be able to generate sophisticated behavior that is sensitively tuned to its environment. In this view, the flexibility and power often attributed to content-independent algorithms is illusory. All else equal, a content-rich system will be able to infer more than a content-poor one.Machines limited to executing Bayes's rule, modus ponens, and other "rational" procedures derived from mathematics or logic are computationally weak compared to the system outlined above (Tooby and Cosmides, 1992). The theories of rationality they embody are "environment-free" -- they were designed to produce valid inferences in all domains. They can be applied to a wide variety of domains, however, only because they lack any information that would be helpful in one domain but not in another. Having no crib sheets, there is little they can deduce about a domain; having no privileged hypotheses, there is little they can induce before their operation is hijacked by combinatorial explosion. The difference between domain-specific methods and domain-independent ones is akin to the difference between experts and novices: experts can solve problems faster and more efficiently than novices because they already know a lot about the problem domain.William James's view of the mind, which was ignored for much of the 20th century, is being vindicated today. There is now evidence for the existence of circuits that are specialized for reasoning about objects, physical causality, number, the biological world, the beliefs and motivations of other individuals, and social interactions (for review, see Hirschfeld & Gelman, 1994). It is now known that the learning mechanisms that govern the acquisition of language are different from those that govern the acquisition of food aversions, and both of these are different from the learning mechanisms that govern the acquisition of snake phobias (Garcia, 1990; Pinker, 1994; Mineka & Cooke, 1985). Examples abound."Instincts" are often thought of as the polar opposite of "reasoning" and "learning". Homo sapiens are thought of as the "rational animal", a species whose instincts, obviated by culture, were erased by evolution. But the reasoning circuits and learning circuits discussed above have the following five properties: (1) they are complexly structured for solving a specific type of adaptive problem, (2) they reliably develop in all normal human beings, (3) they develop without any conscious effort and in the absence of any formal instruction, (4) they are applied without any conscious awareness of their underlying logic, and (5) they are distinct from more general abilities to process information or behave intelligently. In other words, they have all the hallmarks of what one usually thinks of as an "instinct" (Pinker, 1994). In fact, one can think of these special purpose computational systems as reasoning instincts and learning instincts. They make certain kinds of inferences just as easy, effortless, and "natural" to us as humans, as spinning a web is to a spider or dead-reckoning is to a desert ant.” (Cosmides & Tooby 1997)
  • The suggestions that emerges from the report is that, on the grounds of the scarce evidence available and of the current knowledge provided by cognitive science, it seems reasonable to avoid domain-general approaches and to embed the teaching of thinking skills in each and every discipline, hence adopting a discipline-embedded approach. The discipline-embedded approach presents three types of advantage: it provides a knowledge base upon which thinking can be exerted; it facilitates evaluation, because it equates thinking skills with good thinking in a certain discipline; it brings something to the learner even if thinking skills are not really enhanced: This discipline-embedded approach has several advantages. First, it provides a natural knowledge base and environment in which to practice and develop higher order skills. As we have shown earlier, cognitive research has established the very important role of knowledge in reasoning and thinking. One cannot reason in the abstract; one must reason about something. Each school discipline provides extensive reasoning and problem-solving material by incorporating problem- solving or critical thinking training into the disciplines; the problem of “empty thinking”—thinking about nothing—is solved. As knowledge in the discipline develops, the base on which effective problem solving can operate is naturally available.Second, embedding higher order skill training within school disciplines provides criteria for what constitutes good thinking and reasoning within the disciplinary tradition. Each discipline has characteristic ways of reasoning, and a complete higher order education would seek to expose students to all of these. Reasoning and problem solving in the physical sciences, for example, are shaped by particular combinations of inductive and deductive reasoning, by appeal to mathematical tests, and by an extensive body of agreed upon fact for which new theories must account. In the social sciences, good reasoning and problem solving are much more heavily influenced by traditions of rhetorical argument, of weighing alternatives, and of “building a case” for a proposed solution. Mathematics insists on formal proofs—a criterion absent in most other disciplines. Each style of reasoning (and several others that could be elaborated) is worth learning. However, only if higher order skills are taught within each discipline are they likely to be learned.Finally, teaching higher order skills within the disciplines will ensure that something worthwhile will have been learned even if wide transfer proves unattainable. This point is profoundly important. It amounts to saying that no special, separate brief for teaching higher order skills need be made. Rather, it proposes that if a subject matter is worth teaching in school it is worth teaching at a high level—to everyone. A decision to pursue such an approach would transform the whole curriculum in fundamental ways. It would treat higher order skills development as the paramount goal of all schooling. Paradoxically, then, dropping the quest for general skills might, in the end, be the most powerful means of cultivating generally higher levels of cognitive functioning. (Resnick 1987, p. 35-36) 
  • In continuity of Dewey’s view, at least in the USA, critical thinking education entertains a special relationship with science education.  There is a widespread acceptance of the idea that critical thinking should be an important dimension of science education. Thus, for example, the National Science Education Standards (1996) has as one of its goals the promotion of science as inquiry. Included in this goal are numerous items which focus on critical thinking, for example “identification of assumptions, use of critical and logical thinking, and consideration of alternative explanations (p. 23); “analysis of firsthand events and phenomena a well as critical analysis of secondary sources; testing reliability of knowledge they have generated” (p.33); and “the critical abilities of analyzing an argument by reviewing current scientific understanding, weighing the evidence, and examining the logic so as to decide which explanation and models are best.”(p. 175). (Bailin 2002) The privileged relationship of critical thinking with science education and more generally with scientific thinking is questionable on several grounds and it is now common to affirm the rather surprising de-correlation between critical thinking and science education, as well as to acknowledge a certain intractability of irrationality. However, the non-educability of critical thinking is hard to swallow. The focus on science and pseudo-scientific beliefs in relationship with critical thinking is at least in part justified by the fact that science has a big part in our society, and in the life of individuals.  More than ever, policy-making looks at science and evidence for grounding its decisions, and evidence-based approaches are present in fields as different as medicine, agriculture, justice, and education.  As we assist to the multiplication of information, we also assist to the multiplication of scientific knowledge and of knowledge susceptible of having an impact on our health, education, environment, life-style. More than ever it is crucial that decision-makers get the science right, and are able to judge and part science and pseudo-science, established results and exciting but to-be-confirmed ones, theoretical results and applicable ones. A recent editorial of the prestigious Science magazine explicitly endorses this view in its title: « Policy-making needs science ». The capacity of evaluating the role of science in orienting our choices is not a requirement that we can limit to professional decision-makers: we are asked to give our advice on nuclear plants, environmental actions, abortion, cloning, embryos used for research, to consider science when deciding whether to buy cigarettes, whether to eat 3 or rather 5 fruits and vegetables per day, or to let babies sleep on their tummy. Scientific alphabetization is becoming a priority for the education of citizens, not just of future scientists. At the same time, we seem to be in great need for experts in STEM: Science, Technology, Engineering, Mathematics (OCDE, 2010). Scientific literacy, intended as the capacity of using scientific knowledge, has become one of the cornerstones of international evaluations of educational systems, together with reading and mathematics.  « Scientific literacy is the capacity to use scientific knowledge, to identify questions and to draw evidence-based conclusions in order to understand and help make decisions about the natural world and the changes made to it through human activity » (OECD : http://www.oecd.org/pages/0,3417,en_32252351_32236102_1_1_1_1_1,00.html) However, in order to use scientific knowledge, one must be able to judge whether they are suitable, when and how they can and should mobilized, of evaluating their soundness, in terms of the mass of the empirical data and of the consistency of the arguments. One must also be aware of science as work in progress, of major epistemological difficulties. If science education bounds itself at providing students with contents, this will not happen. At the same time, the standards of scientific education have thus incorporated critical thinking as a component and as a product of science education, when science is taught and learnt through inquiry. Critical thinking is a part of the process of making science, thus of learning science in an inquiry-based setting, and one of the desirable outcomes of science education.  The strong connection between science and science education on one side and critical thinking on the other is also justified on the grounds of the very nature of science. Science is fundamentally intertwined with the capacity and the methods for separating wheat from chaff: of deciding whether there are reasons for retaining a certain belief as probably true, in the light of the analysis of arguments and of the evidence available, and this is at least one of the aspects of critical thinking (Ennis,1985 ; Facione 1990 ; Fischer & Scriven 1997; Glaser 1941 ; McPeck 1981 ; Paul 1990). Holding pseudo-scientific beliefs that violate available and uncontroversial knowledge as established by science, and imply some form of logical fallacy, is thus largely used as a test for critical thinking - critical thinking is in this case associated with scientific thinking and skepticism (the skeptical variety of critical thinking).
  • In fact, science literacy is not a sufficient condition for thinking critically.good scientific thinkers can be “bad thinkers” in other domainsthere can be critical thinking in thinking about history, in reading a book, and so on.We will put this objection aside for a moment and quickly review evidence about the de-correlation between scientific education and critical thinking when pseudo-scientific beliefs are used as assessment. Ehud Jungwirth and Amos Dreyfus, affirm that the development of critical thinking has been one of the most essential objectives of science education for more than 100 years and asks whether the provision of such an opportunity has really fructified and produced more critical minds. They have produced a test that evaluates some “basics” of critical or at least scientific thinking, such as spontaneous attention to the logical structure of passages. With disappointing results. Gabennesh defends a position according to which science education and science literacy do not seem to make a real difference. Creationism is still there in spite of the fact that science literacy has certainly grown in the last century. Moreover, scientists do not seem to possess a shield against quackery and mumbo jumbo. However, according to Gabennesh the problem is not necessarily about science, but about the way science is taught and more deeply, about the fact that critical thinking is strongly dependent on contents - not a general capacity that one can acquire and display whatever the issue at stake.  Are the hard sciences doing much better? In the first place, science education is not producing high levels of scientific literacy in the population (National Science Foundation 2004). Besides, there appears to be only a weak relationship between science knowledge and disbelief in various forms of nonsense (Walker and Hoekstra 2002; Johnson and Pigliucci 2004).As many have noted, we teach science as a collection of facts and theories about a certain category of phenomena, rather than as a set of principles for understanding the world. A course in “Science, Pseudoscience, and Anti-science” would stimulate broader critical thought than the typical Chemistry 101 class. But the problem is deeper than this. Full-blown critical thinking is not coterminous with good scientific thinking. Critical thought is the principles of scientific thought projected to the far reaches of everyday life, with all the attendant demands and complications. This expansive generalization of the scientific method is hardly spontaneous or self-evident for most people. Just as learning the truth about Santa does not shatter the typical child’s credulous worldview, learning the principles of science can easily fail to fully penetrate the larger vision of science students-and indeed, of scientists. By themselves, science classrooms are poor competition for the powerful obstacles to highly developed critical thinking that reside in human social life and in the wiring of the human brain. (Gabennesh 2006)Literature about education and scientific thinking offers three factual considerations, summarized in Gabennesh’s statement:the diffusion of scientific literacy has not defeated pseudo-scientific beliefs by and large the study of science, as science is taught today, does not make the difference in terms of pseudo-scientific beliefseven the “professionals of critical thinking”, that is: scientists, are unshielded against pseudo-scientific beliefs. Pseudo-scientific beliefs and the general publicIn 1974 Richard Feynman used to describe our world as a non scientific one, in spite of the fact that scientific literacy is certainly more diffused than in the past: « But even today I meet lots of people who sooner or later get me into a conversation about UFOS, or astrology, or some form of mysticism, expanded consciousness, new types of awareness, ESP, and so forth. And I’ve concluded that it’s not a scientific world. » (Feynman, 1974)  It is often reminded that in the USA, there are more astrologers than astronomers and that creationist beliefs are hold by a majority of the population, in spite of the fact that astronomy and evolutionist theories are currently taught in school, that science has been almost universally introduced in the public school system, and that there are more scientists alive today than the total number of scientists in history to 1900 (Ede 2000). Apparently, a poll realized in France demonstrates a positive relationship between paranormal beliefs and education (Henri Broch). This leads us to a “paradox of irrationality”: How then are we to reconcile having the most scientifically trained society in history with the persistence of irrationality? Why do we not see a significant drop of irrationality corresponding to the significant increase in the levels of general science education in the last fifty years? (Ede 2000) It is possible that the very observation is wrong. Maybe the level of irrationality is dropping.  Goode (2002) cites the work of Jon Miller, whose surveys would  demonstrate a strong negative correlation between education and paranormal belief: The lower the level of the respondent’s education, the higher le likelihood of his or her acceptance of each paranormal belief in his surveys. Miller pins his hopes in the educational system to stamp out the acceptance of such ‘superstition and pseudoscience’ as astrology, belief in numbers and creationism. Miller dubs the uneducated “the scientific illiterate”. … Education is seen as antithetical to paranormal (or ‘pseudoscientific’) belief. In effect, education, especially in scientific subjects, destroys paranormalism; education is the enemy of pseudoscience. … Clearly, since science education refutes such misconceptions, the more of it we have, the less we believe in them. (Goode 2002) However, not Ede nor Goode do share this view. Ede suggests that this is because students fail to understand how scientific ideas are arrived at, the questions behind, why science is done. Goode proposes a specific distinction, based on his lecture of existing polls and of a study of his own.  My hypothesis is a bit different from the “enlightenment” position. I propose that the frequently stated argument that education is an antidote to paranormal beliefs is at least partly erroneous. I suggest that paranormal thinking is made up of a diversity of standards, some of which are discouraged with increased levels of education and some of which are not. I further suggest that the human capacity to compartmentalize categories of thinking is sufficiently great as to permit simultaneous belief in assertions that are contradictory. Many individuals, in fact, accept the truth of paranormal assertions alongside scientific principles that logically and factually contradict them. I suggest that, instead of a simple, unambiguous negative relationship between education and scientific knowledge on the one hand and paranormalism on the other, there are different dimensions of paranormalism, each with its special relationship to education and scientific knowledge. (Goode 2002) The main distinction operated by Goode stands between beliefs that are related to some religious tradition and beliefs that are free from religious bounds; its factual source is represented by polls on citizens’ beliefs in the paranormal that evaluate the level of education (such as the Pew survey or the Gallup poll and the Princeton Survey Research Associates survey about beliefs in the paranormal):  Traditional religious beliefs that are paranormal, that is, that violate the canons of scientific causality, exhibit a negative correlation with education and scientific knowledge … belief in creationism represents the preeminent example. Practically every poll or survey ever conducted has revealed a negative correlation between education and belief in creationism… (Goode 2002)  This is the fate of beliefs in heaven and hell, angels and devils, and humans as created in their present form less than 10000 years ago (it should be noticed that the belief in heaven as a real, physical place diminishes from 92% to 73% with an increasing level of education, which leaves 3+4 of the people with a college-level instruction in the USA believing in the fact that heaven is somewhere up there). But not of non-religion-based paranormal beliefs, such as UFO abductions and visits, astrology, telepathy, ESP, the power of crystals: … most of the classic paranormal beliefs also bear an inconsistent relationship with education. Some surveys indicate a negative relationship for some paranormal beliefs, but for most surveys and for most beliefs, the results are noteworthy for their lack of pattern. (Goode 2002) In other words, not all pseudoscientific beliefs are born equal and have the same fate in relationship to education. Why? Goode’s speculates that those who hold religious beliefs are more traditionalists than those who hold unconventional beliefs of the paranormal type. Whatever the reason, Goode’s distinction invites us to abandon the idea that all pseudoscientific beliefs are equal and that one and the same mechanism underlies the all of them and makes all of them tractable in the same way, e.g. by raising the level of science literacy.  Pseudo-scientific beliefs and science studentsGoode polled 2 classes of students with questions about paranormal beliefs, scientific facts, science-like facts: e.g. which planets are closest to and farthest from the Sun, the most populous country; and questions that tend to elicit statistics and representativeness biases. Fairly consistently, my data demonstrate that a negative relationship exists between adherence to the religious beliefs that contain a paranormal component and scientific and science-like reasoning. The relationship was not always statistically significant, but the direction of the relationship was remarkably consistent. … Believers in UFOs were a bit more likely than non-believers to know that Mercury is the planet closest to the Sun than nonbelievers, but a bit less likely to know that Pluto is the farthest planet from the Sun. Neither relationship approaches statistical significance…A variety of questions entailing reasoning by means of commonsensical judgmental heuristics versus scientific reasoning yielded no differences whatsoever between UFO believers and nonbelievers. … Paranormalism bears an inconsistent relationship with scientific knowledge and reasoning. … If my little study and the many relevant public opinion polls conducted each year are any guide, non-religious paranormalists know about as much science, and reason as scientifically, as persons who reject the validity of paranormal or extrascientific forces. (Goode 2002) The biggest study at date run with students is Walker’s at three undergraduate universities, with 207 students through a 2-units survey (Walker et al 2002). The first unit measures science knowledge (questions are extracted from the Praxis Series national Teacher’s exam), the second asks students to rate the strength of their beliefs in paranormal and pseudoscientific claims (1-7). The correlation between tests scores and beliefs was non-significant. These results are consistent with the notion that having a strong scientific knowledge base is not enough to insulate a person against irrational beliefs. Students who scored well on these tests were no more or less skeptical of pseudoscientific claims than students who scored very poorly. Apparently, the students were not able to apply their scientific knowledge to evaluate these pseudoscientific claims. We suggest that this inability stems in part from the way that science is traditionally presented to students: Students are taught what to think but not how to think.These results need to be replicated using different materials and participants, although the diversity of measures and samples presented here suggests that there is some validity to our conclusions. While some might contend that our tests did not fully measure science knowledge, we counter this concern by emphasizing that our test questions were drawn from national tests designed to assess scientific reasoning. Thus, if there is a bias in our procedure, this bias is entrenched in science education. In our view, addressing the following questions can serve to clarify the relation between science education and pseudoscientific thinking. (Walker, Hoesktra, Vogl 2002) (Pigliucci 2007) reports interviews with students who followed his own Honors course on science and pseudoscience (only half of them pursuit a science major, the rest were mostly from philosophy and psychology), with questions aimed at evaluating their factual knowledge of science (using a model of evaluation for aspiring high school teachers); science majors knew more scientific facts than the others. The students were successively asked to rate their belief in various paranormal phenomena, with surprising results: science majors hold more paranormal beliefs than their fellows the philosophers and psychologists (who follow courses on scientific method and critical thinking). (Johnson & Pigliucci 2004) reports a study in which 170 science-major and non-science major students (4 classes: 2 second year biology classes and 2 second year philosophy classes) were compared. The study has been realized in the framework of Johnson’s Honors thesis project (2003). It was constituted of a 30-questions survey; questions were of three types: 10 5-choice questions on general knowledge about science (e.g. the periodic table), 10 true-false questions about science conceptual understanding (e.g. difference between theory and laws), 1-5 scale of strength of beliefs in paranormal phenomena (from Loch Ness to telepathy and healing magnets). The survey is largely inspired to (Walker et al. 2002) and to the Richard Carrier’s test of scientific literacy (http://www.infidels.org/library/modern/richard_carrier/SciLit.html). The results indicate that the predictable difference in science knowledge was not associated with understanding of the foundations of science and in the degree of acceptance of pseudoscientific factoids. Science facts questions showed a weak negative correlation with paranormal belief, while no correlation was found between understanding of scientific concepts and paranormal. No science method question received even 50% of correct answers both for the science major and the non-science major group, the difference between theory and laws being understood by less than 5% of the respondents of the two groups. The strength of the belief in paranormal was also low (never higher than 3, often 1). It seems that there is little evidence for the idea that better knowledge of science facts leads to better understanding of the nature of science, or to a lower degree of belief in the paranormal. (Pigliucci 2007) It is necessary to underline that both Goode, Walker et al., and Johnson and Pigliucci’s studies have serious limits and conclusions can be hardly generalized: they are conducted on small samples and are just two studies, they are conducted with students that possibly are aware of the aims of the study, and it is even possible that the kind of questions influence a “gullible” attitude.  So what to do with science education? Should we abandon it? (in the optics of critical thinking, at least, because there are many other good reasons for teaching science in schools.) The answer is generally negative, even for those who do not share the optimistic view of science as a candle in the dark.  Among the most common proposal, “skeptics” suggest thatpseudoscience should be directly addressed and debunkedscience teaching should be changed: be more “hands on” aka inquiry based, include history of science (and not be too soon technical or hands on) or provide direct instruction about critical thinking. Others, as we will see later, consider the teaching and learning of thinking critically broader than science education and propose more global programs, or even critical thinking as integrated to several curricula. Their way of testing critical thinking is not bound to pseudoscientific beliefs.  I don’t recommend that we abandon science in our educational curricula. But what I wonder about is how science is taught. It’s possible that most science instructors do not consider paranormal and pseudoscience assertions a sufficient threat to science that they confront them directly with the evidence of our senses. It’s possible that the current curriculum isn’t doing enough to combat pseudoscience. (Goode 2002) The Science, Technology, and Society (STS) model de-emphasizes technical training until much later in the school system. Scientific concepts would be embedded in curriculum for primary levels, and students would be asked to think about how objects work or to investigate concepts in mathematics, physics, chemistry, and biology within the classroom environment. … The objective of the STS model is to provide students with a very broad background in the idea of science before forcing them to make decisions about participation in the subject-specific skills of any particular discipline. (Ede 2000) Massimo Pigliucci ranges himself among those who criticize science as it is taught in school; he advocates a form of Whitehead’s concept of learning deep. He notices that students in science majors seldom receive courses on scientific method and critical thinking, and are inundated with facts or trained for the lab. Teaching vast and shallow gives the impression that science is as boring as the yellow pages and that science is all about results mysteriously obtained by obscure specialists. He thus joins Goode in doubting that more science education in the standard variety will make much difference – because knowledge of science does not seem to be the root of cause of the lack of critical thinking, measured in terms of the possession of paranormal and pseudoscientific beliefs - and Ede in proposing to teach science in its historical context: More importantly it is the best way to explain how and why scientific discoveries are made, which turns science from a barrage of meaningless and boring facts into a vibrant enterprise of discovery and human realization. …Perhaps even more unfortunately, the major response so far to the sorts of concerns I am discussing here has been a shift in emphasis from traditional classroom lectures to “hands on” activities in which students manipulate objects and perform experiments. Moving away from lectures and getting students to actually do things is an excellent idea, but the way the hands-on approaches is often implemented, especially at the pre-college level, may actually produce worst results than the traditional lecture approach. The problem with many hands-on experiences is that the brain stays turned off. (Pigliucci 2007) Pigliucci also advocates for teaching that is inspired by recent developments in knowledge about how the brain works. Unfortunately he cites two books: one is rather old (and certainly not inspired by recent developments in brain sciences, but mostly by classic cognitive psychology and learning sciences) and the other is Jensen’s Teaching with the brain in mind, which is rich in pseudoscience and purports a rather dangerous use of science in education – the generalistic, straightforward import-export attitude. Pigliucci goes on citing the works of neuroscientists, such as Gazzaniga’s on the split brain, which certainly help gaining a deeper knowledge of the brain but can be hardly translated into educational guidelines. He proposes a list of reforms for science education but does not bother to check for evidence. An anecdotal piece of evidence that critical thinking might be so domain-specific as to depend on the content knowledge one possesses.  Pseudo-scientific beliefs and professional scientistsBad news are not confined to laypeople and students. As its name indicates, the “Nobel disease” afflicts the very elite of scientific thinking (http://www.skepdic.com/nobeldisease.html). One list includes, some being more notable than others: Examples of the Nobel disease include:Pierre Curie, physics (Eusapia Palladino)Ivar Giaever, physics (global warming denier)Louis J. Ignarro, physiology or medicine (Herbalife Niteworks)Brian Josephson, physics (psi)Philipp Lenard, physics (Nazi ideology)Luc Montagnier, medicine (autism)Kary Mullis, chemistry (supports astrology, denies anthropogenic climate change, denies HIV causes AIDS)Linus Pauling, chemistry (vitamin C)Charles Richet, physiology (ectoplasm/mediums/telepathy)William Shockley, physics (race & IQ)John William Strutt, 3rd Baron Rayleigh, physics (president Society for Psychical Research)Nikolaas Tinbergen, physiology or medicine (autism)James Watson, physiology or medicine (race & IQ) Let us dig a bit in one example: 2 times nobelized Linus Pauling: …the concept that megadoses of vitamin C can cure cancer has been around for decades now, ever since two-time Nobel Laureate Linus Pauling first proposed it. It began in 1972, when Ewan Cameron hypothesized that ascorbate could have anti-cancer action by inhibiting hyaluronidase and thereby preventing cancer spread after two-time Nobel Laureate Linus Pauling had first proposed that taking 1,000 mg of vitamin C daily can reduce the incidence of colds by 45% for most people. It wasn’t long before the two teamed up, and in 1976 Pauling and Dr. Ewan Cameron reported that a majority of 100 terminal cancer patients treated with 10,000 mg of vitamin C per day survived three to four times longer than patients who were not so treated.Unfortunately, as experimental clinical protocols go, this study was a complete mess. Linus Pauling was not a clinician and had no experience in clinical trial design, and it really showed. Even as a restrospective analysis, the paper was a total embarrassment. There was no standardization, no good matching of controls by age, stage of cancer, or performance status; given the terrible design, there was clearly serious selection bias going on at a minimum. The study’s flaws, which were too numerous to mention, rendered its results essentially meaningless. If you want a quote from his original paper that shows this better than anything, here it is: “We believe that the ascorbate-treated patients represent a random selection of all the terminal patients in the hospital, even though no formal randomization process was used.” Suffice it to say that, in a clinical trial, it is not sufficient to “believe” that your groups were properly randomized and matched. You have to show it. Indeed, Dr. William D. DeWys, Chief of the Clinical Investigations Branch of the National Cancer Institute’s Cancer Therapy Program, pointed out that Pauling and Cameron failed at even a rudimentary effort to control for these variables:Cameron’s patients began getting vitamin C when Cameron judged them “untreatable” and their subsequent survival was compared to that of the control patients from the time they had been labeled “untreatable.”DeWys reasoned that if the two groups were comparable, the average time from the initial diagnosis to “untreatable” status should be similar for both groups. But they were not. He concluded that many of Cameron’s patients had been labeled untreatable earlier in the course of their disease and would therefore be expected to live longer. DeWys also noted that more than 20% of the patients in the control group had died within a few days of being labeled untreatable, whereas none of Cameron’s patients had died. This, too, suggested that Cameron’s patients had had less advanced disease when they were labeled untreatable. (http://www.sciencebasedmedicine.org/index.php/high-dose-vitamin-c-and-cancer-has-linus-pauling-been-vindicated/) Among the most intriguing cases, Linus’ Pauling descent into the pseudoscience of quack medical remedies, points at two different problems 1. how difficult it is to maintain the methodological rigor that leads to scientific discoveries, then to Nobel prizes, when stepping out from one’s domain of research 2. how important it is that, in consideration of the huge difficulty each one of us has at remaining objective – including the best among us -, external controls are put into place. How is it, in fact, that such a bad study was simply published. The answer is: authority bias.  Three decades later, I have to wonder how these studies saw print. It turns out that they were originally published in the Proceedings of the National Academy of Sciences, which is not a clinical journal. Not surprisingly, given his Nobel Prizes, Linus Pauling was a member of the National Academy of Sciences. What is not really known much outside the scientific community is that thirty years ago members of the NAS could contribute papers to PNAS as they see fit and in essence pick their reviewers. Indeed, until recently, the only way that non-members could have papers published in PNAS was if a member of the Academy agreed to submit their manuscript for them (known as “communicating” it), and, in fact, members were supposed to take the responsibility for having such papers reviewed before “communicating them” to PNAS. Thus, in essence a member of the Academy could get nearly anything he or she wished published in PNAS, whether written by him or herself or a friend. Normally, this ability has not been such a big problem for quality, because getting into the NAS is so incredibly difficult and only the most prestigious scientists are invited to join. Consequently, PNAS is still a highly prestigious journal with a high impact factor, and most of its papers are of high quality. Scientists know, however, that sometimes Academy members use it as a journal of last resort to publish some of their leftover findings. They also know that on occasion, when rare members fall for dubious science, as Pauling did, they can “communicate” their questionable findings and get them published in PNAS unless they’re so outrageously ridiculous that even the deferential editorial board can’t stomach publishing them. All they have to do is to find a couple of sympathetic colleagues to review their manuscripts and then submit them. What keeps the overall quality of most of the journal’s articles high is primarily the desire of members of the Academy not to sully their names by communicating papers that they consider to be poor quality science. These days, submission requirements for PNAS are more rigorous, whether that manuscript is submitted by the member or “communicated” to the journal for another investigator. Even so, getting a paper published in PNAS is quite easy for an Academy member and incredibly difficult for a non-member who does not have the connections that allow him to line up an Academy member willing to act as referee and thus is forced to submit his manuscript directly to the journal. These observations largely explain how Linus Pauling could submit such shoddy studies to PNAS and have them published. (Thus endeth my chance for ever getting a manuscript of mine published in PNAS. Probably.) (http://www.sciencebasedmedicine.org/index.php/high-dose-vitamin-c-and-cancer-has-linus-pauling-been-vindicated/) This leads us to the consideration that critical thinking of the skeptical type might not be correlated with science education and more generally to science literacy, at least as it is measured by current factual and conceptual surveys; and to a first hypothesis: that critical thinking might be difficult to acquire and transfer to other domains. Science and pseudoscience have apparently the same object in common, though. But transfer might be so limited that there is no guarantee that knowing about the movement of planets could affect beliefs about the Loch Ness monster (maybe it could affect beliefs about the influence of planets on our life).  However, the connection of critical thinking with science might be misleading. We might be limiting critical thinking to scientific thinking (measured through something like the ACT Science Test), while scientific thinking might be something different from critical thinking.  Tests of critical thinking based on the resilience to pseudoscience might give an image of a specific variety of critical thinking, that is: skeptical thinking, but not of other varieties. As a matter of fact, no real definition of critical thinking has been provided here, yet.  
  • Critical thinking: What is it good for?(A question that can give us hints not only about why to teach, but also more ideas about why it is difficult, how to teach, and what to teach) Glaser (1941), a psychologist, and Gabennesh (a sociologist) have stressed the idea that the mastery of intellectual resources is still insufficient for critical thinking, in the absence of a commitment of rational inquiry and the habits of mind that apparently go with it. Edward Glaser (1941) has defined the mastery of critical thinking in terms of: a. an attitude, that is: being disposed to consider problems reflexively; b. a form of knowledge, that is: knowing the principles of investigation and good reasoning; c. a skill, that is: being able to apply the principles. Critical thinking is hence grounded on the will of using knowledge in an expert manner. A test has been developed in 1980: the Watson-Glaser critical thinking appraisal.Gabennesh points not only to an attitude, but to a conjunction of values and a worldview: Only two possible escapes can save us from the organized mayhem of our dark potentialities-the side of human nature that has given us crusades, witch hunts, enslavements, and holocausts. Moral decency provides one necessary ingredient, but not nearly enough. The second foundation must come from the rational side of our mentality. For, unless we rigorously use human reason . . . we will lose out to the frightening forces of irrationality, romanticism, uncompromising “true” belief, and the apparent resulting inevitability of mob action . . . Skepticism is the agent of reason against organized irrationalism-and is therefore one of the keys to human social and civic decency. (Gabennesh 2006) In this vision, critical thinking is what can protect us from our dark side, which reveals itself in history in our darkest actions. “Us” is not necessarily referred to the single person, but to humanity as a kind, a species that is governed by ancient instincts that are often at odds with the modern ideals and values of democracy and respect for others, whoever they are. In this sense, critical thinking has a moral side, because moral behavior is strongly dependent on reason and the active fight of some natural instincts, thoughts and behaviors that come naturally to the human mind. There’s another point in Gabennesh’s motivation for taking serious steps towards critical thinking, which is: truth.*  * Non-philosophers might feel a bit ill at ease at manipulating concepts such as morality and truth; I would like to reassure them that I feel strongly ill at ease too, because of the incredible burden that philosophy has put on these concepts, but we will treat them as in our practical, daily life – the one from which philosophers often forget to belong. …Peter Berger (1963, 23) states, “It can be said that the first wisdom of sociology is this-things are not what they seem.” I would alter the wording slightly - things are not always entirely what they seem - and propose it as the first wisdom of critical thinking. The recognition that the world is often not what it seems is perhaps the key feature of the critical thinker’s worldview. From this perspective, the world is a deceptive place-not just occasionally but inherently. Such a worldview goes beyond the usual suspects (e.g., deceptive TV ads and phony crop circles) to incorporate a broader recognition of the deceptive nature of the world, including such insights as:Like fish who are unconscious of the water that envelops them, we are often unaware of the constraints imposed on our thinking by the taken-for-granted social forces surrounding us-not to mention the gene-based forces within us… (Gabennesh 2006) Because things are not always or are not necessarily what they seem, then we need to make an effort not to be deceived. This is a very general point, because the world Gabennesh refers to is the physical world – deception then comes from our perceptual mechanisms, as well as from the wealth of heuristics that bias our reasoning; we will come to them later on -, but also the psychological social world of others’ minds and of the relationships and understandings our minds establish with them. So, our capacity of being deceived covers a large spectrum from falling the prey of Berlusconi’s rhetorical skills to falling the prey of astrological mumbo jumbo. The problem is: if we do not know how our mind works, we might think that perception can be taken face value, or that we are capable of resisting the sirens of commercials, and get things wrong. Getting things wrong has consequences. I will cite only one example: vaccines, because it shows how easy it is to get things wrong, and how difficult is to be “critical”, and in particular the MMR vaccine controversy, which is not a controversy because the non-correlation of MMR vaccine with autism is statistically established. However, the debate is still there since 1998, when Andrew Wakefield counterfeited evidence and published a then forced-to-retract paper on Lancet, trumpeted it in the general public press, and started a movement against vaccine. Unfortunately, measles is a leading cause of children mortality, fully preventable thanks to vaccination. MMR vaccine “controversy” illustrates the role of several tools that the human species has developed in historical times in order to protect herself from correlation biases, the power of anecdotes, the power of emotional reactions and to get closer to how things really work in the physical-biological world. As the first point about morality, the point about truth – let’s call it: the epistemological point and philosophers will be happy – can be a point about life and death. We thus have two strong motivations for being interested into critical thinking and understanding what it is exactly and how we might improve ourselves in order to become more critical. Naturally, critical thinking does not need to be so critical in order to be interesting. According to Gabennesh this motivation is an important component of what it means to be a “critical thinker”, then of the definition of critical thinking, together with skills and procedures (we will come to it later on).  By critical thinking skills, I mean the various higher-order cognitive operations involved in processing information, rather than simply absorbing it: analyzing, synthesizing, interpreting, explaining, evaluating, generalizing, abstracting, illustrating, applying, comparing, recognizing logical fallacies.It is primarily the skills dimension that most people appear to have in mind when speaking of critical thinking. This narrow focus has permitted critical thinking to become a hot topic in American education-reasoning skills can be taught in virtually any academic course at any level, and, importantly, they can be taught without venturing into sensitive areas. We can, if we wish, restrict our critical thinking skills to the safe and sanitary.Proficiency in the skills dimension is necessary but not sufficient for anyone who claims to be a critical thinker. One could excel at reasoning while failing at other dimensions of critical thinking. Indeed, this is not uncommon. A more fully developed conception of critical thinking that includes the worldview and values dimensions is both more difficult to teach and more dangerous to display than a narrow conception that focuses on logical reasoning.  … Imagine a juror in the trial of a defendant accused of murdering a child. The juror listens to the prosecution’s case, which is accompanied by grisly photos, testimony from a detective who becomes visibly shaken when describing the crime scene, and audible sobs from the victim’s family. Then, roiled by emotions ranging from grief to outrage, she is called upon to do something remarkable: listen to the defense just as receptively as she did to the prosecution.To do her job well, she will need more than good reasoning skills and the sturdy skepticism that is appropriate when listening to dueling lawyers. She will also need a certain set of values that will motivate her to do the difficult things necessary to reach an honest verdict. It takes a principled person to force aside her personal suspicions and preferences long enough to determine whether the prosecution has proved its case beyond a reasonable doubt. (Gabennesh 2006) What Gabennesh proposes is both a worldview and a set of values: on the epistemological side, the worldview consists in the assertion that things are not necessarily how they appear; the value is: truth is better than living in a lie. Those of you who are familiar with the Matrix trilogy will sense a déjà vu. If one shares both the worldview and the values, then an interest for critical thinking becomes natural.  By identifying a motivation for critical thinking in the way our mind is designed (by natural selection): deceivable not as moral as it would be desirable, we have also identified a “enemy” of critical thinking, a reason why thinking critically is apparently so difficult that many intelligent and instructed people can fall into Wakefield’s arguments or in Berlusconi’s.This is also a good reason for trying to understand whether critical thinking can be taught and enhanced through education, or some form of special education.One might be tempted to consider Gabennesh’s attitude from a relativistic point of view: a worldview is just an opinion, values are relative. However, one should seriously consider: that we wouldn’t have any science without this kind of values and that the recent developments in the study of the mind-brain-behavior provide support to the worldview.   Cognitive biasesLet us consider the classical Mueller-Lyer illusion: we might very well know that the two lines have the same length, we still cannot resist the “temptation” of perceiving them as different. Perceptual illusions are not the effect of our bad functioning (let’s say as myopia) but of the very mechanisms that make us smart and efficient at perceiving the external world. Only, in special conditions, when stimuli are ambiguous or trigger the wrong perceptual mechanism illusions ensue. In the same way, difficulties at thinking critically arise not because we are irrational, but because of the very mechanisms that make us rational and efficient at reasoning in certain conditions. These mechanisms are called heuristics: they provide us with means for answering quickly and efficiently in the situations for which they have been designed by evolution. However, the tendency to use them in other situations leads to disaster. The world does not help us at behaving as rational animals, because it is often random and ambiguous, too rich or too short with information. Erroneous beliefs ensue. A remarkable group of cognitive illusions has been described in the domain of decision-making and the evaluation of probabilities (thus involving domains such as the appreciation of statistics, prevision, choice, economy) by Nobel laureates Kahnemann and Tversky (1985). They do not cease to find further instantiations and applications. After 11/09 terroristic attacks the US have assisted to the growth of car traffic that has produced a meaningful growth of deaths in comparison to previous years and months. Rational animals would have continued to travel by plane, since they would have privileged the information about death rates above the availability of the images of the planes hitting the Twin Towers.  …the strength and resilience of certain beliefs cry out for explanation. Today, more people believe in ESP than in evolution, and in this country there are 20 times as many astrologers as there are astronomers. Both formal opinion polls and informal conversation reveal widespread acceptance of the reality of astral projection, of the authenticity of ‘channeling’, and of the spiritual and psychic value of crystals. …people do not hold questionable beliefs simply because they have not been exposed to the relevant evidence. Erroneous beliefs plague both experienced professionals and less informed laypeople alike. … Nor do people hold questionable beliefs simply because they are stupid or gullible. Quite the contrary. Evolution has given us powerful intellectual tools for processing vast amounts of information with accuracy and dispatch, and our questionable beliefs derive primarily from the misapplication or overutilization of generally valid and effective strategies for knowing. Just as we are subject to perceptual illusions in spite of, and largely because of, our extraordinary perceptual capacities, so too are many of our cognitive shortcomings “closely related to, or even an unavoidable cost of, greatest strengths”. And just as the study of illusions has illuminated general principles of perception, and the study of psycho-pathology has enhanced our knowledge of personality, so too should the study of erroneous beliefs enlarge our understanding of human judgment and reasoning. … We hold many dubious beliefs, in other words, not because they satisfy some important psychological need, but because they seem to be the most sensible conclusions consistent with the available evidence. People hold such beliefs because they seem, in the words of Robert Merton, to be the “irresistible products of their own experience”. They are the products not of irrationality but of flawed rationality. (Gilovich 1991) A good example of that is our capacity and irresistible tendency to see patterns in random distributions of events or features.  People look at the irregularities of heavenly bodies and see a face on the surface of the moon or a series of canals on Mars. Parents listen to their teenagers” music backwards and claim to hear Satanic messages in the chaotic waves of noise that are produced. While praying for his critically ill son, a man looks at the wood grain on the hospital room door and claims to see the face of Jesus; hundreds now visit the clinic each year and confirm the miraculous likeness. Gamblers claim they experience hot and cold streaks in random rolls of the dice, and they alter their bets accordingly. … Often we do impose order even when there is no motive to do so. We do not “want” to see a man in the moon. We do not profit from the illusion. We just see it. The tendency to impute order to ambiguous stimuli is simply built into the cognitive machinery we use to apprehend the world. It may have been bred into us through evolution because of its general adaptiveness: We can capitalize on ordered phenomena in ways that we cannot on those that are random. The predisposition to detect patterns and make connections is what leads to discovery and advance. The problem, however, is that the tendency is so strong that we sometimes detect coherence when it does not exist. …IgnazSemmelweis detected a pattern in the occurrence of childbed fever among women who were assisted in giving birth by doctors who had just finished a dissection. His observation led to the practice of antisepsis. … Clearly, the tendency to look for order and to spot patters is enormously helpful, particularly when we subject whatever hunches it generates to further, more rigorous test… Many times, however, we treat the products of this tendency not as hypotheses, but as established facts.  Not all beliefs, as erroneous as they might be, are born equal. Even if they are primarily entertained by a variety of mechanisms called “biases” and “heuristics”, in some cases, false beliefs are erroneous but self-serving; in other cases they are reinforced by the way information is conveyed, e.g. by the media; or they are related to cultural traditions, e.g. religion; or enforced by social bounds. Some examples of cognitive illusions, and of self-serving onesOther perceptual phenomena, les well-known, deceive us as well, but we might not notice (Chabris & Simons, 2010). A surprising example is represented by Chabris’ and Simons’ video featuring two groups of people exchanging a ball while a gorilla walks in and stops for few seconds. More than half of the viewers do not notice the gorilla if they have been previously asked to concentrate on the passes and count them. Our intuition (self-knowledge or meta-cognition) tells us that we cannot miss such an event, and this is why we are so surprised when the “trick” is revealed. The same consideration applies to our memory: our intuition tells us that we can forget, but that false memories cannot be easily implanted in our mind. A series of experiments conduced by Elisabeth Loftus and colleagues falsifies our intuition. We also have a tendency for overestimating our capacities and knowledge (and to apply the same optimistic filter to the people we know and love). For instance, we have the impression of being able to answer to questions like: Why is the sky blue? But when we are tested deeply, we are not necessarily able to come up with an explanation. Our knowledge is often shallower than we think. This is a reason for testing deeply the knowledge of students. Chabris and Simons have also tested expert chess players before their participation to a tournament: they asked them to evaluate their present position in the classification: 75% thinks to be under-rated (the classification is however robust and valid, since it allows to foresee the result of a match between two participants that hold different positions in the classification, and players receive constant feed-back about their level). It is possible that the tendency to keep track of the hits and forget the misses has a part in this. We are not only self-confident, but appreciate self-confident people (the physician who immediately announces a diagnosis and prescription is more appreciated than the one who takes her time for consulting the literature; even if the second one has the best chances of taking the good decision). We thus entertain a certain number of cognitive illusions with an optimistic allure: « By now you may be sensing a pattern to the everyday illusions we have been discussing : They all tend to cast an overly favorable light on our mental capacities. There are no illusions of blindness, amnesia, idiocy, and cluelessness. Instead, everyday illusions tell us that we perceive and remember more than we do, that we are all above average, and that we know more about the world and the future than is justified. Everyday illusions might be so persistent and pervasive in our thought patterns precisely because they lead us to think better of ourselves that we objectively should. Positive illusions can motivate us to get out of bed and optimistically take up challenges we might shrink from if we constantly had the truth about our minds in mind. » (Chabris & Simons, 2010, p. 126) Opposite to the rest of misconceptions – which can be the byproduct of otherwise useful mechanisms – optimistic illusions might even have an adaptive value in themselves (McKay & Dennett, 2009), and even a “therapeutic value” for our mental health (Taylor & Brown, 1988). It has been shown in fact that those who hold intelligence to be fluid and dynamic do better at learning than those who hold intelligence to be fixed, independently from the fact that they portray themselves as more or less intelligent at the start (Dweck & Sorich, 1999). Because of their intrinsic adaptive value optimistic cognitive illusions might then be especially hard to fight. Cognitive illusions that hinder knowledge about reality (scientific thinking)Meta-cognitive illusions of the optimistic sort are associated with illusions that affect the way we acquire knowledge about the world. We “perceive” patterns and correlations, not only within perceptual cues, but also among conceptual objects.We tend to see associations when there’s none and causal relationships where there is only correlation: there’s no significant association between MMA vaccine and autism, but MMA vaccine is currently suspected of causing it, and avoided by families and physicians. We tend to confirm our views and to reinforce our opinions by searching for concordant information and discarding the rest. This is why science has developed rigorous methods for observation: randomization, control groups, blind assignment and analysis, and the principle of replication. They all testify of the difficulty of observing the world without imposing distortions that depend on our cognitive apparatus.  A further class of illusions shares common grounds with meta-cognitive and observational illusions: we sometimes have the impression of being on the right track, of having understood and of being in front of a good explanation, but this is not necessarily true. The affective component of understanding – the fact that an explanation “sounds” satisfying can be influenced by cognitive biases, such as hindsight (I knew it all along) and self-confidence (Trout, 2002). This pessimism has ben criticized: the epistemic sensation of understanding (the ahah! At the end of a research) might have an adaptive value (equivalent to the orgasm for sexual reproduction) because it would provide the motivation for pursuing the research (Gopnik, 1998). Even if this is the origin of the positive feeling of understanding, nothing says that in some occasions an adaptive trait cannot deceive us: it is the case of the taste for sugar in a world of supermarkets. As a matter of fact, our judgment of understanding seems to be influenced by irrelevant features such as jargon and the presence of images (Weisberg, 2008; McCabe & Castel, 2008; Weisberg, et al., 2008). At least in part, the limits of our intuition represent the counterpart for having developed other, adaptive capacities. Even if we make abstraction from differences and oppositions between positions:reasoning (logical, factual reasoning not influenced by irrelevant features) does not come easily and naturally to the mind, but is hindered by natural constraints in the form of cognitive biases produced by “heuristics” and by the failure to identify themheuristics are shortcuts to decision-making; if we accept the view that heuristics are tools evolved for answering concrete, life-related problems that afflicted our ancestors and facilitating decision-making in the absence of solid grounds and proper reflection, then we should not be surprised that heuristics can serve as badly when the circumstances differ significantly from those that have put the evolutionary pressure on our specieshowever, heuristics are not necessarily always bad; it depends on the circumstances, the quantity and quality of information available, the domain of application of the heuristic; and errors are not just under the responsibility of intuition and heuristics, but also of the failure to identify them and put them under appropriate control.  External featuresThe consideration of the limits of human reasoning and of the illusions that affect daily choices as well as objective knowledge of the world constitutes a good reason for mistrusting our intuition, or at least for being cautious and aware. Other considerations speak in favor of taking critical thinking seriously, especially in present times. We are, as never in the past, submerged of information and “good information” (wheat) risks to be drowned by noise (chaff). This, while we are asked to take decisions that involve the capacity of evaluating scientific knowledge and reacting to it reflectively.   a. Informational overloadThe first consideration is especially connected with educational problems. We live in a time of life-long learning, open education, and in the omni-presence of information. Technology has a big part on this transformation of the image of information and of This observation is not judgmental, but requires us to take into account developments that might change but not reverse their course: ICT are here to stay, available information will be more and more available and its quantity will grow, education will be more and more “open”, in the sense of the MIT Opencourseware or of the Kahn Academy.«  Watching a TEDTalk is not a passive act -- it's the beginning of a deep interaction with a bold idea. Our commenting system on TED.com allows for spirited conversation around the talks, and our Creative Commons license (Attribution-NonCommercial-NonDerivative) lets viewers share them freely. Every day, we watch our audience engage with our content and with one another through email, Twitter, Facebook, and hundreds of thousands of blog posts… TEDTalks often go viral -- gaining wide viewership through "word of mouth" on social media sites such as Facebook, Twitter, YouTube, StumbleUpon and Reddit. When we release a talk, we update our official Facebook page, post messages to our Twitter streams and upload the video to our YouTube channel, immediately reaching more than 4 million users » (TED : http://www.ted.com/) How can we judge whether this information can be trusted, how can we part wheat from chaff? Google provides « About 117,000,000 results (0.14 seconds) » for a query about climate change. Is it possible that a certain moment “the good information” will be buried under tons of trash or drowned by noise? The issue of climate change is controversial and not easy to judge: even Nobel laureates (Cary Mullis) oppose the view that climate change is being influenced by our way of living, and accuse scientists of being at the service of politicians. How does the technology help us taking part to the debate or form a view?   b. Reinforcement of confirmation biasOn my computer the first results are dominated by governmental agencies, but this is not true for everybody. A phenomenon called “filter bubble” primes results that conform with the users’ views as they can be inferred by their previous searches. The phenomenon is apparently common to search engines, social networks, commercial web sites, online newspapers. It maybe helps us gaining some time, but at the same time it certainly reinforces our natural confirmation bias: putting our ideas to the trial, discovering different points of view and becoming more critical is more and more difficult; The multiplication of information and the way it is made available require a difficult exercise of suspension of belief and of skepticism, as well as good tools for evaluating the reliability of sources. A general theoretical frameworkThe (world)view exposed above (and Gabennesh’s approach to critical thinking) fits with the model, developed by psychologists and Nobel laureates (economy) Daniel Kahnemann and Amos Tversky, that pictures the human decision making apparatus as served by two systems (Kahnemann, 2003): (Intuition) Intuitive mode or system 1= judgments and decisions are made automatically and rapidly. Operations of system 1 are fast, automatic, associative, effortless, implicit, emotionally charged, governed by habit, difficult to control and modify. Intuitions are “thoughts and preferences that come to mind quickly and without much reflection” “Intuitive judgments occupy a position – perhaps corresponding to evolutionary history – between the automatic operations of perception and the deliberate operations of reasoning.”(Reasoning) Controlled mode or system 2 = deliberate and slow. Operations of system 2 are slower, serial, effortful, more likely to be monitored and controlled, emotionally neutral, more flexible and rule governed. Reasoning is purely logical. “Doubt is a phenomenon of System 2, a meta-cognitive appreciation of one’s ability to think incompatible thoughts about the same thing”.The 2 systems model is used to explain the - Observation of discrepancies in the statistical judgments: intuitive judgment of experts does not conform to statistical principles- Observation of decision-making- Accessibility = “ease (or effort) with which certain contents come to mind” affects choices- Observation of Framing effect = preferences can be affected by variations of irrelevant features- Observation of the characteristics of judgment under uncertainty (judgments of uncertain events): “people rely on a limited number of heuristic principles which reduce the complex task of assessing probabilities and predicting values to simple judgmental operations. In general these heuristics are quite useful, but sometimes they lead to severe and systematic errors.” Heuristics can thus induce biases (cognitive illusions); i.e. when relying on the blur of contours for estimating the distance of a mountain, one can be wronged by the unaccounted presence of fog. (Heuristics are derived from the observation of the errors they tend to produce; i.e.: Availability, Representativeness, Anchoring, Affect) + related biases).System 2 monitors System 1; hence, errors are also under the responsibility of System 2 that has failed at identifying the mistake (the bias): “An intuitive judgment will be modified or overridden if System 2 identifies it as biased.” E.g., in the domain of statistics, positive effects (enhancement of the accessibility of statistical heuristics) are achieved by increasing the vigilance of monitoring activities, by providing stronger cues to the relevant rules, and by extensive training in applied statistical reasoning. In the absence of primes and reminders the accessibility of statistical heuristics is low. … The present analysis of judgment implies that statistical training does not eradicate intuitive heuristics such as availability or representativeness but only enables people to avoid some biases under favorable circumstances.  This view is partly opposed by GerdGigerenzer, who also studies bounded rationality and decision-making, director of the Max Planck Institute for Human Development, but sees heurisics as valuable assets rather than limits to rational thinking: it is our way of being rational, which is not the informal logic-calculus of probability way.
  • CONCLUSIONS In summary, thinking critically does not seem to come easily (with no effort) and automatically (preferentially) to the mind because:several forms of cognitive illusions “bound our rationality”thinking is effortful and maybe it represents a “second choice” response to the environment, in “normal conditions”.If we extrapolate from this view, teaching and training reason and critical thinking skills seems to be a desirable option, but: reason should not be sharply opposed to intuition in the sense that how to deal with intuitions should be trainedthere are good reasons for thinking that learning to reason and thinking critically is not straightforward, and might not be successful. No miracle Everybody seems to agree, with different shades, with this image of our rational apparatus: bounded, flawed and constituted of several modules, each related to a particular type of problem, rather than by a general purpose algorithm.  Critical thinking might not be a natural cognitive ability, but a term including several forms of good thinking in several disciplines.  A “definition fits all” for good thinking in any discipline or context should then be avoided. Good thinking would consist in adopting the relevant criteria for truth in that discipline or context – it thus permits to part wheat from chaff, but is not limited to that. E.g. in reading a text it could lead to extracting a maximum of information, understanding the intentions of the author, and so on. A good reader has not the same criteria in mind that a good chemist.This definition fits with the fact that critical thinking does not seem to be a general capacity: no one is good at thinking in any discipline, thinking well requires both a mastery of domain-specific criteria and of background knowledge.This is a rather sobering view for those who hope to teach or learn to think critically. Moreover, even if natural germs of critical thinking are present in the human mind, we cannot hope to be critical thinkers by instinct: critical thinking is the effect of an effort, and, apparently, of culture and education.  Bransford and colleagues in 2000 and Bruer in 1999 have listed the main characteristics of expert knowledge, in order to extract rules about how to favor the acquisition of new knowledge.  “People who have developed expertise in particular areas are, by definition, able to think effectively about problems in those areas. 1. Experts notice features and meaningful patterns of information that are not noticed by novices. 2.  Experts have acquired a great deal of content knowledge that is organized in ways that reflect a deep understanding of their subject matter. 3.  Experts' knowledge cannot be reduced to sets of isolated facts or propositions but, instead, reflects contexts of applicability: that is, the knowledge is ''conditionalized" on a set of circumstances. 4.  Experts are able to flexibly retrieve important aspects of their knowledge with little attentional effort. 5.  Though experts know their disciplines thoroughly, this does not guarantee that they are able to teach others. 6.  Experts have varying levels of flexibility in their approach to new situations.” (Bransford et al. 2000, p. 19) Apparently, becoming an expert requires time, but not just for memorizing facts. In fact, extensive training helps constructing pattern recognition skills: experts train in various situations, organize the information, and use their meta-cognitive skills in order to monitor their progression, etc. Thus, it is not just time, but time used well. Since time requires motivation, motivation is a crucial ingredient for becoming experts.  “It has been estimated that world-class chess masters require from 50,000 to 100,000 hours of practice to reach that level of expertise; they rely on a knowledge base containing some 50,000 familiar chess patterns to guide their selection of moves (Chase and Simon, 1973; Simon and Chase, 1973). Much of this time involves the development of pattern recognition skills that support the fluent identification of meaningful patterns of information plus knowledge of their implications for future outcomes” (Bransford, et al. 2000, p. 44) Even if it does not seem possible to learn to learn in the absence of contents and even less in the absence of effort, is it possible to become better learners, or intelligent novices? Intelligent novices are novices capable of becoming experts in a new domain quickly and effectively (in comparison with other novices). Meta-cognitive skills and self-regulation seem to play a role in becoming “ready to become experts”, even if they do not represent shortcuts, thus: domain knowledge remains essential. Critical thinking might travel from one form of expertise to another by the same roads. However, a better knowledge our own mental functioning from a scientific point of view might help: typical biases, typical illusions; at least it seems to be necessary in order to acquire the worldview that goes with critical thinking.  Also, it seems that one must be ready to accept that we are not perfect critical thinking machines, but rather “heuristic machines”. If we cannot hope to become really efficient at parting wheat from chaff, and chaff tends to invade our information panorama, then we should consider the adoption of “external” strategies for reducing chaff, at least in “perilous” situations, and of strategies for favoring the use of the “right heuristic” (reframing of problems). Even if it is not a natural cognitive ability, a preliminary problem to solve, in order to assess critical thinking skills, as well as in order to understand what is it, and to teach and learn how to do it, is then to understand the kind of cognitive faculties that are necessary in order to develop critical thinking skills. This research falls in the domain of cognitive science, but cognitive science does not seem to have dealt with it directly. Natural capacities that might be involved in the process of thinking well, or at least in the skeptical form of critical thinking, are- the capacity of inhibiting immediate adherence to perceptions and ideas- the capacity and disposition to detect cheating in others. If critical thinking does not come naturally to our mind, and it is as difficult to acquire and transfer as it seems, then education alone, intended as the transformation of the learner in a better thinker, is not enough. In addition to providing criteria, nurturing a certain worldview and values, teaching heuristics, educating to disciplinary contents and methods, external scaffoldings might be required. They can take the form of maps for visualizing structures, or of checklists for giving support to procedures and choices.

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  • 1. Teaching for critical thinking CT WHAT IS IT? HOW TO TEACH IT? WHAT FOR?
  • 2. A wide interest, and the multiplication of initiatives
  • 3. Initiatives on the teaching and assessment of 21st century skills originate in the widely-held belief shared by several interested groups teachers, educational researchers, policy makers, politicians, employers that the current century will demand a very different set of skills and competencies from people in order for them to function effectively at work, as citizens and in their leisure time (e.g. Dede, 2007; Kalantzis and Cope, 2008). Initiatives such as the Partnership for 21st skills (www.21stcenturyskills.org) and the Cisco/Intel/Microsoft assessment and teaching of 21st century skills project (www.atc21s.org) also point to the importance currently attached to this area not only by researchers, practitioners and policy makers but also the private sector. Supporters and advocates of the 21st century skills movement argue for the need for reforms in schools and education to respond to the social and economic needs of students and society in the 21st century. (Ananiadou & Claro, 2009)
  • 4. There is a widespread acceptance of the idea that critical thinking should be an important dimension of science education. Thus, for example, the National Science Education Standards (1996) has as one of its goals the promotion of science as inquiry. Included in this goal are numerous items which focus on critical thinking, for example “identification of assumptions, use of critical and logical thinking, and consideration of alternative explanations (p. 23); “analysis of firsthand events and phenomena a well as critical analysis of secondary sources; testing reliability of knowledge they have generated” (p.33); and “the critical abilities of analyzing an argument by reviewing current scientific understanding, weighing the evidence, and examining the logic so as to decide which explanation and models are best. (Bailin 2002)
  • 5. No consensus about what is CT, how to teach it, whether it can be learnt
  • 6. • Resnick 1987 Inevitably, we hear the question: Is there really anything new about schools' trying to teach higher order skills? Haven't schools always hoped to teach students to think critically, to reason, to solve problems, to interpret, to refine ideas and to apply them in creative ways? Nevertheless, we seem to agree that students do not adequately learn these higher order abilities. Perhaps the fact that our schools have been less than successful at meeting these goals means that we have simply given up the old truths in education. Perhaps if we went back to old- fashioned courses and old-fashioned methods, the problem of teaching higher order skills would be solved without further special attention. Or, more pessimistically, perhaps we should conclude that decades of trying unsuccessfully to teach higher order skills in school show that such goals are not reachable; perhaps higher order abilities develop elsewhere than in school, and it would be wisest for schools to concentrate on the “basics,” letting higher order abilities emerge later or under other auspices.
  • 7. • Willingham 2007 virtually everyone would agree that a primary, yet insufficiently met, goal of schooling is to enable students to think critically. In layperson’s terms, critical thinking consists of seeing both sides of an issue, being open to new evidence that disconfirms your ideas, reasoning dispassionately, demanding that claims be backed by evidence, deducing and inferring conclusions from available facts, solving problems, and so forth. Then too, there are specific types of critical thinking that are characteristic of different subject matter: That’s what we mean when we refer to “thinking like a scientist” or “thinking like a historian.” This proper and commonsensical goal has very often been translated into calls to teach “critical thinking skills” and “higherorder thinking skills”—and into generic calls for teaching students to make better judgments, reason more logically, and so forth.
  • 8. Willingham 2007 After more than 20 years of lamentation, exhortation, and little improvement, maybe it’s time to ask a fundamental question: Can critical thinking actually be taught? Decades of cognitive research point to a dis- appointing answer: not really. People who have sought to teach critical thinking have assumed that it is a skill, like riding a bicycle, and that, like other skills, once you learn it, you can apply it in any situation. Research from cognitive science shows that thinking is not that sort of skill. The processes of thinking are intertwined with the content of thought (that is, domain knowledge).
  • 9. Teaching for critical thinking CT WHAT IS IT? HOW TO TEACH IT? WHAT FOR?
  • 10. The problem of the definition
  • 11. The first difficulties arise with the very question of what is meant by the term “higher order skills.” Many candidate definitions are available. Philosophers promote critical thinking and logical reasoning skills, developmental psychologists point to metacognition, and cognitive scientists study cognitive strategies and heuristics. Educators advocate training in study skills and problem solving. How should we make sense of these many labels? Do critical thinking, metacognition, cognitive strategies, and study skills refer to the same kinds of capabilities? And how are they related to the problem-solving abilities that mathematicians, scientists, and engineers try to teach their students? (Resnick 1987)
  • 12. Higher order thinking • Higher order thinking is nonalgorithmic. That is, the path of action is not fully specified in advance. • Higher order thinking tends to be complex. The total path is not “visible” (mentally speaking) from any single vantage point. • Higher order thinking often yields multiple solutions, each with costs and benefits, rather than unique solutions. • Higher order thinking involves nuanced judgment and interpretation. • Higher order thinking involves the application of multiple criteria, which sometimes conflict with one another. • Higher order thinking often involves uncertainty. Not everything that bears on the task at hand is known. • Higher order thinking involves self-regulation of the thinking process. We do not recognize higher order thinking in an individual when someone else “calls the plays” at every step. • Higher order thinking involves imposing meaning, finding structure in apparent disorder. • Higher order thinking is effortful. There is considerable mental work involved in the kinds of elaborations and judgments required. (Resnick 1987 p. 7)
  • 13. sKepticism Critical thinking can be defined at minima, as the faculty of parting wheat from chaff, of distinguishing good arguments from bad ones (because they are ill-formed) and identifying beliefs that can be given away (because they are not justified).
  • 14. In search for consensus… We understand critical thinking to be 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. CT is essential as a tool of inquiry. As such, CT is a liberating force in education and a powerful resource in one's personal and civic life. While not synonymous with good thinking, CT is a pervasive and self-rectifying human phenomenon. The ideal critical thinker is habitually inquisitive, wellinformed, trustful of reason, open-minded, flexible, fair-minded in evaluation, honest in facing personal biases, prudent in making judgments, willing to reconsider, clear about issues, orderly in complex matters, diligent in seeking relevant information, reasonable in the selection of criteria, focused in inquiry, and persistent in seeking results which are as precise as the subject and the circumstances of inquiry permit. Thus, educating good critical thinkers means working toward this ideal. It combines developing CT skills with nurturing those dispositions which consistently yield useful insights and which are the basis of a rational and democratic society. (Facione 1990)
  • 15. Philosophical approach = normative • • • • • • Socrate’s elenchus as in Plato’s dialogues Aristotle Classical skepticism Thomas of Aquinas Descartes: Rules for the direction of the mind … CT = Good thinking (in general/within a discipline) Thinking that complies to norms (logical norms & methods to follow) • • • • Francis Bacon: The advancement of learning Robert Boyle: Sceptical Chymist Galileo Galilei …
  • 16. Definitions of critical thinking emerging from the philosophical tradition include “the propensity and skill to engage in an activity with reflective skepticism” (McPeck, 1981, p. 8); “reflective and reasonable thinking that is focused on deciding what to believe or do” (Ennis, 1985, p. 45); “skillful, responsible thinking that facilitates good judgment because it 1) relies upon criteria, 2) is self-correcting, and 3) is sensitive to context” (Lipman, 1988, p. 39); “purposeful, self-regulatory judgment which results in interpretation, analysis, evaluation, and inference, as well as explanation of the evidential, conceptual, methodological, criteriological, or conceptual considerations upon which that judgment is based” (Facione, 1990, p. 3); “disciplined, self-directed thinking that exemplifies the perfections of thinking appropriate to a particular mode or domain of thought” (Paul, 1992, p. 9); thinking that is goal-directed and purposive, “thinking aimed at forming a judgment,” where the thinking itself meets standards of adequacy and accuracy (Bailin et al., 1999b, p. 287); and “judging in a reflective way what to do or what to believe” (Facione, 2000, p. 61). (Lai 2011)
  • 17. Psychological approach = descriptive • Research on reasoning, and its limits • Research on judgment • Research on decision-making • Research on problem-solving CT = skills & dispositions for - thinking, thinking about thinking - in general or within a certain domain + why thinking is hard • Research on meta-cognition • Research on expertise • Research on strategies …
  • 18. cognitive scientists do not study critical thinking much, at least not as a topic in its own right. This is partly because the topic is too broad and open-ended to be captured by the cognitive scientist’s tightly focuses techniques. Partly, it is also because critical thinking in general is a neglected topic, despite its importance and broad relevance. Nevertheless, cognitive scientists have some contributions to make. They have developed some very general insights into how we think and how we learn, and these can be carried over to critical thinking. They also have studied many phenomena that are particular aspects or dimensions of critical thinking. (van Gelder 2005) humans are not naturally critical. Indeed, like ballet, critical thinking is a highly contrived activity. Running is natural; nightclub dancing is less so; but ballet is something people can only do well with many years of painful, expensive, dedicated training. Evolution did not intend us to walk on the ends of our toes, and whatever Aristotle might have said, we were not designed to be at all that critical either. Evolution foes not waste effort making things better than they need to be, and homo sapiens evolved to be just logical enough to survive, while competitors such as Neanderthals and mastodons died out. (van Gelder 2005)
  • 19. the mental activities that are typically called critical thinking are actually a subset of three types of thinking: reasoning, making judgments and decisions, and problem solving. I say that critical thinking is a subset of these because we think in these ways all the time, but only sometimes in a critical way. Deciding to read this article, for example, is not critical thinking. But carefully weighing the evidence it presents in order to decide whether or not to believe what it says is. Critical reasoning, decision making, and problem solving—which, for brevity’s sake, I will refer to as critical thinking—have three key features: effectiveness, novelty, and self-direction. Critical thinking is effective in that it avoids common pitfalls, such as seeing only one side of an issue, discounting new evidence that disconfirms your ideas, reasoning from passion rather than logic, failing to support statements with evidence, and so on. Critical thinking is novel in that you don’t simply remember a solution or situation that is similar enough to guide you. For example, solving a complex but familiar physics problem by applying a multi-step algorithm isn’t critical thinking because you are really drawing on memory to solve the problem. But devising a new algorithm is critical thinking. Critical thinking is self-directed in that the thinker must be calling the shots: We wouldn’t give a student much credit for critical thinking if the teacher were prompting each step he took. (Willingham 2007)
  • 20. Teaching for critical thinking CT WHAT IS IT? HOW TO TEACH IT? WHAT FOR?
  • 21. «Dreams, the position of the stars, the lines of the hand, may be regarded as valuable signs, and the fall of cards as an inevitable omen, while natural events of the most crucial significance go disregarded. Beliefs in portents of various kinds, now mere nook and cranny superstitions, were once universal. A long discipline of exact science was required for their conquest. » (Dewey, 1910, p. 21) « The whole object of intellectual education is formation of logical disposition » (Dewey, 1910, p. 57).
  • 22. Ways of teaching CT • formal teaching, e.g. working on some form of brain gym, such as chess • theoretical instruction, i.e. by learning the theory • situated cognition, from the extreme of denying general critical thinking skills to the idea of acquiring critical thinking skills through engaging in domainspecific activities • practice, e.g. applying the skills to several domains, that vary • evolutionary psychology, i.e. consolidating skills we are naturally endowed with. • Stand alone: domaingeneral, content-free • Integrated: domainspecific, content-rich • Mixed: domains + generalization
  • 23. Stand-alone • DeBono’s CoRT • Productive Thinking Program – both based on planning and meta-cognitive skills • reading and studying from texts • improvement of general intelligence, roblem-solving techniques, memory strategies, informal • Lipman’s Harry Stottlemeyer - activities for enhancing argumentation skills and logics
  • 24. some programs focus largely on identifying and correctly variety of practice and labeling reasoning fallacies; others concentrate more on developing skills of argumentation in extended discourse, without extensive formal analysis. An important debate in the field exactly parallels psychologists' discussions of whether general cognitive skills or specific knowledge is most central to intellectual competence. (Renick 1987) Most informal logic philosophers believe that general reasoning capacity can be shaped and that it transcends specific knowledge domains (e.g., Ennis, 1980, 1985). In an even stronger claim, Paul (1982, in press) argues that we should seek to develop in students a broadly rational personality rather than any set of technical reasoning skills. This view usually, but not always, supports calls for independent critical thinking courses. However, a competing view, most strongly stated by McPeck (1981), argues that no general reasoning skill is possible and that all instruction in thinking should be situated in particular disciplines.
  • 25. Integrated • Lilienfeld, Lohr and Morier (2001) have underlined the importance of introducing specific teachings of science and pseudo-science in the cursus of psychological studies, where myths abound. • Reif et al 1974 for physics; the work of Frederick Reif is extensive and he has dedicated as much attention to physics as to cognitive science and developing thinking skills in physics • EMB shares many common aims and tools with the idea of teaching and learning to think critically, including the aim of developing a critical appraisal of evidence and ideas received from tradition and authority.
  • 26. Mixed While teaching critical thinking in one discipline, one can • provide explicit instruction about rules and promote the use of metacognitive attitudes towards learning: • anchor instruction on concrete cases, and propose variations (same inner structure, different superficial content), so as to favor flexibility • do not bound instruction to implicit learning, but explicit both acquired knowledge and its contexts of application • explicit the processes that have produced knowledge acquisition, difficulties, strategies, that is: explicitly use and train metacognitive skills.
  • 27. Limits of teaching CT CT & other higher skills teaching programs • Resnick 1987 Thinking and problem-solving programs within the academic disciplines seem to meet their internal goals and perhaps even boost performance more generally. It seems possible to raise reading competence by a variety of methods, ranging from study skill training through the reciprocal teaching methods of Brown and Palincsar to the discussions of philosophical texts in Lipman's program. On the other hand, general improvements in problem-solving, rhetoric, or other general thinking abilities have rarely been demonstrated, perhaps because few evaluators have included convincing assessments of these abilities in their studies.
  • 28. The problem with evaluations • Willingham 2007 How well do these programs work? Many researchers have tried to answer that question, but their studies tend to have methodological problems. Four limitations of these studies are especially typical, and they make any effects suspect : 1) students are evaluated just once after the program, so it’s not known whether any observed effects are enduring; 2) there is not a control group, leaving it unclear whether gains are due to the thinking program, to other aspects of schooling, or to experiences outside the classroom; 3) the control group does not have a comparison intervention, so any positive effects found may be due, for example, to the teacher’s enthusiasm for something new, not the program itself; and 4) there is no measure of whether or not students can transfer their new thinking ability to materials that differ from those used in the program. In addition, only a small fraction of the studies have undergone peer review (meaning that they have been impartially evaluated by independent experts).
  • 29. Difficulties with teaching CT CT & The problem with content • • • • 1. content knowledge boosts performances, e.g. because it affects texts comprehension or because it helps recasting problems in more solvable configurations; 2. the application of general procedures to specific knowledge might require adjustments, or even just raise the problem of understanding that that certain procedure applies 3. specific knowledge might trigger specific naïve ideas, biases and heuristics that hinder a good solution to the problem 4. Even metacognitive skills are not as general as they might seem: even metacognitive skills are enhanced by domain knowledge, and domain knowledge favors the skilled use of metacognitive capacities within the perimeter
  • 30. CT & The problem of transfer and generalization students can learn metacognitive strategies that help them look past the surface structure of a problem and identify its deep structure, thereby get- ting them a step closer to figuring out a solution. Essentially the same thing can happen with scientific thinking. Students can learn certain metacognitive strategies that will cue them to think scientifically. But, as with problem solving, the metacognitive strategies only tell the students what they should do—they do not provide the knowledge that students need to actually do it. The good news is that within a content area like science, students have more context cues to help them figure out which metacognitive strategy to use, and teachers have a clearer idea of what domain knowledge they must teach to enable students to do what the strategy calls for. (Willingham 2005)
  • 31. CT & The modular mind • Resnick 1987 Over the decades, educators have espoused a recurring belief that certain school subject matters “discipline the mind” and therefore should be taught not so much for their inherent value as for their efficacy in facilitating other learning. Latin was defended for many years in these terms; mathematics and logic are often so defended today. Most recently, computer programming has been proposed as a way to develop general problem-solving and reasoning abilities (e.g., Papert, 1980). The view that we can expect strong transfer from learning in one area to improvements across the board has never been well supported empirically.
  • 32. Tooby & Cosmides 1997: Modularims in the framework of the evolved mind "General intelligence" -- a hypothetical faculty composed of simple reasoning circuits that are few in number, content-independent, and general purpose -- was thought to be the engine that generates solutions to reasoning problems. The flexibility of human reasoning -- that is, our ability to solve many different kinds of problems -- was thought to be evidence for the generality of the circuits that generate it. An evolutionary perspective suggests otherwise (Tooby & Cosmides, 1992). Biological machines are calibrated to the environments in which they evolved, and they embody information about the stably recurring properties of these ancestral worlds. is also content-independent. It can be applied indiscriminately to medical diagnosis, card games, hunting success, or any other subject matter. It contains no domain-specific knowledge, so it cannot support inferences that would apply to mate choice, for example, but not to hunting. (That is the price of contentindependence.)
  • 33. Evolved problem-solvers, however, are equipped with crib sheets: they come to a problem already "knowing" a lot about it. Without these privileged hypotheses -- about faces, objects, physical causality, other minds, word meanings, and so on -- a developing child could learn very little about its environment. This suggests that many evolved computational mechanisms will be domain-specific: they will be activated in some domains but not others. Some of these will embody rational methods, but others will have special purpose inference procedures that respond not to logical form but to content-types -- procedures that work well within the stable ecological structure of a particular domain, even though they might lead to false or contradictory inferences if they were activated outside of that domain. The more crib sheets a system has, the more problems it can solve. A brain equipped with a multiplicity of specialized inference engines will be able to generate sophisticated behavior that is sensitively tuned to its environment.
  • 34. Discipline-embedded approach This discipline-embedded approach has several advantages. First, it provides a natural knowledge base and environment in which to practice and develop higher order skills. As we have shown earlier, cognitive research has established the very important role of knowledge in reasoning and thinking. One cannot reason in the abstract; one must reason about something. Second, embedding higher order skill training within school disciplines provides criteria for what constitutes good thinking and reasoning within the disciplinary tradition. Each discipline has characteristic ways of reasoning, and a complete higher order education would seek to expose students to all of these. Reasoning and problem solving in the physical sciences, for example, are shaped by particular combinations of inductive and deductive reasoning, by appeal to mathematical tests, and by an extensive body of agreed upon fact for which new theories must account. Finally, teaching higher order skills within the disciplines will ensure that something worthwhile will have been learned even if wide transfer proves unattainable. This point is profoundly important. It amounts to saying that no special, separate brief for teaching higher order skills need be made. Rather, it proposes that if a subject matter is worth teaching in school it is worth teaching at a high level—to everyone. Resnick 1987
  • 35. Science & CT: a privileged relationship?
  • 36. Science education Apparent de-correlation between CT and • science education • the diffusion of scientific literacy has not defeated pseudo-scientific beliefs by and large (see Gallup Poll, Pew Survey, …) • the study of science, at least as science is taught today, does not make the difference in terms of pseudo-scientific beliefs How then are we to reconcile having the most scientifically trained society in history with the persistence of irrationality? Why do we not see a significant drop of irrationality corresponding to the significant increase in the levels of general science education in the last fifty years? (Ede 2000)
  • 37. THE NOBEL DISEASE • • • • • • • • • • • • • Pierre Curie, physics (Eusapia Palladino) Ivar Giaever, physics (global warming denier) Louis J. Ignarro, physiology or medicine (Herbalife Niteworks) Brian Josephson, physics (psi) Philipp Lenard, physics (Nazi ideology) Luc Montagnier, medicine (autism) Kary Mullis, chemistry (supports astrology, denies anthropogenic climate change, denies HIV causes AIDS) Linus Pauling, chemistry (vitamin C) Charles Richet, physiology (ectoplasm/mediums/telepathy) William Shockley, physics (race & IQ) John William Strutt, 3rd Baron Rayleigh, physics (president Society for Psychical Research) Nikolaas Tinbergen, physiology or medicine (autism) James Watson, physiology or medicine (race & IQ)
  • 38. Teaching for critical thinking CT WHAT IS IT? HOW TO TEACH IT? WHAT FOR?
  • 39. Further difficulties with teaching CT CT & The problem with motivation Some have stressed the idea that the mastery of intellectual resources is still insufficient for critical thinking, in the absence of a commitment of rational inquiry and the habits of mind that apparently go with it. Edward Glaser (1941) has defined the mastery of critical thinking in terms of: a. an attitude, that is: being disposed to consider problems reflexively; b. a form of knowledge, that is: knowing the principles of investigation and good reasoning; c. a skill, that is: being able to apply the principles.
  • 40. A worldview: Irrational minds, with intuitions that cannot be trusted Only two possible escapes can save us from the organized mayhem of our dark potentialities-the side of human nature that has given us crusades, witch hunts, enslavements, and holocausts. Moral decency provides one necessary ingredient, but not nearly enough. The second foundation must come from the rational side of our mentality. For, unless we rigorously use human reason . . . we will lose out to the frightening forces of irrationality, romanticism, uncompromising “true” belief, and the apparent resulting inevitability of mob action . . . Skepticism is the agent of reason against organized irrationalismand is therefore one of the keys to human social and civic decency. (Gabennesh 2006)
  • 41. Values … Imagine a juror in the trial of a defendant accused of murdering a child. The juror listens to the prosecution’s case, which is accompanied by grisly photos, testimony from a detective who becomes visibly shaken when describing the crime scene, and audible sobs from the victim’s family. Then, roiled by emotions ranging from grief to outrage, she is called upon to do something remarkable: listen to the defense just as receptively as she did to the prosecution. To do her job well, she will need more than good reasoning skills and the sturdy skepticism that is appropriate when listening to dueling lawyers. She will also need a certain set of values that will motivate her to do the difficult things necessary to reach an honest verdict. (Gabennesh 2006)
  • 42. NO miracle • CT is not a skill, but a domain-specific aptitude and attitude – CT requires domain knowledge – CT depends on values and a worldview – CT is hardly trasferred from one domain & context to another • Thinking is hard to teach, even within a discipline (e.g. science)