why is metacognition important in critical thinking

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Metacognition & Critical Thinking: What's The Connection?

Introduction.

A few definitions for clarification before we begin: Metacognition: is the cognitive aspect of the self-regulated learning cycle, it refers to knowledge and awareness of thought processes and, in practice, involves the planning, monitoring, evaluating and regulating of thought-processes underpinning learning.

Critical Thinking: most definitions focus on the rational, sceptical, unbiased analysis, or evaluation of factual evidence. A more sophisticated and comprehensive definition is provided by Elder (2007): “Critical thinking is self-guided, self-disciplined thinking which attempts to reason at the highest level of quality in a fair-minded way. People who think critically consistently attempt to live rationally, reasonably, empathically. They are keenly aware of the inherently flawed nature of human thinking when left unchecked. They strive to diminish the power of their egocentric and socio-centric tendencies. They use the intellectual tools that critical thinking offers – concepts and principles that enable them to analyse, assess, and improve thinking. They work diligently to develop the intellectual virtues of intellectual integrity, intellectual humility, intellectual civility, intellectual empathy, intellectual sense of justice and confidence in reason.

[Critical thinkers] realise that no matter how skilled they are as thinkers, they can always improve their reasoning abilities and they will at times fall prey to mistakes in reasoning, human irrationality, prejudices, biases, distortions, uncritically accepted social rules and taboos, self-interest, and vested interest. They strive to improve the world in whatever ways they can and contribute to a more rational, civilized society. At the same time, they recognize the complexities often inherent in doing so. They avoid thinking simplistically about complicated issues and strive to appropriately consider the rights and needs of relevant others. They recognize the complexities in developing as thinkers, and commit themselves to life-long practice toward self-improvement. They embody the Socratic principle: The unexamined life is not worth living, because they realize that many unexamined lives together result in an uncritical, unjust, dangerous world.”

Why Should Teachers & Educators Care About Critical Thinking?

In one word: misinformation. Students are exposed to increasing levels of “fake news” and misinformation as the systems and processes that ensured some degree of information integrity prior to the age of social-media struggle to keep up.

Since most teachers aspire to create lifelong learners with high-levels of metacognition, self-regulation, research skill and learner autonomy, cultivating these skills without accompanying critical thinking skills is dangerous; it is akin to letting a child free in a sweet-shop, able to consume endlessly but without the filter to determine what is worth consuming and what is not.

Aside from preventing obstacles to lofty philosophical ideals about “the pursuit of truth” misinformation is often harmful; as in the case of ‘alternative medicines’, paranormal frauds, conspiracy theories [that prevent vaccination or contribute towards the spread of diseases in a pandemic], manipulative advertising or, simply, fraud.

When an individual, even a well-meaning “truth-seeker”, internalises delusions and misinformation: it is usually occurring within a process that serves another party’s interests at the expense of their own. Misinformation and “fake news” can cost the lives of those who fall for it as well as contribute towards anti-social behaviours that cost the lives of others [e.g. conspiracy theorists who fail to social-distance in a pandemic].

An absence of critical thinking also leaves students vulnerable to political propagandists (both formal and informal ones), extreme political ideologies, and manipulative and hateful political narratives that can result in real world harms (e.g. in cases of racism or other hate crimes).

The rise of social-media and the onset of ‘the information age’ mean that critical thinking skills are, and will continue to be, more and more important.

As we shall see: critical thinking and metacognition are closely related and share a high degree of interdependence (with some authors defining critical thinking as a form of metacognition): so teachers interested in cultivating metacognition and self-regulated learning behaviours must, also, pay attention to critical-thinking skills.

What’s The Link Between Critical-Thinking & Metacognition?

Link 1: Critical Thinking Can Be a Form of Metacognition

Whilst critical-thinking may occur with reference to the claims made by others: being a critical-thinker demands self-examination and an evaluation of our own thoughts and beliefs. The careful examination of our own cognitive and emotional biases, the corruptive role of self-interest, and our own tacit acceptance of unchallenged social-norms and taboos is an essential part of the critical-thinking process.

Since this requires the examination, analysis and evaluation of one’s own thinking critical-thinking is, when self-referential, clearly a form of metacognition (“knowledge and awareness of thought processes”).

Dywer (2004) states: “Critical thinking is a metacognitive process that, through purposeful, reflective judgement, increases the chances of producing a logical conclusion to an argument or solution to a problem.”

Link 2: The Metacognitive Cycle Can Be Applied to Critical-Thinking Processes

The self-regulation cycle (and therefore, the metacognitive cycle) are often conceptualised in a four stage process of: planning, monitoring, evaluating and regulating - this cycle is useful and relevant to the critical-thinking process.

Let’s take a simple example: a student has strange rash on their skin and wants to find out what it is and how they might treat it. The metacognitive cycle helps then to find accurate information as opposed to falling for misinformation and potentially wasting time/money on an ineffective treatment that is deliberately miss-sold to them:

Planning The Learning Process:

What is it I am actually trying to learn here?

What search terms will produce good results?

How might my current state of mind interfere with my learning?

What are reliable sources of information that I can learn from?

Monitoring The Learning Process:

Am I actually learning anything?

Does this information seem trustworthy and reliable?

How are my feelings impacting my thoughts?

Evaluating The Learning Process:

What evidence supports the knowledge I’ve gained through my research?

What are the strengths and weaknesses of my approach to learning?

Why might some of the sources I’ve used not be trustworthy or reliable?

How confident am I in my learning?

What concepts did I find most difficult to understand?

Regulating The Learning Process:

What could I do differently in order to improve the quality of my learning?

How can I deepen my understanding of this topic?

Aside from internet research, what other sources might my research refer to?

How can I improve my state of mind to find greater clarity on this matter?

These questions illustrate the overlap between metacognitive questioning skills and critical-thinking questioning skills and some of the similarities between the two pursuits.

Link 3: Metacognition & Critical-Thinking Share the Same Basic Goals

Metacognition and critical-thinking are, fundamentally, approaches towards the acquisition of knowledge. Both concepts are concerned with accurate learning and require the exploration of basic epistemological issues around the process through which reliable and genuine knowledge can be obtained.

Link 4: Successful Metacognition & Successful Critical-Thinking Require Awareness of Cognitive Biases

Cognitive biases are a shared concern both for those wishing to learn more effectively and those who wish to think more critically. As a teacher hoping to enhance metacognition and develop critical-thinking skills: exploration of cognitive bias is essential.

As per the aforementioned definition from Elder (2007) critical-thinkers “are keenly aware of the inherently flawed nature of human thinking when left unchecked”: the awareness of our own limitations, weaknesses (as well as strengths) as learners, and our own attitudinal and emotional biases is an essential aspect of metacognitive awareness and a prerequisite for metacognitive regulation.

Whilst the detection of logical fallacies is a vital aspect of critical thinking and an important aspect of metacognition; perhaps the detection of cognitive biases is of more significance in the process of metacognition. ‘Overconfidence bias’, for example, refers to “someone’s false sense of their skill, talent, or self-belief” and has an obvious connection to the Dunning-Kruger Effect: it prevents people from identifying their mistakes and working out how to improve (an important aspect of metacognition and self-regulated learning) because students who have this bias tend to assume their work is already the best that it can be.

Another example might be the ‘Moral Credential Effect’, this cognitive bias occurs when someone who does something good and, as a result, gives themselves permission to be less good in the future. Clearly this cognitive bias can have an impact on a students’ attitude to learning or behaviour in class. The bias is both an obstacle to clear thinking but also an obstacle to learning that students can be made of during the metacognitive process.

Other cognitive biases include:

· Illusory Correlation - Inaccurately perceiving a relationship between two unrelated events

· Interoceptive bias - The tendency for sensory input about the body itself to affect one's judgement about external, unrelated circumstances.

· Framing Effect - Drawing different conclusions from the same information, depending on how that information is presented

· Confirmation Bias - The tendency to search for, interpret, focus on and remember information in a way that confirms one's preconceptions

Hopefully it is clear that these biases are something of relevance both in developing students’ critical-thinking skills as well as in developing their metacognitive abilities and self-regulated learning behaviours. For a more comprehensive list of cognitive biases please see this Wikipedia article – you may wish to take some time to realise the connections other cognitive biases have with metacognition and self-regulated learning development (and learning more generally!).

Going Deeper Into Research & Theory

Flavell (1979), often cited as the father of metacognition, sees critical thinking as forming part of the construct of metacognition when he argues that “critical appraisal of message source, quality of appeal, and probable consequences needed to cope with these inputs sensibly” can lead to “wise and thoughtful life decisions” (p. 910).

Kuhn (1999) sees critical thinking as being a form of metacognition, which includes metacognitive knowing (thinking that operates on declarative knowledge), meta-strategic knowing (thinking that operates on procedural knowledge), and epistemological knowing (encompassing how knowledge is produced).

Likewise, Wyre (2007) [ full article here ], researching the impact of metacognitive enrichment exercises on critical thinking skills in college aged students found that “a focus on metacognitive enrichment can significantly increase a student’s personal epistemology and, thereby, the student’s critical thinking skills.”; Wyre (2007) contends that when one facilitates a student’s thinking about his or her thinking process, that student will demonstrate improved skills associated with more mature epistemologies. Similar research was undertaken, reproducing these findings, by Magno (2010).

Lai (2011) [ full article here ] writes: “Metacognition (or thinking about thinking) supports critical thinking in that students who can monitor and evaluate their own thought processes are more likely to demonstrate high-quality thinking. In addition, the ability to critically evaluate one’s own arguments and reasoning is necessary for self-regulated learning.”

Dywer's (2014) 'integrated critical thinking framework for the 21st century', which views critical thinking as a fundamentally metacognitive process, identifies memory and comprehension as foundational processes necessary for the application of critical thinking: his framework integrates reflective judgement and self-regulatory functions of metacognition with past conceptualisations of critical thinking.

Halonen (1995) identifies metacognition as the ability to monitor the quality of critical thinking. Similarly, Halpern (1998) casts metacognition as monitoring thinking and strategy use by asking the following kinds of questions: What do I already know? What is my goal? How will I know when I get there? Am I making progress? (Lai, 2011)

Lai (2011) concludes: “Critical thinking skills relate to several other important student learning outcomes, such as metacognition, motivation, collaboration, and creativity. Metacognition (or thinking about thinking) supports critical thinking in that students who can monitor and evaluate their own thought processes are more likely to demonstrate high-quality thinking. In addition, the ability to critically evaluate one’s own arguments and reasoning is necessary for self-regulated learning.” (p.42)

Dwyer, Hogan, Stewart, An integrated critical thinking framework for the 21st century, Thin

Elder and Paul (2007). The Thinker's Guide to Analytic Thinking. Foundation Critical Thinking. ISBN 978-0944583197.

Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10), 906–911.king Skills and Creativity, Volume 12, 2014, Pages 43-52, ISSN 1871-1871

Halonen, J. S. (1995). Demystifying critical thinking. Teaching of Psychology, 22(1), 75–81.

Kuhn, D., & Dean, D. (2004). A bridge between cognitive psychology and educational practice. Theory into Practice, 43(4), 268–273.

Kuhn, D., & Pearsall, S. (1998). Relations between meta-strategic knowledge and strategic performance. Cognitive Development, 13, 227–247.

Lai, E., Michael Bay-Borelli, R. Kirkpatrick, Anli Lin and Changjiang Wang. “Critical Thinking: A Literature Review Research Report.” (2011).

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

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What Is Metacognition? How Does It Help Us Think?

Metacognitive strategies like self-reflection empower students for a lifetime..

Posted October 9, 2020 | Reviewed by Abigail Fagan

Metacognition is a high order thinking skill that is emerging from the shadows of academia to take its rightful place in classrooms around the world. As online classrooms extend into homes, this is an important time for parents and teachers to understand metacognition and how metacognitive strategies affect learning. These skills enable children to become better thinkers and decision-makers.

Metacognition: The Neglected Skill Set for Empowering Students is a new research-based book by educational consultants Dr. Robin Fogarty and Brian Pete that not only gets to the heart of why metacognition is important but gives teachers and parents insightful strategies for teaching metacognition to children from kindergarten through high school. This article summarizes several concepts from their book and shares three of their thirty strategies to strengthen metacognition.

What Is Metacognition?

Metacognition is the practice of being aware of one’s own thinking. Some scholars refer to it as “thinking about thinking.” Fogarty and Pete give a great everyday example of metacognition:

Think about the last time you reached the bottom of a page and thought to yourself, “I’m not sure what I just read.” Your brain just became aware of something you did not know, so instinctively you might reread the last sentence or rescan the paragraphs of the page. Maybe you will read the page again. In whatever ways you decide to capture the missing information, this momentary awareness of knowing what you know or do not know is called metacognition.

When we notice ourselves having an inner dialogue about our thinking and it prompts us to evaluate our learning or problem-solving processes, we are experiencing metacognition at work. This skill helps us think better, make sound decisions, and solve problems more effectively. In fact, research suggests that as a young person’s metacognitive abilities increase, they achieve at higher levels.

Fogarty and Pete outline three aspects of metacognition that are vital for children to learn: planning, monitoring, and evaluation. They convincingly argue that metacognition is best when it is infused in teaching strategies rather than taught directly. The key is to encourage students to explore and question their own metacognitive strategies in ways that become spontaneous and seemingly unconscious .

Metacognitive skills provide a basis for broader, psychological self-awareness , including how children gain a deeper understanding of themselves and the world around them.

Metacognitive Strategies to Use at Home or School

Fogarty and Pete successfully demystify metacognition and provide simple ways teachers and parents can strengthen children’s abilities to use these higher-order thinking skills. Below is a summary of metacognitive strategies from the three areas of planning, monitoring, and evaluation.

1. Planning Strategies

As students learn to plan, they learn to anticipate the strengths and weaknesses of their ideas. Planning strategies used to strengthen metacognition help students scrutinize plans at a time when they can most easily be changed.

One of ten metacognitive strategies outlined in the book is called “Inking Your Thinking.” It is a simple writing log that requires students to reflect on a lesson they are about to begin. Sample starters may include: “I predict…” “A question I have is…” or “A picture I have of this is…”

Writing logs are also helpful in the middle or end of assignments. For example, “The homework problem that puzzles me is…” “The way I will solve this problem is to…” or “I’m choosing this strategy because…”

2. Monitoring Strategies

Monitoring strategies used to strengthen metacognition help students check their progress and review their thinking at various stages. Different from scrutinizing, this strategy is reflective in nature. It also allows for adjustments while the plan, activity, or assignment is in motion. Monitoring strategies encourage recovery of learning, as in the example cited above when we are reading a book and notice that we forgot what we just read. We can recover our memory by scanning or re-reading.

One of many metacognitive strategies shared by Fogarty and Pete, called the “Alarm Clock,” is used to recover or rethink an idea once the student realizes something is amiss. The idea is to develop internal signals that sound an alarm. This signal prompts the student to recover a thought, rework a math problem, or capture an idea in a chart or picture. Metacognitive reflection involves thinking about “What I did,” then reviewing the pluses and minuses of one’s action. Finally, it means asking, “What other thoughts do I have” moving forward?

Teachers can easily build monitoring strategies into student assignments. Parents can reinforce these strategies too. Remember, the idea is not to tell children what they did correctly or incorrectly. Rather, help children monitor and think about their own learning. These are formative skills that last a lifetime.

3. Evaluation Strategies

According to Fogarty and Pete, the evaluation strategies of metacognition “are much like the mirror in a powder compact. Both serve to magnify the image, allow for careful scrutiny, and provide an up-close and personal view. When one opens the compact and looks in the mirror, only a small portion of the face is reflected back, but that particular part is magnified so that every nuance, every flaw, and every bump is blatantly in view.” Having this enlarged view makes inspection much easier.

When students inspect parts of their work, they learn about the nuances of their thinking processes. They learn to refine their work. They grow in their ability to apply their learning to new situations. “Connecting Elephants” is one of many metacognitive strategies to help students self-evaluate and apply their learning.

In this exercise, the metaphor of three imaginary elephants is used. The elephants are walking together in a circle, connected by the trunk and tail of another elephant. The three elephants represent three vital questions: 1) What is the big idea? 2) How does this connect to other big ideas? 3) How can I use this big idea? Using the image of a “big idea” helps students magnify and synthesize their learning. It encourages them to think about big ways their learning can be applied to new situations.

Metacognition and Self-Reflection

Reflective thinking is at the heart of metacognition. In today’s world of constant chatter, technology and reflective thinking can be at odds. In fact, mobile devices can prevent young people from seeing what is right before their eyes.

John Dewey, a renowned psychologist and education reformer, claimed that experiences alone were not enough. What is critical is an ability to perceive and then weave meaning from the threads of our experiences.

The function of metacognition and self-reflection is to make meaning. The creation of meaning is at the heart of what it means to be human.

Everyone can help foster self-reflection in young people.

Marilyn Price-Mitchell, Ph.D., is an Institute for Social Innovation Fellow at Fielding Graduate University and author of Tomorrow’s Change Makers.

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Metacognition & Critical Thinking: Differences and Similarities

Two terms we usually confuse with each other are Critical Thinking and Metacognition. Even though they both describe the skill of being aware of thinking processes and their possible outcomes, metacognition is a bit more complicated. To fully understand both terms properly, we need to examine their similarities and differences.

Critical Thinking

Critical thinking mostly means putting into practice theoretical frameworks and concepts. This skill is quite necessary because of its ability to allow us to face real-life issues better. When we learn how to critically think and process information, we immediately become smarter consumers, civilians, and people. We are also able to comprehend hidden meanings and to criticize better and more constructively.

Also, when our critical thinking skills are used we can engage in conflict with well-reasoned arguments (in favor; against a party involved).

Overall, critical thinking works as a way of perceiving reality, while it provides us with more ways of dealing with daily life issues.

Critical thinking skills though, need to be practiced, learned, and constantly improved. As critical thinking is not a set of skills that we acquire when we are born, we need to learn it, and how to practice it. This is often achieved through school-college and real-life events that challenge us and require some special treatment that urges us to think differently, and from another perspective.

Also, as our life changes, we need to be “equipped with” the appropriate critical thinking skills that will help us face any kind of situation. This usually occurs by having many challenging experiences, that offer us many new characteristics.

Taking into consideration the fact that a lot of us learn how to “critically think” at school, the educational field should be able to promote such skills and make sure that critical thinking is taught during every class/lesson.

Unfortunately, this is not what occurs. Conventional teaching and learning methods are still used, and they do not support critical thinking at all. In fact, they promote “rigid” learning and most of the time, too theoretical that can’t be applied in real-life situations. That results in students not being able to remember what they have learned, let alone apply all that information in various situations.

When defining this term, we need to take into account four traits.

• Foundation skills:  This category of skills consists of basic skills that also fall under the umbrella of critical thinking skills. For example, proper speculations about an issue, constructing an argument with facts, and doubting the credibility of a piece of information, are all independent skills that, in this case, constitute a foundation base for critical thinking .
• Knowledge base : This includes the context that allows us to apply our skills. For example, academic knowledge is a good part of this category as real-life events that require critical thinking from the participants, are.
• Willingness to question : This category describes the personal attitude of a person towards critical thinking, and towards practices that demand critical thinking. For example, some people avoid events that require critical thinking because they perceive it as difficult or too challenging.
• Self-reflection : This category means Metacognition, which we are going to examine below.

Metacognition

Metacognition, or the “Self-reflection” dimension of Critical Thinking, is a more theoretical and personal concept. It describes our perspective and reflection on our thinking processes. That is why it is also called “Self-reflection”. Because, with Metacognition we can evaluate the efficacy of our thinking procedures before, during, and after an issue.

Basically, Metacognition is the level after critical thinking. It allows us to examine our critical thinking abilities a bit more clearly, and to reflect on their usefulness. It is a slower procedure, and it requires good observation skills, regarding our critical thinking attitude.

In addition, we can control Metacognition, since it is our reflection. Metacognition is a rather new concept and somewhat difficult to examine since it heavily relies on personal thoughts and reflections that are not caused by external factors ( educational field).

Differences

When it comes to the differences these concepts have, there are 4 points to consider:

• When using critical thinking, we usually know our goal and expected result ( resolving an issue, reaching a conclusion). However, when we use Metacognition, we are aware of the efficiency of our thinking processes and methods, rather than the outcome of our critical thinking.
• In general, Critical thinking is more supported, in comparison with Metacognition. For example, educational institutions recognize Creative thinking as a useful tool, when Metacognition is not discussed ( very rarely).
• Overall, Critical Thinking is more directly applicable to real-life situations than Metacognition. Thus, critical thinking is much easier and less complicated.
• Metacognition is more personal than critical thinking. Critical thinking- as mentioned above- is also highly affected by interaction with other people and with external factors. Metacognition is purely personal, as it is a reflection.

Similarities: Metacognition and critical-thinking

Regarding the similarities between these two concepts, three points need to be considered:

• Critical thinking and metacognition need a lot of practice. They both include skills that work better when practiced frequently. However, critical thinking comes first, as Metacognition is a reflection of it (hence, it makes sense for Metacognition to come second).
• Both Critical thinking and metacognition are very much needed. They might have different goals, but they complete each other as concepts.
• Also, they both “require awareness of the relevant procedures”. That means that during both procedures, we learn more when we are conscious of the skills and tools we are using.

On An Ending Note

To sum up, the concept of Critical Thinking and the concept of Metacognition share some elements, but they are also very different from each other. Even though they both are necessary, Critical thinking (as the first level) needs to be more promoted and supported, when Metacognition (the second level) needs to be a concept that people raise awareness of, especially in the educational and academic domain.

Two forms of ‘thinking about thinking’: metacognition and critical thinking

https://www.encyclopedia.com/education/applied-and-social-sciences-magazines/critical-thinking-metacognition-and-problem-based-learningC

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Metacognition.

Thinking about One’s Thinking |   Putting Metacognition into Practice

Thinking about One’s Thinking

Initially studied for its development in young children (Baker & Brown, 1984; Flavell, 1985), researchers soon began to look at how experts display metacognitive thinking and how, then, these thought processes can be taught to novices to improve their learning (Hatano & Inagaki, 1986).  In How People Learn , the National Academy of Sciences’ synthesis of decades of research on the science of learning, one of the three key findings of this work is the effectiveness of a “‘metacognitive’ approach to instruction” (Bransford, Brown, & Cocking, 2000, p. 18).

Metacognitive practices increase students’ abilities to transfer or adapt their learning to new contexts and tasks (Bransford, Brown, & Cocking, p. 12; Palincsar & Brown, 1984; Scardamalia et al., 1984; Schoenfeld, 1983, 1985, 1991).  They do this by gaining a level of awareness above the subject matter : they also think about the tasks and contexts of different learning situations and themselves as learners in these different contexts.  When Pintrich (2002) asserts that “Students who know about the different kinds of strategies for learning, thinking, and problem solving will be more likely to use them” (p. 222), notice the students must “know about” these strategies, not just practice them.  As Zohar and David (2009) explain, there must be a “ conscious meta-strategic level of H[igher] O[rder] T[hinking]” (p. 179).

Metacognitive practices help students become aware of their strengths and weaknesses as learners, writers, readers, test-takers, group members, etc.  A key element is recognizing the limit of one’s knowledge or ability and then figuring out how to expand that knowledge or extend the ability. Those who know their strengths and weaknesses in these areas will be more likely to “actively monitor their learning strategies and resources and assess their readiness for particular tasks and performances” (Bransford, Brown, & Cocking, p. 67).

The absence of metacognition connects to the research by Dunning, Johnson, Ehrlinger, and Kruger on “Why People Fail to Recognize Their Own Incompetence” (2003).  They found that “people tend to be blissfully unaware of their incompetence,” lacking “insight about deficiencies in their intellectual and social skills.”  They identified this pattern across domains—from test-taking, writing grammatically, thinking logically, to recognizing humor, to hunters’ knowledge about firearms and medical lab technicians’ knowledge of medical terminology and problem-solving skills (p. 83-84).  In short, “if people lack the skills to produce correct answers, they are also cursed with an inability to know when their answers, or anyone else’s, are right or wrong” (p. 85).  This research suggests that increased metacognitive abilities—to learn specific (and correct) skills, how to recognize them, and how to practice them—is needed in many contexts.

Putting Metacognition into Practice

In “ Promoting Student Metacognition ,” Tanner (2012) offers a handful of specific activities for biology classes, but they can be adapted to any discipline. She first describes four assignments for explicit instruction (p. 116):

• Preassessments—Encouraging Students to Examine Their Current Thinking: “What do I already know about this topic that could guide my learning?”

• Retrospective Postassessments—Pushing Students to Recognize Conceptual Change: “Before this course, I thought evolution was… Now I think that evolution is ….” or “How is my thinking changing (or not changing) over time?”
• Reflective Journals—Providing a Forum in Which Students Monitor Their Own Thinking: “What about my exam preparation worked well that I should remember to do next time? What did not work so well that I should not do next time or that I should change?”

Next are recommendations for developing a “classroom culture grounded in metacognition” (p. 116-118):

• Giving Students License to Identify Confusions within the Classroom Culture:  ask students what they find confusing, acknowledge the difficulties
• Integrating Reflection into Credited Course Work: integrate short reflection (oral or written) that ask students what they found challenging or what questions arose during an assignment/exam/project
• Metacognitive Modeling by the Instructor for Students: model the thinking processes involved in your field and sought in your course by being explicit about “how you start, how you decide what to do first and then next, how you check your work, how you know when you are done” (p. 118)

To facilitate these activities, she also offers three useful tables:

• Questions for students to ask themselves as they plan, monitor, and evaluate their thinking within four learning contexts—in class, assignments, quizzes/exams, and the course as a whole (p. 115)
• Prompts for integrating metacognition into discussions of pairs during clicker activities, assignments, and quiz or exam preparation (p. 117)
• Questions to help faculty metacognitively assess their own teaching (p. 119)

Weimer’s “ Deep Learning vs. Surface Learning: Getting Students to Understand the Difference ” (2012) offers additional recommendations for developing students’ metacognitive awareness and improvement of their study skills:

“[I]t is terribly important that in explicit and concerted ways we make students aware of themselves as learners. We must regularly ask, not only ‘What are you learning?’ but ‘How are you learning?’ We must confront them with the effectiveness (more often ineffectiveness) of their approaches. We must offer alternatives and then challenge students to test the efficacy of those approaches. ” (emphasis added)

She points to a tool developed by Stanger-Hall (2012, p. 297) for her students to identify their study strategies, which she divided into “ cognitively passive ” (“I previewed the reading before class,” “I came to class,” “I read the assigned text,” “I highlighted the text,” et al) and “ cognitively active study behaviors ” (“I asked myself: ‘How does it work?’ and ‘Why does it work this way?’” “I wrote my own study questions,” “I fit all the facts into a bigger picture,” “I closed my notes and tested how much I remembered,” et al) .  The specific focus of Stanger-Hall’s study is tangential to this discussion, 1 but imagine giving students lists like hers adapted to your course and then, after a major assignment, having students discuss which ones worked and which types of behaviors led to higher grades. Even further, follow Lovett’s advice (2013) by assigning “exam wrappers,” which include students reflecting on their previous exam-preparation strategies, assessing those strategies and then looking ahead to the next exam, and writing an action plan for a revised approach to studying. A common assignment in English composition courses is the self-assessment essay in which students apply course criteria to articulate their strengths and weaknesses within single papers or over the course of the semester. These activities can be adapted to assignments other than exams or essays, such as projects, speeches, discussions, and the like.

As these examples illustrate, for students to become more metacognitive, they must be taught the concept and its language explicitly (Pintrich, 2002; Tanner, 2012), though not in a content-delivery model (simply a reading or a lecture) and not in one lesson. Instead, the explicit instruction should be “designed according to a knowledge construction approach,” or students need to recognize, assess, and connect new skills to old ones, “and it needs to take place over an extended period of time” (Zohar & David, p. 187).  This kind of explicit instruction will help students expand or replace existing learning strategies with new and more effective ones, give students a way to talk about learning and thinking, compare strategies with their classmates’ and make more informed choices, and render learning “less opaque to students, rather than being something that happens mysteriously or that some students ‘get’ and learn and others struggle and don’t learn” (Pintrich, 2002, p. 223).

• What to Expect (when reading philosophy)
• The Ultimate Goal (of reading philosophy)
• Basic Good Reading Behaviors
• Important Background Information, or discipline- and course-specific reading practices, such as “reading for enlightenment” rather than information, and “problem-based classes” rather than historical or figure-based classes
• A Three-Part Reading Process (pre-reading, understanding, and evaluating)
• Flagging, or annotating the reading
• Linear vs. Dialogical Writing (Philosophical writing is rarely straightforward but instead “a monologue that contains a dialogue” [p. 365].)

What would such a handout look like for your discipline?

Students can even be metacognitively prepared (and then prepare themselves) for the overarching learning experiences expected in specific contexts . Salvatori and Donahue’s The Elements (and Pleasures) of Difficulty (2004) encourages students to embrace difficult texts (and tasks) as part of deep learning, rather than an obstacle.  Their “difficulty paper” assignment helps students reflect on and articulate the nature of the difficulty and work through their responses to it (p. 9).  Similarly, in courses with sensitive subject matter, a different kind of learning occurs, one that involves complex emotional responses.  In “ Learning from Their Own Learning: How Metacognitive and Meta-affective Reflections Enhance Learning in Race-Related Courses ” (Chick, Karis, & Kernahan, 2009), students were informed about the common reactions to learning about racial inequality (Helms, 1995; Adams, Bell, & Griffin, 1997; see student handout, Chick, Karis, & Kernahan, p. 23-24) and then regularly wrote about their cognitive and affective responses to specific racialized situations.  The students with the most developed metacognitive and meta-affective practices at the end of the semester were able to “clear the obstacles and move away from” oversimplified thinking about race and racism ”to places of greater questioning, acknowledging the complexities of identity, and redefining the world in racial terms” (p. 14).

Ultimately, metacognition requires students to “externalize mental events” (Bransford, Brown, & Cocking, p. 67), such as what it means to learn, awareness of one’s strengths and weaknesses with specific skills or in a given learning context, plan what’s required to accomplish a specific learning goal or activity, identifying and correcting errors, and preparing ahead for learning processes.

————————

1 Students who were tested with short answer in addition to multiple-choice questions on their exams reported more cognitively active behaviors than those tested with just multiple-choice questions, and these active behaviors led to improved performance on the final exam.

• Adams, Maurianne, Bell, Lee Ann, and Griffin, Pat. (1997). Teaching for diversity and social justice: A sourcebook . New York: Routledge.
• Bransford, John D., Brown Ann L., and Cocking Rodney R. (2000). How people learn: Brain, mind, experience, and school . Washington, D.C.: National Academy Press.
• Baker, Linda, and Brown, Ann L. (1984). Metacognitive skills and reading.  In Paul David Pearson, Michael L. Kamil, Rebecca Barr, & Peter Mosenthal (Eds.), Handbook of research in reading: Volume III (pp. 353–395).  New York: Longman.
• Brown, Ann L. (1980). Metacognitive development and reading. In Rand J. Spiro, Bertram C. Bruce, and William F. Brewer, (Eds.), Theoretical issues in reading comprehension: Perspectives from cognitive psychology, linguistics, artificial intelligence, and education (pp. 453-482). Hillsdale, NJ: Erlbaum.
• Chick, Nancy, Karis, Terri, and Kernahan, Cyndi. (2009). Learning from their own learning: how metacognitive and meta-affective reflections enhance learning in race-related courses . International Journal for the Scholarship of Teaching and Learning, 3(1). 1-28.
• Commander, Nannette Evans, and Valeri-Gold, Marie. (2001). The learning portfolio: A valuable tool for increasing metacognitive awareness . The Learning Assistance Review, 6 (2), 5-18.
• Concepción, David. (2004). Reading philosophy with background knowledge and metacognition . Teaching Philosophy , 27 (4). 351-368.
• Dunning, David, Johnson, Kerri, Ehrlinger, Joyce, and Kruger, Justin. (2003) Why people fail to recognize their own incompetence . Current Directions in Psychological Science, 12 (3). 83-87.
• Flavell,  John H. (1985). Cognitive development. Englewood Cliffs, NJ: Prentice Hall.
• Hatano, Giyoo and Inagaki, Kayoko. (1986). Two courses of expertise. In Harold Stevenson, Azuma, Horishi, and Hakuta, Kinji (Eds.), Child development and education in Japan, New York: W.H. Freeman.
• Helms, Janet E. (1995). An update of Helms’ white and people of color racial identity models . In J.G. Ponterotto, Joseph G., Casas, Manuel, Suzuki, Lisa A., and Alexander, Charlene M. (Eds.), Handbook of multicultural counseling (pp. 181-198) . Thousand Oaks, CA: Sage.
• Lovett, Marsha C. (2013). Make exams worth more than the grade. In Matthew Kaplan, Naomi Silver, Danielle LaVague-Manty, and Deborah Meizlish (Eds.), Using reflection and metacognition to improve student learning: Across the disciplines, across the academy . Sterling, VA: Stylus.
• Palincsar, Annemarie Sullivan, and Brown, Ann L. (1984). Reciprocal teaching of comprehension-fostering and comprehension-monitoring activities . Cognition and Instruction, 1 (2). 117-175.
• Pintrich, Paul R. (2002). The Role of metacognitive knowledge in learning, teaching, and assessing . Theory into Practice, 41 (4). 219-225.
• Salvatori, Mariolina Rizzi, and Donahue, Patricia. (2004). The Elements (and pleasures) of difficulty . New York: Pearson-Longman.
• Scardamalia, Marlene, Bereiter, Carl, and Steinbach, Rosanne. (1984). Teachability of reflective processes in written composition . Cognitive Science , 8, 173-190.
• Schoenfeld, Alan H. (1991). On mathematics as sense making: An informal attack on the fortunate divorce of formal and informal mathematics. In James F. Voss, David N. Perkins, and Judith W. Segal (Eds.), Informal reasoning and education (pp. 311-344). Hillsdale, NJ: Erlbaum.
• Stanger-Hall, Kathrin F. (2012). Multiple-choice exams: An obstacle for higher-level thinking in introductory science classes . Cell Biology Education—Life Sciences Education, 11(3), 294-306.
• Tanner, Kimberly D.  (2012). Promoting student metacognition . CBE—Life Sciences Education, 11, 113-120.
• Weimer, Maryellen.  (2012, November 19). Deep learning vs. surface learning: Getting students to understand the difference . Retrieved from the Teaching Professor Blog from http://www.facultyfocus.com/articles/teaching-professor-blog/deep-learning-vs-surface-learning-getting-students-to-understand-the-difference/ .
• Zohar, Anat, and David, Adi Ben. (2009). Paving a clear path in a thick forest: a conceptual analysis of a metacognitive component . Metacognition Learning , 4 , 177-195.

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Metacognitive thinking skills are important for instructors and students alike. This resource provides instructors with an overview of the what and why of metacognition and general “getting started” strategies for teaching for and with metacognition.

In this page:

What is metacognition?

Why use metacognition, getting started: how to teach both for and with metacognition, metacognition at columbia.

Cite this resource: Columbia Center for Teaching and Learning (2018). Metacognition Resource. Columbia University. Retrieved [today’s date] from https://ctl.columbia.edu/resources-and-technology/resources/metacognition/

• assess the task.
• plan for and use appropriate strategies and resources.
• monitor task performance.
• evaluate processes and products of their learning and revise their goals and strategies accordingly.

The Center for Teaching and Learning encourages instructors to teach metacognitively. This means to teach “ with and for metacognition.” To teach with metacognition involves instructors “thinking about their own thinking regarding their teaching” (Hartman, 2001: 149). To teach for metacognition involves instructors thinking about how their instruction helps to elucidate learning and problem solving strategies to their students (Hartman, 2001).

Learners with metacognitive skills are:

• More self-aware as critical thinkers and problem solvers, enabling them to actively approach knowledge gaps and problems and to rely on themselves.
• Able to monitor, plan, and control their mental processes.
• Better able to assess the depth of their knowledge.
• Able to transfer/apply their knowledge and skills to new situations.
• Able to choose more effective learning strategies.
• More likely to perform better academically.

Instructors who teach metacognitively / think about their teaching are:

• More self-aware of their instructional capacities, and know what teaching strategies they rely upon, when and why these use these strategies, and how to use them effectively and inclusively.
• Better able to regulate their instruction before, during, and after conducting a class session (i.e., to plan what and how to teach, monitor how lessons are going and make adjustments, and evaluate how a lesson went afterwards).
• Better able to communicate, helping students understand the what, why, and how of their learning, which can lead to better learning outcomes.
• Able to use their knowledge of students’ metacognitive skills to plan instruction designed to improve students’ metacognition and to create inclusive course climates.

Teaching for metacognition — Metacognitive strategies that serve students and their learning:

Design homework assignments that ask students to focus on their learning process. This includes having students monitor progress, identify and correct mistakes, and plan next steps.

Provide structures to guide students in creating implementable action plans for improvement.

Show students how to move stepwise from reflection to action. Use appropriate technology to support student self-regulation. Many platforms such as CourseWorks provide tools that students can use to keep up with their course work and monitor their progress.

Teaching with metacognition — Metacognitive strategies that serve the course and the instructor’s teaching practice:

Create an evaluation plan to periodically evaluate one’s teaching and course design, set-up, and content.

Structure the course to provide time for students to give feedback on the course and teaching. Evaluate course progress and successes of teaching Use course and instructional objectives to measure progress.

Schedule mid-course feedback surveys with students.

Request a mid-course review (offered as a service for graduate students).

Review end-of-course evaluations and reflect on the changes that will be made to maximize student learning. Build in time for metacognitive work Set aside time before, during, and after a course to reflect on one’s teaching practice, relationship with students, course climate and dynamics, as well as assumptions about the course material and its accessibility to students.

Metacognition and Memory Lab  |  Dr. Janet Metcalfe (Professor of Psychology and of Neurobiology and Behavior) runs a lab that focuses on how people use their metacognition to improve self-awareness and to guide their own learning and behavior. Dr. Metcalfe is author of Metacognition: A Textbook for Cognitive, Educational, Life Span & Applied Psychology (2009), co-authored with John Dunlosky.

In Fall 2018, the CTL and the Science of LEarning Research (SOLER) initiative co-organized the inaugural Science of Learning Symposium “Metacognition: From Research to Classroom” which brought together Columbia faculty, staff, graduate students, and experts in the science of learning to share the research on metacognition in learning, and to translate it into strategies that maximize student learning. View video recording of the event here .

Ambrose, S. A., Lovett, M., Bridges, M. W., DiPietro, M., & Norman, M. K. (2010). How Learning Works: Seven Research-Based Principles for Smart Teaching . San Francisco: John Wiley & Sons.

Dunlosky, J. and Metcalfe, J. (2009). Metacognition. Thousand Oaks, CA: Sage.

Flavell, J.H. (1976). Metacognitive Aspects of Problem Solving. In L.B. Resnick (Ed.), The Nature of Intelligence (pp. 231-236). Hillsdale, NJ: Erlbaum.

Hacker, D.J. (1998). Chapter 1. Definitions and Empirical Foundations. In Hacker, D.J.; Dunlosky, J.; and Graesser, A.C. (1998). Metacognition in Educational Theory and Practice. Mahwah, N.J.: Routledge.

Hartman, H.J. (2001). Chapter 8: Teaching Metacognitively. In Metacognition in Learning and Instruction. Kluwer Academic Publishers, 149 – 172.

Lai, E.R. (2011). Metacognition: A Literature Review. Pearson’s Research Reports. Retrieved from https://images.pearsonassessments.com/images/tmrs/Metacognition_Literature_Review_Final.pdf

McGuire, S.Y. (2015). Teach Students How to Learn: Strategies You Can Incorporate Into Any Course to Improve Student Metacognition, Study Skills, and Motivation. Sterling, VA: Stylus.

National Research Council (2000). How People Learn: Brain, Mind, Experience, and School . Expanded Edition . Washington, DC: The National Academies Press. https://doi.org/10.17226/9853

Nilson, L. (2013). Creating Self-Regulated Learners: Strategies to Strengthen Students’ Self-Awareness and Learning Skills. Sterling, VA: Stylus.

Schraw, G. and Dennison, R.S. (1994). Assessing Metacognitive Awareness. Contemporary Educational Psychology. 19(4): 460-475.

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Critical-Thinking Basics: Metacognition and Skill Building

Critical thinking is one of the imperatives of education, and research shows that openly practicing basic thought routines can make huge differences for learners. Some of these thinking skills are so commonplace, so ingrained in our daily mental processes, that we may not even realize we’re already doing them. Building thinking skills can bring great dividends and lay the foundation for life-long learning.

So how can teachers lay the foundation for critical and higher-order thinking? What are the building blocks of critical thinking?

The term metacognition was first introduced by developmental psychologist Dr. John Flavell in 1976, who recognized that metacognition consists of both self-monitoring and self-regulation of thought processes. In an educational context, metacognition refers to students’ self-understanding and knowledge about themselves as learners. In short, how they think about thinking. Take, for example, practices like using an internal monologue to solve a math problem or using a mnemonic device to help recall specific information. As part of the suite of executive function skills, metacognitive abilities like self-control and self-assessment are strong indicators of learning success and complex thought . Let’s take a deeper look at metacognition and see how it can be applied in the classroom.

Why Metacognition Matters for Learning

Teaching cognitive processes through direct instruction allows students to foster and develop these learning strategies so that they can call on them efficiently and effectively as they learn. Metacognition not only allows students to take more ownership in their learning process by prompting them to evaluate what they are learning and confront challenges, but it also can help students develop more self-awareness as they learn, where they can better understand their own strengths and weaknesses and develop learning strategies for easier problem-solving. Metacognition lets students own their learning by prompting them to evaluate what they are learning and confront challenges. As students develop self-awareness, they form learning strategies, problem-solving techniques, and study habits.

Practicing Metacognitive Techniques in the Classroom

One aspect of metacognition, distinguishing between what we know and what we don’t, can be built by taking quick, informal assessments like mini quizzes. Through timely, effective immediate feedback, students can differentiate their strengths and weaknesses.

The self-monitoring aspect of metacognition, knowing what you know, allows students to take more ownership over their learning journey through self-assessment. Strong learners know when they need more study, how long the study will take, and how much they can trust their recall in the future. They take corrective action like taking notes or looking up words they don’t know.

The self-regulation aspect of metacognition is often an internal list of instructions we give ourselves to work through tasks. At an advanced level, this inner monologue is a curated list of “if-then” conditions. With self-control, students can think through the consequences and implications of their actions by visualizing outcomes and setting up strategies to maneuver around potential obstacles.

It’s important to be transparent about the value of engaging with your own thinking and evaluating ideas when discussing metacognition with students so that they can better understand how such practices will benefit them. When educators verbalize their thinking process, the example leads students along a problem-solving journey. Remember that it’s important to demonstrate mistakes too. Show how to own your mistakes, then go back and fix them.

Ready to get started? Take a look at a few techniques you can try out in the classroom to help your students develop metacognition and other critical-thinking skills:

When shared in groups, metacognitive techniques are empowering. Creating a community of inquiry is fun too! Imagine that your classroom shares an interactive neural “brain” hanging from the ceiling. It’s a great introduction to brain science and active thinking! Diane Dahl, a teacher in McKinney, Texas, created a mind-map class activity for her elementary students using pipe cleaners, a hole punch, and notecards. Students built a physical model of their shared, connective knowledge like a mind map. Every time that students made a connection, like linking the Mississippi River to the Nile River when studying different units, they created a physical representation of the information.

Think-Pair-Share Another great way to practice cognitive skills is with “ think-pair-share ” activities. After a short period to write, study, or read a short passage, students explain their thought processes to a partner. Eventually, the pair presents its thoughts to the entire class for questions, discussion, and ways to build more ideas. Through discussing ideas openly, teachers can evaluate students’ thought processes and ask open-ended questions for future reflection. It's also a great chance to consider both sides. Taking different perspectives into consideration is important for critical thinking (and everyday life).

Think-Aloud A “ think-aloud ” activity is an easy metacognitive technique to demonstrate ways monitoring thinking. Use think-aloud activities to show the process of problem-solving or reading for summarization. By checking math, making notes, or rereading parts of a text, learners can become self-corrective and self-directed. Incidentally, think-aloud activities are also useful assessments of creative skills that improve comprehension. You can also try these metacognition steps with reading assignments:

• Activate thinking before concentrated learning activities like reading new passages. Research shows that by stimulating recall, learning pathways are stronger. Ask students: “What do we already know about this subject? What do we want to learn?”
• Assess the task. Ask students to look at subheadings and the form of the assignment. By paying attention to the length and structure of tasks, students can plan their reading or practice time.
• During reading, students should check their knowledge and understanding of terms. They can recap the action of the story or go through the steps of problem-solving to check their work.
• Use student learning journals to allow them to reflect on knowledge. The best learning journals go beyond simply recording behaviors. Encourage active goal setting, questioning, and self-assessment.
• Develop conditional, adaptive learning strategies with “if-then” statements. For example, a student could approach a reading assignment with this general strategy: “After I read the chapter, then I can summarize the plot and setting. If I finish that, then I’ll start fresh tomorrow and re-read it to check my knowledge.”

How to Create Motivated Learners

As students develop metacognitive control, they begin to plan and check their work. In later stages of development, they will be able to evaluate their progress and reflect on prior knowledge with skill. Motivated students will think through the consequences and implications of their actions by visualizing outcomes and setting up strategies to maneuver around potential obstacles. Metacognition is the ability to monitor thinking and strategy through self-examination. Ask students to practice active learning and measure themselves with these questions:

• What do I know?
• What do I want to know?
• How will I get there?
• How will I know when I meet my goal?
• Am I making progress?

Remember that building mental fortitude is a long process. It’s important to have patience. Cognitive skills don’t fully develop until the teenage years or after. It’s different for everyone, but it can be scaled quickly in learning communities like schools and classrooms.

Looking for more ways to incorporate critical thinking into your lessons? Learn more about how you can elevate your teaching and empower your students to become inquisitive, reflective thinkers.

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• Published: 08 June 2021

Metacognition: ideas and insights from neuro- and educational sciences

• Damien S. Fleur   ORCID: orcid.org/0000-0003-4836-5255 1 , 2 ,
• Bert Bredeweg   ORCID: orcid.org/0000-0002-5281-2786 1 , 3 &
• Wouter van den Bos 2 , 4  

npj Science of Learning volume  6 , Article number:  13 ( 2021 ) Cite this article

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Metacognition comprises both the ability to be aware of one’s cognitive processes (metacognitive knowledge) and to regulate them (metacognitive control). Research in educational sciences has amassed a large body of evidence on the importance of metacognition in learning and academic achievement. More recently, metacognition has been studied from experimental and cognitive neuroscience perspectives. This research has started to identify brain regions that encode metacognitive processes. However, the educational and neuroscience disciplines have largely developed separately with little exchange and communication. In this article, we review the literature on metacognition in educational and cognitive neuroscience and identify entry points for synthesis. We argue that to improve our understanding of metacognition, future research needs to (i) investigate the degree to which different protocols relate to the similar or different metacognitive constructs and processes, (ii) implement experiments to identify neural substrates necessary for metacognition based on protocols used in educational sciences, (iii) study the effects of training metacognitive knowledge in the brain, and (iv) perform developmental research in the metacognitive brain and compare it with the existing developmental literature from educational sciences regarding the domain-generality of metacognition.

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Introduction.

Metacognition is defined as “thinking about thinking” or the ability to monitor and control one’s cognitive processes 1 and plays an important role in learning and education 2 , 3 , 4 . For instance, high performers tend to present better metacognitive abilities (especially control) than low performers in diverse educational activities 5 , 6 , 7 , 8 , 9 . Recently, there has been a lot of progress in studying the neural mechanisms of metacognition 10 , 11 , yet it is unclear at this point how these results may inform educational sciences or interventions. Given the potential benefits of metacognition, it is important to get a better understanding of how metacognition works and of how training can be useful.

The interest in bridging cognitive neuroscience and educational practices has increased in the past two decades, spanning a large number of studies grouped under the umbrella term of educational neuroscience 12 , 13 , 14 . With it, researchers have brought forward issues that are viewed as critical for the discipline to improve education. Recurring issues that may impede the relevance of neural insights for educational practices concern external validity 15 , 16 , theoretical discrepancies 17 and differences in terms of the domains of (meta)cognition operationalised (specific or general) 15 . This is important because, in recent years, brain research is starting to orient itself towards training metacognitive abilities that would translate into real-life benefits. However, direct links between metacognition in the brain and metacognition in domains such as education have still to be made. As for educational sciences, a large body of literature on metacognitive training is available, yet we still need clear insights about what works and why. While studies suggest that training metacognitive abilities results in higher academic achievement 18 , other interventions show mixed results 19 , 20 . Moreover, little is known about the long-term effects of, or transfer effects, of these interventions. A better understanding of the cognitive processes involved in metacognition and how they are expressed in the brain may provide insights in these regards.

Within cognitive neuroscience, there has been a long tradition of studying executive functions (EF), which are closely related to metacognitive processes 21 . Similar to metacognition, EF shows a positive relationship with learning at school. For instance, performance in laboratory tasks involving error monitoring, inhibition and working memory (i.e. processes that monitor and regulate cognition) are associated with academic achievement in pre-school children 22 . More recently, researchers have studied metacognition in terms of introspective judgements about performance in a task 10 . Although the neural correlates of such behaviour are being revealed 10 , 11 , little is known about how behaviour during such tasks relates to academic achievement.

Educational and cognitive neuroscientists study metacognition in different contexts using different methods. Indeed, while the latter investigate metacognition via behavioural task, the former mainly rely on introspective questionnaires. The extent to which these different operationalisations of metacognition match and reflect the same processes is unclear. As a result, the external validity of methodologies used in cognitive neuroscience is also unclear 16 . We argue that neurocognitive research on metacognition has a lot of potential to provide insights in mechanisms relevant in educational contexts, and that theoretical and methodological exchange between the two disciplines can benefit neuroscientific research in terms of ecological validity.

For these reasons, we investigate the literature through the lenses of external validity, theoretical discrepancies, domain generality and metacognitive training. Research on metacognition in cognitive neuroscience and educational sciences are reviewed separately. First, we investigate how metacognition is operationalised with respect to the common framework introduced by Nelson and Narens 23 (see Fig. 1 ). We then discuss the existing body of evidence regarding metacognitive training. Finally, we compare findings in both fields, highlight gaps and shortcomings, and propose avenues for research relying on crossovers of the two disciplines.

Meta-knowledge is characterised as the upward flow from object-level to meta-level. Meta-control is characterised as the downward flow from meta-level to object-level. Metacognition is therefore conceptualised as the bottom-up monitoring and top-down control of object-level processes. Adapted from Nelson and Narens’ cognitive psychology model of metacognition 23 .

In cognitive neuroscience, metacognition is divided into two main components 5 , 24 , which originate from the seminal works of Flavell on metamemory 25 , 26 . First, metacognitive knowledge (henceforth, meta-knowledge) is defined as the knowledge individuals have of their own cognitive processes and their ability to monitor and reflect on them. Second, metacognitive control (henceforth, meta-control) consists of someone’s self-regulatory mechanisms, such as planning and adapting behaviour based on outcomes 5 , 27 . Following Nelson and Narens’ definition 23 , meta-knowledge is characterised as the flow and processing of information from the object level to the meta-level, and meta-control as the flow from the meta-level to the object level 28 , 29 , 30 (Fig. 1 ). The object-level encompasses cognitive functions such as recognition and discrimination of objects, decision-making, semantic encoding, and spatial representation. On the meta-level, information originating from the object level is processed and top-down regulation on object-level functions is imposed 28 , 29 , 30 .

Educational researchers have mainly investigated metacognition through the lens of Self-Regulated Learning theory (SRL) 3 , 4 , which shares common conceptual roots with the theoretical framework used in cognitive neuroscience but varies from it in several ways 31 . First, SRL is constrained to learning activities, usually within educational settings. Second, metacognition is merely one of three components, with “motivation to learn” and “behavioural processes”, that enable individuals to learn in a self-directed manner 3 . In SRL, metacognition is defined as setting goals, planning, organising, self-monitoring and self-evaluating “at various points during the acquisition” 3 . The distinction between meta-knowledge and meta-control is not formally laid down although reference is often made to a “self-oriented feedback loop” describing the relationship between reflecting and regulating processes that resembles Nelson and Narens’ model (Fig. 1 ) 3 , 23 . In order to facilitate the comparison of operational definitions, we will refer to meta-knowledge in educational sciences when protocols operationalise self-awareness and knowledge of strategies, and to meta-control when they operationalise the selection and use of learning strategies and planning. For an in-depth discussion on metacognition and SRL, we refer to Dinsmore et al. 31 .

Metacognition in cognitive neuroscience

Operational definitions.

In cognitive neuroscience, research in metacognition is split into two tracks 32 . One track mainly studies meta-knowledge by investigating the neural basis of introspective judgements about one’s own cognition (i.e., metacognitive judgements), and meta-control with experiments involving cognitive offloading. In these experiments, subjects can perform actions such as set reminders, making notes and delegating tasks 33 , 34 , or report their desire for them 35 . Some research has investigated how metacognitive judgements can influence subsequent cognitive behaviour (i.e., a downward stream from the meta-level to the object level), but only one study so far has explored how this relationship is mapped in the brain 35 . In the other track, researchers investigate EF, also referred to as cognitive control 30 , 36 , which is closely related to metacognition. Note however that EF are often not framed in metacognitive terms in the literature 37 (but see ref. 30 ). For the sake of concision, we limit our review to operational definitions that have been used in neuroscientific studies.

Metacognitive judgements

Cognitive neuroscientists have been using paradigms in which subjects make judgements on how confident they are with regards to their learning of some given material 10 . These judgements are commonly referred to as metacognitive judgements , which can be viewed as a form of meta-knowledge (for reviews see Schwartz 38 and Nelson 39 ). Historically, researchers mostly resorted to paradigms known as Feelings of Knowing (FOK) 40 and Judgements of Learning (JOL) 41 . FOK reflect the belief of a subject to knowing the answer to a question or a problem and being able to recognise it from a list of alternatives, despite being unable to explicitly recall it 40 . Here, metacognitive judgement is thus made after retrieval attempt. In contrast, JOL are prospective judgements during learning of one’s ability to successfully recall an item on subsequent testing 41 .

More recently, cognitive neuroscientists have used paradigms in which subjects make retrospective metacognitive judgements on their performance in a two-alternative Forced Choice task (2-AFC) 42 . In 2-AFCs, subjects are asked to choose which of two presented options has the highest criterion value. Different domains can be involved, such as perception (e.g., visual or auditory) and memory. For example, subjects may be instructed to visually discriminate which one of two boxes contains more dots 43 , identify higher contrast Gabor patches 44 , or recognise novel words from words that were previously learned 45 (Fig. 2 ). The subjects engage in metacognitive judgements by rating how confident they are relative to their decision in the task. Based on their responses, one can evaluate a subject’s metacognitive sensitivity (the ability to discriminate one’s own correct and incorrect judgements), metacognitive bias (the overall level of confidence during a task), and metacognitive efficiency (the level of metacognitive sensitivity when controlling for task performance 46 ; Fig. 3 ). Note that sensitivity and bias are independent aspects of metacognition, meaning that two subjects may display the same levels of metacognitive sensitivity, but one may be biased towards high confidence while the other is biased towards low confidence. Because metacognitive sensitivity is affected by the difficulty of the task (one subject tends to display greater metacognitive sensitivity in easy tasks than difficult ones and different subjects may find a task more or less easy), metacognitive efficiency is an important measure as it allows researchers to compare metacognitive abilities between subjects and between domains. The most commonly used methods to assess metacognitive sensitivity during retrospective judgements are the receiver operating curve (ROC) and meta- d ′. 46 Both derive from signal detection theory (SDT) 47 which allows Type 1 sensitivity, or d’ ′ (how a subject can discriminate between stimulus alternatives, i.e. object-level processes) to be differentiated from metacognitive sensitivity (a judgement on the correctness of this decision) 48 . Importantly, only comparing meta- d ′ to d ′ seems to give reliable assessments metacognitive efficiency 49 . A ratio of 1 between meta- d’ ′ and d’ ′, indicates that a subject was perfectly able to discriminate between their correct and incorrect judgements. A ratio of 0.8 suggests that 80% of the task-related sensory evidence was available for the metacognitive judgements. Table 1 provides an overview of the different types of tasks and protocols with regards to the type of metacognitive process they operationalise. These operationalisations of meta-knowledge are used in combination with brain imaging methods (functional and structural magnetic resonance imaging; fMRI; MRI) to identify brain regions associated with metacognitive activity and metacognitive abilities 10 , 50 . Alternatively, transcranial magnetic stimulation (TMS) can be used to temporarily deactivate chosen brain regions and test whether this affects metacognitive abilities in given tasks 51 , 52 .

a Visual perception task: subjects choose the box containing the most (randomly generated) dots. Subjects then rate their confidence in their decision. b Memory task: subjects learn a list of words. In the next screen, they have to identify which of two words shown was present on the list. The subjects then rate their confidence in their decision.

The red and blue curves represent the distribution of confidence ratings for incorrect and correct trials, respectively. A larger distance between the two curves denotes higher sensitivity. Displacement to the left and right denote biases towards low confidence (low metacognitive bias) and high confidence (high metacognitive bias), respectively (retrieved from Fig. 1 in Fleming and Lau 46 ). We repeat the disclaimer of the original authors that this figure is not a statistically accurate description of correct and incorrect responses, which are typically not normally distributed 46 , 47 .

A recent meta-analysis analysed 47 neuroimaging studies on metacognition and identified a domain-general network associated with high vs. low confidence ratings in both decision-making tasks (perception 2-AFC) and memory tasks (JOL, FOK) 11 . This network includes the medial and lateral prefrontal cortex (mPFC and lPFC, respectively), precuneus and insula. In contrast, the right anterior dorsolateral PFC (dlPFC) was specifically involved in decision-making tasks, and the bilateral parahippocampal cortex was specific to memory tasks. In addition, prospective judgements were associated with the posterior mPFC, left dlPFC and right insula, whereas retrospective judgements were associated with bilateral parahippocampal cortex and left inferior frontal gyrus. Finally, emerging evidence suggests a role of the right rostrolateral PFC (rlPFC) 53 , 54 , anterior PFC (aPFC) 44 , 45 , 55 , 56 , dorsal anterior cingulate cortex (dACC) 54 , 55 and precuneus 45 , 55 in metacognitive sensitivity (meta- d ′, ROC). In addition, several studies suggest that the aPFC relates to metacognition specifically in perception-related 2-AFC tasks, whereas the precuneus is engaged specifically in memory-related 2-AFC tasks 45 , 55 , 56 . This may suggest that metacognitive processes engage some regions in a domain-specific manner, while other regions are domain-general. For educational scientists, this could mean that some domains of metacognition may be more relevant for learning and, granted sufficient plasticity of the associated brain regions, that targeting them during interventions may show more substantial benefits. Note that rating one’s confidence and metacognitive sensitivity likely involve additional, peripheral cognitive processes instead of purely metacognitive ones. These regions are therefore associated with metacognition but not uniquely per se. Notably, a recent meta-analysis 50 suggests that domain-specific and domain-general signals may rather share common circuitry, but that their neural signature varies depending on the type of task or activity, showing that domain-generality in metacognition is complex and still needs to be better understood.

In terms of the role of metacognitive judgements on future behaviour, one study found that brain patterns associated with the desire for cognitive offloading (i.e., meta-control) partially overlap with those associated with meta-knowledge (metacognitive judgements of confidence), suggesting that meta-control is driven by either non-metacognitive, in addition to metacognitive, processes or by a combination of different domain-specific meta-knowledge processes 35 .

Executive function

In EF, processes such as error detection/monitoring and effort monitoring can be related to meta-knowledge while error correction, inhibitory control, and resource allocation can be related to meta-control 36 . To activate these processes, participants are asked to perform tasks in laboratory settings such as Flanker tasks, Stroop tasks, Demand Selection tasks and Motion Discrimination tasks (Fig. 4 ). Neural correlates of EF are investigated by having subjects perform such tasks while their brain activity is recorded with fMRI or electroencephalography (EEG). Additionally, patients with brain lesions can be tested against healthy participants to evaluate the functional role of the impaired regions 57 .

a Flanker task: subjects indicate the direction to which the arrow in the middle points. b Stroop task: subjects are presented with the name of colour printed in a colour that either matches or mismatches the name. Subjects are asked to give the name of the written colour or the printed colour. c Motion Discrimination task: subjects have to determine in which direction the dots are going with variating levels of noise. d Example of a Demand Selection task: in both options subjects have to switch between two tasks. Task one, subjects determine whether the number shown is higher or lower than 5. Task two, subjects determine whether the number is odd or even. The two options (low and high demand) differ in their degree of task switching, meaning the effort required. Subjects are allowed to switch between the two options. Note, the type of task is solely indicated by the colour of the number and that the subjects are not explicitly told about the difference in effort between the two options (retrieved from Fig. 1c in Froböse et al. 58 ).

In a review article on the neural basis of EF (in which they are defined as meta-control), Shimamura argues that a network of regions composed of the aPFC, ACC, ventrolateral PFC (vlPFC) and dlPFC is involved in the regulations of cognition 30 . These regions are not only interconnected but are also intricately connected to cortical and subcortical regions outside of the PFC. The vlPFC was shown to play an important role in “selecting and maintaining information in working memory”, whereas the dlPFC is involved in “manipulating and updating information in working memory” 30 . The ACC has been proposed to monitor cognitive conflict (e.g. in a Stroop task or a Flanker task), and the dlPFC to regulate it 58 , 59 . In particular, activity in the ACC in conflict monitoring (meta-knowledge) seems to contribute to control of cognition (meta-control) in the dlPFC 60 , 61 and to “bias behavioural decision-making toward cognitively efficient tasks and strategies” (p. 356) 62 . In a recent fMRI study, subjects performed a motion discrimination task (Fig. 4c ) 63 . After deciding on the direction of the motion, they were presented additional motion (i.e. post-decisional evidence) and then were asked to rate their confidence in their initial choice. The post-decisional evidence was encoded in the activity of the posterior medial frontal cortex (pMFC; meta-knowledge), while lateral aPFC (meta-control) modulated the impact of this evidence on subsequent confidence rating 63 . Finally, results from a meta-analysis study on cognitive control identified functional connectivity between the pMFC, associated with monitoring and informing other regions about the need for regulation, and the lPFC that would effectively regulate cognition 64 .

Online vs. offline metacognition

While the processes engaged during tasks such as those used in EF research can be considered as metacognitive in the sense that they are higher-order functions that monitor and control lower cognitive processes, scientists have argued that they are not functionally equivalent to metacognitive judgements 10 , 11 , 65 , 66 . Indeed, engaging in metacognitive judgements requires subjects to reflect on past or future activities. As such, metacognitive judgements can be considered as offline metacognitive processes. In contrast, high-order processes involved in decision-making tasks such as used in EF research are arguably largely made on the fly, or online , at a rapid pace and subjects do not need to reflect on their actions to perform them. Hence, we propose to explicitly distinguish online and offline processes. Other researchers have shared a similar view and some have proposed models for metacognition that make similar distinctions 65 , 66 , 67 , 68 . The functional difference between online and offline metacognition is supported by some evidence. For instance, event-related brain potential (ERP) studies suggest that error negativities are associated with error detection in general, whereas an increased error positivity specifically encodes error that subjects could report upon 69 , 70 . Furthermore, brain-imaging studies suggest that the MFC and ACC are involved in online meta-knowledge, while the aPFC and lPFC seem to be activated when subjects engage in more offline meta-knowledge and meta-control, respectively 63 , 71 , 72 . An overview of the different tasks can be found in Table 1 and a list of different studies on metacognition can be found in Supplementary Table 1 (organised in terms of the type of processes investigated, the protocols and brain measures used, along with the brain regions identified). Figure 5 illustrates the different brain regions associated with meta-knowledge and meta-control, distinguishing between what we consider to be online and offline processes. This distinction is often not made explicitly but it will be specifically helpful when building bridges between cognitive neuroscience and educational sciences.

The regions are divided into online meta-knowledge and meta-control, and offline meta-knowledge and meta-control following the distinctions introduced earlier. Some regions have been reported to be related to both offline and online processes and are therefore given a striped pattern.

Training metacognition

There are extensive accounts in the literature of efforts to improve EF components such as inhibitory control, attention shifting and working memory 22 . While working memory does not directly reflect metacognitive abilities, its training is often hypothesised to improve general cognitive abilities and academic achievement. However, most meta-analyses found that training methods lead only to weak, non-lasting effects on cognitive control 73 , 74 , 75 . One meta-analysis did find evidence of near-transfer following EF training in children (in particular working memory, inhibitory control and cognitive flexibility), but found no evidence of far-transfer 20 . According to this study, training on one component leads to improved abilities in that same component but not in other EF components. Regarding adults, however, one meta-analysis suggests that EF training in general and working memory training specifically may both lead to significant near- and far-transfer effects 76 . On a neural level, a meta-analysis showed that cognitive training resulted in decreased brain activity in brain regions associated with EF 77 . According to the authors, this indicates that “training interventions reduce demands on externally focused attention” (p. 193) 77 .

With regards to meta-knowledge, several studies have reported increased task-related metacognitive abilities after training. For example, researchers found that subjects who received feedback on their metacognitive judgements regarding a perceptual decision-making task displayed better metacognitive accuracy, not only in the trained task but also in an untrained memory task 78 . Related, Baird and colleagues 79 found that a two-week mindfulness meditation training lead to enhanced meta-knowledge in the memory domain, but not the perceptual domain. The authors link these results to evidence of increased grey matter density in the aPFC in meditation practitioners.

Research on metacognition in cognitive science has mainly been studied through the lens of metacognitive judgements and EF (specifically performance monitoring and cognitive control). Meta-knowledge is commonly activated in subjects by asking them to rate their confidence in having successfully performed a task. A distinction is made between metacognitive sensitivity, metacognitive bias and metacognitive efficacy. Monitoring and regulating processes in EF are mainly operationalised with behavioural tasks such as Flanker tasks, Stroop tasks, Motion Discrimination tasks and Demand Selection tasks. In addition, metacognitive judgements can be viewed as offline processes in that they require the subject to reflect on her cognition and develop meta-representations. In contrast, EF can be considered as mostly online metacognitive processes because monitoring and regulation mostly happen rapidly without the need for reflective thinking.

Although there is some evidence for domain specificity, other studies have suggested that there is a single network of regions involved in all meta-cognitive tasks, but differentially activated in different task contexts. Comparing research on meta-knowledge and meta-control also suggest that some regions play a crucial role in both knowledge and regulation (Fig. 5 ). We have also identified a specific set of regions that are involved in either offline or online meta-knowledge. The evidence in favour of metacognitive training, while mixed, is interesting. In particular, research on offline meta-knowledge training involving self-reflection and metacognitive accuracy has shown some promising results. The regions that show structural changes after training, were those that we earlier identified as being part of the metacognition network. EF training does seem to show far-transfer effects at least in adults, but the relevance for everyday life activity is still unclear.

One major limitation of current research in metacognition is ecological validity. It is unclear to what extent the operationalisations reviewed above reflect real-life metacognition. For instance, are people who can accurately judge their performance on a behavioural task also able to accurately assess how they performed during an exam? Are people with high levels of error regulation and inhibitory control able to learn more efficiently? Note that criticism on the ecological validity of neurocognitive operationalisations extends beyond metacognition research 16 . A solution for improving validity may be to compare operationalisations of metacognition in cognitive neuroscience with the ones in educational sciences, which have shown clear links with learning in formal education. This also applies to metacognitive training.

Metacognition in educational sciences

The most popular protocols used to measure metacognition in educational sciences are self-report questionnaires or interviews, learning journals and thinking-aloud protocols 31 , 80 . During interviews, subjects are asked to answer questions regarding hypothetical situations 81 . In learning journals, students write about their learning experience and their thoughts on learning 82 , 83 . In thinking-aloud protocols, subjects are asked to verbalise their thoughts while performing a problem-solving task 80 . Each of these instruments can be used to study meta-knowledge and meta-control. For instance, one of the most widely used questionnaires, the Metacognitive Awareness Inventory (MAI) 42 , operationalises “Flavellian” metacognition and has dedicated scales for meta-knowledge and meta-control (also popular are the MSLQ 84 and LASSI 85 which operate under SRL). The meta-knowledge scale of the MAI operationalises knowledge of strategies (e.g., “ I am aware of what strategies I use when I study ”) and self-awareness (e.g., “ I am a good judge of how well I understand something ”); the meta-control scale operationalises planning (e.g., “ I set a goal before I begin a task ”) and use of learning strategies (e.g., “ I summarize what I’ve learned after I finish ”). Learning journals, self-report questionnaires and interviews involve offline metacognition. Thinking aloud, though not engaging the same degree self-reflection, also involves offline metacognition in the sense that online processes are verbalised, which necessitate offline processing (see Table 1 for an overview and Supplementary Table 2 for more details).

More recently, methodologies borrowed from cognitive neuroscience have been introduced to study EF in educational settings 22 , 86 . In particular, researchers used classic cognitive control tasks such as the Stroop task (for a meta-analysis 86 ). Most of the studied components are related to meta-control and not meta-knowledge. For instance, the BRIEF 87 is a questionnaire completed by parents and teachers which assesses different subdomains of EF: (1) inhibition, shifting, and emotional control which can be viewed as online metacognitive control, and (2) planning, organisation of materials, and monitoring, which can be viewed as offline meta-control 87 .

Assessment of metacognition is usually compared against metrics of academic performance such as grades or scores on designated tasks. A recent meta-analysis reported a weak correlation of self-report questionnaires and interviews with academic performance whereas think-aloud protocols correlated highly 88 . Offline meta-knowledge processes operationalised by learning journals were found to be positively associated with academic achievement when related to reflection on learning activities but negatively associated when related to reflection on learning materials, indicating that the type of reflection is important 89 . EF have been associated with abilities in mathematics (mainly) and reading comprehension 86 . However, the literature points towards contrary directions as to what specific EF component is involved in academic achievement. This may be due to the different groups that were studied, to different operationalisations or to different theoretical underpinnings for EF 86 . For instance, online and offline metacognitive processes, which are not systematically distinguished in the literature, may play different roles in academic achievement. Moreover, the bulk of research focussed on young children with few studies on adolescents 86 and EF may play a role at varying extents at different stages of life.

A critical question in educational sciences is that of the nature of the relationship between metacognition and academic achievement to understand whether learning at school can be enhanced by training metacognitive abilities. Does higher metacognition lead to higher academic achievement? Do these features evolve in parallel? Developmental research provides valuable insights into the formation of metacognitive abilities that can inform training designs in terms of what aspect of metacognition should be supported and the age at which interventions may yield the best results. First, meta-knowledge seems to emerge around the age of 5, meta-control around 8, and both develop over the years 90 , with evidence for the development of meta-knowledge into adolescence 91 . Furthermore, current theories propose that meta-knowledge abilities are initially highly domain-dependent and gradually become more domain-independent as knowledge and experience are acquired and linked between domains 32 . Meta-control is believed to evolve in a similar fashion 90 , 92 .

Common methods used to train offline metacognition are direct instruction of metacognition, metacognitive prompts and learning journals. In addition, research has been done on the use of (self-directed) feedback as a means to induce self-reflection in students, mainly in computer-supported settings 93 . Interestingly, learning journals appear to be used for both assessing and fostering metacognition. Metacognitive instruction consists of teaching learners’ strategies to “activate” their metacognition. Metacognitive prompts most often consist of text pieces that are sent at specific times and that trigger reflection (offline meta-knowledge) on learning behaviour in the form of a question, hint or reminder.

Meta-analyses have investigated the effects of direct metacognitive instruction on students’ use of learning strategies and academic outcomes 18 , 94 , 95 . Their findings show that metacognitive instruction can have a positive effect on learning abilities and achievement within a population ranging from primary schoolers to university students. In particular, interventions lead to the highest effect sizes when they both (i) instructed a combination of metacognitive strategies with an emphasis on planning strategies (offline meta-control) and (ii) “provided students with knowledge about strategies” (offline meta-knowledge) and “illustrated the benefits of applying the trained strategies, or even stimulated metacognitive reasoning” (p.114) 18 . The longer the duration of the intervention, the more effective they were. The strongest effects on academic performance were observed in the context of mathematics, followed by reading and writing.

While metacognitive prompts and learning journals make up the larger part of the literature on metacognitive training 96 , meta-analyses that specifically investigate their effectiveness have yet to be performed. Nonetheless, evidence suggests that such interventions can be successful. Researchers found that metacognitive prompts fostered the use of metacognitive strategies (offline meta-control) and that the combination of cognitive and metacognitive prompts improved learning outcomes 97 . Another experiment showed that students who received metacognitive prompts performed more metacognitive activities inside the learning environment and displayed better transfer performance immediately after the intervention 98 . A similar study using self-directed prompts showed enhanced transfer performance that was still observable 3 weeks after the intervention 99 .

Several studies suggest that learning journals can positively enhance metacognition. Subjects who kept a learning journal displayed stronger high meta-control and meta-knowledge on learning tasks and tended to reach higher academic outcomes 100 , 101 , 102 . However, how the learning journal is used seems to be critical; good instructions are crucial 97 , 103 , and subjects who simply summarise their learning activity benefit less from the intervention than subjects who reflect about their knowledge, learning and learning goals 104 . An overview of studies using learning journals and metacognitive prompts to train metacognition can be found in Supplementary Table 3 .

In recent years, educational neuroscience researchers have tried to determine whether training and improvements in EF can lead to learning facilitation and higher academic achievement. Training may consist of having students continually perform behavioural tasks either in the lab, at home, or at school. Current evidence in favour of training EF is mixed, with only anecdotal evidence for positive effects 105 . A meta-analysis did not show evidence for a causal relationship between EF and academic achievement 19 , but suggested that the relationship is bidirectional, meaning that the two are “mutually supportive” 106 .

A recent review article has identified several gaps and shortcoming in the literature on metacognitive training 96 . Overall, research in metacognitive training has been mainly invested in developing learners’ meta-control rather than meta-knowledge. Furthermore, most of the interventions were done in the context of science learning. Critically, there appears to be a lack of studies that employed randomised control designs, such that the effects of metacognitive training intervention are often difficult to evaluate. In addition, research overwhelmingly investigated metacognitive prompts and learning journals in adults 96 , while interventions on EF mainly focused on young children 22 . Lastly, meta-analyses evaluating the effectiveness of metacognitive training have so far focused on metacognitive instruction on children. There is thus a clear disbalance between the meta-analyses performed and the scope of the literature available.

An important caveat of educational sciences research is that metacognition is not typically framed in terms of online and offline metacognition. Therefore, it can be unclear whether protocols operationalise online or offline processes and whether interventions tend to benefit more online or offline metacognition. There is also confusion in terms of what processes qualify as EF and definitions of it vary substantially 86 . For instance, Clements and colleagues mention work on SRL to illustrate research in EF in relation to academic achievement but the two spawn from different lines of research, one rooted in metacognition and socio-cognitive theory 31 and the other in the cognitive (neuro)science of decision-making. In addition, the MSLQ, as discussed above, assesses offline metacognition along with other components relevant to SRL, whereas EF can be mainly understood as online metacognition (see Table 1 ), which on the neural level may rely on different circuitry.

Investigating offline metacognition tends to be carried out in school settings whereas evaluating EF (e.g., Stroop task, and BRIEF) is performed in the lab. Common to all protocols for offline metacognition is that they consist of a form of self-report from the learner, either during the learning activity (thinking-aloud protocols) or after the learning activity (questionnaires, interviews and learning journals). Questionnaires are popular protocols due to how easy they are to administer but have been criticised to provide biased evaluations of metacognitive abilities. In contrast, learning journals evaluate the degree to which learners engage in reflective thinking and may therefore be less prone to bias. Lastly, it is unclear to what extent thinking-aloud protocols are sensitive to online metacognitive processes, such as on-the-fly error correction and effort regulation. The strength of the relationship between metacognitive abilities and academic achievement varies depending on how metacognition is operationalised. Self-report questionnaires and interviews are weakly related to achievement whereas thinking-aloud protocols and EF are strongly related to it.

Based on the well-documented relationship between metacognition and academic achievement, educational scientists hypothesised that fostering metacognition may improve learning and academic achievement, and thus performed metacognitive training interventions. The most prevalent training protocols are direct metacognitive instruction, learning journals, and metacognitive prompts, which aim to induce and foster offline metacognitive processes such as self-reflection, planning and selecting learning strategies. In addition, researchers have investigated whether training EF, either through tasks or embedded in the curriculum, results in higher academic proficiency and achievement. While a large body of evidence suggests that metacognitive instruction, learning journals and metacognitive prompts can successfully improve academic achievement, interventions designed around EF training show mixed results. Future research investigating EF training in different age categories may clarify this situation. These various degrees of success of interventions may indicate that offline metacognition is more easily trainable than online metacognition and plays a more important role in educational settings. Investigating the effects of different methods, offline and online, on the neural level, may provide researchers with insights into the trainability of different metacognitive processes.

In this article, we reviewed the literature on metacognition in educational sciences and cognitive neuroscience with the aim to investigate gaps in current research and propose ways to address them through the exchange of insights between the two disciplines and interdisciplinary approaches. The main aspects analysed were operational definitions of metacognition and metacognitive training, through the lens of metacognitive knowledge and metacognitive control. Our review also highlighted an additional construct in the form of the distinction between online metacognition (on the fly and largely automatic) and offline metacognition (slower, reflective and requiring meta-representations). In cognitive neuroscience, research has focused on metacognitive judgements (mainly offline) and EF (mainly online). Metacognition is operationalised with tasks carried out in the lab and are mapped onto brain functions. In contrast, research in educational sciences typically measures metacognition in the context of learning activities, mostly in schools and universities. More recently, EF has been studied in educational settings to investigate its role in academic achievement and whether training it may benefit learning. Evidence on the latter is however mixed. Regarding metacognitive training in general, evidence from both disciplines suggests that interventions fostering learners’ self-reflection and knowledge of their learning behaviour (i.e., offline meta-knowledge) may best benefit them and increase academic achievement.

We focused on four aspects of research that could benefit from an interdisciplinary approach between the two areas: (i) validity and reliability of research protocols, (ii) under-researched dimensions of metacognition, (iii) metacognitive training, and (iv) domain-specificity vs. domain generality of metacognitive abilities. To tackle these issue, we propose four avenues for integrated research: (i) investigate the degree to which different protocols relate to similar or different metacognitive constructs, (ii) implement designs and perform experiments to identify neural substrates necessary for offline meta-control by for example borrowing protocols used in educational sciences, (iii) study the effects of (offline) meta-knowledge training on the brain, and (iv) perform developmental research in the metacognitive brain and compare it with the existing developmental literature in educational sciences regarding the domain-generality of metacognitive processes and metacognitive abilities.

First, neurocognitive research on metacognitive judgements has developed robust operationalisations of offline meta-knowledge. However, these operationalisations often consist of specific tasks (e.g., 2-AFC) carried out in the lab. These tasks are often very narrow and do not resemble the challenges and complexities of behaviours associated with learning in schools and universities. Thus, one may question to what extent they reflect real-life metacognition, and to what extent protocols developed in educational sciences and cognitive neuroscience actually operationalise the same components of metacognition. We propose that comparing different protocols from both disciplines that are, a priori, operationalising the same types of metacognitive processes can help evaluate the ecological validity of protocols used in cognitive neuroscience, and allow for more holistic assessments of metacognition, provided that it is clear which protocol assesses which construct. Degrees of correlation between different protocols, within and between disciplines, may allow researchers to assess to what extent they reflect the same metacognitive constructs and also identify what protocols are most appropriate to study a specific construct. For example, a relation between meta- d ′ metacognitive sensitivity in a 2-AFC task and the meta-knowledge subscale of the MAI, would provide external validity to the former. Moreover, educational scientists would be provided with bias-free tools to assess metacognition. These tools may enable researchers to further investigate to what extent metacognitive bias, sensitivity and efficiency each play a role in education settings. In contrast, a low correlation may highlight a difference in domain between the two measures of metacognition. For instance, metacognitive judgements in brain research are made in isolated behaviour, and meta-d’ can thus be viewed to reflect “local” metacognitive sensitivity. It is also unclear to what extent processes involved in these decision-making tasks cover those taking place in a learning environment. When answering self-reported questionnaires, however, subjects make metacognitive judgements on a large set of (learning) activities, and the measures may thus resemble more “global” or domain-general metacognitive sensitivity. In addition, learners in educational settings tend to receive feedback — immediate or delayed — on their learning activities and performance, which is generally not the case for cognitive neuroscience protocols. Therefore, investigating metacognitive judgements in the presence of performance or social feedback may allow researchers to better understand the metacognitive processes at play in educational settings. Devising a global measure of metacognition in the lab by aggregating subjects’ metacognitive abilities in different domains or investigating to what extent local metacognition may affect global metacognition could improve ecological validity significantly. By investigating the neural correlates of educational measures of metacognition, researchers may be able to better understand to what extent the constructs studied in the two disciplines are related. It is indeed possible that, though weakly correlated, the meta-knowledge scale of the MAI and meta-d’ share a common neural basis.

Second, our review highlights gaps in the literature of both disciplines regarding the research of certain types of metacognitive processes. There is a lack of research in offline meta-control (or strategic regulation of cognition) in neuroscience, whereas this construct is widely studied in educational sciences. More specifically, while there exists research on EF related to planning (e.g. 107 ), common experimental designs make it hard to disentangle online from offline metacognitive processes. A few studies have implemented subject reports (e.g., awareness of error or desire for reminders) to pin-point the neural substrates specifically involved in offline meta-control and the current evidence points at a role of the lPFC. More research implementing similar designs may clarify this construct. Alternatively, researchers may exploit educational sciences protocols, such as self-report questionnaires, learning journals, metacognitive prompts and feedback to investigate offline meta-control processes in the brain and their relation to academic proficiency and achievement.

Third, there is only one study known to us on the training of meta-knowledge in the lab 78 . In contrast, meta-knowledge training in educational sciences have been widely studied, in particular with metacognitive prompts and learning journals, although a systematic review would be needed to identify the benefits for learning. Relative to cognitive neuroscience, studies suggest that offline meta-knowledge trained in and outside the lab (i.e., metacognitive judgements and meditation, respectively) transfer to meta-knowledge in other lab tasks. The case of meditation is particularly interesting since meditation has been demonstrated to beneficiate varied aspects of everyday life 108 . Given its importance for efficient regulation of cognition, training (offline) meta-knowledge may present the largest benefits to academic achievement. Hence, it is important to investigate development in the brain relative to meta-knowledge training. Evidence on metacognitive training in educational sciences tends to suggest that offline metacognition is more “plastic” and may therefore benefit learning more than online metacognition. Furthermore, it is important to have a good understanding of the developmental trajectory of metacognitive abilities — not only on a behavioural level but also on a neural level — to identify critical periods for successful training. Doing so would also allow researchers to investigate the potential differences in terms of plasticity that we mention above. Currently, the developmental trajectory of metacognition is under-studied in cognitive neuroscience with only one study that found an overlap between the neural correlates of metacognition in adults and children 109 . On a side note, future research could explore the potential role of genetic factors in metacognitive abilities to better understand to what extent and under what constraints they can be trained.

Fourth, domain-specific and domain-general aspects of metacognitive processes should be further investigated. Educational scientists have studied the development of metacognition in learners and have concluded that metacognitive abilities are domain-specific at the beginning (meaning that their quality depends on the type of learning activity, like mathematics vs. writing) and progressively evolve towards domain-general abilities as knowledge and expertise increase. Similarly, neurocognitive evidence points towards a common network for (offline) metacognitive knowledge which engages the different regions at varying degrees depending on the domain of the activity (i.e., perception, memory, etc.). Investigating this network from a developmental perspective and comparing findings with the existing behavioural literature may improve our understanding of the metacognitive brain and link the two bodies of evidence. It may also enable researchers to identify stages of life more suitable for certain types of metacognitive intervention.

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Acknowledgements

We would like to thank the University of Amsterdam for supporting this research through the Interdisciplinary Doctorate Agreement grant. W.v.d.B. is further supported by the Jacobs Foundation, European Research Council (grant no. ERC-2018-StG-803338), the European Union Horizon 2020 research and innovation programme (grant no. DiGYMATEX-870578), and the Netherlands Organization for Scientific Research (grant no. NWO-VIDI 016.Vidi.185.068).

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Fleur, D.S., Bredeweg, B. & van den Bos, W. Metacognition: ideas and insights from neuro- and educational sciences. npj Sci. Learn. 6 , 13 (2021). https://doi.org/10.1038/s41539-021-00089-5

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• October 28, 2021
• Executive Functioning
• Why Metacognition is Important for Students

Nicole Kaplan, MaSpEd

Share this post:.

Metacognition is a student’s ability to think about their own thinking.

Throughout our day, there are countless opportunities for us to think about our reactions and thought processes to different situations.

Metacognition is not an innate skill but is one that needs to be nurtured and taught to students throughout their adolescent years.

Why is Metacognition Important?

Metacognition is becoming an even more important skill for students to master. Students that have the ability to think about their thinking are more capable of higher-level thinking. Higher-level thinking involves more cognitive effort. It is more than just memorizing, but requires students to apply and generalize their knowledge.

Over the years, education has moved towards teachers including higher-level questions within their curriculum. Gone are the days of students regurgitating facts from memory.

For example, instead of being asked to memorize the start and end of the Civil War, students will be asked to speak about what led up to the war and the aftermath.

This forces students to use critical thinking skills and put themselves in the mindset of the people that lived in that time period.

Having this ability increases students’ understanding and will create individuals with the critical thinking skills that will aid them in their everyday life.

How to Improve Students' Metacognition?

Knowing why metacognition is important is the first step. The next step is to support student growth with their metacognitive ability.

To build a student’s metacognitive ability, teachers need to let students struggle. When a student does not understand a concept, they should be given the opportunity to think.

Interrupting a student’s thinking process and just giving them the answer, does not support their individual growth.

When a student struggles and is able to come to an answer on their own, learn how their thinking process works.

If a student is still unable to come to an answer, they should be given a chance to ask questions on their own.

Realizing they are struggling and being a self-advocate is an important step to becoming an independent metacognitive thinker.

Furthermore, students should be allowed to reflect on their learning.

Allowing students to think about where they were before compared to their current thinking is an effective way to promote metacognitive thinking.

Assisting students with a journal and providing them with writing prompts will give students opportunities to reflect on their thinking process.

Empowering Students with Metacognitive Thinking

Not only will metacognitive training assist students with their learning, but it will also empower them to become more independent.

A student that can demonstrate metacognitive students is aware of what they need to learn and how they learn best.

Students that can self-monitor and think for themselves know their strengths and weaknesses. Metacognitive thinkers can set goals for themselves and monitor their growth.

Teachers that spend time reinforcing this will see students become life-long learners with a passion to grow as individuals.

Within our society, we want future generations to be independent and critical thinkers. To assist with this goal, we need to promote and support metacognitive thinking.

Stay empowerED, Nicole

https://www.edutopia.org/blog/8-pathways-metacognition-in-classroom-marilyn-price-mitchell

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Metacognitive strategies that enhance critical thinking

• Published: 21 July 2010
• Volume 5 , pages 251–267, ( 2010 )

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• Kelly Y. L. Ku 1 &
• Irene T. Ho 2  

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The need to cultivate students’ use of metacognitive strategies in critical thinking has been emphasized in the related literature. The present study aimed at examining the role of metacognitive strategies in critical thinking. Ten university students with comparable cognitive ability, thinking disposition and academic achievement but with different levels of critical thinking performance participated in the study (five in the high-performing group and five in the low-performing group). They were tested on six thinking tasks using think-aloud procedures. Results showed that good critical thinkers engaged in more metacognitive activities, especially high-level planning and high-level evaluating strategies. The importance of metacognitive knowledge as a supporting factor for effective metacognitive regulation was also revealed. The contribution of metacognitive strategies to critical thinking and implications for instructional practice are discussed.

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This paper is based on a presentation at the American Educational Research Association Annual Meeting, San Diego, CA, 13–17 April, 2009. This study was supported by a grant from the Research Grants Council of Hong Kong (Project no. CUHK 4118/04H).

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Ku, K.Y.L., Ho, I.T. Metacognitive strategies that enhance critical thinking. Metacognition Learning 5 , 251–267 (2010). https://doi.org/10.1007/s11409-010-9060-6

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Received : 20 October 2009

Accepted : 07 July 2010

Published : 21 July 2010

Issue Date : December 2010

DOI : https://doi.org/10.1007/s11409-010-9060-6

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