Heutagogy Community of Practice
Advancing the Theory and Practice of Self-Determined Learning
- What Is Heutagogy?
- How To Participate
- Perspectives on Heutagogy: The Blog
- Events & Announcements
- Working Bibliography
- About The Image
Thinking About Thinking: Reflection and Metacognition
Thanks to TIm on Flickr for making this image available.
by Stewart Hase
A major feature of how we naturally learn, according to self-determined learning (heutagogy), is metacognition. Specifically this involves reflection that leads to double loop and even triple loop learning (see Blaschke, 2012; Hase & Kenyon, 2013). Although having a history going back to Dewey, it was Don Schon who first gave prominence to the notion of reflection as a practice in his book The Reflective Practitioner in 1983.
There is evidence that simple reflection in the classroom can enhance learning (e.g., Boud, Keogh and Walker, 2013; Hartman, 2002; Mezirow, 1990; Phelps, Ellis & Hase, 2001; Scott and Winograd, 1990; Sobral, 2001). Many educators use reflective journals with their students as well as verbally stimulating metacognition. There is now, however, hard edged evidence via brain science for the role of metacognitive processes like reflection and its more complex cousin meditation. In a recent article of Scientific American Mind (Sept/Oct 2014) by one of the pioneers in metacognitive research, Stephen Fleming, summarizes the current state of play about the role of reflection and learning.
It seems that metacognition is a feature of the frontal lobe of the brain, specifically the anterior prefrontal cortex, and is affected when this area is damaged. Impairment has the effect of depriving the person of insight (thank you Freud too for first identifying the notion that our insight can be flawed). This means that people lose the capacity to understand their own behaviour as in the case of a severe illness such as dementia, schizophrenia or alcoholism, for example. But it is possible to lack insight into even what we do on in ordinary everyday activities. It seems that metacognition may take many forms including for memory (reminding oneself to do something) and for perception (reflecting on what one saw or heard).
Metacognition may be stimulated by drugs and by brain stimulation. But it may also be improved by meditation, which involves focusing on one’s own mental state. It seems to directly cause physical change the anterior prefrontal cortex. Whether or not meditation induces neuroplasticity is speculative, according to Fleming.
Understanding the neuroscience of metacognition is in its early stages. But taken together with the other research there is enough evidence, in my view, to warrant incorporating reflective processes in ‘classrooms’ and in informal learning to enhance learning. It might be interesting to see if brief, intense reflection through meditation is able to improve learning further.
Self-determined learning is underpinned by the notion of human agency. Reflection is something that is under control of the learner, natural and certainly something we do everyday as part of our normal functioning. However, it is also a skill that can be improved in learners at every level, with some potentially positive effects on learning.
Now, let me think about whether my thinking is on the mark!
Baird, B., Mrazek, M. D. , Phillips, D. T. & Schooler, J.W. (2014). Domain specific enhancement of metacognitive ability following meditation training. Journal of Experimental Psychology General, 143(5), 1972-9Boud, D., Keogh, R., & Walker, D. (2013). Promoting reflection in learning A model. Boundaries of adult learning , 1 , 32.
Fleming, S. (14 August 2014). The power of reflection. Scientific American Mind 25 , pp. 30 – 37. http://www.nature.com/scientificamericanmind/journal/v25/n5/full/scientificamericanmind0914-30.html
Hartman, H. J. (2002). Metacognition in learning and instruction . Dordreecht: Kluwer.
Jensen, E. (2007). Brain based learning . Heatherton: Hawker Brownlow.
Mezirow, J. (1990). How critical reflection triggers transformative learning in J. Mezirow (Ed.). Fostering Critical Reflection in Adulthood. New York: Jossey Bass, pp. 1- 20 .
Phelps, R, Ellis, A & Hase, S. (2001). The role of metacognitive and reflective learning processes in developing capable computer users in G. Kennedy, M. Keppell, C McNaught & T Petrovic (Eds). Meeting at the crossroads: proceedings of the 18th Annual Conference of the Australasian Society for Computers in Learning in Tertiary Education (ASCILITE), University of Melbourne, Vic., 9-12 December.
Sobral, D. T. (2001). An appraisal of medical students’ reflection-in-learning. Medical Education , 34(3), 182-187.
3 comments on “ thinking about thinking: reflection and metacognition ”.
I completely agree with this. Meditation greatly assist metacognition… I have the story where I was an average student through highschool. Then I read something about intelligence being about greater neuro-transmission between left and right hemispheres. Kinda made sense to me, whether it is true or not wasn’t important, it made sense. So I started to visualize greater left-right brain integration with my evening meditation, I’d also reflect upon the current subject matter of my learning during this meditation. Needless to say, I went from a C+ average high-school student to an honors student in college and university. I know, what I am saying is anecdotal and unscientific… but I would hedge, if any student was to meditate and reflect upon their current subjects of study.. and have a routine of meditation and reflection, and include journal writing as a part of all this… they would see a measurable jump in their cognitive abilities within their chosen subject. It is this realization that has driven me toward self-determined learning, and developing a personalized approach to continuous learning. $0.02
Pingback: Teaching Metacognition: Insight Into How Your Students Think Is Key To High Achievement In All Domains [Briggs]
Pingback: Reflection #6: Exercising Metacognition – Fresh Maine Librarian
Leave a Reply Cancel reply
Information, what’s here, twitter conversations.
- Learning in the Social Workplace
- Reading Bumps and Entrails
- The Heutagogic Archives
Follow via Email
Enter your email address to receive notifications of new posts by email.
Looking For Something?
Create a free website or blog at WordPress.com.
- Already have a WordPress.com account? Log in now.
- Follow Following
- Copy shortlink
- Report this content
- View post in Reader
- Manage subscriptions
- Collapse this bar
Center for Teaching
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.
Photo credit: wittygrittyinvisiblegirl via Compfight cc
Photo Credit: Helga Weber via Compfight cc
Photo Credit: fiddle oak via Compfight cc
- Online Course Development Resources
- Principles & Frameworks
- Pedagogies & Strategies
- Reflecting & Assessing
- Challenges & Opportunities
- Populations & Contexts
- Services for Departments and Schools
- Examples of Online Instructional Modules
Internet Explorer is no longer supported
Please upgrade to Microsoft Edge , Google Chrome , or Firefox .
Lo sentimos, la página que usted busca no se ha podido encontrar. Puede intentar su búsqueda de nuevo o visitar la lista de temas populares.
Get this as a PDF
Enter email to download and get news and resources in your inbox.
Share this on social
Metacognition: how thinking about thinking can help kids.
A powerful skill for building resilience
Writer: Rae Jacobson
Clinical Experts: Marc Gladstone , Tamara Rosier, PhD
What You'll Learn
- What is metacognition?
- How does metacognition help kids?
- How can kids learn to be more metacognitive?
Metacognition is a big word for something most of us do every day without even noticing: Thinking about our own thoughts. Reflecting on our thoughts is a big part of understanding our feelings and learning new things.When kids hit challenges — a hard math test, a fight with a friend — it can be tempting for them to give up. But in order to thrive, kids need to be able to go from “I can’t” to “How can I?” Metacognition can help.
Figuring out how to face tough situations without getting frustrated can be extra helpful for kids with learning issues. A kid with ADHD who struggles to stay on task might feel anxious about writing a long essay. Without the skills to reflect on why they feel upset, they might think: “I’m just bad at writing.”
But a kid who knows how to reflect could look at the same situation and say, “I always feel like this when I have to work for a long time. Maybe I should start early and take breaks.” Taking a metacognitive approach makes it easier to manage frustration and find solutions.
Metacognitive skills can also help kids manage their feelings and boost self-esteem. The bad feelings kids have when they feel frustrated easily turn into negative self-talk: “If I failed the test, that means I’m not smart.” Metacognitive thinking can help kids think things through — and stop beating themselves up. For instance: “I failed the test because I wasn’t ready. How can I be more prepared next time?”
Parents can help kids learn metacognitive thinking. Start by asking open-ended questions that give kids space to reflect. For example, “Can you tell me more about why you think that?” It’s also important to help kids think through times when they get upset or act out. Thinking about their behavior can help them learn to manage difficult situations in a better way. For example, “Why do you think you got upset when Dad changed the channel?”
When kids hit difficult problems — the seemingly insurmountable English essay, a math test that takes on epic proportions, social struggles that leave them feeling frustrated — it can be tempting to give up and resort to four words no parent ever wants to hear: “I can’t do it.”
In order to thrive, kids need to be able to make the transition from the negative “I can’t” to the proactive “How can I?”
To do that, they need to think about why they’re stuck, what’s frustrating them, what they would need to get unstuck. They need to think about their own thinking.
There’s a word for that, and it’s metacognition.
Metacognition is a big word for something most of us do every day without even noticing. Reflecting on our own thoughts is how we gain insight into our feelings, needs, and behaviors — and how we learn, manage, and adapt to new experiences, challenges, and emotional setbacks. It’s the running conversation we have in our heads, mentally sounding ourselves out and making plans. Training kids to use it proactively to overcome obstacles, it turns out, can be a powerful tool.
More and more studies are suggesting that kids who are taught to use metacognitive strategies early on are more resilient and more successful, both in and out of school.
“I view metacognition as a goal,” says Marc Gladstone, a learning specialist. “Getting into the habit of using metacognitive strategies early on helps kids become more independent learners and bolsters self-advocacy skills.”
What is metacognition and how does it work?
“Metacognitive thinking teaches us about ourselves,” says Tamara Rosier, a learning coach who specializes in metacognitive techniques. “Thinking about our thinking creates perspective — perspective that leaves room for change.”
She gives an example: “Instead of saying, ‘Math tests make me anxious ,’ we’re asking ourselves, ‘What is it about math tests that makes me feel anxious and what can I do to change that?’ ”
Kids who are taught to think of themselves as being “good” or “bad” at a particular task can have a fixed mindset that makes them passive in approaching a challenge: either they can do it or they can’t, but they aren’t likely to think they can change that outcome.
Teaching kids to become more metacognitive helps them move from a mindset that leaves little room for change to a mindset which promotes self-awareness and resilience.
Help for kids with learning issues
Helping your child learn to work through difficult situations (or homework assignments, as the case may be) without becoming overwhelmed or giving up is especially valuable for kids with learning issues who may need to come up with different strategies than other students in the class.
- A child with ADHD who struggles to stay on task is likely to feel frustrated and anxious when he’s assigned a long essay. If he’s unable to reflect on why the project upsets him he might think, “Everyone else is having an easy time. I’m just bad at writing.”
- A kid who’s learned to reflect on his own learning process, on the other hand, could look at the situation and say, “I always feel like this when I have to work for a long time. Maybe if I take breaks every hour or so I’ll feel less stressed out.” By taking a metacognitive approach, he’s able to manage his frustration and find a better way to approach big assignments in the future.
Great for self-regulation
Metacognitive skills are not only excellent tools for kids who learn differently, and often find themselves struggling to keep up. They also enable kids to self-regulate when faced with challenges, especially unexpected ones.
“One of the most powerful byproducts of metacognitive thinking is increased self-regulation ,” says Gladstone.
Being able to self-regulate helps kids manage experiences that might otherwise overwhelm them. For example, take two girls who have to audition for a school play, both of whom are struggling with unusually difficult material.
A girl who is regularly told how talented she is and is used to being praised for her performances is likely to get frustrated and overwhelmed at the sheer thought of performing badly.
But a girl who is praised for her ability to work hard and persevere when she’s faced with a challenge can draw on her metacognitive skills to help her manage her nerves and help her figure out a way of rehearsing that works better for her.
Quieting negative self-talk
Fallout from a fixed mindset often takes the form of self-criticism. The negative feelings kids experience when they feel frustrated easily turn into negative self-talk. “If I’m so smart, why did I fail the test? I’m not smart. I’m useless.”
“When you place your value on being ‘smart,’ anything that makes you feel less than smart is devastating,” says Rosier. “A lot of kids develop a negative inner voice, and they develop it in place of metacognition.”
This negative voice is sneaky, she explains, often masquerading as a coach. “You can mistake self-criticism for motivation. What we want to do is get rid of the negative inner voice and replace it with metacognitive thinking that helps your child find new ways to manage her challenges instead of beating herself up about them.”
How to encourage metacognition
How do you help your child start becoming more meta?” Metacognitive questions, says Rosier, will help your child begin thinking in a more reflective way. Questions should be:
- Open-ended . Give your child some space to reflect on his thinking: Can you tell me more about why you think that?
- Non-blaming. It can be hard to stay open when kids are acting out, but asking them to think about their behavior can help them learn to manage difficult situations in a better way: Why do you think you got so upset when Dad changed the channel?
- Solution-focused . Encourage him to think about how he can use his understanding to change things in the future: How could you handle that differently next time?
- Process-oriented. Ask questions that help your child get a better idea of how his thought process works: How will you know when this drawing is finished?
“When you teach kids to think about their behavior differently , they begin to behave differently,” says Rosier. But she warns that it’s important not to expect instant results. Learning to think metacognitively is a process, and parents may have to accept that a lot of the work is happening behind the scenes.
“Of course we want to see progress, but our children — especially teenagers — don’t always share their thinking with us and that’s okay.”
Just asking the questions gets the metacognitive work going internally, even if it’s not visible to the parental eye, Rosier explains. The benefits are the same, she says, even if all you get is a grunt in return.
Learning to learn
Asking questions at home will help kids begin to use metacognitive strategies in their schoolwork, too. For many kids — especially those with learning differences — this can be harder than it sounds. It’s easy to get bogged down by poor study habits, procrastination, homework meltdowns, and test stress.
If your child is struggling to work through a long paper, ask questions that help him use his metacognitive skills to try a different approach.
- What do you think is making it hard for you to work on this paper right now?
- What are some strategies that have helped you do well on similar papers in the past?
- Can you use those insights to help you with the work you’re doing now?
Asking metacognitive questions will help him clarify his process, manage his anxiety, and find a better way to approach his paper, but the benefits don’t end when the assignment is done.
The more your child is able to understand his learning process the easier it will be for him to figure out what strategies and supports work best for him — knowledge that will help him succeed — both now and as he grows up.
Was this article helpful?
Explore popular topics, subscribe to our newsletters.
Get our latest tips, new articles, and expert advice direct to your inbox every week.
- Parenting Advice & Articles
- Clinical Care Programs
- School & Educator Programs
- Science, Data, & Research
- Resources in Spanish
- View all journals
- My Account Login
- Explore content
- About the journal
- Publish with us
- Sign up for alerts
- Review Article
- Open Access
- 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
- Human behaviour
- Interdisciplinary studies
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.
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
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.
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 .
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.
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.
Dunlosky, J. & Metcalfe, J. Metacognition (SAGE Publications, 2008).
Pintrich, P. R. The role of metacognitive knowledge in learning, teaching, and assessing. Theory Into Pract. 41 , 219–225 (2002).
Article Google Scholar
Zimmerman, B. J. Self-regulated learning and academic achievement: an overview. Educ. Psychol. 25 , 3–17 (1990).
Zimmerman, B. J. & Schunk, D. H. Self-Regulated Learning and Academic Achievement: Theoretical Perspectives (Routledge, 2001).
Baker, L. & Brown, A. L. Metacognitive Skills and Reading. In Handbook of Reading Research Vol. 1 (ed. Pearson, P. D.) 353–395 (Longman, 1984).
Mckeown, M. G. & Beck, I. L. The role of metacognition in understanding and supporting reading comprehension. In Handbook of Metacognition in Education (eds Hacker, D. J., Dunlosky, J. & Graesser, A. C.) 19–37 (Routledge, 2009).
Desoete, A., Roeyers, H. & Buysse, A. Metacognition and mathematical problem solving in grade 3. J. Learn. Disabil. 34 , 435–447 (2001).
Article CAS PubMed Google Scholar
Veenman, M., Kok, R. & Blöte, A. W. The relation between intellectual and metacognitive skills in early adolescence. Instructional Sci. 33 , 193–211 (2005).
Harris, K. R., Graham, S., Brindle, M. & Sandmel, K. Metacognition and children’s writing. In Handbook of metacognition in education 131–153 (Routledge, 2009).
Fleming, S. M. & Dolan, R. J. The neural basis of metacognitive ability. Philos. Trans. R. Soc. B 367 , 1338–1349 (2012).
Vaccaro, A. G. & Fleming, S. M. Thinking about thinking: a coordinate-based meta-analysis of neuroimaging studies of metacognitive judgements. Brain Neurosci. Adv. 2 , 10.1177%2F2398212818810591 (2018).
Ferrari, M. What can neuroscience bring to education? Educ. Philos. Theory 43 , 31–36 (2011).
Zadina, J. N. The emerging role of educational neuroscience in education reform. Psicol. Educ. 21 , 71–77 (2015).
Meulen, A., van der, Krabbendam, L. & Ruyter, Dde Educational neuroscience: its position, aims and expectations. Br. J. Educ. Stud. 63 , 229–243 (2015).
Varma, S., McCandliss, B. D. & Schwartz, D. L. Scientific and pragmatic challenges for bridging education and neuroscience. Educ. Res. 37 , 140–152 (2008).
van Atteveldt, N., van Kesteren, M. T. R., Braams, B. & Krabbendam, L. Neuroimaging of learning and development: improving ecological validity. Frontline Learn. Res. 6 , 186–203 (2018).
Article PubMed PubMed Central Google Scholar
Hruby, G. G. Three requirements for justifying an educational neuroscience. Br. J. Educ. Psychol. 82 , 1–23 (2012).
Article PubMed Google Scholar
Dignath, C., Buettner, G. & Langfeldt, H.-P. How can primary school students learn self-regulated learning strategies most effectively?: A meta-analysis on self-regulation training programmes. Educ. Res. Rev. 3 , 101–129 (2008).
Jacob, R. & Parkinson, J. The potential for school-based interventions that target executive function to improve academic achievement: a review. Rev. Educ. Res. 85 , 512–552 (2015).
Kassai, R., Futo, J., Demetrovics, Z. & Takacs, Z. K. A meta-analysis of the experimental evidence on the near- and far-transfer effects among children’s executive function skills. Psychol. Bull. 145 , 165–188 (2019).
Roebers, C. M. Executive function and metacognition: towards a unifying framework of cognitive self-regulation. Dev. Rev. 45 , 31–51 (2017).
Clements, D. H., Sarama, J. & Germeroth, C. Learning executive function and early mathematics: directions of causal relations. Early Child. Res. Q. 36 , 79–90 (2016).
Nelson, T. O. & Narens, L. Metamemory. In Perspectives on the development of memory and cognition (ed. R. V. Kail & J. W. Hag) 3–33 (Hillsdale, N.J.: Erlbaum, 1977).
Baird, J. R. Improving learning through enhanced metacognition: a classroom study. Eur. J. Sci. Educ. 8 , 263–282 (1986).
Flavell, J. H. & Wellman, H. M. Metamemory (1975).
Flavell, J. H. Metacognition and cognitive monitoring: a new area of cognitive–developmental inquiry. Am. Psychol. 34 , 906 (1979).
Livingston, J. A. Metacognition: An Overview. (2003).
Nelson, T. O. Metamemory: a theoretical framework and new findings. In Psychology of Learning and Motivation Vol. 26 (ed. Bower, G. H.) 125–173 (Academic Press, 1990).
Nelson, T. O. & Narens, L. Why investigate metacognition. In Metacognition: Knowing About Knowing (eds Metcalfe, J. & Shimamura, A. P.) 1–25 (MIT Press, 1994).
Shimamura, A. P. A Neurocognitive approach to metacognitive monitoring and control. In Handbook of Metamemory and Memory (eds Dunlosky, J. & Bjork, R. A.) (Routledge, 2014).
Dinsmore, D. L., Alexander, P. A. & Loughlin, S. M. Focusing the conceptual lens on metacognition, self-regulation, and self-regulated learning. Educ. Psychol. Rev. 20 , 391–409 (2008).
Borkowski, J. G., Chan, L. K. & Muthukrishna, N. A process-oriented model of metacognition: links between motivation and executive functioning. In (Gregory Schraw & James C. Impara) Issues in the Measurement of Metacognition 1–42 (Buros Institute of Mental Measurements, 2000).
Risko, E. F. & Gilbert, S. J. Cognitive offloading. Trends Cogn. Sci. 20 , 676–688 (2016).
Gilbert, S. J. et al. Optimal use of reminders: metacognition, effort, and cognitive offloading. J. Exp. Psychol. 149 , 501 (2020).
Boldt, A. & Gilbert, S. Distinct and overlapping neural correlates of metacognitive monitoring and metacognitive control. Preprint at bioRxiv https://psyarxiv.com/3dz9b/ (2020).
Fernandez-Duque, D., Baird, J. A. & Posner, M. I. Executive attention and metacognitive regulation. Conscious Cogn. 9 , 288–307 (2000).
Baker, L., Zeliger-Kandasamy, A. & DeWyngaert, L. U. Neuroimaging evidence of comprehension monitoring. Psihol. teme 23 , 167–187 (2014).
Schwartz, B. L. Sources of information in metamemory: Judgments of learning and feelings of knowing. Psychon. Bull. Rev. 1 , 357–375 (1994).
Nelson, T. O. Metamemory, psychology of. In International Encyclopedia of the Social & Behavioral Sciences (eds Smelser, N. J. & Baltes, P. B.) 9733–9738 (Pergamon, 2001).
Hart, J. T. Memory and the feeling-of-knowing experience. J. Educ. Psychol. 56 , 208 (1965).
Arbuckle, T. Y. & Cuddy, L. L. Discrimination of item strength at time of presentation. J. Exp. Psychol. 81 , 126 (1969).
Fechner, G. T. Elemente der Psychophysik (Breitkopf & Härtel, 1860).
Rouault, M., Seow, T., Gillan, C. M. & Fleming, S. M. Psychiatric symptom dimensions are associated with dissociable shifts in metacognition but not task performance. Biol. Psychiatry 84 , 443–451 (2018).
Fleming, S. M., Weil, R. S., Nagy, Z., Dolan, R. J. & Rees, G. Relating introspective accuracy to individual differences in brain structure. Science 329 , 1541–1543 (2010).
Article CAS PubMed PubMed Central Google Scholar
McCurdy, L. Y. et al. Anatomical coupling between distinct metacognitive systems for memory and visual perception. J. Neurosci. 33 , 1897–1906 (2013).
Fleming, S. M. & Lau, H. C. How to measure metacognition. Front. Hum. Neurosci. 8 https://doi.org/10.3389/fnhum.2014.00443 (2014).
Galvin, S. J., Podd, J. V., Drga, V. & Whitmore, J. Type 2 tasks in the theory of signal detectability: discrimination between correct and incorrect decisions. Psychon. Bull. Rev. 10 , 843–876 (2003).
Metcalfe, J. & Schwartz, B. L. The ghost in the machine: self-reflective consciousness and the neuroscience of metacognition. In (eds Dunlosky, J. & Tauber, S. K.) Oxford Handbook of Metamemory 407–424 (Oxford University Press, 2016).
Maniscalco, B. & Lau, H. A signal detection theoretic approach for estimating metacognitive sensitivity from confidence ratings. Conscious Cognition 21 , 422–430 (2012).
Rouault, M., McWilliams, A., Allen, M. G. & Fleming, S. M. Human metacognition across domains: insights from individual differences and neuroimaging. Personal. Neurosci. 1 https://doi.org/10.1017/pen.2018.16 (2018).
Rounis, E., Maniscalco, B., Rothwell, J. C., Passingham, R. E. & Lau, H. Theta-burst transcranial magnetic stimulation to the prefrontal cortex impairs metacognitive visual awareness. Cogn. Neurosci. 1 , 165–175 (2010).
Ye, Q., Zou, F., Lau, H., Hu, Y. & Kwok, S. C. Causal evidence for mnemonic metacognition in human precuneus. J. Neurosci. 38 , 6379–6387 (2018).
Fleming, S. M., Huijgen, J. & Dolan, R. J. Prefrontal contributions to metacognition in perceptual decision making. J. Neurosci. 32 , 6117–6125 (2012).
Morales, J., Lau, H. & Fleming, S. M. Domain-general and domain-specific patterns of activity supporting metacognition in human prefrontal cortex. J. Neurosci. 38 , 3534–3546 (2018).
Baird, B., Smallwood, J., Gorgolewski, K. J. & Margulies, D. S. Medial and lateral networks in anterior prefrontal cortex support metacognitive ability for memory and perception. J. Neurosci. 33 , 16657–16665 (2013).
Fleming, S. M., Ryu, J., Golfinos, J. G. & Blackmon, K. E. Domain-specific impairment in metacognitive accuracy following anterior prefrontal lesions. Brain 137 , 2811–2822 (2014).
Baldo, J. V., Shimamura, A. P., Delis, D. C., Kramer, J. & Kaplan, E. Verbal and design fluency in patients with frontal lobe lesions. J. Int. Neuropsychol. Soc. 7 , 586–596 (2001).
Froböse, M. I. et al. Catecholaminergic modulation of the avoidance of cognitive control. J. Exp. Psychol. Gen. 147 , 1763 (2018).
Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S. & Cohen, J. D. Conflict monitoring and cognitive control. Psychol. Rev. 108 , 624 (2001).
Kerns, J. G. et al. Anterior cingulate conflict monitoring and adjustments in control. Science 303 , 1023–1026 (2004).
Yeung, N. Conflict monitoring and cognitive control. In The Oxford Handbook of Cognitive Neuroscience: The Cutting Edges Vol. 2 (eds Ochsner, K. N. & Kosslyn, S.) 275–299 (Oxford University Press, 2014).
Botvinick, M. M. Conflict monitoring and decision making: reconciling two perspectives on anterior cingulate function. Cogn. Affect. Behav. Neurosci. 7 , 356–366 (2007).
Fleming, S. M., van der Putten, E. J. & Daw, N. D. Neural mediators of changes of mind about perceptual decisions. Nat. Neurosci. 21 , 617–624 (2018).
Ridderinkhof, K. R., Ullsperger, M., Crone, E. A. & Nieuwenhuis, S. The role of the medial frontal cortex in cognitive control. Science 306 , 443–447 (2004).
Koriat, A. The feeling of knowing: some metatheoretical implications for consciousness and control. Conscious Cogn. 9 , 149–171 (2000).
Thompson, V. A., Evans, J. & Frankish, K. Dual process theories: a metacognitive perspective. Ariel 137 , 51–43 (2009).
Arango-Muñoz, S. Two levels of metacognition. Philosophia 39 , 71–82 (2011).
Shea, N. et al. Supra-personal cognitive control and metacognition. Trends Cogn. Sci. 18 , 186–193 (2014).
Nieuwenhuis, S., Ridderinkhof, K. R., Blom, J., Band, G. P. & Kok, A. Error-related brain potentials are differentially related to awareness of response errors: evidence from an antisaccade task. Psychophysiology 38 , 752–760 (2001).
Overbeek, T. J., Nieuwenhuis, S. & Ridderinkhof, K. R. Dissociable components of error processing: on the functional significance of the Pe vis-à-vis the ERN/Ne. J. Psychophysiol. 19 , 319–329 (2005).
McGuire, J. T. & Botvinick, M. M. Prefrontal cortex, cognitive control, and the registration of decision costs. Proc. Natl Acad. Sci. USA 107 , 7922–7926 (2010).
Hester, R., Foxe, J. J., Molholm, S., Shpaner, M. & Garavan, H. Neural mechanisms involved in error processing: a comparison of errors made with and without awareness. Neuroimage 27 , 602–608 (2005).
Melby-Lervåg, M. & Hulme, C. Is working memory training effective? A meta-analytic review. Dev. Psychol. 49 , 270 (2013).
Soveri, A., Antfolk, J., Karlsson, L., Salo, B. & Laine, M. Working memory training revisited: a multi-level meta-analysis of n-back training studies. Psychon. Bull. Rev. 24 , 1077–1096 (2017).
Schwaighofer, M., Fischer, F. & Bühner, M. Does working memory training transfer? A meta-analysis including training conditions as moderators. Educ. Psychol. 50 , 138–166 (2015).
Karbach, J. & Verhaeghen, P. Making working memory work: a meta-analysis of executive-control and working memory training in older adults. Psychol. Sci. 25 , 2027–2037 (2014).
Patel, R., Spreng, R. N. & Turner, G. R. Functional brain changes following cognitive and motor skills training: a quantitative meta-analysis. Neurorehabil Neural Repair 27 , 187–199 (2013).
Carpenter, J. et al. Domain-general enhancements of metacognitive ability through adaptive training. J. Exp. Psychol. 148 , 51–64 (2019).
Baird, B., Mrazek, M. D., Phillips, D. T. & Schooler, J. W. Domain-specific enhancement of metacognitive ability following meditation training. J. Exp. Psychol. 143 , 1972 (2014).
Winne, P. H. & Perry, N. E. Measuring self-regulated learning. In Handbook of Self-Regulation (eds Boekaerts, M., Pintrich, P. R. & Zeidner, M.) Ch. 16, 531–566 (Academic Press, 2000).
Zimmerman, B. J. & Martinez-Pons, M. Development of a structured interview for assessing student use of self-regulated learning strategies. Am. Educ. Res. J. 23 , 614–628 (1986).
Park, C. Engaging students in the learning process: the learning journal. J. Geogr. High. Educ. 27 , 183–199 (2003).
Article CAS Google Scholar
Harrison, G. M. & Vallin, L. M. Evaluating the metacognitive awareness inventory using empirical factor-structure evidence. Metacogn. Learn. 13 , 15–38 (2018).
Pintrich, P. R., Smith, D. A. F., Garcia, T. & Mckeachie, W. J. Reliability and predictive validity of the motivated strategies for learning questionnaire (MSLQ). Educ. Psychol. Meas. 53 , 801–813 (1993).
Prevatt, F., Petscher, Y., Proctor, B. E., Hurst, A. & Adams, K. The revised Learning and Study Strategies Inventory: an evaluation of competing models. Educ. Psychol. Meas. 66 , 448–458 (2006).
Baggetta, P. & Alexander, P. A. Conceptualization and operationalization of executive function. Mind Brain Educ. 10 , 10–33 (2016).
Gioia, G. A., Isquith, P. K., Guy, S. C. & Kenworthy, L. Test review behavior rating inventory of executive function. Child Neuropsychol. 6 , 235–238 (2000).
Ohtani, K. & Hisasaka, T. Beyond intelligence: a meta-analytic review of the relationship among metacognition, intelligence, and academic performance. Metacogn. Learn. 13 , 179–212 (2018).
Dianovsky, M. T. & Wink, D. J. Student learning through journal writing in a general education chemistry course for pre-elementary education majors. Sci. Educ. 96 , 543–565 (2012).
Veenman, M. V. J., Van Hout-Wolters, B. H. A. M. & Afflerbach, P. Metacognition and learning: conceptual and methodological considerations. Metacogn Learn. 1 , 3–14 (2006).
Weil, L. G. et al. The development of metacognitive ability in adolescence. Conscious Cogn. 22 , 264–271 (2013).
Veenman, M. & Spaans, M. A. Relation between intellectual and metacognitive skills: Age and task differences. Learn. Individ. Differ. 15 , 159–176 (2005).
Verbert, K. et al. Learning dashboards: an overview and future research opportunities. Personal. Ubiquitous Comput. 18 , 1499–1514 (2014).
Dignath, C. & Büttner, G. Components of fostering self-regulated learning among students. A meta-analysis on intervention studies at primary and secondary school level. Metacogn. Learn. 3 , 231–264 (2008).
Hattie, J., Biggs, J. & Purdie, N. Effects of learning skills interventions on student learning: a meta-analysis. Rev. Educ. Res. 66 , 99–136 (1996).
Zohar, A. & Barzilai, S. A review of research on metacognition in science education: current and future directions. Stud. Sci. Educ. 49 , 121–169 (2013).
Berthold, K., Nückles, M. & Renkl, A. Do learning protocols support learning strategies and outcomes? The role of cognitive and metacognitive prompts. Learn. Instr. 17 , 564–577 (2007).
Bannert, M. & Mengelkamp, C. Scaffolding hypermedia learning through metacognitive prompts. In International Handbook of Metacognition and Learning Technologies Vol. 28 (eds Azevedo, R. & Aleven, V.) 171–186 (Springer New York, 2013).
Bannert, M., Sonnenberg, C., Mengelkamp, C. & Pieger, E. Short- and long-term effects of students’ self-directed metacognitive prompts on navigation behavior and learning performance. Comput. Hum. Behav. 52 , 293–306 (2015).
McCrindle, A. R. & Christensen, C. A. The impact of learning journals on metacognitive and cognitive processes and learning performance. Learn. Instr. 5 , 167–185 (1995).
Connor-Greene, P. A. Making connections: evaluating the effectiveness of journal writing in enhancing student learning. Teach. Psychol. 27 , 44–46 (2000).
Wong, B. Y. L., Kuperis, S., Jamieson, D., Keller, L. & Cull-Hewitt, R. Effects of guided journal writing on students’ story understanding. J. Educ. Res. 95 , 179–191 (2002).
Nückles, M., Schwonke, R., Berthold, K. & Renkl, A. The use of public learning diaries in blended learning. J. Educ. Media 29 , 49–66 (2004).
Cantrell, R. J., Fusaro, J. A. & Dougherty, E. A. Exploring the effectiveness of journal writing on learning social studies: a comparative study. Read. Psychol. 21 , 1–11 (2000).
Blair, C. Executive function and early childhood education. Curr. Opin. Behav. Sci. 10 , 102–107 (2016).
Clements, D. H., Sarama, J., Unlu, F. & Layzer, C. The Efficacy of an Intervention Synthesizing Scaffolding Designed to Promote Self-Regulation with an Early Mathematics Curriculum: Effects on Executive Function (Society for Research on Educational Effectiveness, 2012).
Newman, S. D., Carpenter, P. A., Varma, S. & Just, M. A. Frontal and parietal participation in problem solving in the Tower of London: fMRI and computational modeling of planning and high-level perception. Neuropsychologia 41 , 1668–1682 (2003).
Sedlmeier, P. et al. The psychological effects of meditation: a meta-analysis. Psychol. Bull. 138 , 1139 (2012).
Bellon, E., Fias, W., Ansari, D. & Smedt, B. D. The neural basis of metacognitive monitoring during arithmetic in the developing brain. Hum. Brain Mapp. 41 , 4562–4573 (2020).
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).
Authors and affiliations.
Informatics Institute, University of Amsterdam, Amsterdam, the Netherlands
Damien S. Fleur & Bert Bredeweg
Departement of Psychology, University of Amsterdam, Amsterdam, the Netherlands
Damien S. Fleur & Wouter van den Bos
Faculty of Education, Amsterdam University of Applied Sciences, Amsterdam, the Netherlands
Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany
Wouter van den Bos
You can also search for this author in PubMed Google Scholar
D.S.F., B.B. and W.v.d.B. conceived the main conceptual idea of this review article. D.S.F. wrote the manuscript with inputs from and under the supervision of B.B. and W.v.d.B.
Correspondence to Damien S. Fleur .
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary materials, rights and permissions.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ .
Reprints and Permissions
About this article
Cite this article.
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
Received : 06 October 2020
Accepted : 09 April 2021
Published : 08 June 2021
DOI : https://doi.org/10.1038/s41539-021-00089-5
Share this article
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.
Provided by the Springer Nature SharedIt content-sharing initiative
This article is cited by
Predictive validity of performance-based metacognitive testing is superior to self-report: evidence from undergraduate freshman students.
- Marcio Alexander Castillo-Diaz
- Cristiano Mauro Assis Gomes
Trends in Psychology (2023)
The many facets of metacognition: comparing multiple measures of metacognition in healthy individuals
- Anneke Terneusen
- Conny Quaedflieg
- Ieke Winkens
Metacognition and Learning (2023)
Normative data and standardization of an international protocol for the evaluation of metacognition in Spanish-speaking university students: A cross-cultural analysis
- Antonio P. Gutierrez de Blume
- Diana Marcela Montoya Londoño
- Jesus Rivera-Sanchez
- Explore articles by subject
- Guide to authors
- Editorial policies
Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.
Home › Stories › Why Reflect? Effective Learning through Metacognition and Self-Regulation
Why Reflect? Effective Learning through Metacognition and Self-Regulation
Teaching metacognition and self-regulation through structured reflection can help students become better learners as they navigate the crucial weeks leading up to the end of the semester.
Much has been said about cultivating a growth mindset , particularly in times of stress or anxiety, but this paradigm really goes hand in hand with metacognition and self-regulation as pedagogical practices that can help students change the way they learn. In educational development, metacognition refers to the practice of intentionally focusing attention on the act of learning and self-regulation is defined as the ability to control one’s body and self, to manage one’s emotions, and to maintain focus and attention on the activities at hand. Together, they are modes of leveraging student motivation. A student who can effectively self-monitor, evaluate their progress, and change behaviors to achieve a desired outcome is more likely to be resilient and successful in your course.
However, it is important to remember that a growth mindset must be cultivated and student motivation may ebb and flow throughout the semester . We can help students stay motivated and become better learners by emphasizing metacognition.
Developing metacognition can increase student motivation and create a sense of belonging in the classroom community. If we explicitly teach metacognition through structured reflection, we can increase the effectiveness of learning activities and encourage students to incorporate feedback and grades from midterms in order to harness intrinsic motivation. This may also help disrupt harmful study behaviors (like cramming) and replace them with more effective and distributed practices.
Self-evaluation after exams and large projects promotes students’ critical thinking about how they approached a task, what worked and what didn’t and why, how they might approach the task differently in the future, and how this particular task fits into the larger course goals. Research on student self-assessment suggests that self-assessment is most beneficial, in terms of both achievement and self-regulated learning, when it is used formatively.
Exam reflections and narrative self-evaluations are two strategies that may help students develop the skills of metacognition and self regulation. These are also a great way to provide low-stakes grades and promote effective learning strategies. Remember that it is important to design these activities with transparency. Students should know why they are being asked to do reflection activities, they should be taught how to use the activities, and they should be prompted to set goals and make concrete plans to reach those goals.
All too often when students receive the graded exam, they focus only on the score. Guided reflections can help them to make sense of the grade, plan, monitor and evaluate their progress, and adjust learning strategies–make sure to share these benefits with students.
When implementing exam reflections, consider providing a guided reflection sheet that asks students to:
- Identify areas of individual strengths and areas for improvement
- Reflect on the adequacy of their preparation time their study strategies
- Characterize the nature of their errors and look for patterns
- Set goals for implementation of feedback
- Name at least one way the instructor can provide support to reach these goals
This kind of reflection allows students to make personal connections between learning, course goals, and the wider context of their field of study. The purpose of these reflections is to improve learning through goal setting, self-regulation, making organic connections between experiences, identifying interests, and planning.
When implementing narrative evaluations/reflections remember to share the purpose of the assignment and give specific instructions. For example:
- Contextualize your reflection: What are your learning goals? What are the objectives of the course? How do these goals fit in with the concepts taught in the course so far?
- Provide important information: What do you think you have done well so far? Can you identify a particular area/concept of understanding that you would like to improve?
- Analytical reflection: What did you learn in this assignment/unit? How do you contextualize this within the course and/or your field of study?
- Lessons from reflection: How did this assignment/unit fit with the goals and concepts of the course? What are your lessons for the future? How will you achieve your goals for the course? Name at least one way the instructor can provide support to reach these goals.
Self-reflection is not reporting what a student has done; rather, we are helping them to make meaning of their learning. Even if a student is a reflective, conscientious learner, everyone needs to learn how to effectively use that reflection. These exercises can help students to make sense of the course in the larger context of their educational journey.
Other sample self-reflection activities:
- Exam Wrappers
- Create a quiz based on Bloom’s taxonomy
- Illustrate learning with mind maps, concept maps, or other visuals and explain it in writing or orally to the instructor
Resources What to Do After the Test – Notre Dame Learning | The Kaneb Center Exam Review Self-Reflection – The Learning Center University of North Carolina at Chapel Hill Student Self-Evaluations – Center for Teaching and Learning Hampshire College Teaching Tips – 2018-2019 Teaching Issues Writing Consortium How to Write a Reflection Paper – Trent University Kaplan, Silver, LaVague-Manty, & Meizlish – Using reflection and metacognition to improve student learning: Across the disciplines, across the academy (2013) McGuire & McGuire – Teach Students How to Learn: Strategies You Can Incorporate Into Any Course to Improve Student Metacognition, Study Skills, and Motivation (2015)
Send a Message
Friend's Email Address
Your Email Address
- Skip to Nav
- Skip to Main
- Skip to Footer
The Role of Metacognition in Learning and Achievement
Failed to save article.
Please try again
- Facebook Share-FB
- Twitter Share-Twitter
- Email Share-Email
- Copy Link Copy Link
Excerpted from " Four-Dimensional Education: The Competencies Learners Need to Succeed ," by Charles Fadel, Bernie Trilling and Maya Bialik. The following is from the section, "Metacognition—Reflecting on Learning Goals, Strategies, and Results."
Metacognition, simply put, is the process of thinking about thinking . It is important in every aspect of school and life, since it involves self-reflection on one’s current position, future goals, potential actions and strategies, and results. At its core, it is a basic survival strategy, and has been shown to be present even in rats.
Perhaps the most important reason for developing metacognition is that it can improve the application of knowledge, skills, and character qualities in realms beyond the immediate context in which they were learned. This can result in the transfer of competencies across disciplines—important for students preparing for real-life situations where clear-cut divisions of disciplines fall away and one must select competencies from the entire gamut of their experience to effectively apply them to the challenges at hand. Even within academic settings, it is valuable—and often necessary—to apply principles and methods across disciplinary lines.
Transfer can also be necessary within a discipline, such as when a particular idea or skill was learned with one example, but students must know how to apply it to another task to complete their homework or exams, or to a different context. Transfer is the ultimate goal of all education, as students are expected to internalize what they learn in school and apply it to life.
To illustrate the value of metacognition and how it actually plays a role in learning, we can consider an example from mathematics, where it has been shown that metacognition plays a central role in learning and achievement. Specifically, when novice students were compared to seasoned mathematicians, the students selected a seemingly useful strategy and continued to apply it without checking to see if the strategy of choice was actually working well. Thus, a significant amount of time was wasted in fruitless pursuits. The more experienced mathematicians on the other hand, exercised metacognition, monitoring their approach all along the way to see if it was actually leading to a solution or merely to a dead end. Being aware of how one is engaging with the process of learning influences how the student interprets the task at hand, and what strategies are selected and employed in service of achieving learning goals. It can help optimize the problem-solving experience at a very high level, and is thus applicable across a large range of contexts. These metacognitive strategies are powerful tools for any discipline, inter-discipline or for learning in general.
It is important to note that since metacognition involves higher-level thinking overseeing lower-level thoughts, there is actually a range of mental processes that fall under its definition. Effects of metacognitive training vary based on what kind of lower-level thoughts are being overseen, and how they are being overseen. Research has identified three levels of reporting on metacognitive processes:
1. Verbalization of knowledge that is already in a verbal state (such as recalling what happened in a story).
2. Verbalization of nonverbal knowledge (such as recalling how one solved a Rubik’s Cube).
3. Verbalization of explanations of verbal or nonverbal knowledge (such as explaining how one makes use of the rhetorical structures of a story as one reads).
Only this third level of metacognitive process has been linked to improved results in problem solving.
Metacognition can be developed in students in the context of their current goals and can enhance their learning of competencies as well as transfer of learning, no matter their starting achievement level. In fact, it may be most useful for lower-achieving students, as the higher-achieving students are already employing strategies that have proven successful for them. For learning disabled and low - achieving students, metacognitive training has been shown to improve behavior more effectively than traditional attention-control training.
Students who have higher levels of self-efficacy (more confidence in their ability to achieve their goals) are more likely to engage in metacognition and, in turn, are more likely to perform at higher levels. This strongly indicates a positive feedback loop for high-achieving students—they are more successful by using metacognitive strategies, which increases their confidence and in turn leads them to continue to increase their performance. Metacognition is an integral part of this virtuous learning cycle, and one that is amenable to further improvement through instruction.
Charles Fadel is founder of the Center for Curriculum Redesign, Bernie Trilling is founder of 21st Century Learning Advisors and Maya Bialik is researcher at CCR.
Want to stay in touch?
Subscribe to receive weekly updates of MindShift stories every Sunday. You’ll also receive a carefully curated list of content from teacher-trusted sources.
Thanks for signing up for the newsletter.
Your browser is not supported
Sorry but it looks as if your browser is out of date. To get the best experience using our site we recommend that you upgrade or switch browsers.
Find a solution
- Skip to main content
- Skip to navigation
- Back to parent navigation item
- Sustainability in chemistry
- Simple rules
- Teacher well-being hub
- Women in chemistry
- Global science
- Escape room activities
- Decolonising chemistry teaching
- Teaching science skills
- Post-lockdown teaching support
- Get the print issue
- RSC Education
- More from navigation items
How thinking about thinking improves problem solving
- No comments
Use metacognition, thinking about thinking, to help your students develop their problem-solving skills
Source: © Claudia Flandoli
Metacognition, thinking about thinking, helps learners to recognise how they solve problems. Doing it provides the opportunity to develop their problem-solving techniques, rather than learning the solution to a specific problem.
And it’s simple to try in class. Arrange students into groups and give each student a specific role within that group; I use talk trios. To make the most of any of the talk activities here and in the EEF Improving secondary science guidance it’s important to model and scaffold both listening and speaking; download the resource below and use it as a prompt or checklist for students and yourself to develop your classroom practice. Next, make the process visible. Use the metacognitive cycle so everyone can locate where they are in the process and where they are going.
There are five steps to the cycle:
7 simple rules to boost science teaching
Click to expand and explore the rules
Build on the ideas that pupils bring to lessons
- Understand the preconceptions that pupils bring to science lessons
- Develop pupils’ thinking through cognitive conflict and discussion
- Allow enough time to challenge misconceptions and change thinking
Help pupils direct their own learning
- Explicitly teach pupils how to plan, monitor, and evaluate their learning
- Model your own thinking to help pupils develop their metacognitive and cognitive knowledge
- Promote metacognitive talk and dialogue in the classroom
Use models to support understanding
- Use models to help pupils develop a deeper understanding of scientific concepts
- Select the models you use with care
- Explicitly teach pupils about models and encourage pupils to critique them
Support pupils to retain and retrieve knowledge
- Pay attention to cognitive load—structure tasks to limit the amount of new information pupils need to process
- Revisit knowledge after a gap to help pupils retain it in their long-term memory
- Provide opportunities for pupils to retrieve the knowledge that they have previously learnt
- Encourage pupils to elaborate on what they have learnt
Use practical work purposefully and as part of a learning sequence
- Know the purpose of each practical activity
- Sequence practical activities with other learning
- Use practical work to develop scientific reasoning
- Use a variety of approaches to practical science
Develop scientific vocabulary and support pupils to read and write about science
- Carefully select the vocabulary to teach and focus on the most tricky words
- Show the links between words and their composite parts
- Use activities to engage pupils with reading scientific text and help them to comprehend it
- Support pupils to develop their scientific writing skills
Use structured feedback to move on pupils’ thinking
- Find out what your pupils understand
- Think about what you’re providing feedback on
- Provide feedback as comments rather than marks
- Make sure pupils can respond to your feedback
- Assess the demands of the task, visualise both what needs to be done and what it will look like when complete.
- Assess your own skills base recognising: strengths, weaknesses and what must be mastered to move forward, an action plan.
- Spend time planning the strategies required to put the action plan into practice.
- Put the plan into action by applying the planned strategies. The real skill at this stage is to continually monitor progress and make small adjustments to the strategy accordingly.
- Once the actions are completed, allow a period of reflection. This can be as simple as asking what went well or what could be improved. From here, you can continue the cycle.
In your class
Download a prompt sheet for using talk trios as MS Powerpoint or pdf .
Using the metacognitive cycle to answer a six-mark question
Talk trios can work together using the metacognitive cycle to answer this question: ‘Describe how you could produce pure dry crystals of magnesium chloride’.
- Students recognise this is a practical procedure question. They take turns to express their thoughts and then the similarities and differences in their thinking.
- Next the students assess their own skills base. You can scaffold this by asking questions or encouraging peer questioning. For example: what do they know already, draw attention to a similar experiment that they have done. Ask them what don’t they know, what’s different about this question to the practical that they did. Question what they want to master and what additional knowledge they need to answer this question. And finally, ask what they will do to improve, and how the method used in class can be modified to answer this question.
- Encourage your students to check for logical sequencing of events – has unreacted magnesium been filtered off before crystallising the salt? Initially students will try and skip the planning phase. Ask the talk trios to compare plans, identify points they may have missed and work together to create a ‘best’ plan.
- Individually, or as talk trios, ask the students to write out an answer to the question. Remind them they have approximately one minute per mark in an exam. The real skill at this stage is to continually think about what they have planned and make small adjustments where necessary. If, for example, they planned to heat the hydrochloric acid they may now realise this is unnecessary as reaction is vigorous at room temperature.
- Reflection; ask the students to read their answer then mark it using an answer rubric and encourage the talk trios to discuss what when well and what could be improved. Ask the students to compare their ‘best’ plan to the marking rubric – what information was unnecessary or missed?
The metacognitive cycle and scientific method are immediately comparable. Draw attention to the similarities in these processes, making your students aware of how much of the process is familiar.
Stress the importance of time, emphasising how much time is needed to plan, to implement the plan, to reflect upon the outcome and how much time is available.
With practice, these processes will become internalised as a cognitive habit.
This article is part of the series 7 simple rules for science teaching , developed in response to the EEF’s Improving secondary science guidance . It supports rule 2c, Promote metacognitive talk and dialogue in the classroom.
Talk trio prompts
More from Naomi Hennah
Help your students understand ethics in science
Toxic socks: nanotechnology, ethics and society | 11–14 years
Make the most of practical work
- Communication skills
- Higher-order thinking and metacognition
Everything you need to teach energetics at 14–16
2023-08-01T07:00:00Z By David Paterson
Use these ideas to help students understand the world of energetics, enthalpy and equilibrium
Nanoparticles in sunscreen challenge | Chemistry for All project | 14–16 years
Make your own sunscreen and determine its SPF using UV light transmission
Analysing the chemistry of food | Chemistry for All project | 14–16 years
Analyse food and drink samples using TLC, titration and visible absorption spectroscopy with this engaging project
No comments yet
Only registered users can comment on this article., more from feature.
Successful strategies for sequencing knowledge
2023-09-11T09:00:00Z By Amanda Clegg , Karen Collins
Discover how to effectively develop your students’ knowledge and skills by sequencing practical activities
2023-08-21T07:05:00Z By Nina Notman
From polymers to inorganic compounds, discover the remarkable science behind fighting fires
Stride into your first classroom with confidence
2023-08-16T06:53:00Z By Emma Owens
Start your science teaching career with six simple, but effective tips from a recent early career teacher
- Print issue
- Email alerts
Site powered by Webvision Cloud
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.
- Find Counselling
- Find a Support Group
- Find Online Therapy
- United Kingdom
- Bipolar Disorder
- Chronic Pain
- Eating Disorders
- Passive Aggression
- Goal Setting
- Positive Psychology
- Stopping Smoking
- Low Sexual Desire
- Child Development
- Therapy Center NEW
- Diagnosis Dictionary
- Types of Therapy
As the lines between real and fake blur, Americans increasingly chase the idea of authenticity. The first step may be to consider self-knowledge, truthfulness, and other building blocks on the road to personal growth.
- Coronavirus Disease 2019
- Affective Forecasting
Health, Brain and Neuroscience
Mental, physical health and neuroscience, metacognition: thinking about thinking improves learning.
Metacognition. Have you ever analyzed the strategies you use for learning new information? Do you read the information out loud several times? Or do you explain it to someone else? Maybe you’re one of those who writes summaries, makes schemes or mind maps? What about making drawings or creating songs?
Maybe when you were young -or even as an adult- you tried different learning techniques. What do you think about them? Were/are they useful? Were/are you able to remember the information after a long period of time? Or did/do you forget most of it after the test you were studying for? If you answered ‘yes’ to the last question, maybe you weren’t taught how to learn the best way. Nowadays, there are many studies showing the benefits and effectiveness of metacognition in education. Have you heard about this term?
Table of Contents
What is Metacognition?
“ Cognition ” is the amazing quality of the human mind to capture and interpret the reality that surrounds us. Cognitive processes allow us to perceive a sunset, concentrate to read a good novel or remember unforgettable moments of our childhood. So how does this relate to metacognition?
Psychology has a section dedicated to the study of the essence of the mind from a scientific point of view. This is known as metacognition.
Thanks to advances in Cognitive Psychology we have learned that the mind is able to self-regulate through its meta-cognitive activity. Thanks to Neuroscience we know that the metacognitive functions are located in the most modern part of the brain: the cerebral cortex. Is metacognition an additional mental process?
Therefore, is metacognition an additional mental process? Let’s say that metacognition “oversees” the rest of mental processes and knowledge, and allows us to have information about ourselves. Traditionally it is used in education to help to learn in the classroom, strategies, memory, reading, writing, exams, self-instruction, attention and concentration problems , self-efficacy, emotional intelligence , social communication skills , etc. Lately, it has also revealed itself as a process to be taken into account in the study of clinical problems such as depression, obsessions, ADHD or schizophrenia.
Imagine that you are speaking to a friend or a teacher, and during the conversation, thoughts like “I do not understand”, “I am not interested” or “perhaps it’s important … I should pay attention”. That mental discourse, that is metacognition in action.
J. Flavell defined metacognition as “the knowledge of oneself about the products themselves (knowledge) and cognitive processes, or everything related to them”.
Metacognition: Thinking About Thinking?
Even though it’s impossible to remember all the information you studied at school, research has found effective ways and techniques for achieving meaningful learning . In this case, thinking about thinking, or using metacognitive strategies or metacognitive processes, is helpful. This concept has also been referred to as “meta-reasoning” because this process involves goal-setting, updating , monitoring, self-regulation and controlling reasoning, problem-solving and decision-making. In other words, thinking about how you’re learning, its effectiveness and what’s the best strategy to use next.
Furthermore, metacognition involves two important dimensions: metacognitive knowledge or reflection and metacognitive self-regulation.
- Cognitive skills – thinking about which abilities are your strengths and weaknesses: “I struggle with reading comprehension”
- Knowledge of specific tasks- “this book I’m reading is complex”
- Use of strategies- not only which ones do you use, but also when to use one or another: “I’ll try chunking the information and try to explain it to myself with other words”
- Plan approaches to plan – by analyzing the problem, selecting a strategy, organizing your thought and anticipating outcomes
- Monitor activities during learning – examining, revising and evaluating your strategies
- Revise outcome – assessing the results according to effectivity and efficiency criteria
Without a doubt, having high metacognitive skills enables you to: identify your flaws on the way you’re thinking; adequate the thinking process you’re using; and supervise the effort made on the task, as well as evaluate the results. Certainly, with this ability, you are able to direct your own learning!
Metacognition and Childhood Cognitive Development
The first time metacognition in a child was used was through the Theory of Mind (ToM). It appears around the 4-5 years. At this age, children realize that different points of view may exist, and different ways of interpreting reality. It is curious to see how the knowledge we have about our own mind begins to unfold when we “realize” the mind of others.
Metacognition will continue its development from infancy until adolescence. However, during adulthood, if it is practiced, you can increase the number of learning strategies and increase effectiveness leading to greater meta-knowledge.
“Not all adults become self-regulating experts. Although maturation plays an important role, this will depend on the educational experiences of each person. “
A metacognitive development is distinguished in three levels : interpersonal, personal (metacognitive control and executive functions) and impersonal (abstract metacognition) . We will focus on these last two:
- 5-6 years old: Over-estimation. There appears a slight consciousness, which coexists with imprecise ideas about the infallibility of memory. Young children use literal memory, are more impulsive, and have difficulty evaluating their own performance.
- 8-9 years old: Realism. They combine effort with capacity and efficiency. They have a knowledge of the functioning of mind and memory (recognition, memory, associations, clues). The first learning strategies are acquired, although initially imprecise, which will be improved during and thanks to the schooling stage.
- + 12 years: Trust. Their assessments are more dependent on external judgments, especially in their peer group. During the adolescence conditional knowledge is applied it refers to how and when to apply different strategies. Increasing cognitive resources (processing speed, capacity, automation) during this stage improves meta cognitive functions.
- Adults: Integration. Ability to select strategies among multiple options, ability to consider different variables (the type of task, the objectives, etc).
Metacognition “Getting Meta”: Learning How To Learn
This expression refers to the employment of metacognitive strategies to acquire, retain and transfer new information. Applying what you’ve learned to new and different situations is what allows you to really learn the information.
Although it might sound like an easy thing to do, it takes awareness to develop this skill, as well as effort. In other words, being reflective and mindful of your own learning process, helps you obtain abilities to be a great problem-solver.
Metacognition in the Classroom
What do I already know? What don’t I know? What do I need to know? How will I find out what I need to know? How am I doing in the process? – Teachers are guides, so they help students reflect on what they know and what they want to know when starting a new topic in class. During the lesson, the teacher encourages self-assessment so that they can direct their learning process. When they finish, they might as well ask themselves what they know now that the lesson has finished. Fortunately, this technique enhances their independence as learners, because they are actively looking to answer these questions. Also, with the information, material, and peer-support that the teacher provides, they can start monitoring their performance.
Often, identifying your own knowledge can help you assist others – that’s why peer support plays a key role in metacognition. By recognizing your strengths and weaknesses, you can offer help or be assisted by others. Consequently, education gets active, dynamic and empathetic.
Now, take a look at the next video to fully understand, in a simple way, the importance of metacognition on teaching techniques!
Metacognition: Metacognitive Strategies
Moreover, there are strategies that help the students analyze the material they’re studying; reflect on what they’re learning and direct their own work.
- Predicting outcomes- It helps the learner realize which information is needed to solve a problem and compare the initial understanding to the final result.
- Evaluating work- Identifying strengths and weaknesses in the student’s thinking process as well as in their work is key.
- Teacher questioning- The teacher asks questions such as “what are you doing now? “why are you doing it?” and “how does it help you?”
- Self-assessing/ self-appraisals – Students must reflect on their performance to determine: what they’ve learned, how well they’ve learned it and the skills they needed to develop to solve the task.
- Self-questioning- Students question their own knowledge while learning and working, in order to direct their thinking and determine the help they may need.
- Selecting strategies- Learners choose which strategies to use in a certain situation according to their learning styles, strengths and the type of problem they’re facing.
- Using directed or selective thinking – A specific line of thinking is used by the student.
- Using discourse – Discussing ideas with teachers and peers helps them ask questions, recognize gaps in their own knowledge, as well as learn from others.
- Critiquing- Giving and receiving constructive feedback helps learners to verbalize their thinking and to improve their performance and thinking process.
- Revising- After receiving feedback students update their thinking and check the learning strategies they’ve used.
- Boosting your cognitive skills – putting into practice your cognitive processes can help you keep these strategies more accessible and easy to do. CogniFit brain training program gives you the opportunity to keep track of your improvement and train cognitive abilities through fun brain games.
Metacognitive Studying Techniques
Another important aspect involves teaching studying strategies. Getting the students to ask themselves “how do I study best?”, “which learning tools help me retain information better?” (Read also how to tell if a child has problems studying ). This way, learners can assess their own abilities in different situations and with different types of information. As an example, a student might think “I don’t understand very well what this chapter is trying to explain. I know I can understand better when I create flow charts, so I’ll see if that way I can make the information clearer”. This is metacognition.
- Self-questioning – As described before, when students work and ask themselves questions about their performance and understanding, it helps them direct their own learning.
- Journaling – Using a journal where they can write the reflections related to their thinking process, their learning, etc. is very effective on metacognition.
- Annotated drawings – Making drawings and adding notes help the learner get a visual support to what he or she is learning.
- Concept mapping – Going from general to particular when studying helps the learner get a more organized idea of the topic and simplify what is not being understood.
- Checklists – Organizing priorities and having visual aids helps the student check on his or her progress.
- Reciprocal teaching – Studying with peers helps in several ways: determining what you’ve learned and what you need to improve; helps others revise what they know and don’t know; helps both reflect and be empathetic to others, etc.
9 Questions to help improve metacognition
- Is this similar to a previous task?
- What do I want to achieve?
- What should I do first?
- Am I on the right track?
- What can I do differently?
- Who can I ask for help?
- What worked well?
- What could I have done better?
- Can I apply this to other situations?
How is Metacognition Effective?
The main benefit of using metacognition is how it helps students be responsible, independent learners ! Being in control of your learning process is a powerful tool to succeed and improve academic achievement. As mentioned before, transferring what you’ve learned from one context to another, helps you solve problems in different environments.
To achieve this in your classroom, is important teachers are well-aware of how metacognition works. Getting practical strategies to use on lessons helps create the learning environment to develop metacognitive skills. In addition, encouraging teachers to share practical expertise is fruitful and enriches other teachers. Finally, promoting the whole school to be involved in a metacognitive learning is successful so students make it part of their lives.
Finally, I leave you with the movie trailer “How to be John Malkovich”. A little humor and good cinema to know more about metacognition and to test what has been learned. Cinema has proven to be a source of fantasy and incredible ideas.
Questions or comments? Leave me a message below 🙂
Ruiz (2004). “Las caras de la memoria”
Gutierrez, M. y Vila, C. “Psicología del desarrollo II”
Marcela is a psychologist specialized in Neuropsychological Rehabilitation by the Universidad Autónoma de Barcelona and is currently specializing on Rational Emotive Behavior Therapy. She’s passionate about volunteering and sharing experiences with people with brain injury as well as trying to help the disabled improve their quality of life. She believes that random acts of kindness make a difference in the world.
Leave a Reply Cancel reply
You must be logged in to post a comment.
- Our Mission
How Metacognition Can Improve Learning Outcomes
Teachers can empower students to recognize their strengths by offering them activities that guide them to reflect on their learning.
Metacognition, the higher-order thinking that enables understanding, analysis, and control of one’s cognitive processes, especially when engaged in learning—or more simply put, evaluating how one thinks and learns —helps students develop an understanding of their own strengths and weaknesses and the strategies that are most useful in specific situations. This self-awareness promotes knowledge and optimizes understanding, memory, and independent learning skills.
Students learn more efficiently and sustain motivation to persevere through setbacks when they understand and use strategies that brought them prior success. They recognize and avoid those that were previously unproductive. Metacognition can build these learning skills and empower students to be their own guides in subsequent learning and in life beyond school.
There are a few things teachers can do to foster metacognition:
- Provide multiple opportunities to practice the metacognitive processes, making the unconscious conscious, as they examine their learning experiences.
- Explain to students why you’re teaching them a new strategy or having them use a previously practiced one. Students can learn more independently and confidently when aware of strategies used to bring them success.
- After a successful activity, especially if it was in an area where they hadn’t been successful previously, ask what they did differently and have them write down the strategy they used.
- Create a journal of successful strategies, including predictions about when these might be used for future challenges and applied to other subjects.
- When reading or reviewing their notes, have students predict the information they think will be on the test. After the test, have them revisit their predictions and note what they specifically considered when their predictions were accurate. How will they apply these prediction guides when preparing for future tests?
Questions to Guide Self-Evaluation and Reflection
Guide students to consider the questions below when they succeed in an assignment or learning goal. Provide encouragement when they recognize success accomplished by reviewing, revising, or relearning instead of being satisfied with just “getting it done.”
- What was easy and what was most difficult?
- What strategies or experiences were most helpful to my understanding of the topic?
- What did I do that was the best use of my time?
- What outcome improvement did I notice?
- What approaches were most valuable to my understanding and test success (e.g., rereading, study groups, practice tests, rewriting notes in a different way)?
- What did I try that I’d do again?
- What would I do differently next time?
Metacognition to Prevent Distractions
Provide guidance and opportunities for learners to build their top-down attention focus skills. Attention focus metacognition is promoted by self-awareness—recognizing the pulls on attention. This involves prioritizing the array of sensory information as to what is most important and using blocking strategies to resist the distractions.
Attention focus requires distraction inhibition. Guided practice can help students build their control of what information is accepted through their attention filters and block their impulses to attend to distracting information. Use activities that build distraction inhibition and incorporate guided metacognition, so that students recognize how to apply these strategies to enhance their attention focus.
- Do slow observations and actions: have a balloon-toss, examine an object considering how it might impact multiple senses (how might this leaf, cube, map location… sound, smell, feel, move?).
- Do a web search, homework, or research without following distracting tangents. Guide students to copy and paste the attractive links they want to follow into a separate list to visit later. This relieves their feelings of needing to do it now for fear of missing out.
Students can self-evaluate their distraction response. Provide them with opportunities to do the following:
- Participate in noncredit, self-corrected timed quizzes under a variety of conditions to recognize their attentive strengths and challenges.
- Self-evaluate their attention outcomes doing defined tasks in optimal conditions versus a range of distracting noises—turn on a radio, keep dropping books, have a colleague come in and talk about “students,” or interrupt with jokes.
- After students have formed an awareness of the impact of distractions, they can develop and share strategies to inhibit their effects.
Applying Metacognition to Math
For a practical example, teachers can incorporate in lesson plans a time and place for students to create and build a metacognition list of strategies they found beneficial in their learning and understanding.
Opportunities for this self-evaluation can include having students use metacognition to recognize best approaches to solving word problems. This isn’t the same as students finding different approaches to manipulate the numbers in a specific problem, such as whether they used a decimal or a fraction to calculate a percentage. In math strategy metacognition, students consider and share the overall approach they took to assess and arrange the information in a word or situation problem to yield success.
Their different approaches and the respective problems can be collected in a class list called “Our Math Strategies.”
Metacognition Regarding Errors
After students receive their homework or tests back with the errors noted, consider not putting a grade on the paper initially, but rather giving students time to evaluate their errors and consider future alternatives. Following their self-evaluations, invite class discussions of the same questions, such as these:
- Did you leave questions unfinished at the end? If so, do you think you knew the answers to some of them? Did you skip more difficult questions along the way so that you could’ve gotten to the last questions (and gone back to the others as time allowed)? In other words, did you get the most points for their time spent?
- Were any of your errors due to not following instructions? What could you do next time, such as underlining key words in instructions and rereading them before answering the questions?
- Were mistakes made because you didn’t review sections of the test material, didn’t focus on the information you were given about what the test would cover, or didn’t ask for help to understand items you knew would be on the test but were confused about?
- What predictions did you make about the test that were correct?
Unless students are given time to go over their test results and read your comments, they may never do so. To assure that process, ask students to respond to your comments in writing, remark on the patterns of their errors, and then return the assignments or tests to you.
Tests or corrected assignments returned soon after they’re completed are especially valuable when students recognize what they were confused about before going too far into the next unit that builds on this preceding information.
To move beyond a process that might cause students to feel criticized or defensive, you can ask them to first respond to your positive comments, recognize their own successes, and write down what they did to achieve these. Then, your written responses or discussions will be enhanced when you respond to their insights about what didn’t work, what promoted their successes, and how they will apply these strategies to their goals in the future.