Metacognition is thinking about your own thinking: knowing what you understand, noticing when you don't, and choosing what to do next. In studying it means planning a session, checking yourself with questions instead of trusting the feeling of familiarity, and changing your method when the evidence says it isn't working. The simplest form is a prediction you can check: say how sure you are, answer with the page closed, and compare.
This page defines metacognition, explains monitoring and control, and gives a three-step routine for any chapter: predict, answer and grade, then let the gap choose what to study.
You finish the chapter, close the laptop and give yourself a seven out of ten. Two days later the practice set says four. Sometimes the set is just hard. More often the number that failed was your estimate, not your knowledge. A student on r/studytips described what usually comes next: "I either reread too much, make a random note, or move on and hope I remember it later" (thread). That is studying on a wrong estimate.
Why does metacognition matter for students?
Because every study decision runs on a judgment of what you already know. You stop reviewing a topic when it feels done, skip the section that feels easy and spend the evening on the one that feels hard. If those feelings are wrong, the effort goes to the wrong places, however much of it there is.
Those feelings can be far off, and the students furthest off are the ones with the most to fix. Douglas Hacker and colleagues (2000) had undergraduates in a real course guess their score before each of three exams and again right after finishing. The top scorers guessed well and got better at it. The lowest scorers guessed high, even with the exam just behind them, and stayed high on the next one.
Overconfidence also costs learning. In John Dunlosky and Katherine Rawson's (2012) experiments, students learned definitions of key terms, recalled them, and judged each attempt as correct or not, studying each term until they judged their answer correct. Students who called incomplete answers correct stopped studying those terms early and remembered less on the final test. A lenient grader, in other words, ends the studying too soon.
If you'd rather not be your own lenient grader, Ritsu is an AI tutor that grades what you write on your own chapter and keeps a score per concept that you earn instead of rate; the second half of this page shows it on a real session. Start Learning Free
How does metacognition work?
John Flavell (1979) introduced the term and described two ingredients: what you know about how thinking works, and the experiences you have while doing it, such as the sense that something isn't adding up. Thomas Nelson and Louis Narens (1990) described a loop between doing a task and watching it:
- Monitoring is the watching: "Do I know this? How well will I do on it?"
- Control is the steering that follows: keep studying, switch strategy, ask for help, move on.
Gregory Schraw and Rayne Dennison (1994) found the same split when they built a questionnaire on metacognitive awareness: knowledge of cognition, and regulation of cognition.
The loop has a weak link. Control can only be as good as the monitoring that feeds it, and monitoring tends to read the wrong signals: how smoothly the page read, how familiar the terms look, how long you spent on it. Keith Thiede, Mary Anderson and David Therriault (2003) showed what happens when the signal improves. Readers who wrote five keywords for each text after a delay judged their comprehension more accurately than readers who wrote them right away or wrote none. They then chose better texts to reread and scored higher on the comprehension test.
What does metacognition look like on a real chapter?
Take the chapter from the video above, heat engines and the Carnot cycle, and three questions on it. Before answering each one, write a prediction: sure, unsure or no idea. Then answer with the page closed and grade the answer against the page.
| Question | Prediction | Graded answer | What the gap says |
|---|---|---|---|
| What limit does Carnot's theorem set on efficiency, and why is it the same for every reversible engine? | Sure | Partial: the limit was right, the "why" was missing | You know the claim, not the argument behind it |
| What is the highest efficiency of an engine working between 327 °C and 27 °C? | Sure | Wrong: 1 − 27/327 ≈ 0.92, about 92%; the right answer is 50% | A rule you know but didn't apply (kelvin) |
| Why can't a frictionless engine reach 100%? | Unsure | Right: heat has to go to the cold reservoir to bring the gas back to its starting state | Better than you thought |
Only the first row comes from a real session, the video's: the answer named the limit and the feedback said it "missed the second half of the question regarding why the working substance doesn't matter." Rows 2 and 3 are an illustration on the same chapter. Row 2 is the classic slip: the ratio only works on an absolute scale. Converted to kelvin, 327 + 273 = 600 K and 27 + 273 = 300 K, so the limit is 1 − 300/600 = 0.50, or 50%.
Read the prediction column against the result column. Here both "sure" answers were the weak ones, and the "unsure" one held. Without the check, tonight's review would go to the frictionless engine, the question that felt shaky and was fine. With it, the evening goes to the kelvin rule and the working-substance argument. That reallocation is what metacognition is for.
Metacognition vs cognition: what's the difference?
Cognition does the work; metacognition checks and steers it. Solving the Carnot problem is cognition. Noticing that you are unsure whether the ratio needs kelvin, and checking before you trust the 92%, is metacognition.
The two are easy to blur because a good study method contains both. Active recall is a cognitive act, pulling the idea back from memory, that also produces metacognitive evidence: what you couldn't retrieve. Self-regulated learning is the wider term for the whole cycle, with goals, motivation and time management around the monitoring-and-control core. A few more neighbours:
- Calibration: how closely your confidence matches your actual performance.
- Judgment of learning: a prediction, made while studying, of how well you will remember something later.
- Mastery check: a short test you run on yourself before moving on. It doesn't ask "Did I finish?" but "Can I retrieve, explain or apply it without my notes?"
- The Feynman technique: explaining a topic simply to find the parts you can't.
How do you use metacognition to study?
Before studying, predict what you know and set one goal. During, test yourself instead of rereading and note where you hesitate. After, compare your prediction with your results and decide what to change tomorrow.
Step 1: Predict before you check (2 minutes)
Write five questions the chapter should let you answer and next to each write sure, unsure or no idea. Do it a few hours after studying, not straight after. Thiede and colleagues' readers judged better when they waited before writing their keywords; a judgment made right away mostly measures how fresh the page is.
In Ritsu: after each answer the tutor suggests a next action from the gap, such as /askme, a command that asks you one question and grades your reply, when you think you already know an idea.
Step 2: Answer with the page closed, then grade against the page (20–30 minutes)
Write each answer in full. Then open the book and grade line by line against the key ideas of the correct answer, not against your memory of what you meant. Dunlosky and Rawson's students judged their recall more accurately when they saw the correct answer broken into its idea units and marked which ones their own answer contained. A partial answer is a partial answer, even when you "basically had it."
In Ritsu: a written answer comes back graded, with what you got right, what you missed and a next step, before the model answer.
Step 3: Let the gap choose what you study next (the rest of the session)
Go to every row where prediction and result disagree, starting with the "sure" answers that failed. Restudy only the missing part, and explain it to yourself as you go: why does this step follow, what would change if it didn't? Kiran Bisra and colleagues (2018) pooled 64 research reports on prompting learners to explain material to themselves and found a medium-sized benefit, g = .55. Then predict and answer again tomorrow, so the next check measures memory rather than freshness, the logic behind spaced repetition.
In Ritsu: the Knowledge Map scores each concept from 0 to 100 from your graded work, so the low bars show where the next hour goes.
What is the most common misconception about metacognition?
That it is a trait: some students are self-aware learners and the rest are not. But monitoring changes with method. In Thiede's study, one small change, writing keywords after a delay instead of right away, made readers' judgments more accurate. Jason Stanton, Amanda Sebesta and John Dunlosky (2021), reviewing the research for biology instructors, describe metacognition as something that develops with practice and that many students struggle to use without support.
The second mistake is equating metacognition with confidence or with reflection in general. A journal entry about how studying felt is not monitoring until it meets a result. Metacognition is the comparison: what you expected against what you produced, and the decision that follows.
How do you check what you actually know in Ritsu?
The routine above works on paper, but its weakest step is the one you grade yourself. Marking your own answer, you read what you meant rather than what you wrote, and next week nobody remembers which "sure" answers failed. Ritsu takes over that part on your own file. Here is the same check in the video's session on the Carnot chapter.
1. Choose the next action from the gap. After each answer the session suggests what to do next and why. If an idea is fuzzy, build it with /explain. If you think you know it, test the feeling with /askme. If you can recall it, apply it to a problem.
2. Answer with the page closed and read the verdict. The first answer in the video said what Carnot's limit is and stopped there. It came back marked partial, six out of ten, with the gap named: "you missed the second half of the question regarding why the working substance doesn't matter." A next step followed, and the model answer came last.
3. Read the map, not the feeling. Each activity is recorded at its Bloom level, the kind of thinking it asked for: explaining, applying, analysing. The Knowledge Map rolls the graded work up per concept, scores you earned, not self-ratings. Reading moves a score a little and then stops; only using the idea makes it climb. In the video, partway through the session, the chapter's overall score reads 8 out of 100, because only 2 of its 14 items have been explored: Carnot's theorem at 79, absolute temperature at 36, everything else still blank. Two ideas tested, one of them weak, twelve not yet checked.
4. Check again later. A mastery score records what you have shown, so it only goes up and can't tell you what has faded since. That is the job of Review: press Add to Review and the material comes back after one day, then three, seven, 16 and 35, to answer from memory and be graded again.
Every question and explanation shows the page of your file it came from, so you can check any grade against your textbook's version. Two limits are worth knowing: the map covers one document at a time, not a whole course, and the score reflects the work you have done in Ritsu, not everything you know.
Try it on the chapter you're studying this week. Upload it, write down which ideas you feel sure of, then answer Ritsu's first questions with the book closed and compare. Start Learning Free Free forever · No credit card · No time limit
To see the scoring itself, the Knowledge Map page shows how a concept earns its number.
FAQ
Q: How do you practise metacognition?
Before studying, predict what you know and set one goal. During, test yourself instead of rereading and note where you hesitate. After, compare your prediction with your results and decide what to change tomorrow. Questions such as 'could I explain this without notes?' turn a vague feeling into a plan.
Q: What is Flavell's theory of metacognition?
John Flavell (1979) described metacognition as knowledge and experience about your own thinking. His model separates what you know about people, tasks and strategies from the in-the-moment experiences, such as a feeling that you don't understand, that tell you to check, slow down or change approach.
Q: What is metacognition in psychology?
In psychology, metacognition is the study of how people monitor and control their own thinking and memory. Nelson and Narens (1990) modelled it as a loop: a monitoring level that judges what you know, and a control level that decides what to do about it.
Q: Is metacognition a rare intelligence trait?
No. It is a skill: a habit of predicting, checking and adjusting that improves with practice and feedback. In Thiede and colleagues' (2003) study, simply writing keywords after a delay made readers judge their own comprehension more accurately.
Q: What is an example of metacognition?
Rating how sure you are that you can solve a type of problem, solving one with your notes closed, and finding that your "sure" was wrong because you skipped a unit conversion. The decision that follows, practising that conversion instead of rereading the chapter, completes it.
Q: Can Ritsu show me what I actually know?
Yes, for the material you study in it. Ritsu grades your written answers on your own file before showing the model answer, and its Knowledge Map scores each concept from 0 to 100 from that graded work. Reading alone barely moves a score. You can start on the free plan.
The takeaway
Metacognition is not a feeling of knowing; it is the habit of checking that feeling against an answer you produced, then studying where the two disagree.
Pick the chapter you are studying this week, write sure or unsure next to five questions on it, and let Ritsu grade your answers before you decide what to review. Start Learning Free
Sources
- Bisra, K., Liu, Q., Nesbit, J. C., Salimi, F., & Winne, P. H. (2018). Inducing self-explanation: A meta-analysis. Educational Psychology Review, 30(3), 703–725. https://doi.org/10.1007/s10648-018-9434-x
- Dunlosky, J., & Rawson, K. A. (2012). Overconfidence produces underachievement: Inaccurate self evaluations undermine students' learning and retention. Learning and Instruction, 22(4), 271–280. https://doi.org/10.1016/j.learninstruc.2011.08.003
- Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American Psychologist, 34(10), 906–911. https://doi.org/10.1037/0003-066X.34.10.906
- Hacker, D. J., Bol, L., Horgan, D. D., & Rakow, E. A. (2000). Test prediction and performance in a classroom context. Journal of Educational Psychology, 92(1), 160–170. https://doi.org/10.1037/0022-0663.92.1.160
- Nelson, T. O., & Narens, L. (1990). Metamemory: A theoretical framework and new findings. Psychology of Learning and Motivation, 26, 125–173. https://doi.org/10.1016/S0079-7421(08)60053-5
- Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19(4), 460–475. https://doi.org/10.1006/ceps.1994.1033
- Stanton, J. D., Sebesta, A. J., & Dunlosky, J. (2021). Fostering metacognition to support student learning and performance. CBE—Life Sciences Education, 20(2), fe3. https://doi.org/10.1187/cbe.20-12-0289
- Thiede, K. W., Anderson, M. C. M., & Therriault, D. J. (2003). Accuracy of metacognitive monitoring affects learning of texts. Journal of Educational Psychology, 95(1), 66–73. https://doi.org/10.1037/0022-0663.95.1.66
By Ritsu Team · Last updated October 19, 2026
