The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Metacomprehension: A Brief History and How to Improve Its Accuracy
Open accessAbstract
People's judgments about how well they have learned and comprehended text materials can be important for effectively regulating learning, but only if those judgments are accurate. Over two decades of research examining judgments of text learning—or metacomprehension—has consistently demonstrated that people's judgment accuracy is quite poor. We review recent research that has shown some success in improving judgment accuracy and then argue that the most common method used to investigate metacomprehension accuracy may inadvertently constrain it. We describe a new method that sidesteps some problems of the older method and present evidence showing how people can achieve high levels of metacomprehension accuracy.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Metacognition in Educational Theory and Practice
(1998) · Routledge eBooks · doi:10.4324/9781410602350 · Cited by 2,119
How do we know that we know? The accessibility model of the feeling of knowing
Koriat, A. (1993) · Psychological Review · doi:10.1037/0033-295x.100.4.609 · Cited by 895
Accuracy of metacognitive monitoring affects learning of texts.
Thiede, K. W., Anderson, M. C. M., & Therriault, D. (2003) · Journal of Educational Psychology · doi:10.1037//0022-0663.95.1.66 · Cited by 826
Glenberg, A. M., & EPSTEIN, W. M. (1985) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037//0278-7393.11.1-4.702 · Cited by 269
Summarizing can improve metacomprehension accuracy
Thiede, K. W., & Anderson, M. C. M. (2003) · Contemporary Educational Psychology · doi:10.1016/s0361-476x(02)00011-5 · Cited by 237
Test Predictions Over Text Material
(1998) · Metacognition in Educational Theory and Practice · doi:10.4324/9781410602350-13 · Cited by 168
Dunlosky, J., Rawson, K. A., & Middleton, E. L. (2005) · Journal of Memory and Language · doi:10.1016/j.jml.2005.01.011 · Cited by 163
Self-citationThe rereading effect: Metacomprehension accuracy improves across reading trials
Rawson, K. A., Dunlosky, J. T., & Thiede, K. W. (2000) · Memory & Cognition · doi:10.3758/bf03209348 · Cited by 162
Self-citationImproving students’ self-evaluation of learning for key concepts in textbook materials
Rawson, K. A., & Dunlosky, J. T. (2007) · The European Journal of Cognitive Psychology · doi:10.1080/09541440701326022 · Cited by 137
Self-citationUnderstanding the Delayed-Keyword Effect on Metacomprehension Accuracy.
Thiede, K. W., Dunlosky, J. T., Griffin, T. D., & Wiley, J. (2005) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/0278-7393.31.6.1267 · Cited by 125
Self-citation
Cited by
Self-Regulated Learning: Beliefs, Techniques, and Illusions
Bjork, R. A., Dunlosky, J., & Kornell, N. (2013) · Annual Review of Psychology · doi:10.1146/annurev-psych-113011-143823 · Cited by 1,468
Self-citationEight Ways to Promote Generative Learning
Fiorella, L., & Mayer, R. E. (2016) · Educational Psychology Review · doi:10.1007/s10648-015-9348-9 · Cited by 832
Dunlosky, J., & Rawson, K. A. (2012) · Learning and Instruction · doi:10.1016/j.learninstruc.2011.08.003 · Cited by 713
Self-citationRethinking the Use of Tests: A Meta-Analysis of Practice Testing
Adesope, O. O., Trevisan, D. A., & Sundararajan, N. (2017) · Review of Educational Research · doi:10.3102/0034654316689306 · Cited by 544
Problem‐based Learning: Influence on Students' Learning in an Electrical Engineering Course
Yadav, A., Subedi, D., Lundeberg, M. A., & Bunting, C. F. (2011) · Journal of Engineering Education · doi:10.1002/j.2168-9830.2011.tb00013.x · Cited by 416
Metadata
- Authors
- Dunlosky, J., & Lipko, A. R.
- Venue
- Current Directions in Psychological Science
- Publisher
- SAGE Publications
- Published
- 2007-08
- Volume
- 16
- Issue
- 4
- Pages
- 228-232
- ISSN
- 0963-7214 (ISSN-L)
- 1467-8721
- OpenAlex
- W2145404435
- Cited by
- 353
- References
- 14
- FWCI
- 24.36
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Metacomprehension: A Brief History and How to Improve Its Accuracy. https://app.cochat.ai/papers/10.1111/j.1467-8721.2007.00509.x
- The paper
- Dunlosky, J., & Lipko, A. R. (2007). Metacomprehension: A Brief History and How to Improve Its Accuracy. Current Directions in Psychological Science. https://doi.org/10.1111/j.1467-8721.2007.00509.x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
