The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Unskilled and unaware of it: How difficulties in recognizing one's own incompetence lead to inflated self-assessments
Abstract
People tend to hold overly favorable views of their abilities in many social and intellectual domains. The authors suggest that this overestimation occurs, in part, because people who are unskilled in these domains suffer a dual burden: Not only do these people reach erroneous conclusions and make unfortunate choices, but their incompetence robs them of the metacognitive ability to realize it. Across 4 studies, the authors found that participants scoring in the bottom quartile on tests of humor, grammar, and logic grossly overestimated their test performance and ability. Although their test scores put them in the 12th percentile, they estimated themselves to be in the 62nd. Several analyses linked this miscalibration to deficits in metacognitive skill, or the capacity to distinguish accuracy from error. Paradoxically, improving the skills of participants, and thus increasing their metacognitive competence, helped them recognize the limitations of their abilities.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“This pattern is consistent with the metacognitive model formulated by Kruger and Dunning (76), who demonstrated that individuals with limited competence in a given domain tend to lack awareness of that very limitation, resulting in systematic self-assessment inflation.”
From Health misinformation, digital health literacy, and attitudes toward science among university students: an exploratory cross-sectional survey (2026) · cites this paper as [76]
In the citing paper
“which is inconsistent with previous studies that have identified low- performing students as demonstrating the most significant metacognitive disconnect due to the Dunning- Kruger effect (Kruger & Dunning,1999; Ehrlinger et al.,2008; Sawdon & Finn,2014; Steuber et al.,2017).”
From Promoting metacognition in an allied health anatomy course (2023) · cites this paper as Kruger & Dunning,1999
In the citing paper
“The decline in performance of human-AI teams when tackling tasks of medium complexity suggests that users may have faced challenges in accurately assessing their own abilities and the capabilities of AI systems, primarily by overestimating their own abilities [64].”
From Dealing with Uncertainty: Understanding the Impact of Prognostic Versus Diagnostic Tasks on Trust and Reliance in Human-AI Decision Making (2024) · cites this paper as [64]
In the citing paper
“By contrast, this literature suggests that individuals who do not know much about a subject tend not to recognize their ignorance and therefore typically fail to seek better information (Kruger and Dunning 1999).”
From Financial literacy, financial advice, and financial behavior (2017) · cites this paper as Kruger and Dunning 1999
In the citing paper
“Media literacy has long focused on personal responsibility, which can not only imbue individuals with a false sense of confidence in their skills (Sanchez & Dunning, 2018; Kruger & Dunning, 1999), but put the onus of monitoring media effects on the audience, rather than media creators, social media platforms, or regulators.”
From The Promises, Challenges, and Futures of Media Literacy (2018) · cites this paper as Kruger & Dunning, 1999
In the citing paper
“This was likely observed in the small proportions of participants whose scores did not change or decreased from pre- to post-test.”
In the citing paper
“Kruger and Dunning (1999) report a series of experiments in which the worst-performing subjects on a variety of tests showed a bigger discrepancy between actual performance and a one-shot rating than the better performers.”
From How to measure metacognition (2014) · cites this paper as Kruger and Dunning (1999)
In the citing paper
“This double curse means that those people who lack the skills to produce the right answers likewise lack the ability to judge whether their own answers (and those of other people) are in fact right.”
From The Exam Autopsy: An Integrated Post-Exam Assessment Model (2019) · cites this paper as Kruger & Dunning, 1999
In the citing paper
“Yet concerns have been raised as to the validity and reliability of self-assessments as true indicators of student ability and progress (Dunn & Mulvenon, 2009;Kruger & Dunning, 1999;Ross, 2006)”
From The Exam Autopsy: An Integrated Post-Exam Assessment Model (2019) · cites this paper as Kruger & Dunning, 1999
In the citing paper
“in other words, students may not know enough to be able to gauge their own ignorance or incompetence, and consequently these may be insufficient as self-monitoring tools.”
From The Exam Autopsy: An Integrated Post-Exam Assessment Model (2019) · cites this paper as Kruger & Dunning, 1999
In the citing paper
“They found that building monitoring skills improved self-evaluations and achievement among struggling students.”
From The Potential of Exam Wrappers in Higher Education Assessment Practice: Fostering Self-Efficacy Through Guided Self-Reflection (2025) · cites this paper as Kruger and Dunning (1999)
In the citing paper
“Kruger and Dunning (1999) extended these findings, showing that poor performers are typically least accurate in appraising their abilities.”
From The Potential of Exam Wrappers in Higher Education Assessment Practice: Fostering Self-Efficacy Through Guided Self-Reflection (2025) · cites this paper as Kruger and Dunning (1999)
In the citing paper
“performance gains often occur without altering individuals’ self-perceptions, the two becoming aligned because performance increases to meet perceptions.”
From Factors influencing responsiveness to feedback: On the interplay between fear, confidence, and reasoning processes. (2012) · cites this paper as Kruger and Dunning’s (1999)
In the citing paper
“Studies of university students also indicate a paradoxical pattern in which generative-AI use can increase perceived efficiency or self-efficacy while simultaneously strengthening technological dependence or false self-efficacy (Zhang and Xu, 2025; Jia et al., 2025; Kruger and Dunning, 1999).”
From College students' metacognitive awareness of generative-AI reliance: an experimental study of decision confidence and attribution bias (2026) · cites this paper as Kruger and Dunning, 1999
Citations
Cites
Baron, R. M., & Kenny, D. A. (1986) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.51.6.1173 · Cited by 91,532
Judgment under Uncertainty: Heuristics and Biases
Tversky, A., & Kahneman, D. (1975) · Utility, Probability, and Human Decision Making · doi:10.1007/978-94-010-1834-0_8 · Cited by 22,650
A theory of social comparison processes
Festinger, L. (1954) · Human Relations · doi:10.1177/001872675400700202 · Cited by 20,926
(1994) · DigitalGeorgetown (Georgetown University Library) · Cited by 10,542
Illusion and well‐being: A social psychological perspective on mental health
Taylor, S. E., & Brown, J. D. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.2.193 · Cited by 7,814
Judgment Under Uncertainty: Heuristics and Biases.
Shafer, G. R., Kahnerman, D., Slovic, P., & Tversky, A. (1984) · Journal of the American Statistical Association · doi:10.2307/2288362 · Cited by 5,658
Unrealistic optimism about future life events
Weinstein, N. D. (1980) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.39.5.806 · Cited by 4,999
The “false consensus effect”: An egocentric bias in social perception and attribution processes
Ross, L., Greene, D., & House, P. (1977) · Journal of Experimental Social Psychology · doi:10.1016/0022-1031(77)90049-x · Cited by 3,139
Goffman, E. (1955) · Psychiatry · doi:10.1080/00332747.1955.11023008 · Cited by 2,878
Calibration of probabilities: the state of the art to 1980
Lichtenstein, S., Fischhoff, B., & Phillips, L. D. (1982) · Judgment under Uncertainty · doi:10.1017/cbo9780511809477.023 · Cited by 1,967
Cited by
Sorted by citations
Items 101–135 of 135
Through the Newsfeed Glass: Rethinking Filter Bubbles and Echo Chambers
Figà Talamanca, G., & Arfini, S. (2022) · Philosophy & Technology · doi:10.1007/s13347-021-00494-z · Cited by 41
Salimzadeh, S., He, G., & Gadiraju, U. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3641905 · Cited by 41
Promoting metacognition in an allied health anatomy course
Cale, A. S., Hoffman, L. A., & McNulty, M. A. (2023) · Anatomical Sciences Education · doi:10.1002/ase.2218 · Cited by 35
“…disconnect, which is inconsistent with previous studies that have identified low- performing students as demonstrating the most significant metacognitive disconnect due to the Dunning- Kruger effect (Kruger & Dunning, 1999; Ehrlinger et al., 2008; Sawdon & Finn, 2014; Steuber et al., 2017).”
Crafting the reflective lifelong learner: why, what and how
Albanese, M. A. (2006) · Medical Education · doi:10.1111/j.1365-2929.2006.02470.x · Cited by 34
A family of experiments on test-driven development
Santos, A., Vegas, S., Dieste, O., Uyaguari, F., Tosun, A., Fucci, D., Turhan, B., Scanniello, G., Romano, S., Karac, I., et al. (2021) · Empirical Software Engineering · doi:10.1007/s10664-020-09895-8 · Cited by 30
Svendsen, B. T., Petersen, L. F., Skjelsager, A., Lippert, A., & Østergaard, D. (2024) · Advances in Simulation · doi:10.1186/s41077-024-00303-5 · Cited by 27
“Now, a paradigm shift is seen in favour of workplace-based learning, but as it is difficult to be objective about one’s own competencies, input from others is essential [7].”
Rosen, M. A., & Dietz, A. S. (2017) · The Wiley Blackwell Handbook of the Psychology of Team Working and Collaborative Processes · doi:10.1002/9781118909997.ch21 · Cited by 26
Maintaining dental implants – do general dental practitioners have the necessary knowledge?
Jayachandran, S., Bhandal, B. S., Hill, K. B., & Walmsley, A. D. (2015) · British Dental Journal · doi:10.1038/sj.bdj.2015.528 · Cited by 25
Fooled twice – people cannot detect deepfakes but think they can
Köbis, N., Doležalová, B., & Soraperra, I. (2021) · doi:10.2139/ssrn.3832978 · Cited by 194
Crawford, J. T., & Ruscio, J. (2021) · Psychological Science · doi:10.1177/0956797620972367 · Cited by 20
Soto-Sanfiel, M. T., Angulo-Brunet, A., & Lutz, C. (2024) · doi:10.31235/osf.io/bvyku · Cited by 20
Trujillo, C. M., Anderson, T. R., & Pelaez, N. J. (2016) · CBE—Life Sciences Education · doi:10.1187/cbe.15-03-0051 · Cited by 19
Knight, J. K., Weaver, D. C., Peffer, M. E., & Hazlett, Z. S. (2022) · CBE—Life Sciences Education · doi:10.1187/cbe.21-12-0341 · Cited by 18
Lu, F.-I., Takahashi, S. G., & Kerr, C. (2021) · Academic Pathology · doi:10.1177/23742895211013528 · Cited by 15
Rizzo, P., Steinhausen, H.-C., & Drechsler, R. (2010) · ADHD Attention Deficit and Hyperactivity Disorders · doi:10.1007/s12402-010-0043-x · Cited by 16
Feasibility and acceptability of virtually coaching residents on communication skills: a pilot study
Sasnal, M., Miller-Kuhlmann, R., Merrell, S. B., Beres, S., Kipp, L., Lee, S., Threlkeld, Z., Nassar, A. K., & Gold, C. A. (2021) · BMC Medical Education · doi:10.1186/s12909-021-02936-w · Cited by 16
‘Insight’ in medical training: what, why, and how?
Ng, I. K. S., Lin, N. H. Y., Goh, W. G. W., Teo, D. B., Tan, L. F., & Ban, K. H. K. (2024) · Postgraduate Medical Journal · doi:10.1093/postmj/qgad115 · Cited by 14
Flanagin, A. J., & Lew, Z. (2023) · Media Psychology · doi:10.1080/15213269.2022.2085116 · Cited by 12
Doucette, E. J., Fullerton, M. M., Pateman, M., Lip, A., Houle, S. K. D., Kellner, J. D., Leal, J., MacDonald, S. E., McNeil, D., Tyerman, J., et al. (2024) · BMC Medical Education · doi:10.1186/s12909-024-05169-9 · Cited by 11
“The use of pre-post measurements with Likert scale assessments introduces a potential for initial overconfi-dence bias and post-test overcorrection due to the Dun-ning-Kruger effect [23, 24], where a lack of knowledge can cause someone to overestimate their skills.”
Haag, C., Bellinghausen, L., & Poirier, C. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1465774 · Cited by 12
Jongkind, R., Bikker, Y., Meinema, J., & Broens, T. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1658415 · Cited by 11
Conformity in large language models
Zhu, X., Zhang, C., Stafford, T., Collier, N., & Vlachos, A. (2025) · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/2025.acl-long.195 · Cited by 10
Predictive Validity and Response Shift in the Equanimity Scale-16
Shires, A., Osborne, S., Cayoun, B. A., Williams, E., & Rogers, K. (2023) · Mindfulness · doi:10.1007/s12671-023-02257-7 · Cited by 8
The Exam Autopsy: An Integrated Post-Exam Assessment Model
Owen, L. R. (2019) · International Journal for the Scholarship of Teaching and Learning · doi:10.20429/ijsotl.2019.130104 · Cited by 9
Raees, M., Khan, V.-J., Lykourentzou, I., & Papangelis, K. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791467 · Cited by 5
Exploring Organic Chemistry I students’ responses to an exam wrapper intervention.
Grandoit, E., Bergdoll, R., Rosales, E., Turbeville, D., Mayer, S., & Horowitz, G. (2020) · Journal of the Scholarship of Teaching and Learning · doi:10.14434/josotl.v20i1.24825 · Cited by 5
Gibbons, R. E., Hokien, D., Hutson, B. L., & Maness, H. T. D. (2025) · Intersection: A Journal at the Intersection of Assessment and Learning · doi:10.61669/001c.129036 · Cited by 2
“Kruger and Dunning (1999) extended these findings, showing that poor performers are typically least accurate in appraising their abilities.”
Talking the talk, not walking the walk: The coevolution of overconfidence and loss aversion
Dawson, C., & de Meza, D. (2026) · Psychological Review · doi:10.1037/rev0000644 · Cited by 2
Jung, W., Jeon, K., & Babon-Ayeng, P. (2026) · Proceedings of the 2026 ACM Sustainability Week · doi:10.1145/3765611.3815499
Ren, S. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1926110
“Studies of university students also indicate a paradoxical pattern in which generative-AI use can increase perceived efficiency or self-efficacy while simultaneously strengthening technological dependence or false self-efficacy (Zhang and Xu, 2025; Jia et al., 2025; Kruger and Dunning, 1999).”
Sarcone, A., Pileggi, C., Nobile, C., Simeone, S., & Mercuri, C. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1931903 · Cited by 1
Deepfakes, Democracy, and the Ethics of Synthetic Media: A Synthesis of the SOLARIS Project
(2026) · University of Maribor Press · doi:10.18690/um.feri.2.2026
Narine, L. K., & Diaz, J. M. (2026) · Education Sciences · doi:10.3390/educsci16101700
Conformity in Large Language Models
Zhu, X., Zhang, C., Stafford, T., Collier, N., & Vlachos, A. (2024) · arXiv · doi:10.48550/arxiv.2410.12428
“However, in humans, more subtle, meta-cognitive biases exist across different knowledge domains, such as the Dunning-Kruger Effect (Kruger and Dunning, 1999), confirmation bias (Mercier and Sperber, 2017), and the one we focus on in this study—the conformity effect .”
Performance and Metacognition Disconnect when Reasoning in Human-AI Interaction
Fernandes, D., Villa, S., Nicholls, S., Haavisto, O., Buschek, D., Schmidt, A., Kosch, T., Shen, C., & Welsch, R. (2024) · arXiv · doi:10.48550/arxiv.2409.16708 · Cited by 71
Metadata
- Authors
- Kruger, J., & Dunning, D.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- Cornell University (US)
- Venue
- Journal of Personality and Social Psychology
- Published
- 1999
- Volume
- 77
- Issue
- 6
- Pages
- 1121-1134
- ISSN
- 0022-3514 (ISSN-L)
- 1939-1315
- OpenAlex
- W2146006411
- Cited by
- 7,731
- References
- 55
- Citations by year
- 2026: 683 · 2025: 606 · 2024: 570 · 2023: 606 · 2022: 549 · 2021: 599 · 2020: 556 · 2019: 549 · 2018: 414 · 2017: 335 · 2016: 288 · 2015: 312 · 2014: 209 · 2013: 203 · 2012: 206
- FWCI
- 20.43
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Personality and Social Psychology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. Public Health Service (R01-56072)
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Psychology › Clinical Psychology › Personality Traits and Psychology
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Keywords
- overconfidence, self-assessment, metacognition, metacognitive skills, self-knowledge, overestimation of ability, metacognitive calibration, grammar, logic, skill deficits, self-awareness
- MeSH terms
- Cognition, Female, Humans, Intelligence, Language, Logic, Male, Problem Solving, Surveys and Questionnaires, Self-Assessment, Self Concept, Social Perception
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