Journal of Personality and Social Psychology
1999, Vol. 77, No. 6. ] 121-1134

Copyright 1999 by the American Psychological Association, Inc.
0022-3514/99/S3.00

Unskilled and Unaware of It: How Difficulties in Recognizing One's Own
Incompetence Lead to Inflated Self-Assessments
Justin Kruger and David DunningThis document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Cornell University
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 makeunfortunate 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, andlogic 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 themrecognize the limitations of their abilities.

as promoting effective leadership, raising children, constructing asolid logical argument, or designing a rigorous psychologicalstudy. Second, people differ widely in the knowledge and strategies they apply in these domains (Dunning, Meyerowitz, & Holzberg, 1989; Dunning, Perie, & Story, 1991; Story & Dunning,1998), with varying levels of success. Some of the knowledge andtheories that people apply to their actions are sound and meet withfavorable results. Others, like the lemon juice hypothesis of
McArthur Wheeler, are imperfect at best and wrong-headed, incompetent, or dysfunctional at worst.
Perhaps more controversial is the third point, the one that is thefocus of this article. We argue that when people are incompetent in
the strategies they adopt to achieve success and satisfaction, they
suffer a dual burden: Not only do they reach erroneous conclusions
and make unfortunate choices, but their incompetence robs them of
the ability to realize it. Instead, like Mr. Wheeler, they are left withthe mistaken impression that they are doing just fine. As Miller(1993) perceptively observed in the quote that opens this article,
and as Charles Darwin (1871) sagely noted over a century ago,
"ignorance more frequently begets confidence than does knowledge" (p. 3).
In essence, we argue that the skills that engender competence ina particular domain are often the very same skills necessary toevaluate competence in that domain—one's own or anyone else's.
Because of this, incompetent individuals lack what cognitive psychologists variously term metacognition (Everson & Tobias,
1998), metamemory (Klin, Guizman, & Levine, 1997), metacomprehension (Maki, Jonas, & Kallod, 1994), or self-monitoringskills (Chi, Glaser, & Rees, 1982). These terms refer to the ability
to know how well one is performing, when one is likely to beaccurate in judgment, and when one is likely to be in error. For
example, consider the ability to write grammatical English. The
skills that enable one to construct a grammatical sentence are thesame skills necessary to recognize a grammatical sentence, andthus are the same skills necessary to determine if a grammaticalmistake has been made. In short, the same knowledge that underlies the ability to produce correct judgment is also the knowledge

It is one of the essential features of such incompetence that the person
so afflicted is incapable of knowing that he is incompetent. To havesuch knowledge would already be to remedy a good portion of theoffense. (Miller, 1993, p. 4)

In 1995, McArthur Wheeler walked into two Pittsburgh banks
and robbed them in broad daylight, with no visible attempt at
disguise. He was arrested later that night, less than an hour aftervideotapes of him taken .from surveillance cameras were broadcast
on the 11 o'clock news. When police later showed him the surveillance tapes, Mr. Wheeler stared in incredulity. "But I wore thejuice," he mumbled. Apparently, Mr. Wheeler was under the
impression that rubbing one's face with lemon juice rendered it
invisible to videotape cameras (Fuocco, 1996).
We bring up the unfortunate affairs of Mr. Wheeler to makethree points. The first two are noncontroversial. First, in many
domains in life, success and satisfaction depend on knowledge,
wisdom, or savvy in knowing which rules to follow and which
strategies to pursue. This is true not only for committing crimes,
but also for many tasks in the social and intellectual domains, such

Justin Kruger and David Dunning, Department of Psychology, Cornell
University.
We thank Betsy Ostrov, Mark Stalnaker, and Boris Veysman for theirassistance in data collection. We also thank Andrew Hayes, Chip Heath,Rich Gonzalez, Ken Savitsky, and David Sherman for their valuablecomments on an earlier version of this article, and Dov Cohen for alerting
us to the quote we used to begin this article. Portions of this research were
presented at the annual meeting of the Eastern Psychological Association,
Boston, March 1998. This research was supported financially by National
Institute of Mental Health Grant RO1 56072.
Correspondence concerning this article should be addressed to Justin
Kruger, who is now at the Department of Psychology, University of Illinois
at Urbana-Champaign, 603 East Daniel Street, Champaign, Illinois 61820,or to David Dunning, Department of Psychology, Uris Hall, Cornell
University, Ithaca, New York 14853-7601. Electronic mail may be sent toJustin Kruger at jkruger@s.psych.uiuc.edu or to David Dunning at
dad6@cornell.edu.
1121

1122

KRUGER AND DUNNING

that underlies the ability to recognize correct judgment. To lack theformer is to be deficient in the latter.

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Imperfect Self-Assessments
We focus on the metacognitive skills of the incompetent to
explain, in part, the fact that people seem to be so imperfect inappraising themselves and their abilities.1 Perhaps the best illustration of this tendency is the "above-average effect," or thetendency of the average person to believe he or she is above
average, a result that defies the logic of descriptive statistics(Alicke, 1985; Alicke, Klotz, Breitenbecher, Yurak, & Vredenburg, 1995; Brown & Gallagher, 1992; Cross, 1977; Dunning etal, 1989; Klar, Medding, & Sarel, 1996; Weinstein, 1980; Weinstein & Lachendro, 1982). For example, high school students tend
to see themselves as having more ability in leadership, getting
along with others, and written expression than their peers (College
Board, 1976-1977), business managers view themselves as moreable than the typical manager (Larwood & Whittaker, 1977), andfootball players see themselves as more savvy in "football sense"than their teammates (Felson, 1981).
We believe focusing on the metacognitive deficits of the unskilled may help explain this overall tendency toward inflated
self-appraisals. Because people usually choose what they think is
the most reasonable and optimal option (Metcalfe, 1998), thefailure to recognize that one has performed poorly will instead
leave one to assume that one has performed well. As a result, theincompetent will tend to grossly overestimate their skills andabilities.
Competence and Metacognitive Skills
Several lines of research are consistent with the notion that
incompetent individuals lack the metacognitive skills necessary for
accurate self-assessment. Work on the nature of expertise, forinstance, has revealed that novices possess poorer metacognitive
skills than do experts. In physics, novices are less accurate thanexperts in judging the difficulty of physics problems (Chi et al.,1982). In chess, novices are less calibrated than experts about how
many times they need to see a given chessboard position before
they are able to reproduce it correctly (Chi, 1978). In tennis,
novices are less likely than experts to successfully gauge whether
specific play attempts were successful (McPherson & Thomas,
1989).
These findings suggest that unaccomplished individuals do notpossess the degree of metacognitive skills necessary for accurate
self-assessment that their more accomplished counterparts possess.
However, none of this research has examined whether metacognitive deficiencies translate into inflated self-assessments orwhether the relatively incompetent (novices) are systematicallymore miscalibrated about their ability than are the competent(experts).
If one skims through the psychological literature, one will findsome evidence that the incompetent are less able than their moreskilled peers to gauge their own level of competence. For example,
Fagot and O'Brien (1994) found that socially incompetent boys
were largely unaware of their lack of social graces (see Bern &Lord, 1979, for a similar result involving college students). Mediocre students are less accurate than other students at evaluating

their course performance (Moreland, Miller, & Laucka, 1981).
Unskilled readers are less able to assess their text comprehension
than are more skilled readers (Maki, Jonas, & Kallod, 1994).
Students doing poorly on tests less accurately predict which questions they will get right than do students doing well (Shaughnessy,
1979; Sinkavich, 1995). Drivers involved in accidents or flunking
a driving exam predict their performance on a reaction test lessaccurately than do more accomplished and experienced drivers(Kunkel, 1971). However, none of these studies has examined
whether deficient metacognitive skills underlie these miscalibrations, nor have they tied these miscalibrations to the above-average
effect.
Predictions
These shards of empirical evidence suggest that incompetent
individuals have more difficulty recognizing their true level ofability than do more competent individuals and that a lack ofmetacognitive skills may underlie this deficiency. Thus, we madefour specific predictions about the links between competence,
metacognitive ability, and inflated self-assessment.
Prediction 1. Incompetent individuals, compared with theirmore competent peers, will dramatically overestimate their ability
and performance relative to objective criteria.
Prediction 2. Incompetent individuals will suffer from deficient
metacognitive skills, in that they will be less able than their morecompetent peers to recognize competence when they see it—be it
their own or anyone else's.
Prediction 3. Incompetent individuals will be less able than theirmore competent peers to gain insight into their true level of
performance by means of social comparison information. In particular, because of their difficulty recognizing competence in others, incompetent individuals will be unable to use information
about the choices and performances of others to form more accurate impressions of their own ability.
Prediction 4. The incompetent can gain insight about theirshortcomings, but this comes (paradoxically) by making themmore competent, thus providing them the metacognitive skills
necessary to be able to realize that they have performed poorly.
The Studies
We explored these predictions in four studies. In each, we
presented participants with tests that assessed their ability in adomain in which knowledge, wisdom, or savvy was crucial: humor(Study 1), logical reasoning (Studies 2- and 4), and English grammar (Study 3). We then asked participants to assess their ability
1
A few words are in order about what we mean by incompetent. First,
throughout this article, we think of incompetence as a matter of degree andnot one of absolutes. There is no categorical bright line that separates"competent" individuals from "incompetent" ones. Thus, when we speakof "incompetent" individuals we mean people who are less competent thantheir peers. Second, we have focused our analysis on the incompetence
individuals display in specific domains. We make no claim that they would
be incompetent in any other domains, although many a colleague has
pulled us aside to tell us a tale of a person they know who is "domaingeneral" incompetent. Those people may exist, but they are not the focusof this research.

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

UNSKILLED AND UNAWARE

and test performance. In all studies, we predicted that participantsin general would overestimate their ability and performance relative to objective criteria. But more to the point, we predicted thatthose who proved to be incompetent (i.e., those who scored in thebottom quarter of the distribution) would be unaware that they had
performed poorly. For example, their score would fall in the 10thor 15th percentile among their peers, but they would estimate thatit fell much higher (Prediction 1). Of course, this overestimation
could be taken as a mathematical verity. If one has a low score, one
has a better chance of overestimating one's performance thanunderestimating it. Thus, the real question in these studies is how
much those who scored poorly would be miscalibrated with respect to their performance.
In addition, we wanted to examine the relationship between
miscalibrated views of ability and metacognitive skills, which we
operationalized as (a) the ability to distinguish what one has
answered correctly from what one has answered incorrectly and(b) the ability to recognize competence in others. Thus, in Study 4,
we asked participants to not only estimate their overall performance and ability, but to indicate which specific test items they
believed they had answered correctly and which incorrectly. In
Study 3, we showed competent and incompetent individuals the
responses of others and assessed how well participants from eachgroup could spot good and poor performances. In both studies, wepredicted that the incompetent would manifest poorer metacognitive skills than would their more competent peers (Prediction 2).
We also wanted to find out what experiences or interventions
would make low performers realize the true level of performancethat they had attained. Thus, in Study 3, we asked participants toreassess their own ability after they had seen the responses of theirpeers. We predicted that competent individuals would learn fromobserving the responses of others, thereby becoming better calibrated about the quality of their performance relative to their peers.
Incompetent participants, in contrast, would not (Prediction 3). In
Study 4, we gave participants training in the domain of logicalreasoning and explored whether this newfound competence would
prompt incompetent individuals toward a better understanding of
the true level of their ability and test performance (Prediction 4).

Study 1: Humor
In Study 1, we decided to explore people's perceptions of theircompetence in a domain that requires sophisticated knowledge andwisdom about the tastes and reactions of other people. That domain was humor. To anticipate what is and what others will findfunny, one must have subtle and tacit knowledge about otherpeople's tastes. Thus, in Study 1 we presented participants with aseries of jokes and asked them to rate the humor of each one. We
then compared their ratings with those provided by a panel ofexperts, namely, professional comedians who make their living byrecognizing what is funny and reporting it to their audiences. By
comparing each participant's ratings with those of our expert
panel, we could roughly assess participants' ability to spot humor.
Our key interest was how perceptions of that ability convergedwith actual ability. Specifically, we wanted to discover whether
those who did poorly on our measure would recognize the low
quality of their performance. Would they recognize it or would
they be unaware?

1123

MethodParticipants. Participants were 65 Cornell University undergraduatesfrom a variety of courses in psychology who earned extra credit for their
participation.
Materials. We created a 30-item questionnaire made up of jokes wefelt were of varying comedic value. Jokes were taken from Woody Allen(1975), Al Frankin (1992), and a book of "really silly" pet jokes by Jeff
Rovin (1996). To assess joke quality, we contacted several professional
comedians via electronic mail and asked them to rate each joke on a scaleranging from 1 (not at all funny) to 11 (very funny). Eight comedians
responded to our request (Bob Crawford, Costaki Economopoulos, PaulFrisbie, Kathleen Madigan, Ann Rose, Allan Sitterson, David Spark, andDan St. Paul). Although the ratings provided by the eight comedians weremoderately reliable (a = .72), an analysis of interrater correlations foundthat one (and only one) comedian's ratings failed to correlate positively
with the others (mean r = -.09). We thus excluded this comedian's ratingsin our calculation of the humor value of each joke, yielding a final a of .76.
Expert ratings revealed that jokes ranged from the not so funny (e.g.,"Question: What is big as a man, but weighs nothing? Answer: His
shadow." Mean expert rating = 1.3) to the very funny (e.g., "If a kid asks
where rain comes from, I think a cute thing to tell him is 'God is crying.'
And if he asks why God is crying, another cute thing to tell him is'probably because of something you did.'" Mean expert rating = 9.6).
Procedure. Participants rated each joke on the same 11-point scale
used by the comedians. Afterward, participants compared their "ability torecognize what's funny" with that of the average Cornell student by
providing a percentile ranking. In this and in all subsequent studies, we
explained that percentile rankings could range from 0 (I'm at the verybottom) to 50 (I'm exactly average) to 99 (I'm at the very top).

Results and Discussion
Gender failed to qualify any results in this or any of the studies
reported in this article, and thus receives no further mention.
Our first prediction was that participants overall would overestimate their ability to tell what is funny relative to their peers. To
find out whether this was the case, we first assigned each participant a percentile rank based on the extent to which his or her joke
ratings correlated with the ratings provided by our panel of professionals (with higher correlations corresponding to better performance). On average, participants put their ability to recognize
what is funny in the 66th percentile, which exceeded the actual
mean percentile (50, by definition) by 16 percentile points, onesample /(64) = 7.02, p < .0001. This overestimation occurred
even though self-ratings of ability were significantly correlatedwith our measure of actual ability, r(63) = .39, p < .001.
Our main focus, however, is on the perceptions of relatively"incompetent" participants, which we defined as those whose testscore fell in the bottom quartile (n = 16). As Figure 1 depicts,
these participants grossly overestimated their ability relative totheir peers. Whereas their actual performance fell in the 12th
percentile, they put themselves in the 58th percentile. These estimates were not only higher than the ranking they actuallyachieved, paired r(15) = 10.33, p < .0001, but were also marginally higher than a ranking of "average" (i.e., the 50th percentile),
one-sample t(15) = 1.96, p < .07. That is, even participants in thebottom quarter of the distribution tended to feel that they were
better than average.
As Figure 1 illustrates, participants in other quartiles did notoverestimate their ability to the same degree. Indeed, those in the

1124

KRUGER AND DUNNING

1009080 70J

60-

§

50-

CL

4030-Perceived Ability-Actual Test Score

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

20100
BottomQuartile

2nd
Quartile

3rd
QuartileTop
Quartile

Figure 1. Perceived ability to recognize humor as a function of actual test
performance (Study 1).

top quartile actually underestimated their ability relative to theirpeers, paired 1(15) = -2.20, p < .05.

Summary
In short, Study 1 revealed two effects of interest. First, although
perceptions of ability were modestly correlated with actual ability,
people tended to overestimate their ability relative to their peers.
Second, and most important, those who performed particularly
poorly relative to theirpeers were utterly unaware of this fact.
Participants scoring in the bottom quartile on our humor test not
only overestimated their percentile ranking, but they overestimatedit by 46 percentile points. To be sure, they had an inkling that they
were not as talented in this domain as were participants in the top
quartile, as evidenced by the significant correlation between perceived and actual ability. However, that suspicion failed to anticipate the magnitude of their shortcomings.
At first blush, the reader may point to the regression effect as analternative interpretation of our results. After all, we examined theperceptions of people who had scored extremely poorly on theobjective test we handed them, and found that their perceptions
were less extreme than their reality. Because perceptions of ability
are imperfectly correlated with actual ability, the regression effectvirtually guarantees this result. Moreover, because incompetentparticipants scored close to the bottom of the distribution, it was
nearly impossible for them to underestimate their performance.
Despite the inevitability of the regression effect, we believe thatthe overestimation we observed was more psychological thanartifactual. For one, if regression alone were to blame for our
results, then the magnitude of miscalibration among the bottom
quartile would be comparable with that of the top quartile. A
glance at Figure 1 quickly disabuses one of this notion. Still, we
believe this issue warrants empirical attention, which we devote inStudies 3 and 4.

Study 2: Logical Reasoning
We conducted Study 2 with three goals in mind. First, we
wanted to replicate the results of Study 1 in a different domain, one

focusing on intellectual rather than social abilities. We chose
logical reasoning, a skill central to the academic careers of theparticipants we tested and a skill that is called on frequently. We
wondered if those who do poorly relative to their peers on a logicalreasoning test would be unaware of their poor performance.
Examining logical reasoning also enabled us to compare perceived and actual ability in a domain less ambiguous than the one
we examined in the previous study. It could reasonably be argued
that humor, like beauty, is in the eye of the beholder.2 Indeed, theimperfect interrater reliability among our group of professional
comedians suggests that there is considerable variability in what is
considered funny even by experts. This criterion problem, or lackof uncontroversial criteria against which self-perceptions can becompared, is particularly problematic in light of the tendency todefine ambiguous traits and abilities in ways that emphasize one's
own strengths (Dunning et al., 1989). Thus, it may have been thetendency to define humor idiosyncratically, and in ways favorable
to one's tastes and sensibilities, that produced the miscalibration
we observed—not the tendency of the incompetent to miss theirown failings. By examining logical reasoning skills, we could
circumvent this problem by presenting students with questions forwhich there is a definitive right answer.
Finally, we wanted to introduce another objective criterion withwhich we could compare participants' perceptions. Because percentile ranking is by definition a comparative measure, the miscalibration we saw could have come from either of two sources. In
the comparison, participants may have overestimated their own
ability (our contention) or may have underestimated the skills of
their peers. To address this issue, in Study 2 we added a second
criterion with which to compare participants' perceptions. At theend of the test, we asked participants to estimate how many of thequestions they had gotten right and compared their estimates with
their actual test scores. This enabled us to directly examine
whether the incompetent are, indeed, miscalibrated with respect totheir own ability and performance.

MethodParticipants. Participants were 45 Cornell University undergraduatesfrom a single introductory psychology course who earned extra credit for
their participation. Data from one additional participant was excluded
because she failed to complete the dependent measures.
Procedure. Upon arriving at the laboratory, participants were told thatthe study focused on logical reasoning skills. Participants then completed
a 20-item logical reasoning test that we created using questions taken froma Law School Admissions Test (LSAT) test preparation guide (Orton,
1993). Afterward, participants made three estimates about their ability andtest performance. First, they compared their "general logical reasoning
ability" with that of other students from their psychology class by providing their percentile ranking. Second, they estimated how their score on thetest would compare with that of their classmates, again on a percentile
scale. Finally, they estimated how many test questions (out of 20) they
thought they had answered correctly. The order in which these questions
were asked was counterbalanced in this and in all subsequent studies.

2

Actually, some theorists argue that there are universal standards ofbeauty (see, e.g., Thomhill & Gangestad, 1993), suggesting that this truism
may not be, well, true.

1125

UNSKILLED AND UNAWARE

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Results and Discussion
The order in which specific questions were asked did not affectany of the results in this or in any of the studies reported in thisarticle and thus receives no further mention.
As expected, participants overestimated their logical reasoning
ability relative to their peers. On average, participants placed
themselves in the 66th percentile among students from their class,which was significantly higher than the actual mean of 50, onesample r(44) = 8.13, p < .0001. Participants also overestimatedtheir percentile rank on the test, M percentile = 61, one-samplet(44) = 4.70, p < .0001. Participants did not, however, overestimate how many questions they answered correctly, M = 13.3
(perceived) vs. 12.9 (actual), t < 1. As in Study 1, perceptions ofability were positively related to actual ability, although in thiscase, not to a significant degree. The correlations between actual
ability and the three perceived ability and performance measures
ranged from .05 to .19, all ns.
What (or rather, who) was responsible for this gross miscalibration? To find out, we once again split participants into quartiles
based on their performance on the test. As Figure 2 clearly illustrates, it was participants in the bottom quartile (n = 11) who
overestimated their logical reasoning ability and test performanceto the greatest extent. Although these individuals scored at the 12th
percentile on average, they nevertheless believed that their generallogical reasoning ability fell at the 68th percentile and their scoreon the test fell at the 62nd percentile. Their estimates not only
exceeded their actual percentile scores, fs(10) = 17.2 and 11.0,
respectively, ps < .0001, but exceeded the 50th percentile as well,fs(10) = 4.93 and 2.31, .respectively, ps < .05. Thus, participantsin the bottom quartile not only overestimated themselves but
believed that they were above average. Similarly, they thought
they had answered 14.2 problems correctly on average—compared with the actual mean score of 9.6, r(10) = 7.66, p < .0001.
Other participants were less miscalibrated. However, as Figure 2
shows, those in the top quartile once again tended to underestimate
their ability. Whereas their test performance put them in the 86th
percentile, they estimated it to be at the 68th percentile and100 -,
9080702.

60 -

CD

a.

40 30—Perceived Ability—Perceived Test Score-Actual Test Score

2010-

estimated their general logical reasoning ability to fall at only the74th percentile, fs(12) = -3.55 and -2.50, respectively,ps < .05.
Top-quartile participants also underestimated their raw score on
the test, although this tendency was less robust, M = 14.0 (perceived) versus 16.9 (actual), r(12) = -2.15,/? < .06.

Summary
In sum, Study 2 replicated the primary results of Study 1 in adifferent domain. Participants in general overestimated their logical reasoning ability, and it was once again those in the bottom
quartile who showed the greatest miscalibration. It is important tonote that these same effects were observed when participantsconsidered their percentile score, ruling out the criterion problem
discussed earlier. Lest one think these results reflect erroneous
peer assessment rather then erroneous self-assessment, participantsin the bottom quartile also overestimated the number of test items
they had gotten right by nearly 50%.

Study 3 (Phase 1): Grammar
Study 3 was conducted in two phases. The first phase consistedof a replication of the first two studies in a third domain, one
requiring knowledge of clear and decisive rules and facts: grammar. People may differ in the worth they assign to American
Standard Written English (ASWE), but they do agree that such astandard exists, and they differ in their ability to produce andrecognize written documents that conform to that standard.
Thus, in Study 3 we asked participants to complete a test
assessing their knowledge of ASWE. We also asked them to rate
their overall ability to recognize correct grammar, how their test
performance compared with that of their peers, and finally how
many items they had answered correctly on the test. In this way,
we could see if those who did poorly would recognize that fact.

MethodParticipants. Participants were 84 Cornell University undergraduates
who received extra credit toward their course grade for taking part in the
study.
Procedure. The basic procedure and primary dependent measures weresimilar to those of Study 2. One major change was that of domain.
Participants completed a 20-item test of grammar, with questions takenfrom a National Teacher Examination preparation guide (Bobrow et al.,1989). Each test item contained a sentence with a specific portion underlined. Participants were to judge whether the underlined portion was
grammatically correct or should be changed to one of four different
rewordings displayed.
After completing the test, participants compared their general ability to"identify grammatically correct standard English" with that of other students from their class on the same percentile scale used in the previous
studies. As in Study 2, participants also estimated the percentile rank of
their test performance among their student peers, as well as the number ofindividual test items they had answered correctly.

Results and Discussion

0
BottomQuartile

2nd
Quartile

3rd
QuartileTop
Quartile

Figure 2. Perceived logical reasoning ability and test performance as afunction of actual test performance (Study 2).

As in Studies 1 and 2, participants overestimated their ability
and performance relative to objective criteria. On average, participants' estimates of their grammar ability (M percentile = 71) andperformance on the test (M percentile = 68) exceeded the actual

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

1126

KRUGER AND DUNNING

mean of 50, one-sample rs(83) = 5.90 and 5.13, respectively, ps <.0001. Participants also overestimated the number of items theyanswered correctly, M = 15.2 (perceived) versus 13.3 (actual),r(83) = 6.63, p < .0001. Although participants' perceptions of
their general grammar ability were uncorrelated with their actual
test scores, r(82) = .14, ns, their perceptions of how their test
performance would rank among their peers was correlated with
their actual score, albeit to a marginal degree, r(82) = .19, p < .09,
as was their direct estimate of their raw test score, r(82) = .54, p <.0001.
As Figure 3 illustrates, participants scoring in the bottom quartile grossly overestimated their ability relative to their peers.
Whereas bottom-quartile participants (n = 17) scored in the 10th
percentile on average, they estimated their grammar ability andperformance on the test to be in the 67th and 61st percentiles,
respectively, ts(16) = 13.68 and 15.75, ps < .0001. Bottomquartile participants also overestimated their raw score on the testby 3.7 points, M = 12.9 (perceived) versus 9.2 (actual),f(16) = 5.79, p< .0001.
As in previous studies, participants falling in other quartiles
overestimated their ability and performance much less than did
those in the bottom quartile. However, as Figure 3 shows, those in
the top quartile once again underestimated themselves. Whereas
their test performance fell in the 89th percentile among their peers,
they rated their ability to be in the 72nd percentile and their test
performance in the 70th percentile, ts(18) = -4.73 and -5.08,
respectively, ps < .0001. Top-quartile participants did not, however, underestimate their raw score on the test, M = 16.9 (perceived) versus 16.4 (actual), r(18) = 1.37, ns.

Study 3 (Phase 2): It Takes One to Know One
Thus far, we have shown that people who lack the knowledge or
wisdom to perform well are often unaware of this fact. We attribute this lack of awareness to a deficit in metacognitive skill.
That is, the same incompetence that leads them to make wrong
choices also deprives them of the savvy necessary to recognize
competence, be it their own or anyone else's.

100 i9080 70-

i£

60 -

|

50 -

°-

40 -

We designed a second phase of Study 3 to put the latter half of
this claim to a test. Several weeks after the first phase of Study 3,
we invited the bottom- and top-quartile performers from this study
back to the laboratory for a follow-up. There, we gave each groupthe tests of five of their peers to "grade" and asked them to assess
how competent each target had been in completing the test. In
keeping with Prediction 2, we expected that bottom-quartile participants would have more trouble with this metacognitive task
than would their top-quartile counterparts.
This study also enabled us to explore Prediction 3, that incompetent individuals fail to gain insight into their own incompetence
by observing the behavior of other people. One of the ways people
gain insight into their own competence is by comparing themselves with others (Festinger, 1954; Gilbert, Giesler, & Morris,
1995). We reasoned that if the incompetent cannot recognize
competence in others, then they will be unable to make use of thissocial comparison opportunity. To test this prediction, we asked
participants to reassess themselves after they have seen the responses of their peers. We predicted that despite seeing the superior test performances of their classmates, bottom-quartile participants would continue to believe that they had performed
competently.
In contrast, we expected that top-quartile participants, because
they have the metacognitive skill to recognize competence andincompetence in others, would revise their self-ratings after thegrading task. In particular, we predicted that they would recognizethat the performances of the five individuals they evaluated wereinferior to their own, and thus would raise their estimates of theirpercentile ranking accordingly. That is, top-quartile participants
would learn from observing the responses of others, whereas
bottom-quartile participants would not.
In making these predictions, we felt that we could account for an
anomaly that appeared in all three previous studies: Despite thefact that top-quartile participants were far more calibrated thanwere their less skilled counterparts, they tended to underestimate
their performance relative to their peers. We felt that this miscalibration had a different source then the miscalibration evidenced bybottom-quartile participants. That is, top-quartile participants did
not underestimate themselves because they were wrong about theirown performances, but rather because they were wrong about theperformances of their peers. In essence, we believe they fell preyto the false-consensus effect (Ross, Greene, & House, 1977). In theabsence of data to the contrary, they mistakenly assumed that theirpeers would tend provide the same (correct) answers as they
themselves—an impression that could be immediately correctedby showing them the performances of their peers. By examining
the extent to which competent individuals revised their ability
estimates after grading the tests of their less competent peers, we
could put this false-consensus interpretation to a test.

/

30-

•
Perceived Ability—-if—Perceived Test Score-"••••-Actual Test Score

20100-

BottomQuartile

2nd
Quartile

3rd
QuartileTop
Quartile

Figure 3. Perceived grammar ability and test performance as a functionof actual test performance (Study 3).

MethodParticipants. Four to six weeks after Phase 1 of Study 3 was completed, we invited participants from the bottom- (n = 17) and top-quartile(n = 19) back to the laboratory in exchange for extra credit or $5. All
agreed and participated.
Procedure. On arriving at the laboratory, participants received apacket of five tests that had been completed by other students in the firstphase of Study 3. The tests reflected the range of performances that theirpeers had achieved in the study (i.e., they had the same mean and standard

1127

UNSKILLED AND UNAWARE

Table 1
Self-Ratings (Percentile Scales) of Ability and Performance on Test Before and After Grading Task
for Bottom- and Top-Quartile Participants (Study 3, Phase 2)
Participant quartile

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

BottomTop

RatingPercentile ability

Percentile test score

Raw test score

Percentile ability

Percentile test score

Raw test score

BeforeAfter
Difference

66.8
63.2
-3.5

60.5
65.4
4.9

12.9
13.7
0.8

71.6
77.2
5.6*

69.5
79.7
10.2**

16.9
16.6
-0.3

Actual

10.1

10.1

9.2

88.7

88.7

16.4

£.05.

**p<.01.

deviation), a fact we shared with participants. We then asked participants
to grade each test by indicating the number of questions they thought eachof the five test-takers had answered correctly.
After this, participants were shown their own test again and were asked
to re-rate their ability and performance on the test relative to their peers,
using the same percentile scales as before. They also re-estimated thenumber of test questions they had answered correctly.

Results and Discussion
Ability to assess competence in others. As predicted, participants who scored in the bottom quartile were less able to gauge thecompetence of others than were their top-quartile counterparts. For
each participant, we correlated the grade he or she gave each testwith the actual score the five test-takers had attained. Bottomquartile participants achieved lower correlations (mean r = .37)
than did top-quartile participants (mean r = .66), f(34) = 2.09, p <.05.3 For an alternative measure, we summed the absolute miscalibration in the grades participants gave the five test-takers andfound similar results, M = 17 A (bottom quartile) vs. 9.2 (topquartile), f(34) = 2.49, p < .02.
Revising self-assessments. Table 1 displays the selfassessments of bottom- and top-quartile performers before andafter reviewing the answers of the test-takers shown during thegrading task. As can be seen, bottom-quartile participants failed togain insight into their own performance after seeing the morecompetent choices of their peers. If anything, bottom-quartile
participants tended to raise their already inflated self-estimates,
although not to a significant degree, all fs(16) < 1.7.
With top-quartile participants, a completely different picture
emerged. As predicted, after grading the test performance of fiveof their peers, top-quartile participants raised their estimates of
their own general grammar ability, £(18) = 2.07, p = .05, and theirpercentile ranking on the test, f(18) = 3.61, p < .005. These results
are consistent with the false-consensus effect account we haveoffered. Armed with the ability to assess competence and incompetence in others, participants in the top quartile realized that theperformances of the five individuals they evaluated (and thus theirpeers in general) were inferior to their own. As a consequence,
top-quartile participants became better calibrated with respect totheir percentile ranking. Note that a false-consensus interpretation
does not predict any revision for estimates of one's raw score, as
learning of the poor performance of one's peers conveys no

information about how well one has performed in absolute terms.
Indeed, as Table 1 shows, no revision occurred, r(18) < 1.
Summary. In sum, Phase 2 of Study 3 revealed several effects
of interests. First, consistent with Prediction 2, participants in thebottom quartile demonstrated deficient metacognitive skills. Compared with top-quartile performers, incompetent individuals wereless able to recognize competence in others. We are reminded ofwhat Richard Nisbett said of the late, great giant of psychology,
Amos Tversky. "The quicker you realize that Amos is smarter thanyou, the smarter you yourself must be" (R. E. Nisbett, personalcommunication, July 28, 1998).
This study also supported Prediction 3, that incompetent individuals fail to gain insight into their own incompetence by observing the behavior of other people. Despite seeing the superior
performances of their peers, bottom-quartile participants continued
to hold the mistaken impression that they had performed just fine.
The story for high-performing participants, however, was quite
different. The accuracy of their self-appraisals did improve. We
attribute this finding to a false-consensus effect. Simply put, because top-quartile participants performed so adeptly, they assumed
the same was true of their peers. After seeing the performances ofothers, however, they were disabused of this notion, and thus thethey improved the accuracy of their self-appraisals. Thus, themiscalibration of the incompetent stems from an error about theself, whereas the miscalibration of the highly competent stems
from an error about others.

Study 4: Competence Begets Calibration
The central proposition in our argument is that incompetent
individuals lack the metacognitive skills that enable them to tell
how poorly they are performing, and as a result, they come to holdinflated views of their performance and ability. Consistent withthis notion, we have shown that incompetent individuals (compared with their more competent peers) are unaware of theirdeficient abilities (Studies 1 through 3) and show deficient metacognitive skills (Study 3).
3
Although the means reported in the text were derived from the raw
correlation coefficients, the t test was performed on the z-transformed
coefficients.

1128

KRUGER AND DUNNING

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

The best acid test of our proposition, however, is to manipulatecompetence and see if this improves metacognitive skills and thus
the accuracy of self-appraisals (Prediction 4). This would not only
enable us to speak directly to causality, but would help rule out the
regression effect alternative account discussed earlier. If the incompetent overestimate themselves simply because their testscores are very low (the regression effect), then manipulatingcompetence after they take the test ought to have no effect on theaccuracy of their self-appraisals. If instead it takes competence torecognize competence, then manipulating competence ought toenable the incompetent to recognize that they have performed
poorly. Of course, there is a paradox to this assertion. It suggeststhat the way to make incompetent individuals realize their own
incompetence is to make them competent.
In Study 4, that is precisely what we set out to do. We gave
participants a test of logic based on the Wason selection task
(Wason, 1966) and asked them to assess themselves in a manner
similar to that in the previous studies. We then gave half of theparticipants a short training session designed to improve theirlogical reasoning skills. Finally, we tested the metacognitive skillsof all participants by asking them to indicate which items they had
answered correctly and which incorrectly (after McPherson &Thomas, 1989) and to rate their ability and test performance once
more.
We predicted that training would provide incompetent individuals with the metacognitive skills needed to realize that they had
performed poorly and thus would help them realize the limitationsof their ability. Specifically, we expected that the training would(a) improve the ability of the incompetent to evaluate which test
problems they had answered correctly and which incorrectly and,in the process, (b) reduce the miscalibration of their ability
estimates.

MethodParticipants. Participants were 140 Cornell University undergraduatesfrom a single human development course who earned extra credit toward
their course grades for participating. Data from 4 additional participants
were excluded because they failed to complete the dependent measures.
Procedure. Participants completed the study in groups of 4 to 20
individuals. On arriving at the laboratory, participants were told that theywould be given a test of logical reasoning as part of a study of logic. The
test contained ten problems based on the Wason selection task (Wason,
1966). Each problem described four cards (e.g., A, 7, B, and 4) and a rule
about the cards (e.g., "If the card has a vowel on one side, then it must havean odd number on the other"). Participants then were instructed to indicate
which card or cards must be turned over in order to test the rule.4
After taking the test, participants were asked to rate their logical reasoning skills and performance on the test relative to their classmates on apercentile scale. They also estimated the number of problems they had
solved correctly.
Next, a random selection of 70 participants were given a short logicalreasoning training packet. Modeled after work by Cheng and her colleagues (Cheng, Holyoak, Nisbett, & Oliver, 1986), this packet described
techniques for testing the veracity of logical syllogisms such as the Wason
selection task. The remaining 70 participants encountered an unrelated
filler task that took about the same amount of time (10 min) as did thetraining packet.
Afterward, participants in both conditions completed a metacognition
task in which they went through their own tests and indicated which
problems they thought they had answered correctly and which incorrectly.
Participants then re-estimated the total number of problems they had

answered correctly and compared themselves with their peers in terms of
their general logical reasoning ability and their test performance.

Results and Discussion
Pretraining self-assessments. Prior to training, participants
displayed a pattern of results strikingly similar to that of theprevious three studies. First, participants overall overestimatedtheir logical reasoning ability (M percentile = 64) and test performance (M percentile = 61) relative to their peers, pairedfs(139) = 5.88 and 4.53, respectively, ps < .0001. Participantsalso overestimated their raw score on the test, M — 6.6 (perceived)
versus 4.9 (actual), r(139) = 5.95, p < .0001. As before, perceptions of raw test score, percentile ability, and percentile test score
correlated positively with actual test performance, rs(138) = .50,
.38, and .40, respectively, ps < .0001.
Once again, individuals scoring in the bottom quartile (n = 37)
were oblivious to their poor performance. Although their score on
the test put them in the 13th percentile, they estimated their logicalreasoning ability to be in the 55fh percentile and their performanceon the test to be in the 53rd percentile. Although neither of theseestimates were significantly greater than 50, ?(36) = 1.49 and 0.81,
they were considerably greater than their actual percentile ranking,rs(36) > 10, ps < .0001. Participants in the bottom quartile also
overestimated their raw score on the test. On average, they thought
they had answered 5.5 problems correctly. In fact, they had answered an average of 0.3 problems correctly, r(36) = 10.75, p <.0001.
As Figure 4 illustrates, the level of overestimation once again
decreased with each step up the quartile ladder. As in the previous
studies, participants in the top quartile underestimated their ability.
Whereas their actual performance put them in the 90th percentile,
they thought their general logical reasoning ability fell in the 76th
percentile and their performance on the test in the 79th percentile,«(27) < -3.00, ps < .001. Top-quartile participants also underestimated their raw score on the test (by just over 1 point), but
given that they all achieved perfect scores, this is hardly surprising.
Impact of training. Our primary hypothesis was that training
in logical reasoning would turn the incompetent participants intoexperts, thus providing them with the skills necessary to recognize
the limitations of their ability. Specifically, we expected that thetraining packet would (a) improve the ability of the incompetent tomonitor which test problems they had answered correctly andwhich incorrectly and, thus, (b) reduce the miscalibration of theirself-impressions.
Scores on the metacognition task supported the first part of thisprediction. To assess participants' metacognitive skills, wesummed the number of questions each participant accurately identified as correct or incorrect, out of the 10 problems. Overall,participants who received the training packet graded their own
tests more accurately (M = 9.3) than did participants who did notreceive the packet (M = 6.3), f(138) = 7.32, p < .0001, adifference even more pronounced when looking at bottom-quartile
participants exclusively, Ms = 9.3 versus 3.5, ?(36) = 7.18, p <.0001. In fact, the training packet was so successful that those who
had originally scored in the bottom quartile were just as accurate
in monitoring their test performance as were those who had ini-

* A and 4.

1129

UNSKILLED AND UNAWARE

100 i
908070 42 60 §

50-

CD

a. 40 30 Perceived Ability
Perceived Test Score
Actual Test Score

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

20 10 0Bottom
Quartile

2nd
Quartile

3rd
QuartileTop
Quartile

Figure 4. Perceived logical reasoning ability and test performance as afunction of actual test performance (Study 4).

tially scored in the top quartile, Ms = 9.3 and 9.9, respectively,f(30) = 1.38, ns. In other words, the incompetent had become
experts.
To test the second part of our prediction, we examined theimpact of training on participants' self-impressions in a series of 2
(training: yes or no) X 2 (pre- vs. postmanipulation) X 4 (quartile: 1 through 4) mixed-model analyses of variance (ANOVAs).
These analyses revealed the expected three-way interactions for
estimates of general ability, F(3, 132) = 2.49, p < .07, percentile
score on the test, F(3, 132) = 8.32, p < .001, and raw test score,F(3, 132) = 19.67, p < .0001, indicating that the impact oftraining on self-assessment depended on participants' initial test
performance. Table 2 displays how training influenced the degreeof miscalibration participants exhibited for each measure.
To examine these interactions in greater detail, we conducted
two sets of 2 (training: yes or no) X 2 (pre- vs. postmanipulation)
ANOVAs. The first looked at participants in the bottom quartile,
the second at participants in the top quartile. Among bottomquartile participants, we found the expected interactions for estimates of logical reasoning ability, F(l, 35) = 6.67, p < .02,
percentile test score, F(l, 35) = 14.30, p < .002, and raw testscore, F(l, 35) = 41.0, p < .0001, indicating that the change inparticipants' estimates of their ability and test performance depended on whether they had received training.
As Table 2 depicts, participants in the bottom quartile who hadreceived training (n = 19) became more calibrated in every way.
Before receiving the training packet, these participants believedthat their ability fell in the 55th percentile, that their performanceon the test fell in the 51st percentile, and that they had answered 5.3 problems correctly. After training, these same participants thought their ability fell in the 44th percentile, their test in
the 32nd percentile, and that they had answered only 1.0 problems
correctly. Each of these changes from pre- to posttraining was
significant, f(18) = -2.53, -5.42, and -6.05, respectively,/« <.03. To be sure, participants still overestimated their logical reasoning ability, ?(18) = 5.16, p < .0001, and their performance on
the test relative to their peers, f(18) = 3.30, p < .005, but they
were considerably more calibrated overall and were no longer
miscalibrated with respect to their raw test score, ?(18) = 1.50, ns.
No such increase in calibration was found for bottom-quartile
participants in the untrained group (n = 18). As Table 2 shows,

Table 2
Self-Ratings in Percentile Terms of Ability and Performance for Trained and Untrained Participants (Study •Trained

Untrained
RatingBottom (n, = 18) Second (n = 15) Third (n = 22) Top (n = 15) Bottom (n = 19) Second (n = 20) Third (n = 18) Top {n = 13)
Self-ratings of percentile ability

BeforeAfter
Difference

55.0
55.8
0.8

58.5
56.3
-2.1

67.2
68.1
0.9

78.3
81.9
3.6

54.7
44.3
-10.4*

59.3
52.3
-7.0*

68.6
68.6
0.1

73.4
81.4
8.0

Actual

11.9

32.2

62.9

90.0

14.5

41.0

69.1

90.0

Self-ratings of percentile test performance
BeforeAfter
Difference

55.2
54.3
-0.8

57.9
58.8
0.9

57.5
59.8
2.3

83.1
84.3
1.3

50.5
31.9
-18.6***

53.4
46.8
-6.6*

61.9
69.7
7.8

74.8
86.8
12.1*

Actual

11.9

32.2

62.9

90.0

14.5

41.0

69.1

90.0

Self-ratin gs of raw test ]performance
BeforeAfter
Difference

5.8
6.3
0.6*

5.4
6.1
0.7

6.9
7.5
0.6*

9.3
9.6
0.3

5.3
1.0
-4.3***

5.4
4.1
-1.4*

7.0
8.2
1.2**

8.5
9.9
1.5*

Actual

0.2

2.7

6.7

10.0

0.4

3.3

7.9

10.0

. Note. "Bottom," "Second," "Third," and "Top" refer to quartiles on the grading task.
*/><.O5. * * / » < . 0 1 . ***/>< .001.

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

1130

KRUGER AND DUNNING

they initially reported that both their ability and score on the test
fell in the 55th percentile, and did not change those estimates intheir second set of self-ratings, all rs < 1. Their estimates of their
raw test score, however, did change—but in the wrong direction.
In their initial ratings, they estimated that they had solved 5.8
problems correctly. On their second ratings, they raised that estimate to 6.3, t(17) = 2.62, p < .02.
For individuals who scored in the top quartile, training had avery different effect. As we did for their bottom-quartile counterparts, we conducted a set of 2 (training: yes or no) X 2 (pre- vs.
postmanipulation) ANOVAs. These analyses revealed significant
interactions for estimates of test performance, F(l, 26) = 6.39,
p < .025, and raw score, F(l, 26) = 4.95, p < .05, but not for
estimates of general ability, F(l, 26) = 1.03, ns.
As Table 2 illustrates, top-quartile participants in the training
condition thought their score fell in the 78th percentile prior toreceiving the training materials. Afterward, they increased that
estimate to the 87th percentile, t{\2) = 2.66, p < .025. Topquartile participants also raised their estimates of their percentile
ability, t(l2) = 1.91,p < .09, and raw test score, r(12) = 2.99,/> <.025, although only the latter difference was significant. In contrast, top-quartile participants in the control condition did notrevise their estimates on any of these measures, rs < 1. Although
not predicted, these revisions are perhaps not surprising in light of
the fact that top-quartile participants in the training condition
received validation that the logical reasoning they had used was
perfectly correct.
The mediational role of metacognitive skills. We have argued
that less competent individuals overestimate their abilities because
they lack the metacognitive skills to recognize the error of theirown decisions. In other words, we believe that deficits in metacognitive skills mediate the link between low objective performance and inflated ability assessment. The next two analyses were
designed to test this mediational relationship more explicitly.
In the first analysis, we examined objective performance, metacognitive skill, and the accuracy of self-appraisals in a mannersuggested by Baron and Kenny (1986). According to their procedure, metacognitive skill would be shown to mediate the link
between incompetence and inflated self-assessment if (a) low
levels of objective performance were associated with inflated
self-assessment, (b) low levels of objective performance wereassociated with deficits in metacognitive skill, and (c) deficits inmetacognitive skill were associated with inflated self-assessment
even after controlling for objective performance. Focusing on
the 70 participants in the untrained group, we found considerable
evidence of mediation. First, as reported earlier, participants' test
performance was a strong predictor of how much they overestimated their ability and test performance. An additional analysis
revealed that test performance was also strongly related to metacognitive skill, /3(68) = .75, p < .0001. Finally, and most important, deficits in metacognitive skill predicted inflated selfassessment on the all three self-ratings we examined (generallogical reasoning ability, comparative performance on the test, andabsolute score on the test)—even after objective performance on
the test was held constant. This was true for the first set ofself-appraisals, /3s(67) = —.40 to — .49, ps < .001, as well as thesecond, J3s(67) = - . 4 1 to -.50,ps < .001. 5
Given these results, one could wonder whether the impact oftraining on the self-assessments of participants in the bottom

quartile was similarly mediated by metacognitive skills. To findout, we conducted a mediational analysis focusing on bottom
quartile participants in both trained and untrained groups. Heretoo, all three mediational links were supported. As previously
reported, bottom-quartile participants who received training (a)provided less inflated self-assessments and (b) evidenced bettermetacognitive skills than those who did not receive training. Completing this analysis, regression analyses revealed that metacognitive skills predicted inflated self-assessment with participants'
training condition held constant, £(34)s = —.68 to -.97,ps < .01.
In fact, training itself failed to predict miscalibration when bottomquartile participants' metacognitive skills were taken into account,j8s(34) = .00 to .25, ns. These analyses suggest that the benefit oftraining on the accuracy of self-assessment was achieved by meansof improved metacognitive skills.6
Summary. Thomas Jefferson once said, "he who knows best
best knows how little he knows." In Study 4, we obtained experimental support for this assertion. Participants scoring in the bottom quartile on a test of logic grossly overestimated their test
performance—but became significantly more calibrated after theirlogical reasoning skills were improved. In contrast, those in thebottom quartile who did not receive this aid continued to hold themistaken impression that they had performed just fine. Moreover,mediational analyses revealed that it was by means of their improved metacognitive skills that incompetent individuals arrived attheir more accurate self-appraisals.
General Discussion
In the neurosciences, practitioners and researchers occasionallycome across the curious malady of anosognosia. Caused by certain
types of damage to the right side of the brain, anosognosia leaves
people paralyzed on the left side of their body. But more than that,when doctors place a cup in front of such patients and ask them topick it up with their left hand, patients not only fail to comply but
also fail to understand why. When asked to explain their failure,
such patients might state that they are tired, that they did not hear
the doctor's instructions, or that they did not feel like responding—but never that they are suffering from paralysis. In essence,anosognosia not only causes paralysis, but also the inability torealize that one is paralyzed (D'Amasio, 1994).
In this article, we proposed a psychological analogue to anosognosia. We argued that incompetence, like anosognosia, not only
causes poor performance but also the inability to recognize that
one's performance is poor. Indeed, across the four studies, participants in the bottom quartile not only overestimated themselves,
but thought they were above-average, Z = 4.64, p < .0001. In a5
A mediational analysis of the absolute miscalibration (independent ofsign) in participants' self-appraisals revealed a similar pattern: Controllingfor objective performance on the test, deficits in metacognitive skill predicted absolute miscalibration on the all three self-ratings we examined forboth the first set of self-appraisals, j3s(67) = - . 5 3 to - . 7 8 , ps < .001, andthe second, /3s(67) = -.60 to -.79, ps < .0001
6
An analysis of the absolute miscalibration (independent of sign) revealed a similar pattern. Controlling for objective performance on the test,
deficits in bottom-quartile participants' metacognitive skill predicted theirabsolute miscalibration on all three of the self-ratings, |3s(34) = — .79 to- . 9 8 , ps < .01.

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

UNSKILLED AND UNAWARE

phrase, Thomas Gray was right: Ignorance is bliss—at least whenit comes to assessments of one's own ability.
What causes this gross overestimation? Studies 3 and 4 pointed
to a lack of metacognitive skills among less skilled participants.
Bottom-quartile participants were less successful than were topquartile participants in the metacognitive tasks of discerning what
one has answered correctly versus incorrectly (Study 4) and distinguishing superior from inferior performances on the part of
one's peers (Study 3). More conclusively, Study 4 showed that
improving participants' metacognitive skills also improved theaccuracy of their self-appraisals. Note that these findings areinconsistent with a simple regression effect interpretation of ourresults, which does not predict any changes in self-appraisals given
different levels of metacognitive skill. Regression also cannot
explain the fact that bottom-quartile participants were nearly 4times more miscalibrated than their top-quartile counterparts.
Study 4 also revealed a paradox. It suggested that one way tomake people recognize their incompetence is to make them competent. Once we taught bottom-quartile participants how to solve
Wason selection tasks correctly, they also gained the metacognitive skills to recognize the previous error of their ways. Of course,
and herein lies the paradox, once they gained the metacognitive
skills to recognize their own incompetence, they were no longer
incompetent. "To have such knowledge," as Miller (1993) put it in
the quote that began this article, "would already be to remedy agood portion of the offense."

The Burden of Expertise
Although our emphasis has been on the miscalibration of incompetent individuals, along the way we discovered that highly
competent individuals also show some systematic bias in their self
appraisals. Across the four sets of studies, participants in the top
quartile tended to underestimate their ability and test performance
relative to their peers, Zs = —5.66 and —4.77, respectively, ps <.0001. What accounts for this underestimation? Here, too, theregression effect seems a likely candidate: Just as extremely low
performances are likely to be associated with slightly higher perceptions of performance, so too are extremely high performances
likely to be associated with slightly lower perceptions of
performance.
As it turns out, however, our data point to a more psychologicalexplanation. Specifically, top-quartile participants appear to havefallen prey to a false-consensus effect (Ross et al, 1977). Simply
put, these participants assumed that because they performed sowell, their peers must have performed well likewise. This would
have led top-quartile participants to underestimate their comparative abilities (i.e., how their general ability and test performancecompare with that of their peers), but not their absolute abilities(i.e., their raw score on the test). This was precisely the pattern ofdata we observed: Compared with participants falling in the third
quartile, participants in the top quartile were an average of 23%
less calibrated in terms of their comparative performance on thetest—but 16% more calibrated in terms of their objective performance on the test.7
More conclusive evidence came from Phase 2 of Study 3. Once
top-quartile participants learned how poorly their peers had performed, they raised their self-appraisals to more accurate levels.
We have argued that unskilled individuals suffer a dual burden:1131

Not only do they perform poorly, but they fail to realize it. It thus
appears that extremely competent individuals suffer a burden as
well. Although they perform competently, they fail to realize that
their proficiency is not necessarily shared by their peers.

Incompetence and the Failure of Feedback
One puzzling aspect of our results is how the incompetent fail,through life experience, to learn that they are unskilled. This is nota new puzzle. Sullivan, in 1953, marveled at "the failure oflearning which has left their capacity for fantastic, self-centereddelusions so utterly unaffected by a life-long history of educative
events" (p. 80). With that observation in mind, it is striking that ourstudent participants overestimated their standing on academicallyoriented tests as familiar to them as grammar and logical reasoning. Although our analysis suggests that incompetent individuals
are unable to spot their poor performances themselves, one would
have thought negative feedback would have been inevitable atsome point in their academic career. So why had they not learned?
One reason is that people seldom receive negative feedback
about their skills and abilities from others in everyday life (Blumberg, 1972; Darley & Fazio, 1980; Goffman, 1955; Matlin &Stang, 1978; Tesser & Rosen, 1975). Even young children arefamiliar with the notion that "if you do not have something nice tosay, don't say anything at all." Second, the bungled robbery
attempt of McArthur Wheeler not withstanding, some tasks andsettings preclude people from receiving self-correcting information that would reveal the suboptimal nature of their decisions(Einhorn, 1982). Third, even if people receive negative feedback,they still must come to an accurate understanding of why that
failure has occurred. The problem with failure is that it is subject
to more attributional ambiguity than success. For success to occur,
many things must go right: The person must be skilled, apply
effort, and perhaps be a bit lucky. For failure to occur, the lack of
any one of these components is sufficient. Because of this, even if
people receive feedback that points to a lack of skill, they may
attribute it to some other factor (Snyder, Higgins, & Stucky, 1983;
Snyder, Shenkel, & Lowery, 1977).
Finally, Study 3 showed that incompetent individuals may beunable to take full advantage of one particular kind of feedback:social comparison. One of the ways people gain insight into theirown competence is by watching the behavior of others (Festinger,
1954; Gilbert, Giesler & Morris, 1995). In a perfect world, everyone could see the judgments and decisions that other people reach,accurately assess how competent those decisions are, and thenrevise their view of their own competence by comparison. However, Study 3 showed that incompetent individuals are unable totake full advantage of such opportunities. Compared with theirmore expert peers, they were less able to spot competence when
they saw it, and as a consequence, were less able to learn that theirability estimates were incorrect.

7
These data are based on the absolute miscalibration (regardless of sign)in participants' estimates across the three studies in which both comparative and objective measures of perceived performance were assessed (Studies 2, 3, and 4).

1132

KRUGER AND DUNNING

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Limitations of the Present Analysis
We do not mean to imply that people are always unaware of
their incompetence. We doubt whether many of our readers would
dare take on Michael Jordan in a game of one-on-one, challenge
Eric Clapton with a session of dueling guitars, or enter into afriendly wager on the golf course with Tiger Woods. Nor do wemean to imply that the metacognitive failings of the incompetentare the only reason people overestimate their abilities relative totheir peers. We have little doubt that other factors such as motivational biases (Alicke, 1985; Brown, 1986; Taylor & Brown,1988), self-serving trait definitions (Dunning & Cohen, 1992;
Dunning et al., 1989), selective recall of past behavior (Sanitioso,
Kunda, & Fong, 1990), and the tendency to ignore the proficiencies of others (Klar, Medding, & Sarel, 1996; Kruger, 1999) also
play a role. Indeed, although bottom-quartile participants accounted for the bulk of the above-average effects observed in ourstudies (overestimating their ability by an average of 50 percentile
points), there was also a slight tendency for the other quartiles tooverestimate themselves (by just over 6 percentile points)—a fact
our metacognitive analysis cannot explain.
When can the incompetent be expected to overestimate themselvesbecause of their lack of skill? Although our data do not speak to thisissue directly, we believe the answer depends on the domain underconsideration. Some domains, like those examined in this article, arethose in which knowledge about the domain confers competence inthe domain. Individuals with a great understanding of the rules ofgrammar or inferential logic, for example, are by definition skilled
linguists and logicians. In such domains, lack of skill implies both theinability to perform competently as well as the inability to recognize
competence, and thus a¥e also the domains in which the incompetentare likely to be unaware of their lack of skill.
In other domains, however, competence is not wholly dependent
on knowledge or wisdom, but depends on other factors, such as
physical skill. One need not look far to find individuals with animpressive understanding of the strategies and techniques of basketball, for instance, yet who could not "dunk" to save their lives.
(These people are called coaches.) Similarly, art appraisers make aliving evaluating fine calligraphy, but know they do not possess
the steady hand and patient nature necessary to produce the work
themselves. In such domains, those in which knowledge about thedomain does not necessarily translate into competence in thedomain, one can become acutely—even painfully—aware of thelimits of one's ability. In golf, for instance, one can know all about
the fine points of course management, club selection, and effective"swing thoughts," but one's incompetence will become sorely
obvious when, after watching one's more able partner drive theball 250 yards down the fairway, one proceeds to hit one's ownball 150 yards down the fairway, 50 yards to the right, and onto thehood of that 1993 Ford Taurus.
Finally, in order for the incompetent to overestimate themselves,
they must satisfy a minimal threshold of knowledge, theory, or
experience that suggests to themselves that they can generatecorrect answers. In some domains, there are clear and unavoidable
reality constraints that prohibits this notion. For example, mostpeople have no trouble identifying their inability to translate Slovenian proverbs, reconstruct an 8-cylinder engine, or diagnose
acute disseminated encephalomyelitis. In these domains, withouteven an intuition of how to respond, people do not overestimate

their ability. Instead, if people show any bias at all, it is to ratethemselves as worse than their peers (Kruger, 1999).

Relation to Work on Overconfidence
The finding that people systematically overestimate their ability
and performance calls to mind other work on calibration in whichpeople make a prediction and estimate the likelihood that theprediction will prove correct. Consistently, the confidence withwhich people make their predictions far exceeds their accuracy
rates (e.g., Dunning, Griffin, Milojkovic, & Ross, 1990; Vallone,
Griffin, Lin, & Ross, 1990; Lichtenstein, Fischhoff, & Phillips,
1982).
Our data both complement and extend this work. In particular,
work on overconfidence has shown that people are more miscalibrated when they face difficult tasks, ones for which they fail topossess the requisite knowledge, than they are for easy tasks, ones
for which they do possess that knowledge (Lichtenstein & Fischhoff, 1977). Our work replicates this point not by looking at
properties of the task but at properties of the person. Whether thetask is difficult because of the nature of the task or because theperson is unskilled, the end result is a large degree ofoverconfidence.
Our data also provide an empirical rebuttal to a critique that has
been leveled at past work on overconfidence. Gigerenzer (1991)
and his colleagues (Gigerenzer, Hoffrage, & Kleinbolting, 1991)
have argued that the types of probability estimates used in traditional overconfidence work—namely, those concerning the occurrence of single events—are fundamentally flawed. According to
the critique, probabilities do not apply to single events but only tomultiple ones. As a consequence, if people make probability
estimates in more appropriate contexts (such as by estimating thetotal number of test items answered correctly), "cognitive illusions" such as overconfidence disappear. Our results call thiscritique into question. Across the three studies in which we haverelevant data, participants consistently overestimated the numberof items they had answered correctly, Z = 4.94, p < .0001.
Concluding Remarks
In sum, we present this article as an exploration into why people
tend to hold overly optimistic and miscalibrated views about
themselves. We propose that those with limited knowledge in adomain suffer a dual burden: Not only do they reach mistaken
conclusions and make regrettable errors, but their incompetencerobs them of the ability to realize it. Although we feel we havedone a competent job in making a strong case for this analysis,
studying it empirically, and drawing out relevant implications, ourthesis leaves us with one haunting worry that we cannot vanquish.
That worry is that this article may contain faulty logic, methodological errors, or poor communication. Let us assure our readersthat to the extent this article is imperfect, it is not a sin we havecommitted knowingly.
References
Alicke, M. D. (1985). Global self-evaluation as determined by the desirability and controllability of trait adjectives. Journal of Personality andSocial Psychology, 49, 1621-1630.
Alicke, M. D., Klotz, M L., Breitenbecher, D. L., Yurak, T. J., & Vre-

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

UNSKILLED AND UNAWARE
denburg, D. S. (1995). Personal contact, individuation, and the betterthan-average effect. Journal of Personality and Social Psychology, 68,
804-825.
Allen, W. (1975). Without feathers. New York, NY: Random House.
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable
distinction in social psychological research. Journal of Personality andSocial Psychology, 51, 1173-1182.
Bern, D. J., & Lord, C. G. (1979). Template matching: A proposal for
probing the ecological validity of experimental settings in social psychology. Journal of Personality and Social Psychology, 37, 833-846.
Blumberg, H. H. (1972). Communication of interpersonal evaluations.
Journal of Personality and Social Psychology, 23, 157-162.
Bobrow, J., Nathan, N., Fisher, S., Covino, W. A., Orton, P. Z., Bobrow,B., & Weber, L. (1989). Cliffs NTE preparation guide. Lincoln, NE:
Cliffs Notes, Inc.
Brown, J. D. (1986). Evaluations of self and others: Self-enhancement
biases in social judgments. Social Cognition, 4, 353-376.
Brown, J. D., & Gallagher, F. M. (1992). Coming to terms with failure:
Private self-enhancement and public self-effacement. Journal of Experimental Social Psychology, 28, 3-22.
Cheng, P. W., Holyoak, K. J., Nisbett, R. E., & Oliver, L. M. (1986).
Pragmatic versus syntactic approaches to training deductive reasoning.
Cognitive Psychology, 18, 293-328.
Chi, M. T. H. (1978). Knowledge structures and memory development. In
R. Siegler (Ed.), Children's thinking: What develops? (pp. 73-96).
Hillsdale, NJ: Erlbaum.
Chi, M. T. H., Glaser, R., & Rees, E. (1982). Expertise in problem solving.
In R. Sternberg (Ed.), Advances in the psychology of human intelligence(Vol. 1, pp. 17-76). Hillsdale, NJ: Erlbaum.
College Board. (1976-1977). Student descriptive questionnaire. Princeton,
NJ: Educational Testing Service.
Cross, P. (1977). Not can but will college teaching be improved? New
Directions for Higher Education, 17, 1-15.
D'Amasio, A. R. (1994). Descartes' error: Emotion, reason, and thehuman brain. New York: Putnam.
Darley, J. M., & Fazio, R. H. (1980). Expectancy confirmation processes
arising in the social interaction sequence. American Psychologist, 35,
867-881.
Darwin, C. (1871). The descent of man. London: John Murray.
Dunning, D., & Cohen, G. L. (1992). Egocentric definitions of traits andabilities in social judgment. Journal of Personality and Social Psychology, 63, 341-355.
Dunning, D., Griffin, D. W., Milojkovic, J. D., & Ross, L. (1990). The
overconfidence effect in social prediction. Journal of Personality andSocial Psychology, 58, 568-581.
Dunning, D., Meyerowitz, J. A., & Holzberg, A. D. (1989). Ambiguity andself-evaluation: The role of idiosyncratic trait definitions in self-serving
assessments of ability. Journal of Personality and Social Psychology, 57, 1082-1090.
Dunning, D., Perie, M., & Story, A. L. (1991). Self-serving prototypes ofsocial categories. Journal of Personality and Social Psychology, 61,
957-968.
Einhom, H. J. (1982). Learning from experience and suboptimal rules indecision making. In D. Kahneman, P. Slovic, & A. Tversky (Eds.),
Judgment under uncertainty: Heuristics and biases (pp. 268-286). New
York: Cambridge University Press.
Everson, H. T., & Tobias, S. (1998). The ability to estimate knowledge andperformance in college: A metacognitive analysis. Instructional Science, 26, 65-79.
Fagot, B. I., & O'Brien, M. (1994). Activity level in young children:
Cross-age stability, situational influences, correlates with temperament,
and the perception of problem behaviors. Merrill Palmer Quarterly, 40,
378-398.

1133

Felson, R. B. (1981). Ambiguity and bias in the self-concept. Social
Psychology Quarterly, 44, 64-69.
Festinger, L. (1954). A theory of social comparison processes. Human
Relations, 7, 117-140.
Frankin, A. (1992). Deep Thoughts by Jack Handy. New York: Berkley
Publishing Group.
Fuocco, M. A. (1996, March 21). Trial and error: They had larceny in theirhearts, but little in their heads. Pittsburgh Post-Gazette, p. Dl.
Gigerenzer, G. (1991). How to make cognitive illusions disappear: Beyond"heuristics and biases." European Review of Social Psychology, 2,
83-115.
Gigerenzer, G., Hoffrage, U., & Kleinbolting, H. (1991). Probabilistic
mental models: A Brunswickian theory of confidence. Psychological
Review, 98, 506-528.
Gilbert, D. T., Giesler, R. B., & Morris, K. E. (1995). When comparisonsarise. Journal of Personality and Social Psychology, 69, 227—236.
Goffman, E. (1955). On face-work: An analysis of ritual elements in social
interaction. Psychiatry: Journal for the Study of Interpersonal Processes, 18, 213-231.
Klar, Y., Medding, A., & Sarel, D. (1996). Nonunique invulnerability:
Singular versus distributional probabilities and unrealistic optimism incomparative risk judgments. Organizational Behavior and Human Decision Processes, 67, 229-245.
Klin, C. M., Guizman, A. E., & Levine, W. H. (1997). Knowing that you
don't know: Metamemory and discourse processing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23, 1378-1393.
Kruger, J. (1999). Lake Wobegon be gone! The "below-average effect" andthe egocentric nature of comparative ability judgments. Journal of
Personality and Social Psychology, 77, 221—232.
Kunkel, E. (1971). On the relationship between estimate of ability anddriver qualification. Psychologie und Praxis, 15, 73—80.
Larwood, L., & Whittaker, W. (1977). Managerial myopia: Self-serving
biases in organizational planning. Journal of Applied Psychology, 62,
194-198.
Lichtenstein, S., & Fischhoff, B. (1977). Do those who know more also
know more about how much they know? The calibration of probability
judgments. Organizational Behavior and Human Performance, 20,
159-193.
Lichtenstein, S., Fischhoff, B., & Phillips, L. D. (1982). Calibration ofprobabilities: The state of the art to 1980. In D. Kahneman, P. Slovic, &A. Tversky (Ed.), Judgment under uncertainty: Heuristics and biases(pp. 306-334). New York: Cambridge University Press.
Maki, R. H., Jonas, D., & Kallod, M. (1994). The relationship between
comprehension and metacomprehension ability. Psychonomic Bulletin& Review, 1, 126-129.
Matlin, M., & Stang, D. (1978). The Pollyanna principle. Cambridge, MA:
Schenkman.
McPherson, S. L., & Thomas, J. R. (1989). Relation of knowledge andperformance in boys' tennis: Age and expertise. Journal of Experimental
Child Psychology, 48, 190-211.
Metcalfe, J. (1998). Cognitive optimism: Self-deception or memory-based
processing heuristics? Personality and Social Psychology Review, 2,
100-110.
Miller, W. I. (1993). Humiliation. Ithaca, NY: Cornell University Press.
Moreland, R., Miller, J., & Laucka, F. (1981). Academic achievement andself-evaluations of academic performance. Journal of Educational Psychology, 73, 335-344.
Orton, P. Z. (1993). Cliffs Law School Admission Test preparation guide.
Lincoln, NE: Cliffs Notes Incorporated.
Ross, L., Greene, D., & House, P. (1977). The false consensus effect: An
egocentric bias in social perception and attributional processes. Journalof Experimental Social Psychology, 13, 279-301.
Rovin, J. (1996). More Really Silly Pet Jokes. Boca Raton, FL: Globe
Communications Corp.

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

1134

KRUGER AND DUNNING

Sanitioso, R., Kunda, Z,, & Fong, G. T. (1990). Motivated recruitment of
autobiographical memories. Journal of Personality and Social Psychology, 59, 229-241.
Shaughnessy, J. J. (1979). Confidence judgment accuracy as a predictor oftest performance. Journal of Research in Personality, 13, 505-514.
Sinkavich, F. J. (1995). Performance and metamemory: Do students knowwhat they don't know? Instructional Psychology, 22, 77-87.
Snyder, C. R., Higgins, R. L., & Stucky, R. J. (1983). Excuses: Masquerades in search of grace. New York: Wiley.
Snyder, C. R., Shenkel, R. J., & Lowery, C. R. (1977). Acceptance of
personality interpretations: The "Barnum effect" and beyond. Journal ofConsulting and Clinical Psychology, 45, 104-114.
Story, A. L., & Dunning, D. (1998). The more rational side of self-serving
prototypes: The effects of success and failure performance feedback.
Journal of Experimental Social Psychology, 34, 513—529.
Sullivan, H. S. (1953). Conceptions of modern psychiatry. New York:
Norton.
Taylor, S. E., & Brown, J. D. (1988). Illusion and well-being: A social
psychological perspective on mental health. Psychological Bulletin, 103,
193-210.

Tesser, A., & Rosen, S. (1975). The reluctance to transmit bad news. In L.
Berkowitz (Ed.), Advances in experimental psychology (Vol. 8, pp.
193-232). New York: Academic Press.
Thomhill, R., & Gangestad, S. W. (1993). Human facial beauty: Averageness, symmetry, and parasite resistance. Human Nature, 4, 237-269.
Vallone, R. P., Griffin, D. W., Lin, S., & Ross, L. (1990). Overconfident
prediction of future actions and outcomes by self and others. Journal of
Personality and Social Psychology, 58, 582-592.
Wason, P. C. (1966). Reasoning. In B. M. Foss (Ed.), New horizons in
psychology (pp. 135—151). Baltimore: Penguin Books.
Weinstein, N. D. (1980). Unrealistic optimism about future life events.
Journal of Personality and Social Psychology, 39, 806-820.
Weinstein, N. D., & Lachendro, E. (1982). Egocentrism as a source of
unrealistic optimism. Personality and Social Psychology Bulletin, 8,

195-200.
Received January 25, 1999
Revision received May 28, 1999
Accepted June 10, 1999