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How unaware are the unskilled? Empirical tests of the “signal extraction” counterexplanation for the Dunning–Kruger effect in self-evaluation of performance

Author

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  • Schlösser, Thomas
  • Dunning, David
  • Johnson, Kerri L.
  • Kruger, Justin

Abstract

Previous work on the Dunning–Kruger effect has shown that poor performers often show little insight into the shortcomings in their performance, presumably because they suffer a double curse. Deficits in their knowledge prevent them from both producing correct responses and recognizing that the responses they produce are inferior to those produced by others. Krajč and Ortmann (2008) offered a different account, suggesting instead that poor performers make performance estimates with no more error than top performers. Floor effects, coupled with the assumption of a backwards-J performance distribution, force their self-evaluations errors to be frequently positive in nature. Krajč and Ortmann, however, offered no empirical data to test their “signal extraction” account. In three studies, we assessed their theoretical model by examining whether (1) the data producing the Dunning–Kruger effect fit the statistical assumptions considered by Krajč and Ortmann necessary to produce it, and (2) to see if their framework reproduced Dunning–Kruger errors in a data set that fit their statistical assumptions. We found that the Krajč–Ortmann framework failed to anticipate self-evaluative misperceptions on the part of poor performers, but that it does much better at accounting for misperceptions among top performers. Paradoxically, the model suggests that Kruger and Dunning (1999) may have underestimated the accuracy of top performers, even though their account asserts such accuracy.

Suggested Citation

  • Schlösser, Thomas & Dunning, David & Johnson, Kerri L. & Kruger, Justin, 2013. "How unaware are the unskilled? Empirical tests of the “signal extraction” counterexplanation for the Dunning–Kruger effect in self-evaluation of performance," Journal of Economic Psychology, Elsevier, vol. 39(C), pages 85-100.
  • Handle: RePEc:eee:joepsy:v:39:y:2013:i:c:p:85-100
    DOI: 10.1016/j.joep.2013.07.004
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    References listed on IDEAS

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    1. Krajc, Marian & Ortmann, Andreas, 2008. "Are the unskilled really that unaware? An alternative explanation," Journal of Economic Psychology, Elsevier, vol. 29(5), pages 724-738, November.
    2. Ehrlinger, Joyce & Johnson, Kerri & Banner, Matthew & Dunning, David & Kruger, Justin, 2008. "Why the unskilled are unaware: Further explorations of (absent) self-insight among the incompetent," Organizational Behavior and Human Decision Processes, Elsevier, vol. 105(1), pages 98-121, January.
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    Cited by:

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    4. Jan R. Magnus & Anatoly A. Peresetsky, 2021. "A statistical explanation of the Dunning-Kruger effect," Working Papers w0286, New Economic School (NES).
    5. Ingrid Taylor & Pia Bing‐Jonsson & Sigrid Wangensteen & Elisabeth Finnbakk & Leiv Sandvik & Brendan McCormack & Lisbeth Fagerström, 2020. "The self‐assessment of clinical competence and the need for further training: A cross‐sectional survey of advanced practice nursing students," Journal of Clinical Nursing, John Wiley & Sons, vol. 29(3-4), pages 545-555, February.
    6. Bruce Hewitson & Katinka Waagsaether & Jan Wohland & Kate Kloppers & Teizeen Kara, 2017. "Climate information websites: an evolving landscape," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 8(5), September.
    7. Brookins, Philip & Lucas, Adriana & Ryvkin, Dmitry, 2014. "Reducing within-group overconfidence through group identity and between-group confidence judgments," Journal of Economic Psychology, Elsevier, vol. 44(C), pages 1-12.
    8. Peter J. Baldacchino & Chantelle Camilleri & Simon Grima & Frank H. Bezzina, 2017. "Assessing Incentive and Monitoring Schemes in the Corporate Governance of Maltese Co-operatives," European Research Studies Journal, European Research Studies Journal, vol. 0(3A), pages 177-195.
    9. Meeran, Sheik & Goodwin, Paul & Yalabik, Baris, 2016. "A parsimonious explanation of observed biases when forecasting one’s own performance," International Journal of Forecasting, Elsevier, vol. 32(1), pages 112-120.
    10. Benjamin Heslop & Kylie Bailey & Jonathan Paul & Elizabeth Stojanovski, 2018. "The PILAR Model as a Measure of Peer Ratings of Collaboration Viability in Small Groups," Social Sciences, MDPI, vol. 7(3), pages 1-14, March.
    11. Dunkel, Curtis S. & Nedelec, Joseph & van der Linden, Dimitri, 2023. "Reevaluating the Dunning-Kruger effect: A response to and replication of Gignac and Zajenkowski (2020)," Intelligence, Elsevier, vol. 96(C).

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    More about this item

    Keywords

    Calibration; Judgment errors; Performance evaluation; Metacognition; Self-evaluation; Overconfidence;
    All these keywords.

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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