@inproceedings{f5f1850e697a48a09c77e8b73ddc11ce,
title = "Modeling the Dunning-Kruger Effect: A Rational Account of Inaccurate Self-Assessment",
abstract = "Self-assessment, or the evaluation of one's ability on a task, is widely perceived as a fundamental skill, yet in most studies, people are found to be poorly calibrated to their own abilities. Some results seem to show poorer calibration for low performers than for high performers. This effect has been explained in multiple ways: it could indicate worse metacognitive ability among the low performers (the “Dunning-Kruger” effect), or simply regression to the mean. To tease apart these explanations we develop a Bayesian model of self-assessment and evaluate its predictions in two experiments. Our results suggest that poor self-assessment is caused by the influence of prior beliefs and imperfect skill at determining whether a problem was solved correctly or not, and offer only weak support for of a relationship between metacognitive ability and performance.",
keywords = "Bayesian modeling, logical reasoning, metacognition, self-assessment",
author = "Jansen, {Rachel A.} and Rafferty, {Anna N.} and Griffiths, {Thomas L.}",
note = "Publisher Copyright: {\textcopyright} 2018 Proceedings of the 40th Annual Meeting of the Cognitive Science Society, CogSci 2018. All rights reserved.; 40th Annual Meeting of the Cognitive Science Society: Changing Minds, CogSci 2018 ; Conference date: 25-07-2018 Through 28-07-2018",
year = "2018",
language = "English (US)",
series = "Proceedings of the 40th Annual Meeting of the Cognitive Science Society, CogSci 2018",
publisher = "The Cognitive Science Society",
pages = "548--553",
booktitle = "Proceedings of the 40th Annual Meeting of the Cognitive Science Society, CogSci 2018",
}