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My guess is that the spread in self-evaluation is largest at low skill level and decreases as skill level increases. This would produce results more similar to what D-K actually observed, and is much more plausible than postulating that highly skilled people have no more idea of their skill level than low skilled people.

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What strikes me about that graph is that the entire group is likely to be more skilled than the general population. The selection only of people who have the interest and means to attend higher education seems like a narrow window at the furthest edge of the true graph. So I wonder what it would look like if we included people of all education levels and social strata?

My gut, based on this article, is that it would look generally the same but with a larger spread at the lower end of the scale. But I don't think we can truly say we've disproved the Dunning-Kruger effect without a more varied dataset.

I dunno, if we account for the whole mosaic I think there is a higher probability of younger Cornell undergraduates performing poorly and self-assessing highly. They could very well be thinking, and especially against the backdrop of their high school peers, that they know it all. I think the explanation of "You don't know what you don't know." with a splash of "I'm the top 10% of my public high school class!" moreover I'd operate with the presumption they don't read outside of the curricula and so they're exceedingly unaware of the boundaries of their knowledge within the bounds of all knowledge, and the scope of the surface they cover. It's a wonder that they're as accurate as they are. But I think that has to do with the nature of the test, which as I recall was something like the ACT/SAT where they're effectively only testing to 8th grade standards. What happens if they test people against the whole of human knowledge?

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