> I really don't see how it concludes that the DK effect is wrong based on the analysis. Neither do I. Basically what the article actually shows is that these

> I really don't see how it concludes that the DK effect is wrong based on the analysis. Neither do I. Basically what the article actually shows is that these two statements are equivalent: (1) People with low test scores tend to overpredict their test scores, while people with high test scores tend to underpredict their test scores. (2) People's predictions of their test scores are uncorrelated (or more precisely very weakly correlated [1]) with their actual test scores. This is not a statement that the D-K effect is wrong. It's just restating what the D-K effect is in different words. All the talk about "autocorrelation" is just another way of saying that, if people's predictions of their test scores are only weakly correlated with their test scores, then people with low test scores will have to overpredict their test scores (because there's virtually no room to underpredict them--there's a minimum possible test score and their actual score is already close to it), and people with high test scores will have to underpredict them (because there's virtually no room to overpredict them--there's a maximum possible test score and their actual score is already close to it). But the real question is: why are x and y so weakly correlated? Why are people's predictions of their test scores so weakly correlated with their actual test scores? That is not what one would intuitively expect. That is the question the D-K effect raises, and the author not only doesn't answer it, he doesn't even see it. Also, this statement in the description of the Nuhfer research doesn't make sense: "What’s important here is that people’s ‘skill’ is measured independently from their test performance and self assessment." Um, the test performance is the people's "skill". And in the original D-K research, it was "measured independently" from the people's self-assessment (their prediction of their test performance). [1] Notice that in the "uncorrelated data" graph, Figure 10, the red line is basically horizontal. That's what you get when x and y are uncorrelated. But in the original D-K graph, Figure 2, the thick black line is not horizontal--it slopes upward. That's what you get when x and y are weakly correlated. If the author had put in a weak correlation between x and y in his own experiment, he would have gotten a graph that looked like Figure 2. But of course that still would do nothing to explain why x and y are so weakly correlated, which is the actual question.