Perceptual Learning in Correlation Estimation: The Role of Learning Category Organization

AbstractResearch has shown that estimation of correlation from scatter plots is done poorly by both novices and experts. We tested whether proficiency in correlation estimation could be improved by perceptual learning interventions, in the form of perceptual-adaptive learning modules (PALMs). We also tested learning effects of alternative category structures in perceptual learning. We organized the same set of 252 scatter plot displays either into a PALM that implemented spacing in learning by shape categories or one in which the categories were ranges of correlation strength. Both PALMs produced markedly reduced errors, and both led trained participants to classify near transfer items as accurately as trained items. Differences in category organization produced modest effects on learning; there was some indication of more consistent reduction of absolute error when learning categories were organized by shape, whereas average bias of judgments was best reduced by categories organized by different numerical ranges of correlation.

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