Abstract
S's task was to learn the correct method for classifying visually presented geometric patterns. Misinformation feedback (MF) was a significant source of variance in the analysis. The relationship between errors and Complexity was found to be linear. The relationship between the reciprocal of the estimated proportion of relevant cues and the number of irrelevant dimensions was linear in accordance with Restle's learning model. Number of errors as predicted by this model was greatly divergent from the obtained errors for all the combined MF X Complexity conditions. (PsycINFO Database Record (c) 2006 APA, all rights reserved)