Item recognition with automatized performance.

A theory for automatized performance in item recognition tasks is outlined. Automation occurs during practice with consistent mappings of stimuli to responses. Automatized processing at stages of pattern recognition, binary coding, and response evocation is described in sufficient detail to provide a qualitative explanation for (a) extant data on transfer of training (where previous theories fail), (b) known effects of visual confusability and positive set size, and (c) null effect of negative set size (demonstrated in Experiment 1). The effects of visual confusability and positive set size are ascribed to the stage of pattern recognition; it is suggested that their joint effects on reaction times and error rates (measured in Experiment 2) be explained at a quantitative level by a parallel random walk recognition model.

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