AUTOMATIZATION AND TRAINING IN VISUAL-SEARCH

In several search tasks, the amount of practice on particular combinations of targets and distractors was equated in varied-mapping (VM) and consistent-mapping (CM) conditions. The results indicate the importance of distinguishing between memory and visual search tasks, and implicate a number of factors that play important roles in visual search and its learning. Visual search was studied in Experiment 1. VM and CM performance were almost equal, and slope reductions occurred during practice for both, suggesting the learning of efficient attentive search based on features, and no important role for automatic attention attraction. However, positive transfer effects occurred when previous CM targets were re-paired with previous CM distractors, even though these targets and distractors had not been trained together. Also, the introduction of a demanding simultaneous task produced advantages of CM over VM. These latter two results demonstrated the operation of automatic attention attraction. Visual search was further studied in Experiment 2, using novel characters for which feature overlap and similarity were controlled. The design and many of the findings paralleled Experiment 1. In addition, enormous search improvement was seen over 35 sessions of training, suggesting the operation of perceptual unitization for the novel characters. Experiment 3 showed a large, persistent advantage for CM over VM performance in memory search, even when practice on particular combinations of targets and distractors was equated in the two training conditions. A multifactor theory of automatization and attention is put forth to account for these findings and others in the literature.