Abstract
A variable based on the Gestalt principle of organizational unity (meaningfulness) was combined with feature measures of polygons (reflecting area and jaggedness), and measures of differences in feature levels, in an attempt to predict discrimination latency for 20 polygons. Meaningfulness was evaluated through a free-learning, free-recall paired-associate task with polygons and numbers, and was found to be independent of all measures based on physical features of form. When meaningfulness was combined with dmax (a measure reflecting selective attention to the maximum discriminating feature) in an attempt to predict latency, a multiple correlation of .85 was obtained for 10 Ss (who had previously performed the paired-associate task), and a multiple correlation of .70 for another group of ten Ss (who performed only the discrimination-latency task). Direct feature measures were not significantly related to latency for either group of Ss, and latencies from the groups were significantly intercorrelated. Results were interpreted as indicating the existence of two independent predictors of discrimination latency—one based on the component feature measures of forms (dmax) and one on the organizational unity of forms (meaningfulness).
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