Identification of dot patterns from memory as a function of complexity.

Abstract

The identification of dot patterns from memory was studied as a function of the complexity of the patterns. Each of 768 basic trainees was required to learn the corresponding arbitrary city names for a group of 12 random dot patterns representing the possible appearance of each city on a radar scope. The number of dots in the patterns was varied from 1 to 12 for independent groups of Ss as a means of varying complexity. The results indicate that a degree of complexity represented by 6 to 8 dots is optimal for identification under these conditions. Ease of identification is clearly shown to be associated with patterns having dots arranged either symmetrically or in linear arrays.