1. Generalization gradients as indicants of learning and retention of a recognition task
- Author
-
Harry P. Bahrick, Sandra E. Clark, and Phyllis Bahrick
- Subjects
Similarity (geometry) ,Series (mathematics) ,Stimulus generalization ,business.industry ,Generalization ,Pattern recognition ,General Medicine ,Function (mathematics) ,Task (project management) ,Learning curve ,Statistics ,Artificial intelligence ,Sensitivity (control systems) ,business ,Mathematics - Abstract
Ss were required to select previously exposed pictures of common objects from among series of alternative pictures graded in similarity to the prototypes. Response frequencies were plotted in the form of generalization gradients, and such gradients were obtained following 4 stages of training and 3 retention intervals. In Part II, Ss were trained by exposing the same prototype stimuli, but recognition tests consisted of alternatives at 1 of 3 homogeneous levels of similarity to the prototypes. Learning curves based upon the 3 types of tests differ markedly in slope, reflecting the differential sensitivity of various dichotomous tests to the changes in the discriminability function. It was shown that the slope of each curve could be predicted accurately from the gradients obtained in Part I. Thus, generalization gradients were shown to be sensitive, parsimonious representations of the recognition learning process. The purpose of this study was to obtain a series of generalizatio n gradients to reflect the acquisition and retention of a visual discrimination skill. A number of previous investigators (Hovland, 1937; Jensen & Cotton, 1961; Margolius, 1955; Razran, 1949) have obtained gradients of stimulus generalization at several stages of training. As Brown (1965) and Prokasy and Hall (1963) have pointed out, however, such gradients do not necessarily reflect discriminability functions.
- Published
- 1967