Levels of Learning: Relations Between Identification and Classification Processes
Dewey, Gerald Irving
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https://hdl.handle.net/2142/69695
Description
Title
Levels of Learning: Relations Between Identification and Classification Processes
Author(s)
Dewey, Gerald Irving
Issue Date
1987
Department of Study
Psychology
Discipline
Psychology
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Psychology, Experimental
Abstract
Research has shown that learning categories of stimuli (classification learning) proceeds faster, with fewer errors, and promotes better transfer to novel stimuli than does learning unique names for stimuli (identification learning). These findings were examined in two levels of learning experiments using artificial stimuli. In Experiment 1 each stimulus contained (distortions of) superordinate and ordinate category level attributes. In addition, there were attributes unique to the particular stimulus. Two groups of subjects classified the stimuli based on either the superordinate or ordinate category level attributes (classification learning). A third group of subjects learned a unique name for each stimulus (identification learning). In contrast to previous findings, the results showed that identification learning was faster and led to fewer errors than did classification learning. The same finding was obtained in Experiment 2 which employed a less complex set of stimulus materials. In an attempt to determine what subjects had learned about the stimuli, portions of the stimuli were presented for classification/identification subsequent to learning. Results showed that best performance was on stimulus components related to a subject's level of learning. The results of learning and transfer were evaluated in light of a partial encoding hypothesis which assumes that during learning only portions of stimuli become represented in memory. It was suggested that previous level of learning studies are of limited generality because the stimulus items lacked unique attributes. Implications for current models of classification learning were discussed in light of partial encoding.
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