{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/69695"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/69695","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Levels of Learning: Relations Between Identification and Classification Processes","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Dewey, Gerald Irving"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Psychology","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-12-15T19:46:22Z","date_published":"2014-12-15T19:46:22Z","updated_at":"2026-07-22T22:26:01Z","subjects":["Psychology, Experimental"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(UMI)AAI8803017"],"render_values":[{"text":"(UMI)AAI8803017","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/69695","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Dewey, Gerald Irving"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-12-15T19:46:22Z","10000-01-01","1987"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Psychology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Psychology, Experimental"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/69695","(UMI)AAI8803017"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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.","Made available in DSpace on 2014-12-15T19:46:22Z (GMT). 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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.","Made available in DSpace on 2014-12-15T19:46:22Z (GMT). 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