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Taxonomies, knowledge and artifacts; interactivity in category learning Open Access


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Type of item
Degree grantor
University of Alberta
Author or creator
Hoff, Michael
Supervisor and department
Spalding, Thomas (Psychology)
Gagne, Christina (Psychology)
Dixon, Peter (Psychology)
Examining committee member and department
Bolger, Patrick (Linguistics)
Scott, Allen (Psychology) University of Lethbridge
Department of Psychology

Date accepted
Graduation date
Doctor of Philosophy
Degree level
Many adult concepts can be represented in taxonomies – hierarchical systems in which concepts are differentiated into varying levels of abstraction (e.g., musical instrument, wind instrument, flute) related by class inclusion (a flute is a wind instrument and a wind instrument is a musical instrument). Indeed, most natural kinds (e.g., whale, tree) and artifacts (e.g., flute, truck) are generally believed to fall within taxonomies. Moreover, in real world contexts, concepts are probably rarely learned as explicitly contrasting sets existing completely outside of known taxonomies (that is, one might not learn cats vs. dogs without also learning that both are types of animals, and that both include more specific subcategories). Surprisingly, relatively little research has been done on the learning of categories that are hierarchically structured. The present study began an investigation into how adults learned new concepts that are hierarchically structured. In Experiment 1, participants learned to classify items at one taxonomic level then at a later time classified items at either the same or a different level. The results suggested that people were unable to clearly detect the relationship among alternate levels of the hierarchy prior to exposure of those levels. However, results in Experiment 1 also suggested that learning multiple categories might lead to deeper understanding of how features transfer or generalize to higher taxonomic levels. The remaining experiments addressed more explicitly the influence of hierarchical structures on category learning by including prototype and control items, along with artificial and knowledge-based category labels. Results from these experiments indicated that, at least within the parameters of this study, prior experience cued by knowledge-based category labels interacted adversely with abstract materials and interfered with mapping of item information to categories. Moreover, when the relationship between categories and item information is unclear, generalization might be one important means by which people categorize.
License granted by Michael Hoff ( on 2009-10-25T22:37:08Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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