Alignability and Prior Knowledge in Category Learning
Kaplan, Audrey Susan
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/82289
Description
Title
Alignability and Prior Knowledge in Category Learning
Author(s)
Kaplan, Audrey Susan
Issue Date
1999
Doctoral Committee Chair(s)
Murphy, Gregory L.
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
Language
eng
Abstract
This thesis is concerned with the roles of structural alignment and prior knowledge in category learning. Structural alignment (Gentner, 1983, 1989) is a theory that claims that similarity comparisons entail a process of aligning the components of the things being compared, determining what corresponds to what. The experiments presented here explore the implications of this view of similarity for category learning. Many theories of category leaning (e.g., Medin & Schaffer, 1978) argue that categories are easy to learn to the extent that they have low between-category similarity and high within-category similarity. Experiments 1 and 1a assessed the within- and between-category similarity characteristics for pairs of alignable and nonalignable categories. Experiment 2 then compared the learning of these two category types. A dissociation between similarity and categorization was observed whereby alignable categories were easier to learn than nonalignable categories despite having an identical similarity profile. Experiment 3 expanded on this result by showing an alignability advantage for categories that contained both alignable and nonalignable features, but in which only one of these kinds of features was predictive of category membership. Experiments 4 and 5 began to explore whether alignability helps category learning when the categories can be related to prior knowledge. The results suggested that alignable features and features related to prior knowledge may compete for attention in category learning. The General Discussion proposes that alignability effects may be due to increased attention allocated to alignable over nonalignable features.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
