Classification versus inference learning contrasted with real-world categories
Jones, Erin L.
Loading…
Permalink
https://hdl.handle.net/2142/16208
Description
Title
Classification versus inference learning contrasted with real-world categories
Author(s)
Jones, Erin L.
Issue Date
2010-05-19T18:40:37Z
Director of Research (if dissertation) or Advisor (if thesis)
Ross, Brian H.
Department of Study
Psychology
Discipline
Psychology
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.A.
Degree Level
Thesis
Keyword(s)
categorization
concepts
learning
Abstract
A number of studies have contrasted classification and inference, using a variety of stimuli and tests, but in all cases the difference between these tasks could be attributed to either methodological differences or an inherent difference between the tasks. The inherent difference explanation argues that classification and inference learners use different strategies during learning, which reflect the goals of the tasks. Inference learners focus more on what each category is like, while classification learners focus on finding the information that best predicts category membership. These differences during learning lead to performance differences on later tests of category knowledge. In two experiments, using real-world categories and controlling for methodological differences, inference learners learned more about what each category was like than classification learners. These results suggest that there is an inherent difference between classifying an item and inferring a feature that cannot be explained by methodological differences between the tasks.
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.
