Author
Soyer, Emre, Hogarth, R. M.
Publication Date
2015-09
Publication Place
-
Elsevier
Subject
Probability assessment, Kind learning environments, Nonlinear judgmental tasks, Linear models, Exemplar-based models
Type
Periodical
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
0010-0285
Record ID
ae28fd64-2554-4722-aa10-15b2fa03ebe6
Library Location
Business Administration
Date
2015-09
Notes
Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text
We test people’s ability to learn to estimate a criterion (probability of success in a competition scenario) that requires aggregating information in a nonlinear manner. The learning environments faced by experimental participants are kind in that they are characterized by immediate, accurate feedback involving either naturalistic outcomes (information on winning and/or ranking) or the normatively correct probabilities. We find no evidence of learning from the former and modest learning from the latter, except that a group of participants endowed with a memory aid performed substantially better. However, when the task is restructured such that information should be aggregated in a linear fashion, participants learn to make more accurate assessments. Our experiments highlight the important role played by prior beliefs in learning tasks, the default status of linear aggregation in many inferential judgments, and the difficulty of learning in nonlinear environments even in the presence of veridical feedback.
DOI
10.1016/j.cogpsych.2015.08.002
Cilt
81
