Yazar
Soyer, Emre, Hogarth, R. M.
Basım Tarihi
2015-09
Basım Yeri
-
Elsevier
Konu
Probability assessment, Kind learning environments, Nonlinear judgmental tasks, Linear models, Exemplar-based models
Tür
Süreli Yayın
Dil
İngilizce
Dijital
Evet
Yazma
Hayır
Kütüphane
Özyeğin Üniversitesi
Demirbaş Numarası
0010-0285
Kayıt Numarası
ae28fd64-2554-4722-aa10-15b2fa03ebe6
Lokasyon
Business Administration
Tarih
2015-09
Notlar
Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin
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
