Learning from experience in nonlinear environments: Evidence from a competition scenario

Name: Learning from experience in nonlinear environments: Evidence from a competition scenario
Author: Soyer, Emre, Hogarth, R. M.

İsim	Learning from experience in nonlinear environments: Evidence from a competition scenario
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

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Learning from experience in nonlinear environments: Evidence from a competition scenario

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