Soyer, EmreHogarth, R. M.2016-06-302016-06-302015-090010-0285http://hdl.handle.net/10679/4158https://doi.org/10.1016/j.cogpsych.2015.08.002Due to copyright restrictions, the access to the full text of this article is only available via subscription.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.enginfo:eu-repo/semantics/restrictedAccessArticle81487300036193020000310.1016/j.cogpsych.2015.08.002Probability assessmentKind learning environmentsNonlinear judgmental tasksLinear modelsExemplar-based models2-s2.0-84940787598