Which cognitive individual differences predict good Bayesian reasoning? Concurrent comparisons of underlying abilities.
We know a lot about how to present Bayesian reasoning tasks in order to aid performance, but less about underlying individual differences that can account for interindividual variability on the same tasks. Such information would be useful for both theoretical and practical reasons. Two theoretical p...
| Published in: | Memory & Cognition Vol. 49; no. 2; pp. 235 - 249 |
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| Format: | Article |
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Springer Nature
Feb2021
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=148754135&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 148754135 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 0090502X MEG jtl: Memory & Cognition issn: 0090502X maglogo: N pubinfo: dt: Feb2021 vid: 49 iid: 2 pid: 237 pub: Springer Nature artinfo: ui: 148754135 10.3758/s13421-020-01087-5 ppf: 235 ppct: 14 formats: fmt: @attributes: type: P size: 452KB tig: atl: Which cognitive individual differences predict good Bayesian reasoning? Concurrent comparisons of underlying abilities. aug: au: Brase, Gary affil: Department of Psychological Sciences, Kansas State University, North Manhattan, KS, USA su: Cognition Ecology Memory Task performance Mathematical models Probability theory Space perception Thought & thinking Theory sug: subj: Cognition Ecology Memory Task performance Mathematical models Probability theory Space perception Thought & thinking Theory keyword: Bayesian reasoning Ecological rationality Individual differences Nested sets Numerical literacy Spatial ability Bayesian reasoning Ecological rationality Individual differences Nested sets Numerical literacy Spatial ability ab: We know a lot about how to present Bayesian reasoning tasks in order to aid performance, but less about underlying individual differences that can account for interindividual variability on the same tasks. Such information would be useful for both theoretical and practical reasons. Two theoretical positions, ecological rationality and nested set views, generate multiple hypotheses about which individual difference traits should be most relevant as underlying Bayesian reasoning performance. However, because many of these traits are somewhat overlapping, testing variables in isolation can yield misleading results. The present research assesses Bayesian reasoning abilities in conjunction with multiple individual different measures. Across three experiments, Bayesian reasoning was best predicted by measures of numerical literacy and visuospatial ability, as opposed to several different measures of cognitive thinking dispositions/styles, ability to conceptually model set-theoretic relationships, or cognitive processing ability (working memory span). These results support an ecological rationality view of Bayesian reasoning, rather than nested sets views. There also was some predictive ability for the Cognitive Reflection Task, which was only partially due to the numeracy aspects of that instrument, and further work is needed to clarify if this is a distinct factor. We are now beginning to understand not only how to build Bayesian reasoning tasks, but also how to build good Bayesian reasoners. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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