Literature DB >> 25218460

Using forced choice to test belief bias in syllogistic reasoning.

Dries Trippas1, Michael F Verde2, Simon J Handley2.   

Abstract

In deductive reasoning, believable conclusions are more likely to be accepted regardless of their validity. Although many theories argue that this belief bias reflects a change in the quality of reasoning, distinguishing qualitative changes from simple response biases can be difficult (Dube, Rotello, & Heit, 2010). We introduced a novel procedure that controls for response bias. In Experiments 1 and 2, the task required judging which of two simultaneously presented syllogisms was valid. Surprisingly, there was no evidence for belief bias with this forced choice procedure. In Experiment 3, the procedure was modified so that only one set of premises was viewable at a time. An effect of beliefs emerged: unbelievable conclusions were judged more accurately, supporting the claim that beliefs affect the quality of reasoning. Experiments 4 and 5 replicated and extended this finding, showing that the effect was mediated by individual differences in cognitive ability and analytic cognitive style. Although the positive findings of Experiments 3-5 are most relevant to the debate about the mechanisms underlying belief bias, the null findings of Experiments 1 and 2 offer insight into how the presentation of an argument influences the manner in which people reason.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Belief bias; Forced choice; Individual differences; Signal detection theory

Mesh:

Year:  2014        PMID: 25218460     DOI: 10.1016/j.cognition.2014.08.009

Source DB:  PubMed          Journal:  Cognition        ISSN: 0010-0277


  2 in total

1.  Alleviating the concerns with the SDT approach to reasoning: reply to Singmann and Kellen (2014).

Authors:  Dries Trippas; Michael F Verde; Simon J Handley
Journal:  Front Psychol       Date:  2015-02-19

2.  Characterizing belief bias in syllogistic reasoning: A hierarchical Bayesian meta-analysis of ROC data.

Authors:  Dries Trippas; David Kellen; Henrik Singmann; Gordon Pennycook; Derek J Koehler; Jonathan A Fugelsang; Chad Dubé
Journal:  Psychon Bull Rev       Date:  2018-12
  2 in total

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