Belief bias in individual and collective reasoning

In this paper, we investigate whether collaborative group performance is better than individual performance in solving a syllogism evaluation task. We hypothesise that collaborative group settings will outperform individual settings and that the belief bias effect will be mitigated in a group setting. Two empirical studies were conducted with Argentinian undergraduate students. Study 1 (<i>N</i> = 239) used a between-subjects design with two conditions: individual resolution and interactive group resolution. Overall, the group condition performed better than the individual condition, but there were no significant differences in evaluating invalid syllogisms. Study 2 (<i>N</i> = 115) used a within-subjects design with three conditions: individual resolution, interactive group resolution, and individual after-interactive group resolution. Overall, the group condition performed better than the individual condition, and the individual after-interactive group condition showed an increase in accurate answers compared to individual resolution. However, as observed in Study 1, the collaborative group setting did not improve the evaluation of invalid syllogisms. We propose an explanation for the group resolution of invalid believable syllogisms within the framework of the selective processing model of the belief bias. This research provides new data on the effects of collaborative settings in deductive reasoning beyond the Western Educated Industrialised Rich Democratic (WEIRD) cultures.

Authors

Institutions

Publication Details

Journal
Europe’s Journal of Psychology
Published
2024-11-25
DOI
https://doi.org/10.5964/ejop.12041
Primary Topic
Decision-Making and Behavioral Economics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Belief bias in individual and collective reasoning

Alba Massolo, Mariel Traversi, M. Iacono Alfonso
Europe’s Journal of Psychology
Decision-Making and Behavioral Economics
article

Belief bias in individual and collective reasoning

Alba Massolo, Mariel Traversi, M. Iacono Alfonso
article en

Abstract

In this paper, we investigate whether collaborative group performance is better than individual performance in solving a syllogism evaluation task. We hypothesise that collaborative group settings will outperform individual settings and that the belief bias effect will be mitigated in a group setting. Two empirical studies were conducted with Argentinian undergraduate students. Study 1 (<i>N</i> = 239) used a between-subjects design with two conditions: individual resolution and interactive group resolution. Overall, the group condition performed better than the individual condition, but there were no significant differences in evaluating invalid syllogisms. Study 2 (<i>N</i> = 115) used a within-subjects design with three conditions: individual resolution, interactive group resolution, and individual after-interactive group resolution. Overall, the group condition performed better than the individual condition, and the individual after-interactive group condition showed an increase in accurate answers compared to individual resolution. However, as observed in Study 1, the collaborative group setting did not improve the evaluation of invalid syllogisms. We propose an explanation for the group resolution of invalid believable syllogisms within the framework of the selective processing model of the belief bias. This research provides new data on the effects of collaborative settings in deductive reasoning beyond the Western Educated Industrialised Rich Democratic (WEIRD) cultures.

Europe’s Journal of PsychologyVol. 20(4)
Universidad Católica de Córdoba (AR), Universidad Nacional de Córdoba (AR)
Universidad Católica de Córdoba, Universidad de Córdoba
Openalex Percentile: Top 76%
Decision-Making and Behavioral Economics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.