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Uncovering iconic patterns of syllogistic reasoning: A clustering analysis

Authors
Mr. Daniel Brand
Chemnitz University of Technology ~ Predictive Analytics
Mr. Nicolas Riesterer
F. Hoffmann - La Roche
Marco Ragni
TU Chemnitz ~ Behavioral and Social Sciences
Abstract

Syllogistic reasoning is one of the core domains of human reasoning research. Over its century of being actively researched, various theories have been proposed attempting to disentangle and explain the various strategies human reasoners are relying on. In this article we propose a data-driven approach to behaviorally cluster reasoners into archetypal groups based on non-negative matrix factorization. The identified clusters are interpreted in the context of state-of-the-art theories in the field and analyzed based on the posited key assumptions, e.g., the dual-processing account. We show interesting contradictions that add to a growing body of evidence suggesting shortcomings of the current state of the art in syllogistic reasoning research and discuss possibilities of overcoming them.

Tags

Keywords

syllogistic reasoning
cognitive modeling
clustering
non-negative matrix factorization
dual-process theory
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Cite this as:

Brand, D., Riesterer, N. O., & Ragni, M. (2023, July). Uncovering iconic patterns of syllogistic reasoning: A clustering analysis. Paper presented at MathPsych/ICCM/EMPG 2023. Via mathpsych.org/presentation/1196.