Responses to Raven matrices

Governed by visual complexity and centrality

Journal article (2023)

Authors

J.C.F. de Winter Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
J. C.F. de Winter Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
D. Dodou Medical Instruments & Bio-Inspired Technology - Mechanical, Maritime and Materials Engineering
Dimitra Dodou Medical Instruments & Bio-Inspired Technology - Mechanical, Maritime and Materials Engineering
D Dodou Medical Instruments & Bio-Inspired Technology - Mechanical, Maritime and Materials Engineering
Y.B. Eisma Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
Y. B. Eisma Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
Research Group
Human-Robot Interaction (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2023 J.C.F. de Winter, D. Dodou, Y.B. Eisma
DOI: https://doi.org/10.1177/03010066231178149
More Info
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Published Date

2023

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Human-Robot Interaction

Abstract

Raven matrices are widely considered a pure test of cognitive abilities. Previous research has examined the extent to which cognitive strategies are predictive of the number of correct responses to Raven items. This study examined whether response times can be explained directly from the centrality and visual complexity of the matrix cells (edge density and perceived complexity). A total of 159 participants completed a 12-item version of the Raven Advanced Progressive Matrices. In addition to item number (an index of item difficulty), the findings demonstrated a positive correlation between the visual complexity of Raven items and both the mean response time and the number of fixations on the matrix (a strong correlate of response time). Moreover, more centrally placed cells as well as more complex cells received more fixations. It is concluded that response times on Raven matrices are impacted by low-level stimulus attributes, namely, visual complexity and eccentricity.