Verbal analogy problem sets: An inventory of testing materials
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Verbal analogy problem sets: An inventory of testing materials Nicholas Ichien 1 & Hongjing Lu 1,2 & Keith J. Holyoak 1
# The Psychonomic Society, Inc. 2020
Abstract Analogical reasoning is an active topic of investigation across education, artificial intelligence (AI), cognitive psychology, and related fields. In all fields of inquiry, explicit analogy problems provide useful tools for investigating the mechanisms underlying analogical reasoning. Such sets have been developed by researchers working in the fields of educational testing, AI, and cognitive psychology. However, these analogy tests have not been systematically made accessible across all the relevant fields. The present paper aims to remedy this situation by presenting a working inventory of verbal analogy problem sets, intended to capture and organize sets from diverse sources. Keywords Analogy, Relational Reasoning, Language, Education, Artificial Intelligence
Introduction Analogical reasoning is the ability to grasp and exploit similarities based on relations between sets of entities, rather than solely on features of the individual entities themselves (Holyoak, 2012). The general ability to think in terms of explicit relations is highly developed in humans, and indeed may constitute a discontinuity between human intelligence and non-human intelligence (Penn, Holyoak, & Povinelli, 2008). This cognitive process supports human performance in a wide range of activities (Holyoak & Thagard, 1995), including classroom learning (Richland, Zur, & Holyoak, 2007; Jee et al., 2010), engineering design (Chan & Schunn, 2015), and scientific reasoning (Dunbar, 1995; Gentner & Jeziorski, Electronic supplementary material The online version of this article (https://doi.org/10.3758/s13428-019-01312-3) contains supplementary material, which is available to authorized users. * Nicholas Ichien [email protected] Hongjing Lu [email protected] Keith J. Holyoak [email protected] 1
Department of Psychology, University of California, Los Angeles, 405 Hilgard Ave., Los Angeles, CA 90095-1563, USA
2
Department of Statistics, University of California, Los Angeles, 405 Hilgard Ave., Los Angeles 90095-1563, CA, USA
1993). Performance on analogy tests is highly correlated with measures of fluid intelligence (Snow, Kyllonen, & Marshalek, 1984). Analogy problems also provide an important source of benchmarks for assessing the performance of models of relational processing developed by researchers in artificial intelligence (AI) (e.g., Mikolov, Chen, Corrado, & Dean, 2013; Turney, 2013). Sets of explicit analogy problems provide useful tools for investigating the mechanisms underlying analogical reasoning. Such sets have been developed by researchers working in the fields of educational testing, AI, and cognitive psychology. However, these analogy tests have not been systematically made accessible across all the relevant fields. The present paper aims to remedy this situation by presenting a working inventory of verbal analogy problem sets, intended to capture and organize
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