Computationally constructing a repository of compound remote associates test items in American English with comRAT-G

Abstract

The Remote Associates Test (RAT) has been used to measure creativity, however few repositories or standardizations of test items exist, like the normative data on 144 items provided by Bowden and Jung-Beeman. comRAT is a computational solver which has been used to solve the compound RAT in linguistic and visual forms, showing correlation to human performance over the normative data provided by Bowden and Jung-Beeman. This paper describes using a variant of comRAT, comRAT-G, to generate and construct a repository of compound RAT items for use in the cognitive psychology and cognitive modeling community. Around 17 million compound Remote Associates Test items are created from nouns alone, aiming to provide control over (i) frequency of occurrence of query items, (ii) answer items, (iii) the probability of coming up with an answer, (iv) keeping one or more query items constant and (v) keeping the answer constant. Queries produced by comRAT-G are evaluated in a study in comparison with queries from the normative dataset of Bowden and Jung-Beeman, showing that comRAT-G queries are similar to the established query set.