Examining the applicability of representational change theory for remote associates problem-solving with eye movement evidence

Abstract

Remote associates problems are a significant measuring tool for the creative process. Scholars have argued that remote associates problems and insight problems share similar core processes. However, there is little empirical evidence for their similarities. The main purpose of this study is to examine the applicability of Representational Change Theory (an insight theory) for remote associates problem-solving. This study manipulated the occurrence position of the keyword of a remote associates problem to alter the constraint relaxation in the problem. The problems were divided into three kinds, namely Keyword-in-Front (KF), Keyword-in-Middle (KM), and Keyword-in-Back (KB) problems. Individuals' eye movements were recorded during problem-solving. The results indicate that the solution rates of KM problems are higher than that of KB problems. Further, when individuals solved KF or KB problems, they had more regression counts and spent longer dwell time on the fixation region than on the key region. However, more time was spent on the key region as well as more regression counts when one was solving KM problems than the other two problems. The results of this study support the applicability of Representational Change Theory in the solving process of remote associates problems.