Abstract

Creative thinking is thought to be supported by both spontaneous associative and controlled executive processes. Recently, a new measure of associative cognition has been developed—forward flow—which uses computational semantic models (e.g., latent semantic analysis; LSA) to capture “how far” people travel in semantic space during a chained free association task. The present research aims to extend the psychometrics of forward flow by 1) leveraging multiple computational semantic models for forward flow computation (reliability) and 2) testing how this metric of associative ability relates to divergent creative thinking (validity). In addition, using structural equation modeling, we test dual-process theories of creative cognition by examining the relative contribution of associative and executive abilities to divergent thinking. Study 1 (n = 151) finds moderately improved reliability of forward flow using the new multi-model approach (compared to LSA only), as well as positive effects of both forward flow (β = .48) and general intelligence (β = .36) on divergent thinking (human creativity ratings) in the same structural regression model. This pattern of results was replicated in Study 2 (n = 150), which showed large effects of forward flow (β = .42) and general intelligence (β = .46) on divergent thinking. The results expand the psychometrics of forward flow and provide new evidence for dual process models of creative cognition.

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