Abstract
The aim of the current study is to enhance our understanding of cognitive creativity, specifically divergent thinking, by employing an interdisciplinary methodological approach. By integrating methodology from computational linguistics and complex systems into creativity research, the current study aims to shed light on the relationship between divergent thinking and the temporal structure of semantic associations. In complex systems, temporal structures can be described on a continuum from random to flexible-stable and to persistent. Random structures are highly unpredictable, persistent structures are highly predictable, and flexible-stable structures are in-between, they are partly predictable from previous observations. Temporal structures of associations that are random (e.g., dog–graveyard–north pole) or persistent (e.g., dog–cat–rat) are hypothesized to be detrimental to divergent thinking. However, a flexible-stable structure (e.g., dog–police–drugs) is hypothesized to be related to enhanced divergent thinking (inverted-U). This notion was tested (N = 59) in an association chain task, combined with a frequently used measure of divergent thinking (i.e., Alternative Uses Test). Latent Semantic Analysis from computational linguistics was used to quantify the associations, and methods from complex systems in form of Power Spectral Density analysis and detrended fluctuation analysis were used to estimate the temporal structure of those associations. Although the current study does not confirm that a flexible-stable (vs. random/persistent) temporal structure of associations is related to enhanced divergent thinking skills, it hopefully challenges fellow researchers to refine the recent methodological developments for assessing the (temporal) structure of associations. Moreover, the current cross-fertilization of methodological approaches may inspire creativity researchers to take advantage of other fields’ ideas and methods. To derive a theoretically sound cognitive theory of creativity, it is important to integrate research ideas and empirical methods from a variety of disciplines.
Highlights
Creativity has often been defined as the generation of novel and useful insights or solutions to a problem (e.g., Stein, 1953; Runco and Jaeger, 2012)
The results indicated that individuals scoring high on creativity, as measured by the two divergent thinking tasks, formed more associations and more uncommon responses
To test the main hypothesis that novelty and creativity in the Alternative Uses Test (AUT) can be modeled as a quadratic function of Power Spectral Density (PSD) and DFA, two multiple regressions, one with AUTnovelty and the other with AUTcreativity as dependent variable and PSD and DFA
Summary
Creativity has often been defined as the generation of novel and useful insights or solutions to a problem (e.g., Stein, 1953; Runco and Jaeger, 2012). One example is the Four C Model of creativity by Kaufman and Beghetto (2009, 2013) where a distinction between mini-c, little-c, pro-c, and big-c is made. This separation of four levels of creativity is mainly driven by the indirect assumption of different gradients of experiences. Pro-c, on the other hand, distinguishes accomplishments in professional settings that are transformative for certain arts or crafts (e.g., inventing a new statistical method) but is lacking the eminent accomplishment that revolutionizes the world (e.g., formulating probability theory) Those eminent accomplishments could be understood as big-c following Kaufman and Beghetto. Semantic associations are proposed to contribute to divergent thinking (e.g., Acar and Runco, 2014)
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