Initioning-semantic model of divergent creativity

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Abstract

The author carried out frequency analysis of semantic categories of the testees’ responses to the task of the divergent test of emotional creativity of D.V.Ushakov and O.N.Ivanova and constructed a semantic network which shows the statistics of transitions between categories in the responses sequences. The contribution analyses structural characteristics of the semantic network including its clusterization and assortiveness. Basing on statistical analysis of the category structure of the responses it proposes a new two-factor initioning-semantic probability model of semantic categories production in the situation of divergent creativity assessment. The main factor of divergent creativity in the model is the person’s initiativeness. Another factor is related to the originality of semantics of the testee’s responses. Probability parameters of the model are defined on the basis of processing the data of the model sampling. New test values are introduced which provide uniform and norm-related calculation of individual characteristics of creativity which include independent indices of initioning creativity and semantic creativity as well as integral creativity index.

General Information

Keywords: productive thinking, divergent creativity, emotional creativity, psychological assessment, creativity indices, semantic networks, initiativeness, probability model

Journal rubric: Interdisciplinary Researches

Article type: scientific article

For citation: Artemenkov S.L. Initioning-semantic model of divergent creativity [Elektronnyi resurs]. Psikhologicheskaya nauka i obrazovanie psyedu.ru [Psychological Science and Education psyedu.ru], 2012. Vol. 4, no. 3, pp. 1–15. (In Russ., аbstr. in Engl.)

References

Information About the Authors

Sergei L. Artemenkov, PhD in Engineering, Professor, Head of the Department of Applied Informatics and Multimedia Technologies, Head of the Center of Information Technologies for Psychological Research of the Faculty of Information Technologies, Moscow State University of Psychology and Education, Moscow, Russia, ORCID: https://orcid.org/0000-0002-1619-2209, e-mail: slart@inbox.ru

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