Dynamics of subjective uncertainty in complex problem solving

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Abstract

The study of processes of complex problems solving is an important task of many areas of modern psychological science, which can be successfully solved at the intersection of different disciplines, i.e. through an interdisciplinary approach. The present work is devoted to the experimental study of complex problems solving in a situation of uncertainty. The experimental situation required the construction of an effective system of management of the virtual factory on the basis of the developed computer model of its activity and in accordance with an adequate to reality dynamic scenario. Comparative analysis of the indicators of the effectiveness of complex problems solving, as well as indicators of the resistance to the situation of uncertainty of the two groups of subjects – beginners and experts – indicates a significant positive relationship between tolerance to uncertainty and successful performance of the task in the group of experts, as well as the absence of the significant differences between the indicators of successful performance of the task and the indicators of tolerance for uncertainty in the group of beginners. Results of the study suggest that tolerance to uncertainty, along with the experience and cognitive abilities of a person, is an important factor that affects the effective implementation of the management of complex technological systems.

General Information

Keywords: complex problems solving, uncertainty, dynamics, computer scenario

Journal rubric: Cognitive Psychology

Article type: scientific article

For citation: Eliseenko A.S. Dynamics of subjective uncertainty in complex problem solving . Eksperimental'naâ psihologiâ = Experimental Psychology (Russia), 2013. Vol. 6, no. 3, pp. 16–30. (In Russ., аbstr. in Engl.)

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Information About the Authors

Alexander S. Eliseenko, Master Sci. in Psychology, Trainee-researcher of the Laboratory of Cognitive studies of the Faculty of Psychology, National Research University Higher School of Economics, Moscow, Russia, e-mail: aseliseenko@edu.hse.ru

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