Previous issue (2019. Vol. 12, no. 1)
Included in Web of Science СС (ESCI)
Dynamics of subjective uncertainty in complex problem solving 1697
, 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, firstname.lastname@example.org
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.
Keywords: complex problems solving, uncertainty, dynamics, computer scenario
Column: Cognitive Psychology
- Barabanshikov V. A. Princip sistemnosti v sovremennoj psihologii //
Psihologija. Zhurnal GU-VShE. 2004. № 4. S. 3–17.
- Derner D. Logika neudachi. M.: Smysl, 1997.
- Korotkova A. V. Specifika orientirovochnoj osnovy v myslitel'noj
dejatel'nosti pri reshenii kompleksnyh problem. M., 2005.
- Podd'jakov A. N. Neopredelennost' v reshenii kompleksnyh problem //
Chelovek v situacii neopredelennosti. M., 2007. S. 177–193.
- Berry D. C., Broadbent D. E. On the relationship between task
performance and associated verbalizable knowledge // Quarterly Journal of
Experimental Psychology. 1984. V. 36. P. 209–231.
- Brehmer B. Dynamic decision-making—human control of complex-systems
//Acta Psychologica. 1992. V. 81. P. 211–241.
- Broadbent D., Fitzgerald P., Broadbent M. H. Implicit and explicit
knowledge in the control of complex systems // British Journal of Psychology.
1986. V. 77. P. 33–50.
- Busemeyer J. R. Dynamic decision making // International
Encyclopedia of the Social and Behavioral Sciences: Methodology, Mathematics
and Computer Science / Eds. N. J. Smelser, P. B. Bates. Oxford: Elsevier, 2002.
- Complex Problem Solving / Eds. J. R. Sternberg, P. Frensch. Hillsdale, N Y:
Lawrence Erlbaum associates, 1991.
- Complex Problem Solving: The European Perspective / Eds. P. A. Frensch, J.
Funke. Hillsdale, N J: Lawrence Erlbaum, 1995.
- Frensch P., Funke J. Definitions, traditions and a general framework
for understanding complex problem solving // Complex Problem Solving: The
European Perspective / Eds. P. A. Frensch, J. Funke. Hillsdale, N J: Lawrence
Erlbaum, 1995. P. 3–25.
- Greco V., Roger D. Coping with uncertainty: the construction and
validation of a new measure // Personality and Individual Differences. 2001. V.
31. P. 519–534.
- Klein G. The recognition-primed decision model: looking back,
looking forward // Naturalistic Decision Making / Eds. C. Zsambok, G. Klein.
Mahwah, N J: Lawrence Erlbaum Associates, 1997. P. 285–292.
- Quesada J., Kintsch W., Gomez E. Complex problem-solving: a field in
search of a definition? // Theoretical Issues in Ergonomics Science. 2005. V.
6. № 1. P. 5–33.
- Simon H. The Structure of Ill-Structured Problems // Artificial
Intelligence. 1973. V. 4. P. 181–201.