A flashlight on attainments and prospects of research into complex problem solving
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Abstract
Research on complex problem solving (CPS) has reached a stage where certain standards have been achieved, whereas the future development is quite ambiguous. In this situation, the editors of the Journal of Dynamic Decision Making asked a number of representative authors to share their point of view with respect to seven questions about the relevance of (complex) problem solving as a research area, about the contribution of laboratory-based CPS research to solving real life problems, about the roles of knowledge, strategies, and intuition in CPS, and about the existence of expertise in CPS.
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References
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Gobet, F., & Chassy, P. (2009). Expertise and intuition: A tale of three theories. Minds and Machines, 19(2), 151–180. Retrieved from http://dx.doi.org/10.1007/s11023-008-9131-5
Greiff, S., Fischer, A., Wüstenberg, S., Sonnleitner, P., Brunner, M., & Martin, R. (2013). A multitrait-multimethod study of assessment instruments for complex problem solving. Intelligence, 41(5), 579–596. Retrieved from http://dx.doi.org/10.1016/j.intell.2013.07.012
Greiff, S., & Martin, R. (2014). What you see is what you (don’t) get: A comment on Funke’s (2014) opinion paper. Frontiers in Psychology, 5(1120). https://doi.org/10.3389/fpsyg.2014.01120
Klein, G. (2008). Naturalistic decision making. Human Factors, 50(3), 456–460.
Lotz, C., Scherer, R., Greiff, S., & Sparfeldt, J. R. (2017). Intelligence in action – Effective strategic behaviors while solving complex problems. Intelligence, 64, 98–112. https://doi.org/10.1016/j.intell.2017.08.002
Osman, M. (2010). Controlling uncertainty: A review of human behavior in complex dynamic environments. Psychological Bulletin, 136(1), 65–86.
Schiepek, G., & Strunk, G. (2010). The identification of critical fluctuations and phase transitions in short term and coarsegrained time series—a method for the real-time monitoring of human change processes. Biological Cybernetics, 102, 197–207.
Schoppek, W. (2002). Examples, rules, and strategies in the control of dynamic systems. [References]. Cognitive Science Quarterly, 2(1), 63–92.
Schoppek,W.(2004). Teaching structural knowledge in the control of dynamic systems: Direction of causality makes a difference. In K. D. Forbus, D. Gentner, & T. Regier (Eds.), Proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 1219–1224). Mahwah, NJ: Lawrence Erlbaum Associates.
Schoppek, W. (in press). Tut denken weh? Überlegungen zur Ökonomietendenz beim komplexen Problemlösen. In K. Viol & H. Schöller (Eds.), Selbstorganisation - Ein Paradigma für die Humanwissenschaften? (x-y). Berlin [u.a.]: Springer.
Schoppek, W., & Fischer, A. (2017). Common process demands of two complex dynamic control tasks: Transfer is mediated by comprehensive strategies. Frontiers in psychology, 8, 2145. https://doi.org/10.3389/fpsyg.2017.02145
Tricot, A., & Sweller, J. (2014). Domain-specific knowledge and why teaching generic skills does not work. Educational Psychology Review, 26(2), 265–283. https://doi.org/10.1007/s10648013-9243-1
Dörner, D. (1996). The logic of failure: Recognizing and avoiding error in complex situations. New York, NY: Basic Books.
Evans,JonathanSt. B.T.(2012). Spotthedifference: Distinguishing between two kinds of processing. Mind & Society, 11(1), 121–131. Retrieved from http://dx.doi.org/10.1007/s11299012-0104-2
Funke, J. (2014). Analysis of minimal complex systems and complex problem solving require different forms of causal cognition. Frontiers in Psychology, 5(739), 1–3.
Gobet, F., & Chassy, P. (2009). Expertise and intuition: A tale of three theories. Minds and Machines, 19(2), 151–180. Retrieved from http://dx.doi.org/10.1007/s11023-008-9131-5
Greiff, S., Fischer, A., Wüstenberg, S., Sonnleitner, P., Brunner, M., & Martin, R. (2013). A multitrait-multimethod study of assessment instruments for complex problem solving. Intelligence, 41(5), 579–596. Retrieved from http://dx.doi.org/10.1016/j.intell.2013.07.012
Greiff, S., & Martin, R. (2014). What you see is what you (don’t) get: A comment on Funke’s (2014) opinion paper. Frontiers in Psychology, 5(1120). https://doi.org/10.3389/fpsyg.2014.01120
Klein, G. (2008). Naturalistic decision making. Human Factors, 50(3), 456–460.
Lotz, C., Scherer, R., Greiff, S., & Sparfeldt, J. R. (2017). Intelligence in action – Effective strategic behaviors while solving complex problems. Intelligence, 64, 98–112. https://doi.org/10.1016/j.intell.2017.08.002
Osman, M. (2010). Controlling uncertainty: A review of human behavior in complex dynamic environments. Psychological Bulletin, 136(1), 65–86.
Schiepek, G., & Strunk, G. (2010). The identification of critical fluctuations and phase transitions in short term and coarsegrained time series—a method for the real-time monitoring of human change processes. Biological Cybernetics, 102, 197–207.
Schoppek, W. (2002). Examples, rules, and strategies in the control of dynamic systems. [References]. Cognitive Science Quarterly, 2(1), 63–92.
Schoppek,W.(2004). Teaching structural knowledge in the control of dynamic systems: Direction of causality makes a difference. In K. D. Forbus, D. Gentner, & T. Regier (Eds.), Proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 1219–1224). Mahwah, NJ: Lawrence Erlbaum Associates.
Schoppek, W. (in press). Tut denken weh? Überlegungen zur Ökonomietendenz beim komplexen Problemlösen. In K. Viol & H. Schöller (Eds.), Selbstorganisation - Ein Paradigma für die Humanwissenschaften? (x-y). Berlin [u.a.]: Springer.
Schoppek, W., & Fischer, A. (2017). Common process demands of two complex dynamic control tasks: Transfer is mediated by comprehensive strategies. Frontiers in psychology, 8, 2145. https://doi.org/10.3389/fpsyg.2017.02145
Tricot, A., & Sweller, J. (2014). Domain-specific knowledge and why teaching generic skills does not work. Educational Psychology Review, 26(2), 265–283. https://doi.org/10.1007/s10648013-9243-1
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2019-12-31
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