Complex problem

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In psychology, a complex problem is a problem that differs from a simple problem by the following five characteristics: Complexity, interconnectedness, momentum, intransparency and polytelie. The term comes from general psychology and was coined by Dietrich Dörner and further developed by Joachim Funke .

Characteristics

Complex problems are characterized by the following five characteristics:

  • Complexity : Complexity is traditionally defined in terms of the number of variables in the given situation. To solve the problem, information reduction is therefore necessary.
  • Networkedness : The variables of the problem situation are strongly networked with one another. However, the degree of networking can vary. A variable can be networked with another up to all other variables. Therefore there is a need to structure the information.
  • Dynamic of its own: The system's variables can change over time without the assistance of the problem solver. These changes are usually unpredictable, which means that quick decisions are required.
  • Lack of transparency : Not all information is always accessible in a complex problem. Some of the information is not available and some are not yet available in the current situation. Therefore, information must be actively obtained.
  • Polytelie / multifariousness : Complex problems contain several, sometimes contradicting goals. The problem solver must therefore set priorities and compromise.

As part of his research on naturalistic decision making, Gary Klein brings in the emotional and motivational significance (high stakes) of a problem as a further characteristic. This means that the problem must appear emotionally significant to the problem solver and motivate him to find a solution.

The extent to which these properties are actually useful in distinguishing complex problems from simple problems (e.g. Tower of London ) is not without controversy. For example, the distinction between complexity and interconnectedness is problematic, since these two properties are strongly interdependent. Furthermore, there is no clear definition of complexity in this context that would make it possible to describe a problem as more or less complex.

Psychological diagnostics

Due to the characteristics of complex problems, computer programs (so-called micro-worlds ) are used to measure the ability to solve complex problems in order to be able to present dynamic and non-transparent problem situations. Micro-worlds as computer-simulated scenarios try to represent realistic problem situations . Well-known micro-worlds in this research tradition are the Schneiderwerkstatt, FSYS or PowerPlant .

More recent work, based on the research of Joachim Funke , uses a different approach: minimally complex systems. In addition, the relation to reality is less strong and the psychometric quality criteria (i.e. in particular reliability ) are emphasized. On the one hand, the survey instruments still meet the five characteristics of a complex problem, but at the same time they have the lowest levels of these characteristics. Well-known survey instruments in this research tradition are MicroDYN, MicroFIN and Genetics Lab. This measurement approach was also used in the international PISA 2012 study .

Connection with other subject areas

In research on solving complex problems it is discussed whether complex problem solving and intelligence represent substantially the same constructs . One research tradition (represented by Dietrich Dörner and Joachim Funke, among others ) argues that the ability to solve complex problems contains more than intelligence alone and even postulated a new ability, operational intelligence. The other research tradition (represented by Heinz-Martin Süß, among others ) formulated the thesis that there is a substantial connection between the two constructs. In one of the most extensive works on this question, it was empirically proven that the performance in complex problem solving can be almost completely explained by intelligence and knowledge. In more recent studies, too, empirical relationships between complex problem-solving performance and performance in intelligence tests have been consistently found, the level of which is comparable to correlations between different intelligence tests. It can therefore be assumed that complex problem solving describes the performance in novel, interactive intelligence tests rather than actually representing a skill other than intelligence.

The connection to other constructs such as B. Working memory , personality traits , motivation or emotions were examined. In the case of simple problems, for example, positive affects lead to better performance, although the influence of emotions on the problem-solving ability in complex problems is not fully understood.

Research on Naturalistic Decision Making and Dynamic Decision Making in the Anglo-American language area also deals with complex problems.

Complex problems in the world

Some complex problems affect the whole world, so-called "World's Biggest Problems". There is currently a debate between two research institutes about which exactly are the biggest problems in the world. The Arlington Institute currently has the following problems:

The Copenhagen Consensus Center with President Bjørn Lomborg , however, lists the following problems in its 2012 report:

literature

  • Dietrich Dörner: Problem solving as information processing. Kohlhammer, Stuttgart 1976, ISBN 3-17-001353-X .
  • Joachim Funke: Problem-solving thinking. Kohlhammer, Stuttgart 2003, ISBN 3-17-017425-8 .
  • Gary Klein: Naturalistic Decision Making. In: Human Factors. No. 50, June 2008, doi : 10.1518 / 001872008X288385 , pp. 456-460.
  • Heinz-Martin Süß: Intelligence, knowledge and problem solving. Cognitive prerequisites for successful action in computer-simulated problems. Hogrefe, Göttingen 1996, ISBN 978-3-8017-1089-7 .
  • Walter Schönwandt, Katrin Voermanek, Jürgen Utz, Jens Grunau, Christoph Hemberger: "Solving complex problems - A manual", JOVIS Verlag Berlin 2013, ISBN 978-3-86859-227-6 .

References

  1. Joachim Funke: Problem-solving thinking. Kohlhammer, Stuttgart 2003, ISBN 3-17-017425-8 .
  2. Funke, J. (2014). Analysis of minimal complex systems and complex problem solving require different forms of causal cognition. Frontiers in Psychology, 5. doi : 10.3389 / fpsyg.2014.00739
  3. Schoppek, W., & Fischer, A. (2015). Complex problem solving - single ability or complex phenomenon? Frontiers in Psychology, 6 (1669). doi : 10.3389 / fpsyg.2015.01669
  4. ^ Greiff, S., Wüstenberg, S., & Funke, J. (2012). Dynamic Problem Solving: A New Assessment Perspective. Applied Psychological Measurement, 36 (3), 189-213. doi : 10.1177 / 0146621612439620
  5. ^ Neubert, JC, Kretzschmar, A., Wüstenberg, S., & Greiff, S. (2015). Extending the Assessment of Complex Problem Solving to Finite State Automata: Embracing Heterogeneity. European Journal of Psychological Assessment, 31 (3), 181–194. doi : 10.1027 / 1015-5759 / a000224
  6. Sonnleitner, P., Brunner, M., Greiff, S., Funke, J., Keller, U., Martin, R.,… Latour, T. (2012). The Genetics Lab: Acceptance and psychometric characteristics of a computer-based microworld assessing complex problem solving. Psychological Test and Assessment Modeling, 54 (1), 54-72. doi : 10.1037 / e578442014-045
  7. ^ The Genetics Lab: a computer-based test to assess students' complex problem solving abilities website of the University of Luxembourg. Retrieved April 24, 2016.
  8. ^ Funke, J. (2010). Complex problem solving: a case for complex cognition? Cognitive Processing, 11, 133-142. doi : 10.1007 / s10339-009-0345-0
  9. Dörner, D. (1986). Diagnostics of operational intelligence. Diagnostica, 32, 290-208.
  10. Suess, H.-M. (1999). Intelligence and complex problem solving: Perspectives for cooperation between differential psychometric and cognitive psychological research. Psychological Rundschau, 50 (4), 220–228. doi : 10.1026 // 0033-3042.50.4.220
  11. Heinz-Martin Süß: Intelligence, Knowledge and Problem Solving. Cognitive prerequisites for successful action in computer-simulated problems. Hogrefe, Göttingen 1996, ( ISBN 978-3-8017-1089-7 )
  12. ^ Kröner, S., Plass, JL, & Leutner, D. (2005). Intelligence assessment with computer simulations. Intelligence, 33 (4), 347-368. doi : 10.1016 / j.intell.2005.03.002
  13. Kretzschmar, A., Neubert, JC, Wüstenberg, S., & Greiff, S. (2016). Construct validity of complex problem solving: A comprehensive view on different facets of intelligence and school grades. Intelligence, 54, 55-69. doi : 10.1016 / j.intell.2015.11.004

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