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Differentiating between static and complex problems: A theoretical framework and its empirical validation

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  • Stadler, Matthias
  • Niepel, Christoph
  • Greiff, Samuel

Abstract

Ever since its first conception, the concept of complex problem solving (CPS) has been debated regarding its role within the conception of human intelligence. The aim of the current paper was to theoretically introduce and empirically test a multifaceted framework of CPS that subsumes different positions and provides testable predictions on the nature of CPS. Following a review of the existing literature on complex problem solving, we conclude that it is necessary to differentiate between the dimensions of connectivity and dynamics. These dimensions are further distinguishable for both phases of CPS, knowledge acquisition and knowledge application, resulting in four facets. Static problems, as used in conventional measures of intelligence, on the other hand, do not include dynamics as much as complex problems. We argue that the differences in CPS and static problem solving proposed by various researchers result from the dimension of dynamics that is highly relevant for CPS but less so for static problem solving. An empirical analysis based on two independent samples supported the assumptions made by the framework. This brings substantial implications for the understanding of CPS as well as the interpretation of previous research, which we discuss.

Suggested Citation

  • Stadler, Matthias & Niepel, Christoph & Greiff, Samuel, 2019. "Differentiating between static and complex problems: A theoretical framework and its empirical validation," Intelligence, Elsevier, vol. 72(C), pages 1-12.
    • Handle: RePEc:eee:intell:v:72:y:2019:i:c:p:1-12
    DOI: 10.1016/j.intell.2018.11.003
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    References listed on IDEAS

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    1. Berbeglia, Gerardo & Cordeau, Jean-François & Laporte, Gilbert, 2010. "Dynamic pickup and delivery problems," European Journal of Operational Research, Elsevier, vol. 202(1), pages 8-15, April.
    2. Albert Satorra & Peter Bentler, 2010. "Ensuring Positiveness of the Scaled Difference Chi-square Test Statistic," Psychometrika, Springer;The Psychometric Society, vol. 75(2), pages 243-248, June.
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    Cited by:

    1. Herrmann, W. & Beckmann, J.F. & Kretzschmar, A., 2023. "The role of learning in complex problem solving using MicroDYN," Intelligence, Elsevier, vol. 100(C).
    2. Nicolay, Björn & Krieger, Florian & Kuhn, Jörg-Tobias & Graesser, Arthur C. & Ifenthaler, Dirk & Baker, Ryan & Greiff, Samuel, 2023. "Unsuccessful and successful complex problem solvers – A log file analysis of complex problem solving strategies across multiple tasks," Intelligence, Elsevier, vol. 101(C).
    3. Lotz, Christin & Scherer, Ronny & Greiff, Samuel & Sparfeldt, Jörn R., 2022. "g's little helpers – VOTAT and NOTAT mediate the relation between intelligence and complex problem solving," Intelligence, Elsevier, vol. 95(C).
    4. Weise, Julius J. & Greiff, Samuel & Sparfeldt, Jörn R., 2020. "The moderating effect of prior knowledge on the relationship between intelligence and complex problem solving – Testing the Elshout-Raaheim hypothesis," Intelligence, Elsevier, vol. 83(C).

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