A Dynamic Network Model to Explain the Development of Excellent Human Performance

Across different domains, from sports to science, some individuals accomplish excellent levels of performance. For over 150 years, researchers have debated the roles of specific nature and nurture components to develop excellence. In this article, we argue that the key to excellence does not reside...

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Published inFrontiers in psychology Vol. 7; p. 532
Main Authors Den Hartigh, Ruud J R, Van Dijk, Marijn W G, Steenbeek, Henderien W, Van Geert, Paul L C
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 20.04.2016
Subjects
Complexity
dynamic systems
Expertise
Psychology
simulation models
skewed distributions
talent development
giftedness
simulation models
complexity
idiosyncratic patterns
skewed distributions
dynamic systems
expertise
talent development
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Summary:Across different domains, from sports to science, some individuals accomplish excellent levels of performance. For over 150 years, researchers have debated the roles of specific nature and nurture components to develop excellence. In this article, we argue that the key to excellence does not reside in specific underlying components, but rather in the ongoing interactions among the components. We propose that excellence emerges out of dynamic networks consisting of idiosyncratic mixtures of interacting components such as genetic endowment, motivation, practice, and coaching. Using computer simulations we demonstrate that the dynamic network model accurately predicts typical properties of excellence reported in the literature, such as the idiosyncratic developmental trajectories leading to excellence and the highly skewed distributions of productivity present in virtually any achievement domain. Based on this novel theoretical perspective on excellent human performance, this article concludes by suggesting policy implications and directions for future research.
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This article was submitted to Developmental Psychology, a section of the journal Frontiers in Psychology
Edited by: Daniel Richardson, University College London, UK
Reviewed by: Vanessa R. Simmering, University of Wisconsin Madison, USA; Dean Keith Simonton, University of California, Davis, USA
ISSN:1664-1078
1664-1078
DOI:10.3389/fpsyg.2016.00532