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The dynamics of development: Challenges for Bayesian rationality

Published online by Cambridge University Press:  12 February 2009

Nils Straubinger ,
Edward T. Cokely  and
Jeffrey R. Stevens
Nils Straubinger
Affiliation:
Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, Berlin, 14195, Germany. straubinger@mpib-berlin.mpg.decokely@mpib-berlin.mpg.dejstevens@mpib-berlin.mpg.dewww-abc.mpib-berlin.mpg.de/users/jstevens/
Edward T. Cokely
Affiliation:
Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, Berlin, 14195, Germany. straubinger@mpib-berlin.mpg.decokely@mpib-berlin.mpg.dejstevens@mpib-berlin.mpg.dewww-abc.mpib-berlin.mpg.de/users/jstevens/
Jeffrey R. Stevens
Affiliation:
Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, Berlin, 14195, Germany. straubinger@mpib-berlin.mpg.decokely@mpib-berlin.mpg.dejstevens@mpib-berlin.mpg.dewww-abc.mpib-berlin.mpg.de/users/jstevens/
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Abstract

Oaksford & Chater (O&C) focus on patterns of typical adult reasoning from a probabilistic perspective. We discuss implications of extending the probabilistic approach to lifespan development, considering the role of working memory, strategy use, and expertise. Explaining variations in human reasoning poses a challenge to Bayesian rational analysis, as it requires integrating knowledge about cognitive processes.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 32 , Issue 1 , February 2009 , pp. 103 - 104
Copyright
Copyright © Cambridge University Press 2009

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References

Anderson, J. R. (1991a) Is human cognition adaptive? Behavioral and Brain Sciences 14:471–84; discussion 485–517.CrossRefGoogle Scholar
Baltes, P. B., Staudinger, U. M. & Lindenberger, U. (1999) Lifespan psychology: Theory and application to intellectual functioning. Annual Review of Psychology 50:471–507.CrossRefGoogle ScholarPubMed
Brighton, H. & Gigerenzer, G. (2008) Bayesian brains and cognitive mechanisms: Harmony or dissonance? In: The probabilistic mind: Prospects for Bayesian cognitive science, ed. Chater, N. & Oaksford, M., pp. 189–208, Oxford University Press.CrossRefGoogle Scholar
Cokely, E. T., Kelley, C. M. & Gilchrist, A. L. (2006) Sources of individual differences in working memory: Contributions of strategy to capacity. Psychonomic Bulletin and Review 13:991–97.CrossRefGoogle ScholarPubMed
Conlin, J. A., Gathercole, S. E. & Adams, J. W. (2005) Children's working memory: Investigating performance limitations in complex span tasks. Journal of Experimental Child Psychology 90:303–17.CrossRefGoogle ScholarPubMed
Dick, F., Leech, R., Moses, P. & Saccuman, M. C. (2006) The interplay of learning and development in shaping neural organization. Developmental Science 9:14–17.CrossRefGoogle ScholarPubMed
Ericsson, K. A., Charness, N., Hoffmann, R. R. & Feltovich, P. J. (2006) Cambridge handbook of expertise and expert performance. Cambridge University Press.CrossRefGoogle Scholar
Ericsson, K. A. & Kintsch, W. (1995) Long-term working memory. Psychological Review 102:211–45.CrossRefGoogle ScholarPubMed
Ericsson, K. A. & Lehmann, A. C. (1996) Expert and exceptional performance: Evidence of maximal adaptation to task constraints. Annual Reviews in Psychology 47:273–305.CrossRefGoogle ScholarPubMed
Falk, R. & Wilkening, F. (1998) Children's construction of fair chances: Adjusting probabilities. Developmental Psychology 34:1340–57.CrossRefGoogle ScholarPubMed
Galotti, K. M., Komatsu, L. K. & Voelz, S. (1997) Children's differential performance on deductive and inductive syllogisms. Developmental Psychology 33:70–78.CrossRefGoogle ScholarPubMed
Howe, M. L. & Rabinowitz, F. M. (1996) Reasoning from memory: A lifespan inquiry into the necessity of remembering when reasoning about class inclusion. Journal of Experimental Child Psychology 61:1–42.CrossRefGoogle ScholarPubMed
Kyllonen, P. C. & Christal, R. E. (1990) Reasoning ability is (little more than) working-memory capacity?! Intelligence 14:389–433.CrossRefGoogle Scholar
Markovits, H. & Barrouillet, P. (2002) The development of conditional reasoning: A mental model account. Developmental Review 22:5–36.CrossRefGoogle Scholar
Navarro, D. J., Griffiths, T. L., Steyvers, M. & Lee, M. D. (2006) Modeling individual differences using Dirichlet processes. Journal of Mathematical Psychology 50:101–22.CrossRefGoogle Scholar
Oaksford, M. & Chater, N. (2007) Bayesian rationality: The probabilistic approach to human reasoning. Oxford University Press.CrossRefGoogle Scholar
Piaget, J. & Inhelder, B. (1975) The origin of the idea of chance in children. W. W. Norton.Google Scholar
Shultz, T. R. (2007) The Bayesian revolution approaches psychological development. Developmental Science 10:357–64.CrossRefGoogle ScholarPubMed
Sobel, D. M., Tenenbaum, J. B. & Gopnik, A. (2004) Children's causal inferences from indirect evidence: Backwards blocking and Bayesian reasoning in preschoolers. Cognitive Science 28:303–33.Google Scholar
Sternberg, R. J. (1999) Intelligence as developing expertise. Contemporary Educational Psychology 24:359–75.CrossRefGoogle ScholarPubMed
Verhaeghen, P. & Salthouse, T. A. (1997) Meta-analyses of age-cognition relations in adulthood: Estimates of linear and nonlinear age effects and structural models. Psychological Bulletin 122:231–49.CrossRefGoogle ScholarPubMed