Causal intervention strategies change across adolescence

Kate Nussenbaum, Alexandra O. Cohen, Zachary J. Davis, David Halpern, Todd M. Gureckis, Catherine Hartley

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Intervening on causal systems can illuminate their underlying structures. Past work has shown that, relative to adults, young children often make intervention decisions that confirm single hypotheses rather than those that discriminate alternative hypotheses. Here, we investigated how the ability to make informative intervention decisions changes across development. Ninety participants between the ages of 7 and 25 completed 40 different puzzles in which they had to intervene on various causal systems to determine their underlying structures. We found that the use of discriminatory strategies increased through adolescence and plateaued into adulthood. Our results identify a clear developmental trend in causal reasoning, and highlight the need to expand research on causal learning mechanisms in adolescence.

Original languageEnglish (US)
Title of host publicationProceedings of the 41st Annual Meeting of the Cognitive Science Society
Subtitle of host publicationCreativity + Cognition + Computation, CogSci 2019
PublisherThe Cognitive Science Society
Pages2481-2487
Number of pages7
ISBN (Electronic)0991196775, 9780991196777
StatePublished - 2019
Event41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019 - Montreal, Canada
Duration: Jul 24 2019Jul 27 2019

Publication series

NameProceedings of the 41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019

Conference

Conference41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019
Country/TerritoryCanada
CityMontreal
Period7/24/197/27/19

Keywords

  • causal learning
  • cognitive development
  • hypothesis testing
  • information-seeking

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

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