What is Cognitive Science
Stable instability in development
Thursday, December 07, 2006, 12:00pm - 07:00pm
Rutgers University, Department of Psychology
Traditional studies in cognitive development use group averages at different ages to infer developmental patterns of change. Microgenetic studies, which follow a group of children with repeated testing, produce developmental curves through a period of change. Still, curves based on group data are difficult to interpret because they could represent many individuals� abrupt change or many individuals� slow change, or a combination thereof. The problem of describing development is rendered more complex when multiple abilities are under question. Studies using group data show a correlation between preschoolers� ability to attribute beliefs to others and their inhibitory control (Carlson, Moses & Breton, 2002). But what of the pattern of development within the individual? Is the correlation between these abilities an artifact of group statistics, or is there a theoretically-relevant relationship between these abilities in individuals� development?We examined individual development on standard false belief (FB) tasks and inhibitory control (IC) tasks, repeatedly testing the same individuals over a period of several months. Using the Gallistel algorithm, we identified statistically significant change points in each individual�s development. By studying curves for FB and IC, we can relate change points on different tasks within a given individual.Our analyses show various developmental patterns across individuals, though most children show neither �sudden insight� nor steady monotonic change. We reveal a very long period of change, or �stable instability�. The microgenetic method coupled with individual change-point analysis gives a new picture of developmental change.
"What is Cognitive Science?"
This lunchtime talks series is designed to introduce the University community to issues in Cognitive Science. Cognitive Science is one the the few fields where modern developments in computer science and artificial intelligence promise to shed light on classical problems in psychology and the philosophy of the mind. Ancient questions of how we see the world, understand language, and reason, and questions such as 'how a material system can know about the outside world', are being explored with the powerful new conceptual prosthetics of computer modeling.
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