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Colloquium - Colunga

Using Networks to Understand Word Learning in Early and Late Talkers
Department of Psychology
12/1/2011
3:30pm-4:30pm

There is a lot of variability in the rate at which children learn words: An 18-month-old in the bottom 10th percentile in normative measures of expressive vocabulary knows about 2 words; an 18-month-old in the top 10th percentile knows more than 200. Evidence from our lab suggests that late and early talkers differ not only on the number of words they know (the measure used to define them as belonging to one or the other group), but also on a) the sorts of words that they know and b) the ways in which they learn new words. In this talk I will present new evidence suggesting that the words in late and early talker vocabularies also differ in the way they relate to each other. That is, the semantic networks of late talker vocabularies have different connectivity characteristics than the networks of early talker vocabularies. I will discuss our working hypothesis on the features of the learning algorithms that might give rise to the different patterns of connectivity observed.

Dr. Colunga is an Associate Professor in the department of Psychology and Neuroscience and an Adjunct Associate Professor in the Computer Science Department, and a faculty fellow with the Institute of Cognitive Science at the University of Colorado Boulder. Her research studies interactions between language and cognition using cross-linguistic, developmental and computational modeling methods. Her work on building neural network models of early word learning has been funded by the John Merck scholars foundation and awarded a 5-year R01 grant by the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institute of Health. Colunga received her PhD in Computer Science and Cognitive Science from Indiana University and her MS in Artificial Intelligence and BS in Computer Science from the Instituto Tecnologico y de Estudios Superiores de Monterrey, Mexico.

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