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Prof. Michael Frank

Prof. Michael Frank

Stanford University


Variability and consistency in children's early language learning: A data-driven approach

Every typically developing child learns to talk, but children differ tremendously in how and when they do so. What predicts this variability? And which aspects of early language learning are consistent across the world’s languages and cultures? Here I’ll illustrate our efforts to create and curate datasets capturing children’s language input, processing, and vocabulary growth using data from tens of thousands of children learning dozens of different languages. Our aim is to create integrative, quantitative models of the growth of children’s early language.


Prof. Michael C. Frank is David and Lucile Packard Professor of Human Biology at Stanford University and Director of the Symbolic Systems Program. He received his Ph.D. from MIT in Brain and Cognitive Sciences in 2010. He studies language use and language learning, focusing especially on early word learning. He is the founder of the ManyBabies Consortium, a collaborative replication network for infancy research, and has led open-data projects including Wordbank and MetaLab. He was a Jacobs Foundation Fellow and has received the Troland Award from the National Academy of Sciences, the FABBS Early Career Impact Award, and the Marr Prize and Glushko Dissertation Prize from the Cognitive Science Society. He served as Chair of the Governing Board of the Cognitive Science Society and has edited for journals including Cognition and Child Development. (http://web.stanford.edu/~mcfrank/)

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