Variability and Consistency in Early Language Learning: The Wordbank Project

A data-driven exploration of how children's language learning varies across different languages, providing both a theoretical framework and reference.

The Wordbank Project examines variability and consistency in children's language learning across different languages and cultures, drawing on Wordbank, an open database with data from more than 75,000 children and twenty-nine languages or dialects. This big data approach makes the book the most comprehensive cross-linguistic analysis to date of early language learning. Moreover, its data-driven picture of which aspects of language learning are consistent across languages suggests constraints on the nature of children's language learning mechanisms. The book provides both a theoretical framework for scholars of language learning, language, and human cognition, and a resource for future research.

Michael C. Frank is David and Lucile Packard Professor of Human Biology and the Director of the Symbolic Systems Program at Stanford University. Virginia Marchman is Research Scientist at Stanford University. Daniel Yurovsky is Assistant Professor of Psychology at Carnegie Mellon University. Mika Braginsky is a PhD candidate in the Department of Brain and Cognitive Science at MIT.