Variability and Consistency in Early Language Learning: The Wordbank Project

by Michael C. Frank, Mika Braginsky, Daniel Yurovsky, Virginia A. Marchman

Overview

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.

Product Details

ISBN-13:	9780262045100
Publisher:	MIT Press
Publication date:	03/16/2021
Pages:	384
Product dimensions:	7.00(w) x 9.10(h) x 1.00(d)

About the Author

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.

Table of Contents

Preface ix
Overview ix
Outline xi
How to Read This Book xiii
Acknowledgments xiv
1 Theoretical Foundations 1
2 Practical Foundations 15
3 Methods and Data 27
4 Measurement Properties of the CDI 45
5 Vocabulary Size 65
6 Demographic Effects on Vocabulary Size 85
7 Gesture and Communication 111
8 Consistency in Early Vocabulary 125
9 Demographic Variation in Individual Words 139
10 Predictive Models of the Acquisition of Individual Words 165
11 Vocabulary Composition: Syntactic Categories 181
12 Vocabulary Composition: Semantic Categories 203
13 Morphology, Grammar, and the Lexicon 221
14 Morphological Overgeneralization 243
15 Individual Variation in Vocabulary 255
16 Variability and Consistency within and across Languages 283
17 Language Development at Scale 289
18 Beyond the CDI 303
Appendix A Individual Datasets 311
Appendix B Measures of Variability 325
Appendix C Stitching across Forms 329
Appendix D Estimating Age of Acquisition 333
References 337
Index 357

What People are Saying About This

From the Publisher

“Variability and Consistency in Early Language Learning is a tour de force. The scope of the topics covered through through the lens of parental report measures of early language development is remarkable. The authors have a total command of the extant literature, which motivates detailed and thoughtful exploration of this rich dataset. This marriage of theory and data makes me very excited to use this volume as the basis for future graduate seminars.”
—Jenny Saffran, Professor of Psychology, University of Wisconsin–Madison


“The era of big data in the study of language acquisition has officially begun! Frank and colleagues have used enormous amounts of data from the CDI to answer a number of theoretically interesting and important questions about children's early language, mostly using a web-based database and automated procedures. For the study of word learning, in particular, this book will be the necessary anchoring point for almost all future work.”
—Michael Tomasello, James F. Bonk Distinguished Professor of Psychology, Duke University
 
“Based on data from 29 languages and thousands of children, this impressive and systematic analysis shows in detail how early language development involves a ‘tightly woven’  developmental progression, along with room for variation that is predictable from input frequency, child gender, mother education, and unique features of the target language.”
—Brian MacWhinney, Professor of Psychology and Modern Languages, Carnegie Mellon University