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This book examines the role of experience-based learning on children's acquisition of language and concepts. It reviews, compares, and contrasts accounts of how the opportunity to recognize and generalize patterns influences learning. The book offers the first systematic integration of three highly influential research traditions in the domains of language and concept acquisition: Statistical Learning, Structural Alignment, and the Bayesian learning perspective. Chapters examine the parameters that constrain learning, address conditions that optimize learning, and offer explanations for cases in which implicit exemplar-based learning fails to occur. By exploring both the benefits and challenges children face as they learn from multiple examples, the book offers insight on how to better able to understand children's early unsupervised learning about language and concepts.
Topics featured in this book include:
- Competing models of statistical learning and how learning might be constrained by infants' developing cognitive abilities.
- How experience with multiple exemplars helps infants understand space and other relations.
- The emergence of category-based inductive reasoning during infancy and early childhood.
- How children learn individual verbs and the verb system over time.
- How statistical learning leads to aggregation and abstraction in word learning.
- Mechanisms for evaluating others' reliability as sources of knowledge when learning new words.
- The Search for Invariance (SI) hypothesis and its role in facilitating causal learning.
Language and Concept Acquisition from Infancy Through Childhood is an essential resource for researchers, clinicians and related professionals, and graduate students in infancy and early child development, applied linguistics, language education, child, school, and developmental psychology and related mental health and education services.
List of contents
Chapter 1: Introduction.- Chapter 2: Mechanisms of statistical learning in infancy.- Chapter 3: How multiple exemplars matter for infant spatial categorization.- Chapter 4: How the demands of a variable environment give rise to statistical learning.- Chapter 5: Structure-mapping processes enable infants' learning across domains, including language.- Chapter 6: The emergence of inductive reasoning during infancy: Learning from single and multiple exemplars.- Chapter 7: Learning individual verbs and the verb system: When are multiple examples helpful?.- Chapter 8: Multiple examples support children's word learning: The roles of aggregation, decontextualization and memory dynamics.- Chapter 9: Mechanisms for evaluating others' reliability when learning novel words.- Chapter 10: The search for invariance: Repeated positive testing serves the goals of causal learning in exploration and experimentation.- Chapter 11: Multiple exemplars of relations.- Chapter 12: Epilogue: Comparing comparison theories: What can we gain?.
About the author
Dr. Jane B. Childers (Ph.D. 1998, University of Texas at Austin), is a Professor and Chair of the Department of Psychology, and Director of the Linguistics Program, at Trinity University, San Antonio. Her main focus of research examines children's early verb learning, with an emphasis on how the comparison of events may be useful for deducing verb meaning. Her research has been funded by the Spencer Foundation and the National Institutes of Health, and she serves on the Editorial Board of the
Journal of Cognition and Development and the
Journal of Experimental Child Psychology.
