Language and Concept Acquisition from Infancy Through Childhood: Learning from Multiple Exemplars

Preface\nAcknowledgments\nContents\nContributors\nAbout the Editor\nChapter 1: Introduction\n	References\nChapter 2: Mechanisms of Statistical Learning in Infancy\n	Statistical Learning in Infancy\n	Kinds of Statistical Structure Infants Are Able to Learn\n	Testing Methods\n	Implications of Infant SL for Cognitive Development and Developmental Disabilities\n	Mechanisms Underlying Statistical Learning in Infancy\n	Conclusions and Broader Implications\n	References\nChapter 3: How Multiple Exemplars Matter for Infant Spatial Categorization\n	Why Spatial Relations?\n	Do Infants Require Multiple Exemplars for Forming Spatial Categories?\n	Procedures for Testing Infants’ Categorization of Spatial Relations\n	Does Infant Spatial Categorization Benefit from Multiple Examples?\n	What Mechanisms Are Central to Infant Spatial Categorization?\n	How Could the Other Theories in This Area Impact or Contribute to Your Findings?\n	Can Infant Spatial Categorization Inform Other Types of Spatial Learning?\n	References\nChapter 4: How the Demands of a Variable Environment Give Rise to Statistical Learning\n	Conditional Statistical Learning and Language Acquisition\n	Distributional Statistics\n	Representing Variability Across Exemplars\n	Encoding and Generalization in Memory\n	Memory and Statistical Learning\n	References\nChapter 5: Structure-Mapping Processes Enable Infants’ Learning Across Domains Including Language\n	When Is High Variability Helpful and When Not?\n	Promoting Relational Learning\n	What Paradigms Are Usually Used to Test Our Theory?\n	How Could Structure-Mapping Theory Extend Beyond Contexts?\n	Conclusions\n	References\nChapter 6: The Emergence of Inductive Reasoning During Infancy: Learning from Single and Multiple Exemplars\n	Inductive Reasoning During Early Childhood\n	Inductive Reasoning in Infancy\n	Developmental Origins of Inductive Reasoning\n		Unfamiliar Animal Categories\n		Familiar Animal Categories\n	Learning from One Versus Many: Integrating Findings Across Studies\n	Conclusions\n	References\nChapter 7: Learning Individual Verbs and the Verb System: When Are Multiple Examples Helpful?\n	Children’s Challenge in Acquiring the Lexical System of Verbs\n	Bootstrapping from Perceptual to Relational Similarity in Extracting the Core of Verb Meanings\n		Use of Multimodal Similarity (Iconicity)\n		Use of Object Similarity\n		Summary and Implications\n	An Additional Mechanism for Verb Learning: Contrast\n	Verb Meaning Acquisition Within the Constraints of the Lexical System\n		Complexity of the Semantic Structures in Lexical Domains in the Real World\n		What Do Children Need to Discover to Acquire Verbs in a Complex-Structured Lexical Domain?\n		Findings from the “Carry” Verb Acquisition Study\n			How Many Verb Types Did Children Know?\n			Does Children’s Representation of the Lexical Domain Stay the Same Between 3 and 7?\n			Reliance of Object Similarity to Structure the Semantic Domain\n			Factors Determining the Ease of Learning\n		Summary and Implications: Object Saliency, Similarity, and Contrast as Driving Forces for Structuring the Verb Lexicon\n	Conclusion\n	References\nChapter 8: Multiple Examples Support Children’s Word Learning: The Roles of Aggregation, Decontextualization, and Memory Dynamics\n	Statistical Learning\n	Multiple Examples Provide Support for Aggregation\n	Multiple Examples Provide Support for Abstraction and Decontextualization\n	Multiple Examples Provide Support for Retention and Memory\n	Conclusion\n	References\nChapter 9: Mechanisms for Evaluating Others’ Reliability When Learning Novel Words\n	Associative Origins of Selective Learning\n	Do More Sophisticated Mechanisms Underlie Children’s Social Learning: A Gaze Following Example\n	Questions Can Answer Questions About Mechanisms of Selective Word Learning\n	Concluding Thoughts: Beyond Selective Word Learning\n	References\nChapter 10: The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning\n	Positive Testing Strategy\n		PTS in Scientific Reasoning\n		PTS in Rule Learning\n		Theories of PTS\n			PTS as a Means of Generating Outcomes\n			PTS as a Means of Generating Evidence\n			Other Accounts and Overlapping Evidence\n	The Current Theory: Positive Testing and Causal Learning\n		Causal Invariance and Interventionism\n		The Search for Invariance (SI) Hypothesis\n			As an Alternative to “Engineering Desirable Outcomes”\n			As an Alternative to “Seeking Confirmatory Evidence”\n				Beyond Evidence of Sufficiency\n			As an Account of Previously Ambiguous Evidence\n	Conclusion: Relationship to Truth\n	References\nChapter 11: Multiple Exemplars of Relations\n	Exemplars of Relations—Unique Challenges\n	Why Is It Difficult to Perceive Multiple Exemplars of Relations?\n		Not Knowing the Relations\n		The Relations Are Known, but the Relational Similarity Is Not Salient\n	The Solution: Structural Alignment\n		Comparing What? Similarity of Exemplars\n		How Many Exemplars to Compare?\n		How Does Comparison Happen?\n			Object Similarity Invites Comparison\n			Progressive Alignment\n			Language Invites Comparison\n	Social Relational Learning\n		The Problem\n			Problem 1: Lack of Domain Knowledge\n			Problem 2: Relational Versus Object Matches\n		The Solution: How Does Structure Mapping Work in the Social Domain?\n			Language for Learning Relational Concepts\n			Does Object Similarity Help?\n			Social Comparison and Object Versus Relational Similarity\n			Alignable Differences\n	Summary\n	References\nChapter 12: Epilogue: Comparing Comparison Theories: What Can We Gain?\n	References\nIndex