Computational Models of Reading: A Handbook

Description

This book is about computational models of reading, or models that explain (and often simulate) the mental processes that allow us to convert the marks on a printed page into the representations that allow us to understand the contents of what we are reading. Computational Models of Reading assumes no prior knowledge of the topic and is intended for psychologists, linguists, and educators who are interested in gaining a better understanding of what happens in the mind during reading. Erik D. Reichle includes introductory chapters on reading research and computational modelling, and the "core" chapters of the book review both important empirical findings and the models designed to explain those findings within four domains of reading research: word identification, sentence processing, discourse representation, and eye-movement control (which involves coordinating word, sentence, and discourse processing with the perceptual, cognitive, and motoric systems responsible for vision, attention, and eye movements). The final chapter of the book describes a new integrative model of reading, �ber-Reader, and several simulations using the models that demonstrate how it explains several key reading phenomena. Title Page Copyright Page Dedication Contents Acknowledgments 1. Introduction Information-Processing Metaphors Brief Overview of the Human Information-Processing System Reading versus Spoken Language and Other Communication Summary and Conclusions Chapter Previews 2. Formal Models What are Formal Models? Different Approaches to Formal Modeling in Cognitive Science Process Models Production-System Models Connectionist Models Comparative Examples How are Models Compared? Computational Models of Reading 3. Models of Word Identification Word-Identification Research Word-Identification Tasks Learning Effects Orthographic Effects Phonological Effects Semantic Effects Patterns of Impairment Strategic Effects Precursor Theories and Models Logogen Model Bin Model Dual-Route Model Analogy Model Parallel-Coding Systems (PCS) Model Interactive-Activation (IA) Model Activation-Verification Model Triangle Model Multiple-Levels Model Multiple Read-Out Model Multiple-Trace Memory Model Connectionist Dual Process (CDP) Model Dual-Route Cascaded (DRC) Model SERIOL ACT-R Lexical-Decision Task Model Bayesian Reader Connectionist Dual Process (CDP+) Model Overlap Model Spatial-Coding Model (SCM) Model Comparisons Conclusions 4. Models of Sentence Processing Sentence-Processing Research Precursor Theories and Models Augmented Transitional Networks Sausage Machine Model Garden-Path Model Sentence-Gestalt (SG) Model Simple-Recurrent Network (SRN) CC-Reader Probabilistic Parser Attractor-Based Parser Constraint-Based Models Dependency-Locality Theory (DLT) Cue-Based Parser Activation-Based Model Surprisal Model Comparisons Conclusions 5. Models of Discourse Representation Discourse-Representation Research Precursor Theories and Models Story Grammars Kintsch & van Dijk’s (1978) Model Construction-Integration (CI) Model Situation-Space Model 3CI-Dynamic Model State-Space Search Model Landscape Model Resonance Model Langston-Trabasso Connectionist Model Distributed Situation-Space (DSS) Model Model Comparisons Conclusions 6. Models of the Reading Architecture Eye-Movement Research Precursor Theories and Models Gough’s (1972) Model Reader Morrison’s (1984) Model Rayner & Pollatsek’s (1989) Model Attention-Shift Model (ASM) E-Z Reader EMMA SWIFT Glenmore SERIF OB1-Reader Model Comparisons Conclusions 7. Synthesis Candidate Reading Architectures Über-Reader Word Identification Sentence Processing Discourse Representation Peripheral Systems Simulations Simulation 1: The Identification of Words Simulation 2: The Parsing of Sentences Simulation 3: The Reading of Sentences Simulation 4: The Representation and Recall of Discourse Limitations of Über-Reader Conclusions Appendix A—ACT-R Appendix B—3CAPS Appendix C—Connectionist Models Appendix D—Models of Episodic Memory References Index