Comprehension : a paradigm for cognition . -1998

목차 (Table of Contents)

• CONTENTS
• Preface = xiii
• Acknowledgments = xv
• 1. Introduction = 1
• 1.1. Understanding and comprehension = 2
• 1.2. A paradigm for cognition = 3
• 1.3. The architecture of cognition = 5
• 1.4. The goals and scope of the book = 7
• Ⅰ. The theory = 11
• 2. Cognition and representation = 13
• 2.1. Multiple representations : How the mind represents the world = 13
• 2.1.1. Types of mental representation = 15
• 2.1.2. The evidence for levels of representations = 19
• 2.1.3. Implications = 30
• 2.2. Propositional representations : How science represents the mind = 32
• 2.2.1. Features, semantic nets, and schemas = 34
• 2.2.2. The predicate-argument schema : Networks of propositions = 37
• 2.2.3. Encapsulated meaning = 42
• 2.2.4. Imagery = 44
• 3. Propositional representations = 49
• 3.1. The propositional representation of text = 49
• 3.1.1. The microstructure = 50
• 3.1.2. The macrostructure = 64
• 3.1.3. The psychological reality of propositions = 69
• 3.2. The propositional representation of knowledge = 73
• 3.2.1. The construction of meaning : Concepts = 74
• 3.2.2. Emergent structures = 82
• 3.3. Latent semantic analysis : A vector representations = 86
• 4. Modeling comprehension processes : The construction-integration model = 93
• 4.1. Construction and integration = 96
• 4.2. Processing cycles in text comprehension = 101
• 4.3. Textbase and situation model = 103
• 4.3.1. Imagery as a situation model = 108
• 4.3.2. A script-based situation model = 111
• 4.4. Earlier versions of the model = 118
• Ⅱ. Models of comptrhension = 121
• 5. Word identification in discourse = 123
• 5.1. The construction of word meanings = 123
• 5.1.1. From the retina to working memory = 124
• 5.1.2. Homographs = 128
• 5.1.3. Local and global priming in discourse : What words mean = 130
• 5.1.4. A simulation of priming effects in discourse = 136
• 5.2. Anaphora = 144
• 5.2.1. The psycholinguistics of anaphora resolution = 144
• 5.2.2. Anaphora resolution in the CI model = 149
• 5.3. Metaphor = 157
• 6. Textbases and situation models = 167
• 6.1 Parsing = 168
• 6.2. Macrostructure formation = 174
• 6.2.1. Signaling the macrostructure = 1777
• 6.2.2. Dominance of the macrostructure : Contradictions in the text = 181
• 6.2.3. Macrostructures as vectors in the LSA space = 184
• 6.3. Inferences = 188
• 6.3.1. Classification of inferences = 189
• 6.3.2. Inference generation during discourse comprehension = 193
• 6.3.3. Time course for constructing knowldege-based inferences = 198
• 6.3.4. The construction of situation models = 198
• 6.4. Spatial situation models = 199
• 6.5. Literary texts = 204
• 6.5.1. Versification as a source of constraints = 206
• 6.5.2. Multilevel situation models = 209
• 6.5.3. Comprehension strategies for literary language = 211
• 7. The role of working memory in comprehension = 215
• 7.1. Working memory and skilled memory = 217
• 7.2. Long-term working memory in text comprehension = 221
• 7.3. Retrieval structures in the CI model = 224
• 7.3.1. Episodic text memory during comprehension = 224
• 7.3.2. The activation of knowledge during comprehension = 227
• 7.3.3. The short-term memory buffer = 234
• 7.4. An LSA model of retrieval structures = 235
• 7.5. Capacity differences in working memory? = 238
• 8. Memory for text = 247
• 8.1. Recognition memory = 247
• 8.1.1. List-learning data and theory = 247
• 8.1.2. Sentence recognition = 251
• 8.2. Recall and summarization = 264
• 8.2.1. Simulations of story recall = 368
• 8.2.2. Evaluation of summaries = 277
• 9. Learning from text = 282
• 9.1. What makes for a good reader? = 282
• 9.1.1. Decoding skills = 282
• 9.1.2. Language skills = 284
• 9.1.3. Domain knowledge = 287
• 9.2. Learning and memory = 290
• 9.2.1. Textbase and situation model = 291
• 9.2.2. Learning = 293
• 9.3. The measurement of learning = 295
• 9.4. A simulation of learning with the CI model = 302
• 9.5. Using coherent text to improve learning = 307
• 9.6. Improving learning by stimulating active processing = 313
• 9.7. Matching students with instructional texts = 323
• 9.8. Educational implications = 327
• 10. Word problems = 332
• 10.1 Word arithmetic problems = 333
• 10.1.1. Schemas for solving word arithmetic problems = 334
• 10.1.2. Error simulation = 339
• 10.1.3. Situation models = 345
• 10.1.4. The CI model for word problem solving = 347
• 10.1.5. The emergence of schemas = 354
• 10.2. Word algebra problems = 358
• 10.2.1. Algebraic schemas = 359
• 10.2.2. A model for word algebra problems = 360
• 10.2.3. The ANIMATE tutor for solving word algebra problems = 364
• 11. Beyond text = 371
• 11.1. Action planning = 372
• 11.1.1. Routine actions = 372
• 11.1.2. Novices and experts = 381
• 11.1.3. Simulation of errors = 387
• 11.2. Problem solving, decision, and judgment = 394
• 11.2.1. The role of comprehension in problem solving and decision making = 394
• 11.2.2. Impression fromation = 402
• 11.3. The representation of the self in working memory = 409
• 11.3.1. Evaluative and motivational functions of self representation = 413
• 11.3.2. Cognition and emotion = 419
• 11.4. Outlook = 421
• References = 425
• Name Index = 449
• Subject Index = 459