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140122 ||| eng |
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|a 9781461258803
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| 100 |
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|a Graesser, A.C.
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| 245 |
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|a Prose Comprehension Beyond the Word
|h Elektronische Ressource
|c by A.C. Graesser
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| 250 |
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|a 1st ed. 1981
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| 260 |
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|a New York, NY
|b Springer New York
|c 1981, 1981
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| 300 |
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|a X, 310 p
|b online resource
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| 505 |
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|a 1. A Schema-Based Framework for Representing Knowledge -- Cognitive Psychology and Cognitive Science -- Domains of Knowledge and Levels of Structure -- Linguistic Knowledge -- Rhetorical Knowledge -- Causal Conceptualizations -- Intentional Conceptualizations -- Spatial Knowledge -- Knowledge about Roles, Personalities, and Objects -- Schemas -- The Functioning of Schemas -- 2. Allocation of Cognitive Resources During Prose Comprehension -- Allocating Cognitive Resources to Different Components of Reading -- The Relationship Between Resource Allocation During Comprehension and Performance on Comprehension and Retention Tests -- Models of Reading -- Extracting Information from Newspapers -- 3. A Schema Pointer Plus Tag Model of Prose Memory -- Representational Assumptions of the SP+T Model -- Memory for Scripted Action Sequences -- Memory for Stereotype-Based Personality Descriptions -- Generating Guesses in Recall and Recognition --
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| 505 |
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|a Prose Representations -- Effects of Prior Context on the Interpretation of Statements -- Generation and Disconfirmation of Inferences and Expectations -- A Structural-Conceptual Analysis of On-line Comprehension -- Some Considerations for a Model of On-line Prose Comprehension -- Final Comments -- References -- Author Index
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| 505 |
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|a Retrieval Mechanisms During Recall and Recognition -- Effects of Retention Interval on Memory for Typical and Atypical Items -- Mathematical Formulation of the SP+T Model -- Alternative Explanations and Models -- Extensions of the Model -- 4. The Conceptual Representation of Prose in Memory -- Goals of the Proposed Theory of Prose Representation -- A System for Representing Prose -- A Question-Answering Method of Exposing Prose Inferences -- Conceptual Graph Structures for Narrative Passages -- Conceptual Graph Structures for Expository Passages -- Differences Between Narrative and Expository Prose -- Conceptual Graph Structures for Schemas -- Additional Issues Concerning the Conceptual Graph Structures -- 5. The Utilization of Prose Representations -- Question Answering -- Verification of Nodes -- Recall of Prose -- Conceptual Graph Structures Revisited -- 6. The Construction of Prose Representations -- A Question-Answering Method of Exploring the Construction of --
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| 653 |
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|a Psycholinguistics
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| 653 |
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|a Cognitive psychology
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| 653 |
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|a Psycholinguistics
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| 653 |
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|a Cognitive Psychology
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| 653 |
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|a Natural Language Processing (NLP)
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| 653 |
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|a Natural language processing (Computer science)
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b SBA
|a Springer Book Archives -2004
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| 856 |
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|u https://doi.org/10.1007/978-1-4612-5880-3?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 153
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| 520 |
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|a When individuals read or listen to prose they try to understand what it means. This is quite obvious. However, the cognitive mechanisms that participate in prose comprehension are far from obvious. Even simple stories involve com plexities that have stymied many cognitive scientists. Why is prose comprehen sion so difficult to study? Perhaps because comprehension is guided by so many domains of knowledge. Perhaps because some critical mysteries of prose comprehension reside between the lines-in the mind of the comprehender. Ten years ago very few psychologists were willing to dig beyond the surface of explicit code in their studies of discourse processing. Tacit knowledge, world knowledge, inferences, and expectations were slippery notions that experimental psychologists managed to circumvent rather than understand. In many scientific circles it was taboo to investigate mechanisms and phenomena that are not directly governed by the physical stimulus. Fortunately, times have changed. Cognitive scientists are now vigorously exploring the puzzles of comprehension that lie beyond the word. The study of discourse processing is currently growing at a frenetic pace
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