Muutke küpsiste eelistusi

E-raamat: Computational Models of Reading: A Handbook

(Professor of Cognitive Psychology, Macquarie University)
  • Formaat - PDF+DRM
  • Hind: 44,45 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

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.
Acknowledgments xi
1 Introduction
1(24)
Information-Processing Metaphors
4(4)
Brief Overview of the Human Information-Processing System
8(9)
Reading versus Spoken Language and Other Communication
17(3)
Summary and Conclusions
20(2)
Chapter Previews
22(3)
2 Formal Models
25(39)
What are Formal Models?
27(6)
Different Approaches to Formal Modeling in Cognitive Science
33(18)
Process Models
39(1)
Production-System Models
40(2)
Connectionist Models
42(6)
Comparative Examples
48(3)
How are Models Compared?
51(11)
Computational Models of Reading
62(2)
3 Models Of Word Identification
64(122)
Word-Identification Research
67(21)
Word-Identification Tasks
67(5)
Learning Effects
72(3)
Orthographic Effects
75(5)
Phonological Effects
80(3)
Semantic Effects
83(3)
Patterns of Impairment
86(1)
Strategic Effects
87(1)
Precursor Theories and Models
88(13)
Logogen Model
89(3)
Bin Model
92(2)
Dual-Route Model
94(2)
Analogy Model
96(2)
Parallel-Coding Systems (PCS) Model
98(3)
Interactive-Activation (IA) Model
101(6)
Activation-Verification Model
107(5)
Triangle Model
112(12)
Multiple-Levels Model
124(3)
Multiple Read-Out Model
127(2)
Multiple-Trace Memory Model
129(12)
Connectionist Dual Process (CDP) Model
141(6)
Dual-Route Cascaded (DRC) Model
147(7)
SERIOL
154(6)
ACT-R Lexical-Decision Task Model
160(3)
Bayesian Reader
163(5)
Connectionist Dual Process (CDP+) Model
168(2)
Overlap Model
170(3)
Spatial-Coding Model (SCM)
173(8)
Model Comparisons
181(4)
Conclusions
185(1)
4 Models Of Sentence Processing
186(90)
Sentence-Processing Research
199(7)
Precursor Theories and Models
206(6)
Augmented Transitional Networks
206(2)
Sausage Machine Model
208(4)
Garden-Path Model
212(6)
Sentence-Gestalt (SG) Model
218(6)
Simple-Recurrent Network (SRN)
224(5)
CC-Reader
229(3)
Probabilistic Parser
232(5)
Attractor-Based Parser
237(6)
Constraint-Based Models
243(10)
Dependency-Locality Theory (DLT)
253(3)
Cue-Based Parser
256(5)
Activation-Based Model
261(6)
Surprisal
267(1)
Model Comparisons
268(6)
Conclusions
274(2)
5 Models Of Discourse Representation
276(81)
Discourse-Representation Research
284(18)
Precursor Theories and Models
302(7)
Story Grammars
302(2)
Kintsch & van Dijk's (1978) Model
304(5)
Construction-Integration (CI) Model
309(6)
Situation-Space Model
315(7)
3CI-Dynamic Model
322(2)
State-Space Search Model
324(6)
Landscape Model
330(3)
Resonance Model
333(4)
Langston-Trabasso Connectionist Model
337(5)
Distributed Situation-Space (DSS) Model
342(8)
Model Comparisons
350(5)
Conclusions
355(2)
6 Models Of The Reading Architecture
357(85)
Eye-Movement Research
362(18)
Precursor Theories and Models
380(11)
Gough's (1972) Model
380(2)
Reader
382(3)
Morrison's (1984) Model
385(1)
Rayner & Pollatsek's (1989) Model
386(5)
Attention-Shift Model (ASM)
391(6)
E-Z Reader
397(10)
EMMA
407(3)
SWIFT
410(9)
Glenmore
419(5)
SERIF
424(8)
OB1-Reader
432(6)
Model Comparisons
438(2)
Conclusions
440(2)
7 Synthesis
442(73)
Candidate Reading Architectures
452(5)
Uber-Reader
457(30)
Word Identification
460(12)
Sentence Processing
472(5)
Discourse Representation
477(3)
Peripheral Systems
480(7)
Simulations
487(22)
Simulation 1 The Identification of Words
493(3)
Simulation 2 The Parsing of Sentences
496(4)
Simulation 3 The Reading of Sentences
500(6)
Simulation 4 The Representation and Recall of Discourse
506(3)
Limitations of Uber-Reader
509(2)
Conclusions
511(4)
Appendix A ACT-R 515(6)
Appendix B 3CAPS 521(3)
Appendix C Connectionist Models 524(7)
Appendix D Models Of Episodic Memory 531(8)
References 539(40)
Index 579
Erik D. Reichle is a Professor of Cognitive Psychology and the Head of the Department of Psychology at Macquarie University. His research uses computer modelling and eye-tracking experiments to understand the mental processes that are engaged during skilled reading. He has published more than 60 articles on these topics in leading peer-reviewed journals (e.g., Psychological Review, Psychological Science, Brain and Behavioral Sciences) and has received fellowships from the Hanse Institute for Advanced Study (Germany) and the Leverhulme Trust (United Kingdom).