The development of reading skill and bases of developmental dyslexia were explored using connectionist models. Four issues were examined: the acquisition of phonological knowledge prior to reading, how this knowledge facilitates learning to read, phonological and non phonological bases of dyslexia, and effects of literacy on phonological representation. Compared with simple feedforward networks, representing phonological knowledge in an attractor network yielded improved learning and generalization. Phonological and surface forms of developmental dyslexia, which are usually attributed to impairments in distinct lexical and nonlexical processing “routes,” were derived from different types of damage to the network. The results provide a computationally explicit account of many aspects of reading acquisition using connectionist principles.

the properties of distributed network models, and support this account by demonstrating that an implemented simulation closely approximates the empirical findings despite the absence of expectancy-based processes and postlexical semantic matching. The results suggest that distributed network models can provide a viable single-mechanism account of lexical processing. Introduction It is well-established that people are faster and more accurate to read a word (e.g., BUTTER) when it is preceded by a related word (e.g., BREAD) compared with when it is preceded by an unrelated word (e.g., DOCTOR; The research was supported by an NIMH FIRST award (MH55628) to the first author and by NIMH Training Grant 5T32MH19102 and NICHD Grant 80258. The computational simulation was run using customized software written within the Xerion simulator (version 3.1) developed by Drew van Camp, Tony Plate, and Geoff Hinton at the Univers

This monograph discusses research, theory, and practice relevant to how children learn to read English. After an initial overview of writing systems, the discussion summarizes research from developmental psychology on children's language competency when they enter school and on the nature of early reading development. Subsequent sections review theories of learning to read, the characteristics of children who do not learn to read (i.e., who have developmental dyslexia), research from cognitive psychology and cognitive neuroscience on skilled reading, and connectionist models of learning to read. The implications of the research findings for learning to read and teaching reading are discussed. Next, the primary methods used to teach reading (phonics and whole language) are summarized. The final section reviews laboratory and classroom studies on teaching reading. From these different sources of evidence, two inescapable conclusions emerge: (a) Mastering the alphabetic principle (that written symbols are associated with phonemes) is essential to becoming proficient in the skill of reading, and (b) methods that teach this principle directly are more effective than those that do not (especially for children who are at risk in some way for having difficulty learning to read). Using whole-language activities to supplement phonics instruction does help make reading fun and meaningful for children, but ultimately, phonics instruction is critically important because it helps beginning readers understand the alphabetic principle and learn new words. Thus, elementary -school teachers who make the alphabetic principle explicit are most effective in helping their students become skilled, independent readers.

xi 1 Introduction 1 1.1 Intuitions and Evidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Previous Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.2.1 The Classical Dual Route Model . . . . . . . . . . . . . . . . . . . . . . . 6 1.2.2 Seidenberg and McClelland 1989 . . . . . . . . . . . . . . . . . . . . . . 10 1.2.3 Plaut and Shallice 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.2.4 Plaut et al. 1996: Naming . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.2.5 Bullinaria 1996 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.2.6 Plaut 1997: Lexical Decision . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.2.7 Harm and Seidenberg 1998: Naming . . . . . . . . . . . . . . . . . . . . 16 1.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2 A New Computational Model 18 2.1 Principles . . . . . . . . . . . . . . . . . . . . . . . . ...

Graphemes are commonly defined as the written representation of phonemes. For example, the word 'BREAD' is composed of the four phonemes Po/, /r/, /e/ and /d/, and consequently, of the four graphemes 'B', 'R', 'EA', and 'D'. Graphemes can thus be considered the minimal 'functional bridges' in the mapping between orthography and phonology. In the present study, we investigated the hypothesis that graphemes are processed as perceptual units by the reading system. If the reading system processes graphemes as units, then detecting a letter in a word should be harder when this letter is embedded in a multi-letter grapheme than when it corresponds to a single-letter grapheme. In Experiment 1 A, done in English, participants were slower to detect a target letter in a word when the target letter was embedded in multi-letter grapheme (i.e. 'A' in 'BEACH') than when it corresponded to a single-letter grapheme (i.e. 'A' in 'PLACE'). In Experiment lB, this effect was replicated in French. In Experiment 2, done in English, this grapheme effect remained when phonemic similarity between the target letter alone and the target letter inside the word was controlled. Together, the results are consistent with the assumption that graphemes are processed as perceptual reading units in alphabetic writing systems such as English or French. 2000 Elsevier Science B.V. All fights reserved.

The development of reading depends on phonological awareness across all languages so far studied. Languages vary in the consistency with which phonology is represented in orthography. This results in developmental differences in the grain size of lexical representations and accompanying differences in developmental reading strategies and the manifestation of dyslexia across orthographies. Differences in lexical representations and reading across languages leave developmental “footprints ” in the adult lexicon. The lexical organization and processing strategies that are characteristic of skilled reading in different orthographies are affected by different developmental constraints in different writing systems. The authors develop a novel theoretical framework to explain these cross-language data, which they label a psycholinguistic grain size theory of reading and its development. Reading is the process of understanding speech written down. The goal is to gain access to meaning. To acquire reading, children must learn the code used by their culture for representing speech as a series of visual symbols. Learning to read is thus fundamentally a process of matching distinctive visual symbols to units of sound (phonology). In most languages, the relationship between symbol

This study examined the reading skills of children who have deficient decoding skills in the years following the first grade and traced their progress across 20 sessions of a decoding skills intervention called Word Building. Initially, the children demonstrated deficits in decoding, reading comprehension, and phonemic awareness skills. Further examination of decoding attempts revealed a pattern of accurate decoding of the first grapheme in a word, followed by relatively worse performance on subsequent vowels and consonants, suggesting that these children were not engaging in full alphabetic decoding. The intervention directed attention to each grapheme position within a word through a procedure of progressive minimal pairing of words that differed by one grapheme. Relative to children randomly assigned to a control group, children assigned to the intervention condition demonstrated significantly greater improvements in decoding attempts at all grapheme positions and also demonstrated significantly greater improvements in standardized measures of decoding, reading comprehension, and phonological awareness. Results are discussed in terms of the consequences of not fully engaging in alphabetic decoding during early reading experience, and the self-teaching role of alphabetic decoding for improving word identification, reading comprehension, and phonological awareness skills.

Developmental dyslexia and specific language impairment (SLI) were for many years treated as distinct disorders but are now often regarded as different manifestations of the same underlying problem, differing only in severity or developmental stage. The merging of these categories has been motivated by the reconceptualization of dyslexia as a language disorder in which phonological processing is deficient. The authors argue that this focus underestimates the independent influence of semantic and syntactic deficits, which are widespread in SLI and which affect reading comprehension and impair attainment of fluent reading in adolescence. The authors suggest that 2 dimensions of impairment are needed to conceptualize the relationship between these disorders and to capture phenotypic features that are important for identifying neurobiologically and etiologically coherent subgroups. Specific language impairment (SLI) and developmental dyslexia (also known as specific reading disability; SRD) are common developmental disorders that have a serious impact on a child’s educational and psychosocial outcome. SLI affects around 3%– 10 % of children (Tomblin et al., 1997) and is diagnosed when oral language lags behind other areas of development for no apparent

Abstract not found

Word recognition develops with such remarkable speed that, by the end of eighth grade, we expect children learning to read English to know and recognize over 80,000 words (Adams, 1990). At a basic level, beginning readers must establish a system of mappings or correspondences between the letters or graphemes of written words and the phonemes of spoken words (Ehri, 1992), and it is generally thought that this alphabetic decoding system is underpinned by phonological skills (Brady & Shankweiler, 1991; Byrne, 1998; Goswami & Bryant, 1990). To become an accurate and efficient reader of the English language, however, children need to do more than assemble or decode pronunciations on the basis of spelling-sound mappings. They need to acquire a rapid and flexible word-recognition system that embodies knowledge of both the regularities and the irregularities of the English orthography. While it is clear that the development of skilled word recognition requires more than the mastery of alphabetic decoding, we know very little about