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LPC Augment: An LPC-Based ASR Data Augmentation Algorithm for Low and Zero-Resource Children's Dialects ...
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Is that a pibu or a pibo? Children with reading and language deficits show difficulties in learning and overnight consolidation of phonologically similar pseudowords
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In: Dev Sci (2020)
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Individual differences in learning the regularities between orthography, phonology and semantics predict early reading skills
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In: J Mem Lang (2020)
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Strength of resting state functional connectivity and local GABA concentrations predict oral reading of real and pseudo-words
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Individual Differences in Reading Skill Are Related to Trial-by-Trial Neural Activation Variability in the Reading Network
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Dough, Tough, Cough, Rough: A “Fast” fMRI Localizer of Component Processes in Reading
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A model of phonological processing, language, and reading for students with mild intellectual disability
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In: Psychology Faculty Publications (2013)
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A Model of Phonological Processing, Language, and Reading for Students with Mild Intellectual Disability
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Multiple component remediation of developmental reading disabilities: A Controlled factorial evaluation of the influence of IQ, socioeconomic status, and race on outcomes
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In: Psychology Faculty Publications (2012)
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A randomized control study of instructional approaches for struggling adult readers
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Neurocognitive Predictors of Reading Outcomes for Children With Reading Disabilities
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In: Psychology Faculty Publications (2011)
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Abstract:
This study reports on several specific neurocognitive process predictors of reading outcomes for a sample of 278 children with reading disabilities. Three categories of response (i.e., poor, average, and good) were formed via growth curve models of six reading outcomes. Two nested discriminant function analyses were conducted to evaluate the predictive capability of the following models: (a) an intervention and phonological processing model that included intervention group, phonological awareness, and rapid naming and (b) an additive cognitive neuropsychological model that included measures of memory, visual processes, and cognitive or intellectual functioning. Over and above the substantial explanatory power of the base model, the additive model improved classification of poor and good responders. Several of the cognitive and neuropsychological variables predicted degree of reading outcomes, even after controlling for type of intervention, phonological awareness, and rapid naming.
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Keyword:
dyslexia; neuropsychological assessment; Psychology; reading; response to intervention; treatment
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URL: https://scholarworks.gsu.edu/psych_facpub/164 https://scholarworks.gsu.edu/cgi/viewcontent.cgi?article=1165&context=psych_facpub
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