The Effect of Facilitative Versus Inhibitory Word Training Corpora on Word Reading Accuracy Growth in Children With Dyslexia

2020 ◽  
pp. 073194872093868
Author(s):  
Laura M. Steacy ◽  
Yaacov Petscher ◽  
James D. Elliott ◽  
Kathryn Smith ◽  
Valeria M. Rigobon ◽  
...  

We modeled word reading growth in typically developing ( n = 118) and children with dyslexia ( n = 20), Grades 2–5, across multiple exposures to 30 words. We explored the facilitative versus inhibitory effects of exposures to differential mixes of words that support high- versus low-frequency vowel pronunciations. One training corpus contained a ratio of 80%–20% high- to low-frequency pronunciations (e.g., for ea; 80% ea pronounced as /i/ as in bead and 20% ea pronounced /ε/ as in dead), whereas the other consisted of a ratio of 20%–80%. We also modeled accuracy at the final exposure for a subset of 12 shared words across conditions using item-level crossed-random effects models with reading skill (i.e., typically developing vs. dyslexic), condition, word frequency, and vowel pronunciation (i.e., high- vs. low-frequency vowel pronunciation) as predictors in the model. We were particularly interested in the interaction between condition and vowel pronunciation across reading groups. Results suggest typically developing children were influenced by the interaction between condition and vowel pronunciation, suggesting both facilitation and inhibition, whereas children with dyslexia were influenced by condition and vowel pronunciation without an interaction. Results are interpreted within the overfitting model of dyslexia.

2020 ◽  
Author(s):  
Laura Steacy ◽  
Yaacov Petscher ◽  
James Elliott ◽  
Kathryn Smith ◽  
Valeria Maria Rigobon ◽  
...  

We modeled word reading growth in typically developing (n = 118) and children with dyslexia (n = 20), grades 2-5, across multiple exposures to 30 words. We explored the facilitative vs. inhibitory effects of exposures to differential mixes of words that support high vs. low frequency vowel pronunciations. One training corpus contained a ratio of 80%-20% high to low frequency pronunciations (e.g. for ea; 80% ea pronounced as /i/ as in bead and 20% ea pronounced /ε/ as in dead) while the other consisted of a ratio of 20%-80%. We also modeled accuracy at the final exposure for a subset of 12 shared words across conditions using item-level crossed random effects models with reading skill (i.e., typically developing vs. dyslexic), condition, word frequency, and vowel pronunciation (i.e., high vs. low frequency vowel pronunciation) as predictors in the model. We were particularly interested in the interaction between condition and vowel pronunciation across reading groups. Results suggest typically developing children were influenced by the interaction between condition and vowel pronunciation, suggesting both facilitation and inhibition; whereas children with dyslexia were influenced by condition and vowel pronunciation without an interaction. Results are interpreted within the overfitting model of dyslexia (Harm & Seidenberg, 1999).


2021 ◽  
pp. 002221942110232
Author(s):  
Miao Li ◽  
John R. Kirby ◽  
Esther Geva ◽  
Poh Wee Koh ◽  
Huan Zhang

This study examined (a) the identification of various reading groups across languages in Chinese (L1) adolescents learning English as a second language (ESL), in terms of their word-reading and reading comprehension skills, (b) overlap in reading group membership across languages, and (c) the performance of the various reading groups on reading-related language comprehension measures in English. The participants were 246 eighth-grade students from an English-immersion program in a middle school in China. Latent profile analysis identified three reading groups in each language: (a) a typically developing reader group with average or above-average word-reading and reading comprehension, (b) a group with poor decoding/word-reading skills and weak reading comprehension, and (c) a group with poor reading comprehension in the absence of poor decoding/word reading. The overlap in profile characteristics across languages for typically developing readers and poor decoders was high (about 68% for typically developing readers and 54% for poor decoders), whereas the overlap for being poor comprehenders in each language was moderate (about 37%). Furthermore, poor decoders in either language performed more poorly than the typically developing and poor comprehender groups on word reading in the other language, while poor comprehenders in either language performed more poorly than the typically developing and poor decoder groups on reading comprehension in the other language. The comparison of the reading groups’ performance on English reading-related language comprehension measures showed that poor comprehenders and poor decoders performed worse than typically developing readers. Implications for identification and instruction of ESL children with reading difficulties are discussed.


2021 ◽  
pp. 174702182199892
Author(s):  
Chiara Valeria Marinelli ◽  
Marika Iaia ◽  
Cristina Burani ◽  
Paola Angelelli

The study examines statistical learning in the spelling of Italian children with dyslexia and typically developing readers by studying their sensitivity to probabilistic cues in phoneme-grapheme mappings. In the first experiment children spelled to dictation regular words and words with unpredictable spelling that contained either a high- or a low-frequency (i.e., typical or atypical) sound-spelling mappings. Children with dyslexia were found to rely on probabilistic cues in writing stimuli with unpredictable spelling to a greater extent than typically developing children. The difficulties of children with dyslexia on words with unpredictable spelling were limited to those containing atypical mappings. In the second experiment children spelled new stimuli, that is, pseudowords, containing phonological segments with unpredictable mappings. The interaction between lexical knowledge and reliance on probabilistic cues was examined through a lexical priming paradigm in which pseudowords were primed by words containing related typical or atypical sound-to-spelling mappings. In spelling pseudowords, children with dyslexia showed sensitivity to probabilistic cues in the phoneme-to-grapheme mapping but lexical priming effects were also found, although to a smaller extent than in typically developing readers. The results suggest that children with dyslexia have a limited orthographic lexicon but are able to extract regularities from the orthographic system and rely on probabilistic cues in spelling words and pseudowords.


2000 ◽  
Vol 31 (3) ◽  
pp. 265-279 ◽  
Author(s):  
Elaine R. Silliman ◽  
Ruth Bahr ◽  
Jill Beasman ◽  
Louise C. Wilkinson

Purpose: This article describes a study on the scaffolding of learning to read in a primary-level, continuous-progress, inclusion classroom that stressed a critical thinking curriculum and employed a collaborative teaching model. Two emergent reading groups were the focus of study—one group that was taught by a general educator and the other by a special educator. The primary purposes were to discern the teachers’ discourse patterns in order to define whether scaffolding sequences were more directive or more supportive and the degree to which these sequences represented differentiated instruction for children with a language learning disability (LLD). Method: Two students with an LLD and two younger, typically developing peers were videotaped in their emergent reading groups during an 8-week period. The distribution, types, and functions of teacher scaffolding sequences were examined. Results: Both team members primarily used directive scaffolding sequences, suggesting that the assistance provided to children emphasized only direct instruction (skill learning) and not analytical thinking concerning phonemegrapheme relationships (strategy learning). Distribution of scaffolding sequence types directed to the four students indicated that the two children with an LLD were receiving reading instruction that was undifferentiated from the two typically developing, younger children. Clinical Implications: In order for children with an LLD to benefit from inclusion, explicit, systematic, and intensive instruction in phonological awareness and spelling-sound relationships should be implemented within the context of multilevel instruction that balances skill- and strategy-based learning.


2019 ◽  
Author(s):  
Yaacov Petscher ◽  
Donald Compton ◽  
Laura M. Steacy ◽  
Hannah Kinnon

Models of word reading that simultaneously take into account item-level and person-level fixed and random effects are broadly known as explanatory item response models (EIRM). Although many variants of the EIRM are available, the field has generally focused on the doubly explanatory model for modeling individual differences. Moreover, the historical application of the EIRM has been a Rasch version of the model where the item discrimination values are fixed at 1.0 and the random or fixed item effects only pertain to the item difficulties. The statistical literature has advanced to allow for more robust testing of observed or latent outcomes, as well as more flexible parameterizations of the EIRM. The purpose of the present study was to compare the observed and latent Rasch EIRM using commonly used statistical software (R and Mplus) and more broadly compare Rasch and 2PL EIRM when including person-level and item-level predictors. Results showed that not only was the error variance smaller in the unconditional 2PL EIRM compared to the Rasch EIRM due to including the item discrimination random effect, but that patterns of unique item-level explanatory variables difference between the two approaches. Results are interpreted within the context of what each statistical model affords to the opportunity for describing and explaining individual differences in word-level performance.


2019 ◽  
Author(s):  
Brianna L. Yamasaki ◽  
Karla Kay McGregor ◽  
James R. Booth

According to the Interactive Specialization Theory, cognitive skill development is facilitated by a process of neural specialization. In line with this theory, the current study investigated whether neural specialization for phonological and semantic processing at 5-to-6 years old was predictive of growth in word reading skills from 5-to-8 years old. Specifically, four regression models were estimated in which reading growth was predicted from: (1) an intercept-only model, (2) measures of semantic and phonological neural specialization, (3) performance on semantic and phonological behavioral tasks, or (4) a combination of neural specialization and behavioral performance. Results from the preregistered analyses revealed little evidence in favor of the hypothesis that early semantic and phonological skills predict growth in reading. However, results from the exploratory analyses, which included a larger sample, focused exclusively on the phonological predictors, and investigated relative growth in reading, demonstrated strong evidence that variability in phonological processing is predictive of growth in word reading skills. Specifically, the best fitting model included both measures of phonological neural specialization within the posterior superior temporal gyrus and performance on a phonological behavioral task. This work provides important preliminary evidence in favor of the Interactive Specialization Theory and, more specifically, for the role of phonological neural specialization in the development of early word reading skills.


Biometrika ◽  
2019 ◽  
Author(s):  
O Papaspiliopoulos ◽  
G O Roberts ◽  
G Zanella

Summary We develop methodology and complexity theory for Markov chain Monte Carlo algorithms used in inference for crossed random effects models in modern analysis of variance. We consider a plain Gibbs sampler and propose a simple modification, referred to as a collapsed Gibbs sampler. Under some balancedness conditions on the data designs and assuming that precision hyperparameters are known, we demonstrate that the plain Gibbs sampler is not scalable, in the sense that its complexity is worse than proportional to the number of parameters and data, but the collapsed Gibbs sampler is scalable. In simulated and real datasets we show that the explicit convergence rates predicted by our theory closely match the computable, but nonexplicit rates in cases where the design assumptions are violated. We also show empirically that the collapsed Gibbs sampler extended to sample precision hyperparameters significantly outperforms alternative state-of-the-art algorithms.


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