Exploring Differential Effects Across Two Decoding Treatments on Item-Level Transfer in Children With Significant Word Reading Difficulties: A New Approach for Testing Intervention Elements

Abstract

In English, gains in decoding skill do not map directly onto increases in word reading. However, beyond the Self-Teaching Hypothesis (Share, 1995), little is known about the transfer of decoding skills to word reading. In this study, we offer a new approach to testing specific decoding elements on transfer to word reading. To illustrate, we modeled word-reading gains among children with reading disability (RD) enrolled in Phonological and Strategy Training (PHAST) or Phonics for Reading (PFR). Conditions differed in sublexical training with PHAST stressing multi-level connections and PFR emphasizing simple grapheme-phoneme correspondences. Thirty-seven children with RD, 3rd – 6th grade, were randomly assigned 60 lessons of PHAST or PFR. Crossed random-effects models allowed us to identify specific intervention elements that differentially impacted word-reading performance at posttest, with children in PHAST better able to read words with variant vowel pronunciations. Results suggest that sublexical emphasis influences transfer gains to word reading.

Preventative Reading Interventions Teaching Direct Mapping of Graphemes in Texts and Set-for-Variability Aid At-Risk Learners

“…It was noted in the introduction that there exist a number of somewhat distinct conceptions of 'set-for-variability'. Both Gibson and Venezky's original work, and some recent intervention research (e.g., Steacy et al, 2016) focuses pedagogical attention on the variable pronunciations of many vowels in English.…”

“…Recently, Steacy, Elleman, Lovett, and Compton (2016) isolated the more specific effects of attention to the variable pronunciations of vowels and other taught word reading strategies, showing improved reading of closely related experimental items with variant vowels at post-test compared to a phonics control group that learned about GPCs but did not learn about processing variable vowels. In other works, 'set-for-variability' has been construed as a strategy primarily for correcting the pronunciations of erroneously regularized exception words (e.g., Dyson, Best, Solity, & Hulme, 2017;Zipke, 2016).…”

Development and Prediction of Context-Dependent Vowel Pronunciation in Elementary Readers

“…We estimated the variability explained by calculating the reduction in child and nonword variance from the base model using the formula ( r 010( Base model ) − r 010( model n ) )/ r 010( Base model ) , where n represents the model to which the base model was compared (Bryk & Raudenbush, 1992). A detailed description of these analyses is beyond the scope of this report, but these models have been widely reported in the literature (e.g., Duff & Hulme, 2012; Gilbert, Compton, & Kearns, 2011; Goodwin, Gilbert, & Cho, 2013; Kearns et al, 2015; Kim, Petscher, Foorman, & Zhou, 2010; Steacy et al, 2016; Steacy et al, 2017).…”

Cross-Linguistic Word Recognition Development Among Chinese Children: A Multilevel Linear Mixed-Effects Modeling Approach

“…Linear mixed-effects (LME) modeling permits a closer examination of these questions through item-level analysis of word and, ergo, character reading (Gilbert et al, 2011;Steacy et al, 2016). Here, we apply LME models to a large data set of lexical processing by children with Chinese characters and English words (365,760 total trials) to test item-level and subject-level factors that contribute to word recognition development in both Chinese and English.…”

“…Error bars depict 95% confidence intervals across subjects. Steacy et al, 2016;Guan et al, 2020). Here, we applied such models to understanding the development of word recognition from a cross-linguistic perspective.…”