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The International Dyslexia Association definition of dyslexia was updated 20 years ago and has been referenced frequently in research and practice. In this paper, researchers from the Florida Center for Reading Research consider the components of the definition and make recommendations for revisions. These include recognizing the persistence of word-reading, decoding, and spelling difficulties, acknowledging the multifactorial causal basis of dyslexia, clarifying exclusionary factors, and denoting comorbidity with other developmental disorders. It is also suggested that the academic and psychosocial consequences of dyslexia be highlighted to reinforce a preventive service delivery model. Lastly, the inclusion of dyslexia within a specific learning disability category is supported. [ABSTRACT FROM AUTHOR]

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 on item responses. 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 four types of Rasch-based EIRMs (i.e., doubly descriptive, person explanatory, item explanatory, doubly explanatory) 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 differ between the two approaches. Results are interpreted within the context of what each statistical model affords to the opportunity for describing and explaining differences in word-level performance.

The orthographic choice (OC) task--requiring individuals to choose the correct spelling between a word and a pseudohomophone foil (e.g., "goat" vs. "gote")--has been used as an outcome measure of orthographic learning and as a predictor of individual differences in word reading development. Some consider the OC task a measure of orthographic knowledge (e.g., Conrad, Harris, & Williams (Reading and Writing, 26(8), 1223-1239, 2013)), whereas others have suggested that the task measures a reader's familiarity with the word's orthographic representation and thus measures word reading skill (e.g., Castles & Nation, 2006). We examined this assertion by testing OC task performance of individuals ages 8 to 18 (J = 296) and their ability to read the OC target words (I = 80) in isolation using crossed random effects item-response models. Results reveal that response on the OC task is not fully determined by the ability of an individual to read the target word in isolation. Specifically, the probability of choosing the correct orthographic form when the word was pronounced incorrectly was 0.79; whereas it was 0.90 when the word was pronounced correctly. Measures of receptive spelling and phonemic awareness (person-characteristics) and word frequency and orthographic neighborhood size (item-characteristics) accounted for significant variance in orthographic choice after controlling for target item reading and other reading-related abilities. We interpret the results to suggest that the OC task taps both item-specific orthographic knowledge and more general orthographic knowledge.

A study investigated predictors of individual differences in responsiveness to word reading instruction in 55 typical first-graders and 41 identified as at-risk. A combination of rapid naming speed, letter sound knowledge, and phonemic awareness skill predicted word and nonword reading growth in the at-risk group. Growth modeling increased reading skills. (Contains references.) (Author/CR)