The simple view of reading proposes that reading comprehension is the product of word reading and language comprehension. In this study, we used the simple view framework to examine the early prediction of reading comprehension abilities. Using multiple measures for all constructs, we assessed word reading precursors (i.e., letter knowledge, phonological awareness, rapid naming) and oral language at the beginning of kindergarten and reading comprehension at the end of third grade. Word reading was also assessed at the end of second grade and served as a mediator. Structural equation modeling showed that precursors of word reading and language comprehension accurately predicted reading comprehension in both mediated and non-mediated models. The results have important implications for the early identification of reading comprehension difficulties.

This study examined the structure of oral language and reading and their relation to comprehension from a latent variable modeling perspective in Kindergarten, Grade 1, and Grade 2. Participants were students in Kindergarten (n = 218), Grade 1 (n = 372), and Grade 2 (n = 273), attending Title 1 schools. Students were administered phonological awareness, syntax, vocabulary, listening comprehension, and decoding fluency measures in mid-year. Outcome measures included a listening comprehension measure in Kindergarten and a reading comprehension test in Grades1 and 2. In Kindergarten, oral language (consisting of listening comprehension, syntax, and vocabulary) shared variance with phonological awareness in predicting a listening comprehension outcome. However, in Grades 1 and 2, phonological awareness was no longer predictive of reading comprehension when decoding fluency and oral language were included in the model. In Grades 1 and 2, oral language and decoding fluency were significant predictors of reading comprehension.

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Recently, Tunmer and Chapman (2012) provided an alternative model of how decoding and listening comprehension affect reading comprehension that challenges the simple view of reading. They questioned the simple view’s fundamental assumption that oral language comprehension and decoding make independent contributions to reading comprehension by arguing that one component of oral language comprehension (vocabulary) affects decoding. They reported results from hierarchical regression analyses, exploratory factor analysis, and structural equation modeling to justify their conclusion. Their structural equation modeling results provided the strongest and most direct test of their alternative view. However, they incorrectly specified their simple view model. When correctly specified, the simple view of reading model and an alternative model in which listening comprehension affects decoding provide identically good fits to the data. This results from the fact that they are equivalent models. Although Tunmer and Chapman’s results do not support their assertion that a model in which oral language comprehension affects decoding provides a better fit to their data, the presence of equivalent models provides an ironic twist: The mountain of evidence that supports the simple view of reading provides equivalent support to their alternative interpretation. Additional studies are needed to differentiate these two theoretical accounts.

This randomized controlled trial in 55 low-performing schools across Florida compared 2 early literacy interventions-1 using stand-alone materials and 1 using materials embedded in the existing core reading/language arts program. A total of 3,447 students who were below the 30th percentile in vocabulary and reading-related skills participated in the study. Both interventions were implemented with fidelity for 45 minutes daily for 27 weeks in small groups of 4 students (or 5 in grade 2). The standalone intervention significantly improved grade 2 spelling outcomes relative to the embedded intervention; there were some differential impacts due to cohort and baseline and, in kindergarten, to English-learner status. On average, students in schools in both interventions showed similar improvement in reading and language outcomes and similar percentile gains to those in recent systematic reviews. Results are discussed with respect to alignment of Tier 2 instruction with Tier 1 instruction.

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The literature reports mixed findings on whether measuring individual change over time on an interim progress monitoring assessment adds value to understanding student differences in future performance on an assessment. This study examines the relations among descriptive measures of growth (simple difference and average difference) and inferential measures [ordinary least squares (OLS) and empirical Bayes] for 800,000 students in grades 4, 8, and 10 and considers how well such measures statistically explain differences in end-of-year reading comprehension after controlling for student performance on a mid-year status assessment. Student differences in their reading comprehension performance were explained by the four growth estimates (simple difference, average difference, OLS, and empirical Bayes) and differed by status variable used (i.e., performance on the fall, winter, or spring benchmark assessment). The four growth estimates examined in the study all contributed significantly to predicting end-of-year reading comprehension when initial, fall performance was used as a covariate. The simple difference growth estimate was the best predictor when controlling for mid-year (winter) status, and all but the simple difference estimate contributed significantly when controlling for final (spring) status.