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This study was part of a larger longitudinal study in which we focused on measuring reading acquisition and observing the impact of SES, curriculum and gender on reading subtest scores. In Part 1 of our study (in review), we reported on findings for students in Grade 1. For Part 2 of our study, we report on our findings for students in Grades 3 and 5 and offer a comparison across the three elementary grades. Participants for the current study included 657 students from Grade 3 (n = 328) and 5 (n = 329) representing low-cost, middle-cost and high-cost schools in Bangalore, India. The students' reading skills were measured using progress-monitoring tools and we utilized a mixed-effects hierarchical growth model to observe reading growth. The results suggested that both SES and curriculum had the most significant and positive effect on skills acquisition. These results will shed light on reading assessment and intervention practices in the Indian context.

Purpose: Bayesian-based models for diagnosis are common in medicine but have not been incorporated into identification models for dyslexia. The purpose of the present study was to evaluate Bayesian identification models that included a broader set of predictors and that capitalized on recent developments in modeling the prevalence of dyslexia. Method: Model-based meta-analysis was used to create a composite correlation matrix that included common predictors of dyslexia such as decoding, phonological awareness, oral language, but also included response to intervention (RTI) and family risk for dyslexia. Bayesian logistic regression models were used to predict poor reading comprehension, unexpectedly poor reading comprehension, poor decoding, and unexpectedly poor decoding, all at two levels of severity. Results: Most predictors made independent and substantial contributions to prediction, supporting models of dyslexia that rely on multiple rather than single indicators. RTI was the strongest predictor of poor reading comprehension and unexpectedly poor reading comprehension. Phonological awareness was the strongest predictor of poor decoding and unexpectedly poor decoding, followed closely by family risk. Conclusion: Bayesian-based models are a promising tool for implementing multiple-indicator models of identification. Ideas for improving prediction and implications for theory and practice are discussed.

Definitions of dyslexia typically make reference to unexpected poor reading, although how best to operationalize unexpected remains an issue. When operationally defined as reading below expectations based on the level of oral language, cases of unexpected poor reading make up fewer than half of cases of poor reading, and cases of unexpected poor reading occur throughout the range of reading proficiency. An implication is that what optimally predicts poor reading may not optimally predict unexpected poor reading. The goal of the three presented studies was to test this implication empirically. In Study 1, a model-based meta-analysis, phonological awareness accounted for 40% of the variance in decoding but only 1% of the variance in decoding that was unexpected based on level of vocabulary. Conversely, unexpected phonological awareness accounted for 34% of the variance in unexpected decoding but only 1% of the variance in decoding. An analogous pattern of results occurred for reading comprehension. In Study 2, a study of 766 children in kindergarten, first grade, and second grade, latent variables were used to represent oral vocabulary, phonological awareness, and decoding. As was seen in Study 1, unexpected decoding was better predicted by unexpected phonological awareness than by phonological awareness. In Study 3, a longitudinal study of 1025 children followed from preschool through grade 2, the pattern of results mirrored those of Studies 1 and 2. An important implication of these studies is that typical assessments may be better at identifying poor reading than they are at identifying unexpected poor reading or dyslexia.

The purpose of this meta-analysis was to examine the comprehension problems of children who have a specific reading comprehension deficit (SCD), which is characterized by poor reading comprehension despite adequate decoding. The meta-analysis included 86 studies of children with SCD who were assessed in reading comprehension and oral language (vocabulary, listening comprehension, storytelling ability, and semantic and syntactic knowledge). Results indicated that children with SCD had deficits in oral language (d = -0.78, 95% confidence interval, CI [-0.89, -0.68], but these deficits were not as severe as their deficit in reading comprehension (d = -2.78, 95% CI [-3.01, -2.54]). When compared with reading comprehension age-matched normal readers, the oral language skills of the two groups were comparable (d = 0.32, 95% CI [-0.49, 1.14]), which suggests that the oral language weaknesses of children with SCD represent a developmental delay rather than developmental deviance. Theoretical and practical implications of these findings are discussed.

Many individuals with poor reading comprehension have levels of reading comprehension that are consistent with deficits in their ability to decode the words on the page. However, there are individuals who are poor at reading comprehension despite being adequate at decoding. This phenomenon is referred to as specific reading comprehension deficit (SRCD). The two purposes of this study were to use a new approach to estimate the prevalence of SRCD and to examine the extent to which SRCD can be explained by the simple view of reading. We used model-based meta-analysis of correlation matrices from standardized tests to create composite correlation matrices for the constructs of reading comprehension, decoding, and listening comprehension. Using simulated datasets generated from the composite correlation matrices, we used residuals from regressing reading comprehension on decoding to create a continuous index of SRCD. The prevalence of SRCD is best represented not as a single number but as a continuous distribution in which prevalence varies as a function of the magnitude of the severity of the deficit in reading comprehension relative to the level of decoding. Examining the joint distribution of the residuals with reading comprehension makes clear that the phenomenon of reading comprehension that is poor relative to decoding occurs throughout the distribution of reading comprehension skill. Although the simple view of reading predictors of listening comprehension and decoding makes significant contributions to predicting reading comprehension, nearly half of the variance is unaccounted for.

This study explores the possibility of adapting specific progress-monitoring tools developed in the US for use in English-medium private schools in Bangalore. In the US, many teachers adopt progress-monitoring tools like the Dynamic Indicators of Basic Early Literacy Skills (DIBELS) and Curriculum Based Measurement (easyCBM) to keep track of their students' reading abilities. We report on Phase 1 of a longitudinal study that included three phases of data collection. Participants included 1003 students in Grades 1, 3 and 5, and 50 teachers. Both quantitative and qualitative data were collected. Results indicated that students in low-cost schools struggled on all reading measures throughout elementary school; students in middle-cost schools had below average to average scores on reading measures; and students from high-cost schools had average to above average scores on all measures. Moreover, factors like oral language proficiency in English, socio-economic status, school and curriculum increased in their significance in predicting reading as students progressed through elementary grades. Teacher data suggested that the reading goals and instructional strategies varied considerably across schools. Implications for reading instruction and practice within the Indian context will be discussed.

The science of reading should be informed by an evolving evidence base built on the scientific method. Decades of basic research and randomized controlled trials of interventions and instructional routines have formed a substantial evidence base to guide best practices in reading instruction, reading intervention, and the early identification of at-risk readers. The recent resurfacing of questions about what constitutes the science of reading is leading to misinformation in the public space that may be viewed by educational stakeholders as merely differences of opinion among scientists. The authors' goals in this article were to revisit the science of reading through an epistemological lens to clarify what constitutes evidence in the science of reading, and to offer a critical evaluation of the evidence provided by the science of reading. To this end, the authors summarize those things that they believe have compelling evidence, promising evidence, or a lack of compelling evidence. The authors conclude with a discussion of areas of focus that they believe will advance the science of reading to meet the needs of all students in the 21st century.

In this large-scale study of students from Title 1 schools (N = 14,773), we used multiple-group latent change score (LCS) modeling to investigate the developmental relations between vocabulary knowledge and reading comprehension in students with a school-identified learning disability (LD; n = 627) and typically developing students (n = 14,146). Students were tested for their vocabulary breadth and passage comprehension skills in kindergarten through fourth grade. For typically developing students, there were bidirectional influences between their vocabulary knowledge and reading comprehension skills. There were no cross-lagged influences across constructs for students with an LD. We find evidence for a developmental delay, such that students with an LD had similar levels and gains in their vocabulary knowledge relative to typically developing students, but these students started much lower in their reading comprehension skills and did not catch up to their typically developing peers. We discuss the implications for children with learning disabilities and the development of their reading comprehension skills.

Despite the importance of identifying individuals with reading disabilities, existing operational definitions of reading disability do not result in reliable identification. A large part of the problem arises from measurement error when a cut-point is imposed on a continuous distribution, especially for low base-rate conditions. One way to reduce measurement error is to include additional predictors in reading disability models. The present study examined co-occurring math disability as a possible additional criterion for predicting reading disability. Meta-analysis was used to examine the probability of individuals with reading disability also having a comorbid math disability. The main result was an average weighted odds ratio of 2.12, 95% confidence interval [1.76, 2.55], indicating that students with a math disability are just over 2 times more likely to also have a reading disability than those without a math disability. The purpose of the present study was to use meta-analysis to examine the extent to which the presence of math disability was associated with greater risk of reading disability.

How prevalent is dyslexia? A definitive answer to this question has been elusive because of the continuous distribution of reading performance and predictors of dyslexia and because of the heterogeneous nature of samples of poor readers. Samples of poor readers are a mixture of individuals whose reading is consistent with or expected based on their performance in other academic areas and in language, and individuals with dyslexia whose reading is not consistent with or expected based on their other performances. In the present article, we replicate and extend a new approach for determining the prevalence of dyslexia. Using model-based meta-analysis and simulation, three main results were found. First, the prevalence of dyslexia is better represented as a distribution that varies as a function of severity as opposed to any single-point estimate. Second, samples of poor readers will contain more expected poor readers than unexpected or dyslexic readers. Third, individuals with dyslexia can be found across the reading spectrum as opposed to only at the lower tail of reading performance. These results have implications for screening and identification, and for recruiting participants for scientific studies of dyslexia.

In the present study we investigated a developmentally changing role of text reading fluency in mediating the relations of word reading fluency and listening comprehension to reading comprehension. We addressed this question by using longitudinal data from Grades 1 to 4 and employing structural equation models. Results showed that the role of text reading fluency changes over time as children's reading proficiency develops. In the beginning phase of reading development (Grade 1), text reading fluency was not independently related to reading comprehension over and above word reading fluency and listening comprehension. In Grades 2 to 4, however, text reading fluency completely mediated the relation between word reading fluency and reading comprehension, whereas it partially mediated the relation between listening comprehension and reading comprehension. These results suggest that text reading fluency is a dissociable construct that plays a developmentally changing role in reading acquisition. [This article was published in "Scientific Studies of Reading," (EJ1055944).]

Despite decades of research, it has been difficult to achieve consensus on a definition of common learning disabilities such as dyslexia. This lack of consensus represents a fundamental problem for the field. Our approach to addressing this issue is to use model-based meta-analyses and Bayesian models with informative priors to combine the results of a large number of studies for the purpose of yielding a more stable and well-supported conceptualization of reading disability. A prerequisite to implementing these models is establishing informative priors for dyslexia. We illustrate a new approach for doing so based on the known distribution of the difference between correlated variables, and use this distribution to determine the proportion of poor readers whose poor reading is unexpected (i.e., likely to be due to dyslexia) as opposed to expected.

The present study examined the reading comprehension and receptive vocabulary skills of children with poor reading comprehension despite adequate decoding using a regression-based matching technique. Participants included five cohorts of children who were identified as typical readers (N = 70,493 - 75,553) or as children with specific reading comprehension difficulties (N = 480 - 8,717). Across cohorts, children with specific reading comprehension difficulties exhibited oral language difficulties based on a measure of vocabulary; however, the observed weakness in vocabulary was not as severe as their reading comprehension difficulties. Results from the regression-based matching technique suggested that the vocabulary weakness for these children is better characterized as a developmental delay rather than a developmental deficit. This outcome also emerged when more stringent criteria were used to identify subgroups of readers. Although children with poor reading comprehension despite adequate decoding have a weakness in at least one aspect of oral language, their oral language weakness does not account for the severity of their reading comprehension difficulties. Theoretical and practical implications are discussed.

The purpose of this review was to introduce readers of "Child Development" to the meta-analytic structural equation modeling (MASEM) technique. Provided are a background to the MASEM approach, a discussion of its utility in the study of child development, and an application of this technique in the study of reading comprehension (RC) development. MASEM uses a two-stage approach: first, it provides a composite correlation matrix across included variables, and second, it fits hypothesized a priori models. The provided MASEM application used a large sample (N = 1,205,581) of students (ages 3.5-46.225) from 155 studies to investigate the factor structure and relations among components of RC. The practical implications of using this technique to study development are discussed. [This research was also funded by The U.S. Department of Education, however no grant number was provided at this time. ]

A fairly recent definition of reading disability (RD) is that in the form of a hybrid model. The model views RD as a latent construct that is manifested through various observable unexpected impairments in reading-related skills and through inadequate response to intervention. The current report evaluated this new conceptualization of RD from an etiological perspective. The sample consisted of 2,737 twin pairs in 1st through 4th grade (M[subscript age] = 8.52) from the Florida Twin Project on Reading. Using twin analyses, results showed that a substantial proportion of genetic variance, a small proportion of shared environmental, and a small proportion of nonshared environmental variance was attributed to the RD factor. Findings suggest that the etiological architecture of RD closely mirrors the structure of the hybrid model of RD.

Text-to-speech and related read-aloud tools are being widely implemented in an attempt to assist students' reading comprehension skills. Read-aloud software, including text-to-speech, is used to translate written text into spoken text, enabling one to listen to written text while reading along. It is not clear how effective text-to-speech is at improving reading comprehension. This study addresses this gap in the research by conducting a meta-analysis on the effects of text-to-speech technology and related read-aloud tools on reading comprehension for students with reading difficulties. Random effects models yielded an average weighted effect size of (d-bar = 0.35, with a 95% confidence interval of 0.14 to 0.56, p < 0.01). Moderator effects of study design were found to explain some of the variance. Taken together, this suggests that text-to-speech technologies may assist students with reading comprehension. However, more studies are needed to further explore the moderating variables of text-to-speech and read-aloud tools' effectiveness for improving reading comprehension. Implications and recommendations for future research are discussed.

We conducted a meta-analysis of 16 existing studies to examine the nature of the comprehension problems for children who were second-language learners with poor reading comprehension despite adequate decoding. Results indicated that these children had deficits in oral language (d = -0.80), but these deficits were not as severe as their reading comprehension deficit (d = -2.47). Second-language learners also had weaker oral language skills compared with native-speaking children regardless of comprehension status (d = -0.84). We discuss theoretical and practical implications of the finding that second-language learners who are poor at reading comprehension despite adequate decoding have deficits in oral language but the deficit is not sufficient to explain their deficit in reading comprehension.

It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education ("EduYears") to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample of 5,825 unrelated individuals. "EduYears" GPS accounts for up to 5% of the variance in reading performance at age 14. GPS predictions remained significant after accounting for general cognitive ability and family socioeconomic status. Reading performance of children in the lowest and highest 12.5% of the "EduYears" GPS distribution differed by a mean growth in reading ability of approximately two school years. It seems certain that polygenic scores will be used to predict strengths and weaknesses in education.

Conceptualizations of developmental trends are driven by the particular method used to analyze the period of change of interest. Various techniques exist to analyze developmental data, including individual growth curve analysis in observed and latent frameworks, cross-lagged regression to assess interrelations among variables, and multilevel frameworks that consider time as nested within individual. In this paper, we report on findings from a latent change score analysis of oral reading fluency and reading comprehension data from a longitudinal sample of approximately 16,000 students from first to fourth grade. Results highlight the utility of latent change score models compared to alternative specifications of linear and nonlinear quadratic latent growth models as well as implications for modeling change with correlated traits.

The present study employed data simulation techniques to investigate the 1-year stability of alternative classification schemes for identifying children with reading disabilities. Classification schemes investigated include low performance, unexpected low performance, dual-discrepancy, and a rudimentary form of constellation model of reading disabilities that included multiple criteria. Data from a previously published study were used to construct a growth model of reading development. The parameters estimated from this model were then used to construct three simulated data sets wherein the growth parameters were manipulated in one of three ways: a stable-growth pattern, a mastery learning pattern, and a fan-spread pattern. Results indicated that overall the constellation model provided the most stable classifications across all conditions of the simulation, and that classification schemes were most stable in the fan-spread condition and were the least stable under the mastery learning growth pattern. These results also demonstrate the utility of data simulations in reading research.

We report results from two studies on the underlying dimensions of morphological awareness and vocabulary knowledge in elementary-aged children. In Study 1, 99 fourth-grade students were given multiple measures of morphological awareness and vocabulary. A single factor accounted for individual differences in all morphology and vocabulary assessments. Study 2 extended these results by giving 90 eighth-grade students expanded measures of vocabulary and morphology that assessed (a) definitional knowledge, (b) usage, (c) relational knowledge, and (d) knowledge of morphological variants, with each potential aspect of knowledge assessed using an identical set of 23 words to control for differential knowledge of specific vocabulary items. Results indicated that a single-factor model that encompassed morphological and vocabulary knowledge provided the best fit to the data. Finally, explanatory item response modeling was used to investigate sources of variance in the vocabulary and morphological awareness tasks we administered. Implications for assessment and instruction are discussed.

This study demonstrates the utility of applying a causal indicator modeling framework to investigate important predictors of reading comprehension in third, seventh, and tenth grade students. The results indicated that a 4-factor multiple indicator multiple indicator cause (MIMIC) model of reading comprehension provided adequate fit at each grade level. This model included latent predictor constructs of decoding, verbal reasoning, nonverbal reasoning, and working memory and accounted for a large portion of the reading comprehension variance (73-87%) across grade levels. Verbal reasoning contributed the most unique variance to reading comprehension at all grade levels. In addition, we fit a multiple group 4-factor MIMIC model to investigate the relative stability (or variability) of the predictor contributions to reading comprehension across development (i.e., grade levels). The results revealed that the contributions of verbal reasoning, nonverbal reasoning, and working memory to reading comprehension were stable across the three grade levels. Decoding was the only predictor that could not be constrained to be equal across grade levels. The contribution of decoding skills to reading comprehension was higher in third grade and then remained relatively stable between seventh and tenth grade. These findings illustrate the feasibility of using MIMIC models to explain individual differences in reading comprehension across the development of reading skills.

Reading impairment is more common in males, but the magnitude and origin of this gender difference are debated. In a large-scale study of reading impairment among 491,103 beginning second-graders, gender differences increased with greater severity of reading impairment, peaking at a ratio of 2.4:1 for a broad measure of fluency and a ratio of 1.6:1 for a narrow measure of decoding. Results from three tests indicate that gender differences in reading impairment are attributable primarily to male vulnerability rather than ascertainment bias. Correspondence between identification as an impaired reader by our study criteria and school identification as learning disabled was poor overall and worse for girls: Only 1 out of 4 boys and 1 out of 7 girls identified as reading impaired in our study was school identified as learning disabled.

In the present study we investigated a developmentally changing role of text reading fluency in mediating the relations of word reading fluency and listening comprehension to reading comprehension. We addressed this question by using longitudinal data from Grades 1 to 4 and employing structural equation models. Results showed that the role of text reading fluency changes over time as children's reading proficiency develops. In the beginning phase of reading development (Grade 1), text reading fluency was not independently related to reading comprehension over and above word reading fluency and listening comprehension. In Grades 2 to 4, however, text reading fluency completely mediated the relation between word reading fluency and reading comprehension, whereas it partially mediated the relation between listening comprehension and reading comprehension. These results suggest that text reading fluency is a dissociable construct that plays a developmentally changing role in reading acquisition.

The present study followed a sample of first-grade (N = 316, M[subscript age] = 7.05 at first test) through fourth-grade students to evaluate dynamic developmental relations between vocabulary knowledge and reading comprehension. Using latent change score modeling, competing models were fit to the repeated measurements of vocabulary knowledge and reading comprehension to test for the presence of leading and lagging influences. Univariate models indicated growth in vocabulary knowledge, and reading comprehension was determined by two parts: constant yearly change and change proportional to the previous level of the variable. Bivariate models indicated previous levels of vocabulary knowledge acted as leading indicators of reading comprehension growth, but the reverse relation was not found. Implications for theories of developmental relations between vocabulary and reading comprehension are discussed.

Recently, Tunmer and Chapman 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.

The purpose of this study was to use a mixed methods approach to learn about inadequate response to a year-long multi-tier response to intervention (RTI) model that allowed first-grade students to move up and down tiers. Participants were 156 students who received supplemental intervention services during a larger multi-tier RTI study involving classrooms and 522 students across 10 schools. Findings from an all-subset regression indicate letter word reading, the fluency composite, and blending words explained the most variance (15%) in response among initial skills. Adding additional teacher ratings of behavior and academics accounted for a small amount of additional variance (3%) in-group membership. The receiver operating characteristic curve analysis indicated 87.5% of students were correctly classified, yielding a sensitivity of 85.3 and a specificity of 65.0. Findings from qualitative observations of intervention sessions suggest inadequate responders demonstrated physical and verbal task avoidance and displayed emotions of hopelessness and shame. Implications for practice are discussed.

This randomized controlled experiment compared the efficacy of two response-to-intervention (RTI) models--typical RTI and dynamic RTI--and included 34 first-grade classrooms (n = 522 students) across 10 socioeconomically and culturally diverse schools. Typical RTI was designed to follow the two-stage RTI decision rules that wait to assess response to Tier 1 in many districts, whereas dynamic RTI provided Tier 2 or Tier 3 interventions immediately according to students' initial screening results. Interventions were identical across conditions except for when intervention began. Reading assessments included letter-sound, word, passage reading, and teacher-reported severity of reading difficulties. An intent-to-treat analysis based on multilevel modeling indicated an overall effect favoring the dynamic RTI condition (d = 0.36); growth curve analyses demonstrated that students in dynamic RTI showed an immediate score advantage and that effects accumulated across the year. Analyses of standard score outcomes confirmed that students in the dynamic condition who received Tier 2 and Tier 3 ended the study with significantly higher reading performances than students in the typical condition. Implications for RTI implementation practice and future research are discussed.