Trajectories of Math and Reading Achievement in Low-Achieving Children in Elementary School: Effects of Early and Later Retention in Grade

Department of Psychology, Arizona State University.
Journal of Educational Psychology (Impact Factor: 3.52). 08/2012; 104(3):603-621. DOI: 10.1037/a0027571
Source: PubMed


This study investigated the effects of retention or promotion in first grade on growth trajectories in mathematics and reading achievement over the elementary school years (grades 1-5). From a large multiethnic sample (n = 784) of children who were below the median in literacy at school entrance, 363 children who were either promoted (n = 251) or retained (n = 112) in first grade could be successfully matched on 72 background variables. Achievement was measured annually using Woodcock-Johnson W scores; scores of retained children were shifted back one year to permit same-grade comparisons. Using longitudinal growth curve analysis, trajectories of math and reading scores for promoted and retained children were compared. Retained children received a one year boost in achievement; this boost fully dissipated by the end of elementary school. The pattern of subsequent retention in grades 2, 3 and 4 and placement in special education of the sample during the elementary school years is also described and their effects are explored. Policy implications for interventions for low achieving children are considered.

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    • "In fact, by fifth grade, the retained students had somewhat lower math and much lower reading standardized test scores than their peers. Moser et al. (2012) contend that had the students who were retained in first grade been promoted , they would have performed just as well on the fifth grade achievement test as they actually did, indicating that grade-level retention does not evidence long-term beneficial effects. Gottfried (2012) similarly found a post-retention achievement gap when he compared the performance of retained versus continuously promoted students over a 6- year period. "
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    ABSTRACT: Research indicates that the practice of grade-level retention may have negative effects on students; nevertheless it is often used in practice for students who fail to meet academic standards. In contrast to retention, response to intervention (RtI) is a sound practice that is based on a preventive framework and utilizes differentiated instruction and progress monitoring to meet student needs. The present study examined a sample of students from a district where RtI implementation was being scaled-up, but retention also occurred. Academic assessment data for those students identified as having specific learning disabilities in the area of reading were examined to determine whether there were differences between students who were retained prior to referral and their non-retained peers. Results indicated that the retained students performed significantly worse on the reading comprehension and math domains of the standardized academic tests and had fewer progress monitoring data points collected prior to referral for evaluation. The results suggested that retention may have offered little academic skills benefit and, perhaps, even a delay in the time to eligibility for special education. The implications for the impact of retention on academic skills are discussed and future directions for research are presented.
    01/2014; 18(1). DOI:10.1007/s40688-013-0007-1
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    ABSTRACT: Objectives The aim of this work is to examine the promise that propensity scores can yield accurate effect estimates in nonrandomized experiments, review research on the realities of the conditions needed to meet this promise, and caution against irrational exuberance about their capacity to meet this promise. Methods A review of selected experimental work that illustrates both the promise and realities of propensity score analysis. Results Propensity score analysis of nonrandomized experiments can yield the same results as randomized experiments. Those estimates depend on meeting the strong ignorability assumption that the available covariates well describe selection processes and on use of comparison groups that are from the same location with very similar focal characteristics. When those assumptions are not met, propensity scores may not yield accurate estimates. Conclusions The use of propensity score analysis has proliferated exponentially, especially in the last decade, but careful attention to its assumptions seems to be very rare in practice. Researchers and policymakers who rely on these extensive propensity score applications may be using evidence of largely unknown validity. All stakeholders should devote far more empirical attention to justifying that each study has met these assumptions.
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    ABSTRACT: This study examined the effects of first-grade retention on children's academic growth, psychosocial growth, and future school career by following a cohort of first graders until the start of secondary school. The study took place in the Flemish educational context where primary school students are taught in uniform curricular year groups; the same curricular goals are set for all students, irrespective of ability; and grade retention is used as the main way to cater for students not reaching these goals. Propensity score stratification was used to deal with selection bias. Three-level curvilinear growth curve models, encompassing both grade and age comparisons, were used to model children's growth in math skills, reading fluency skills, and psychosocial skills. Two-level logistic regression models were used to model children's likelihood of repeating any grade between Grades 2 and 6, transitioning to a special education primary school, moving to another primary school, and transitioning to the A (versus B) track in secondary education. Overall, results showed that first-grade retention was less helpful for struggling students than generally thought by parents and educators. Limitations of the study and further research suggestions are provided, and practical implications are discussed.
    Journal of school psychology 06/2013; 51(3):323-347. DOI:10.1016/j.jsp.2013.03.002 · 2.31 Impact Factor
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