Search

Some of the worst long-term outcomes of children are associated with the presence of externalizing behavior and low academic achievement. However, the nature of the causal and predictive relationship between these two domains remains contested due to inconsistent findings in previous literature. Leveraging a nationally representative sample (N = 7330) from the Early Childhood Longitudinal Study (ECLS)–Kindergarten Cohort of 2011, we used latent class growth analysis and machine learning cross validation techniques to analyze the association of early math and reading achievement with the development of externalizing behavior trajectories in elementary school. Several theoretically and empirically important covariates were utilized to develop a profile of learners in each trajectory. Results indicated stable teacher ratings of behavior across kindergarten to fifth grade and three primary trajectories, consisting of (1) higher persistent, (2) low persistent, and (3) no problem behavior. Importantly, teacher rated early inattention and approaches to learning behaviors, rather than direct standardized measures of academic achievement, were the strongest malleable predictors to trajectory membership. Student demographics, including being a boy and identifying as Black, contributed to these students being almost twice as likely to belong to the higher problem behavior trajectory as compared to girls and White peers. Educational implications for intervention, as well as the influence of implicit bias and structural racism in the role of teacher ratings, are discussed. [ABSTRACT FROM AUTHOR]

Nearly 50 years of research show persistent racial disproportionality in the identification of special education disabilities, but the underlying mechanisms for these disparities remain largely unexplored. Because ambiguous regulations defining disabilities may allow subjectivity and unlawful differential treatment (i.e., racial bias or discrimination) in the special education eligibility process, an important target of study is disparate treatment of students by race in evaluations required to determine eligibility. School psychologists have long been recognized as highly influential in this process and in schools' resultant decisions. We used a 3 × 2 mixed factorial experimental design in three studies with simulated case report data to measure the influence of race and assessment data on school psychologists' perceptions of students' eligibility for special education in cases centering on emotional disturbance, intellectual disability, or autism, respectively. Participants included 302 practicing school psychologists in three states across the three experiments. There was little evidence of racial disparity, but participants tended to render decisions unsupported by, and even contrary to, evaluation data. Implications for research, practice, and professional development are discussed. [ABSTRACT FROM AUTHOR]

Abstract Studying change over time requires rigorous and sometimes novel statistical methods that can support increasingly complex applied research questions. In this article, we provide an overview of the potential of piecewise growth mixture models. This type of longitudinal model can be used to advance our understanding of group and individual growth that may follow a segmented, or disjointed, pattern of change, and where the data come from a mixture of two or more latent classes. We then demonstrate the practical utility of piecewise growth mixture models by applying it to a subsample of students from the Early Childhood Longitudinal Study – Kindergarten Cohort of 1998 (ECLS-K) to ascertain whether mathematics achievement is characterized by one or two latent classes akin to students with and without mathematics difficulties. We discuss the applicability for school psychological research and provide supplementary online files that include an instructional sample dataset and corresponding R routine with explanatory annotations to assist in understanding the R routine before applying this approach in novel applications (https://doi.org/10.1016/j.jsp.2019.03.004). [ABSTRACT FROM AUTHOR]

Highlights • We tested effects of childcare subsidy on outcomes of children with or at-risk for special needs. • Subsidies were had significant negative effects on early literacy and numeracy. • There was no effect on behavioral readiness or communication skills. Abstract Children with special needs are now a population of special interest under federal child care policy. Findings on the effects of child care subsidy for the general population are mixed, but no studies have considered the effects for children with or at-risk for special needs. The purpose of this study was to ascertain the average effects of child care subsidies on school readiness of children with or at-risk for special needs. Using data for 1250 participants in the Early Childhood Longitudinal Study–Birth Cohort, we applied propensity score matching and regression analyses to estimate subsidy's effects on kindergarten academic and behavioral competencies of children with or at-risk for special needs who came from low-income families. Results indicated that for the average recipient, subsidized child care had significant negative effects on early literacy (d = 0.21) and numeracy (d = 0.18), and no significant effects on communication, impulsivity, hyperactivity, and prosocial behavior. These findings add to a growing number of largescale analyses showing negative or null effects of subsidized care on early childhood outcomes and highlight the need for continued attention to the appropriateness and effectiveness of subsidized child care, particularly for children with or at-risk for special needs. [ABSTRACT FROM AUTHOR]

One goal of childcare subsidies is to increase access to quality childcare for families of low-income, thus supporting child and family wellbeing, but subsidies may not equally benefit children with and without special needs. This study examined patterns and predictors of subsidy use among children with disabilities or delays relative to children without special needs. A nationally representative sample of approximately 4050 young children from families of low-income was drawn from the Early Childhood Longitudinal Study–Birth Cohort. We examined subsidized care receipt at ages nine months, two years, and four years using descriptive analyses and multivariate logistic regression. Results suggest young children with special needs utilize childcare subsidies at significantly lower rates than their peers without disabilities. Mothers' marital status, work status, education, and age, along with child's race and number of siblings were significant predictors of subsidy use. We discuss implications for policy implementation and multisector collaboration to support the early care and education of young children with special needs. [ABSTRACT FROM AUTHOR]

Effective instructional planning and intervening rely heavily on accurate understanding of students' growth, but relatively few researchers have examined mathematics achievement trajectories, particularly for students with special needs. We applied linear, quadratic, and piecewise linear mixed-effects models to identify the best-fitting model for mathematics development over elementary and middle school and to ascertain differences in growth trajectories of children with learning disabilities relative to their typically developing peers. The analytic sample of 2150 students was drawn from the Early Childhood Longitudinal Study — Kindergarten Cohort, a nationally representative sample of United States children who entered kindergarten in 1998. We first modeled students' mathematics growth via multiple mixed-effects models to determine the best fitting model of 9-year growth and then compared the trajectories of students with and without learning disabilities. Results indicate that the piecewise linear mixed-effects model captured best the functional form of students' mathematics trajectories. In addition, there were substantial achievement gaps between students with learning disabilities and students with no disabilities, and their trajectories differed such that students without disabilities progressed at a higher rate than their peers who had learning disabilities. The results underscore the need for further research to understand how to appropriately model students' mathematics trajectories and the need for attention to mathematics achievement gaps in policy. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this study was to examine the average treatment effect of preschool special education services on children''s kindergarten academic skills. Using data from a nationally representative sample of United States children who participated in the Early Childhood Longitudinal Study—Birth Cohort, we examined the effectiveness of preschool special education services by comparing reading and math outcomes for children who received special education services at preschool-age to a propensity-score-weighted sample of children who did not receive these services. Results indicated that the receipt of these special education services had a statistically significant moderate negative effect on children''s kindergarten skills in both reading (d =−0.21) and mathematics (d =−0.29). These findings have implications for the implementation and evaluation of services for young children experiencing developmental delays or disabilities. [Copyright &y& Elsevier]

Unlabelled Image • We studied 13 international development projects addressing Food Loss and Waste (FLW). • A wide variety of interventions achieved substantial reductions in FLW. • Greenhouse gas emissions per unit production decreased for many food products. • Targeting FLW may also lower greenhouse gas emissions from food production. • Reduced FLW and lowered emissions could be a win-win for international development. Food loss and waste (FLW) reduce food available for consumption and increase the environmental burden of production. Reducing FLW increases agricultural and value-chain productivity and may reduce greenhouse gas emissions associated with feeding the global population. Although studies of interventions that reduce FLW exist, almost no research systematically investigates FLW interventions across multiple value chains or countries, most likely due to challenges in collecting and synthesizing data and estimates, let alone estimating greenhouse gas emissions. Our research team investigated changes in FLW in projects supported by the United States Agency for International Development 's (USAID) global hunger and food security initiative, Feed the Future. This was a unique opportunity to conduct ex-ante estimates of the impacts of FLW interventions across 20 value chains in 12 countries, based on project documents and interviews with USAID and project staff. This paper describes specific interventions in each value chain and country context, providing insight to interventions that decrease FLW at multiple points along food value chains, from upstream producer-dominated stages to downstream consumer-dominated stages. Amongst the sub-sectors studied, FLW interventions directed at extensive dairy systems could decrease FLW by 4–10%, providing meaningful greenhouse gas mitigation, since these systems are both emission-intensive and experience high FLW. More modest emissions reductions were found for other key agricultural products, including maize, rice, vegetables, fruits and market goods. [ABSTRACT FROM AUTHOR]

By engaging in construction-based robotics activities, children as young as four can play to learn a range of concepts. The TangibleK Robotics Program paired developmentally appropriate computer programming and robotics tools with a constructionist curriculum designed to engage kindergarten children in learning computational thinking, robotics, programming, and problem-solving. This paper documents three kindergarten classrooms' exposure to computer programming concepts and explores learning outcomes. Results point to strengths of the curriculum and areas where further redesign of the curriculum and technologies would be appropriate. Overall, the study demonstrates that kindergartners were both interested in and able to learn many aspects of robotics, programming, and computational thinking with the TangibleK curriculum design. [Copyright &y& Elsevier]