Children Who Receive Special Education Services for ADHD: Early Indicators and Evidence of Disproportionate Representation in the Early Childhood Longitudinal Study (ECLS-K: 2011)

Approximately one in 10 children in the United States is diagnosed with Attention-Deficit Hyperactivity Disorder (ADHD), a disability that can negatively affect academic achievement, yet relatively few children with ADHD are in special education. To better understand factors that determine which students with ADHD are in special education, we analyzed students in the Early Childhood Longitudinal Study, Kindergarten Class of 2010–2011 (ECLS-K: 2011). Using logistic regression, we looked to see which sociodemographic, academic, executive functioning, and behavioral skills, all measured in kindergarten, significantly influenced the odds a student would receive special education services for ADHD in fourth grade ( N = 220). Results showed higher conflict with teachers and lower working memory significantly increased these odds. Furthermore, even when controlling for academic and social skills, students who are girls, Hispanic/Latinx, and/or living in a home where a language other than English is spoken were less likely to receive special education services for ADHD. Findings suggest early identification of students with ADHD and special education needs is possible and that sociodemographic characteristics play a significant role in determining who receives special education services for ADHD.

Summer Learning: Who Gains, Who Slides, and Does It Matter?

Secondary data from the Early Childhood Longitudinal Study: Kindergarten Cohort: 2011-2012

Summer Learning: Who Gains, Who Slides, and Does It Matter?

Secondary data from the Early Childhood Longitudinal Study: Kindergarten Cohort: 2011-2012

Increasing the Consequential Validity of Reading Assessment Using Dynamic Measurement Modeling: A Comment on Dumas and McNeish (2017)

Dynamic measurement modeling (DMM) has been shown to improve the consequential validity of longitudinal mathematics assessment in the Early Childhood Longitudinal Study-Kindergarten (ECLS-K) database. Here, the authors demonstrate the capability of DMM to similarly improve the consequential validity of ECLS-K reading assessment through the estimation of student-specific learning capacities and growth parameters for reading.