Despite evidence that frequent progress monitoring to identify children at-risk of delays and inform early intervention services improves child outcomes, this practice is rare in infant-toddler settings where children could benefit the most from early intervention. Using a descriptive research design within an Implementation Science framework, we…

Through time-series graphs, teachers often evaluate progress monitoring data to make both low- and high-stakes decisions for students. The construction of these graphs--specifically, the presence of an aimline and the data points per x- to y-axis ratio (DPPXYR)--may impact decisions teachers make. The purpose of this study was to evaluate the…

While working memory (WM) is a powerful predictor for children's school outcomes, autistic children are more likely to experience delays. This study compared autistic children and their neurotypical peers' WM development over their elementary school years, including relative growth and period of plasticity. Using a nationally-representative…

Many children with developmental disabilities are not identified before age 3 years of age, preventing them from being able to fully benefit from early intervention services. Early childhood educators, particularly those in Early Head Start (EHS) programs, are important partners in the early identification of children with developmental delays.…

Background: Progress monitoring is a vital strategy for evaluating skill development of young children receiving disability related services. Few effective progress monitoring tools exist for infants and toddlers, and research is needed to examine feasibility as they become available. Objective: The current study examined the implementation of an…

For students with intensive learning needs for whom standard, validated interventions do not effectively promote academic growth, data-based instruction (DBI) is suggested as an effective, fine-grained approach to individualization. Key to DBI's success is making instructional changes based on individual students' progress monitoring data. The…

For students with intensive learning needs for whom standard, validated interventions do not effectively promote academic growth, data-based instruction (DBI) is suggested as an effective, fine-grained approach to individualization. Key to DBI's success is making instructional changes based on individual students' progress monitoring data. The…

Behavioral and social-emotional challenges experienced in childhood are risk factors for negative educational and health outcomes. Universal social-emotional screening in schools has been identified as an effective approach to identifying children at risk for mental health and behavioral challenges and is congruent with tiered frameworks for…

Background: Using progress monitoring data to make effective and timely decisions in early intervention (EI) requires high quality assessment. Infant/toddler individual growth and development indicators (I/T IGDIs) have been developed to be brief, reliable and engaging progress monitoring tools that are sensitive to change over short time periods…

The Devereux Early Childhood Assessment (DECA) and recently updated Devereux Early Childhood Assessment for Preschoolers, Second Edition (DECA-P2) are strength-based measures that can inform early intervention. Whereas the short-term psychometric properties of these parent rating scales are strong, little is known about their long-term stability.…

The National Center for Systemic Improvement (NCSI) conducted a series of focused conversations on child assessment with 31 Part C (Infant-Toddler) and Part B-619 (Preschool) program state representatives and NCSI Technical Assistance (TA) Facilitators. The purpose was to learn more about how state early intervention and early childhood programs…

This article examined the impact of a math-intensive summer academy for rising kindergartners (N = 17) enrolled in an elementary school with low socioeconomic populations. The program was designed to support student understanding of early number concepts. The research plan included the administration of the Texas Early Mathematics Inventory:…

Identifying at-risk students as soon as possible is a challenge in educational institutions. Decreasing the time lag between identification and real at-risk state may significantly reduce the risk of failure or disengage. In small courses, their identification is relatively easy, but it is impractical on larger ones. Current Learning Management…

Programs serving infants and toddlers are expected to use child data to inform decisions about intervention services; however, few tools exist to support these efforts. The Making Online Decisions (MOD) system is an adaptive intervention that guides early educators' data-based intervention decision making for infants and toddlers at risk for…

Programs serving infants and toddlers are expected to use child data to inform decisions about intervention services; however, few tools exist to support these efforts. The Making Online Decisions (MOD) system is an adaptive intervention that guides early educators' data-based intervention decision making for infants and toddlers at risk for…