Human Development & Family Relations

Increasingly, states are implementing quality rating and improvement systems (QRIS) as a means of improving the availability of high-quality child care and children's school readiness skills. A fundamental design decision under QRIS is where to set the thresholds on the quality measures used in the program assessment component of the QRIS. This study applied generalized additive modeling (GAM) on data from Colorado's QRIS in order to identify thresholds on several components of Colorado's QRIS, including the Early Childhood Environment Rating Scale-Revised (ECERS-R), classroom ratios, and staff credentials. We found evidence of baseline thresholds that needed to be surpassed before significant relationships between quality and outcomes could be observed. In addition, there were ceiling thresholds, such that beyond certain cut-points, gains in quality were associated with little to no improvements in outcomes. Based on this work, it appears that GAM can be used to empirically identify thresholds, but more research is needed to understand the applicability of the GAM-derived thresholds in other early care contexts and settings.

Child care studies that have examined links between teachers' qualifications and children's outcomes often ignore teachers' and children's transitions between classrooms at a center throughout the day and only take into account head teacher qualifications. The objective of this investigation was to examine these traditional assumptions and to compare inferences made from these traditional models to methods accounting for transitions between classrooms and multiple teachers in a classroom. The study examined the receptive language, letter-word identification, and passage comprehension skills of 307 children enrolled in 49 community-based childcare centers serving primarily low-income families in Colorado. Results suggest that nearly one-third of children and over 80% of teachers moved daily between classrooms. Findings also reveal that failure to account for daily transitions between classrooms can affect interpretations of the relationship between teacher qualifications and child outcomes, with the model accounting for movement providing significant improvements in model fit and inference.

Research linking high-quality child care programs and children's cognitive development has contributed to the growing popularity of child care quality benchmarking efforts such as quality rating and improvement systems (QRIS). Consequently, there has been an increased interest in and a need for approaches to identifying thresholds, or cutpoints, in the child care quality measures used in these benchmarking efforts that differentiate between different levels of children's cognitive functioning. To date, research has provided little guidance to policymakers as to where these thresholds should be set. Using the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) data set, this study explores the use of generalized additive modeling (GAM) as a method of identifying thresholds on the Infant/Toddler Environment Rating Scale (ITERS) in relation to toddlers' performance on the Mental Development subscale of the Bayley Scales of Infant Development (the Bayley Mental Development Scale Short Form–Research Edition, or BMDSF-R). The present findings suggest that simple linear models do not always correctly depict the relationships between ITERS scores and BMDSF-R scores and that GAM-derived thresholds were more effective at differentiating among children's performance levels on the BMDSF-R. Additionally, the present findings suggest that there is a minimum threshold on the ITERS that must be exceeded before significant improvements in children's cognitive development can be expected. There may also be a ceiling threshold on the ITERS, such that beyond a certain level, only marginal increases in children's BMDSF-R scores are observed.

Research linking high-quality child care programs and children's cognitive development has contributed to the growing popularity of child care quality benchmarking efforts such as quality rating and improvement systems (QRIS). Consequently, there has been an increased interest in and a need for approaches to identifying thresholds, or cutpoints, in the child care quality measures used in these benchmarking efforts that differentiate between different levels of children's cognitive functioning. To date, research has provided little guidance to policymakers as to where these thresholds should be set. Using the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) data set, this study explores the use of generalized additive modeling (GAM) as a method of identifying thresholds on the Infant/Toddler Environment Rating Scale (ITERS) in relation to toddlers' performance on the Mental Development subscale of the Bayley Scales of Infant Development (the Bayley Mental Development Scale Short Form–Research Edition, or BMDSF-R). The present findings suggest that simple linear models do not always correctly depict the relationships between ITERS scores and BMDSF-R scores and that GAM-derived thresholds were more effective at differentiating among children's performance levels on the BMDSF-R. Additionally, the present findings suggest that there is a minimum threshold on the ITERS that must be exceeded before significant improvements in children's cognitive development can be expected. There may also be a ceiling threshold on the ITERS, such that beyond a certain level, only marginal increases in children's BMDSF-R scores are observed.