Year of Publication

2016

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Education

Department

Educational, School, and Counseling Psychology

First Advisor

Dr. Michael D. Toland

Abstract

The large proportion of children from low SES backgrounds and the increasing achievement gap between disadvantaged children and their more advantaged peers are beckoning national attention to investment in early childhood education (Reid, Kagan, Hilton, & Potter, 2015). As evidenced in many research studies (e.g., Heckman & Masterov, 2007), early childhood experiences are critical to the development of children. High-quality early learning is necessary for children, especially disadvantaged children, to narrow the school readiness gap and to build a foundation for more advanced academic, social, and cognitive skills. Importantly, high quality assessment tools (i.e., reliability and validity evidence supporting the use and interpretation of scores from a given instrument) are a necessary component of early childhood education.

The Preschool Child Observation Record (Preschool OnlineCOR, High/Scope, 2003) is an observational assessment tool created by the High/Scope Educational Research Foundation, a nonprofit, research, and training organization focused on early childhood development. First, a comprehensive evaluation of the psychometric qualities of the Preschool OnlineCOR was conducted; including dimensionality, reliability, item properties, and measurement invariance. Second, a short form of the Preschool OnlineCOR (COR-ST) was developed. Third, this study examined the growth trajectories of 3- and 4-year-old children on the general factor measured by the COR-ST through traditional multilevel growth modeling and more advanced multilevel growth modeling approaches, including multilevel item response theory modeling (MLIRT; Kamata, 2001; Liu & Hedeker, 2006; Pastor & Beretvas, 2006; Sulis & Toland, 2016), and multiple indicator multilevel modeling (MIML; Muthén and Muthén, 1998-2015). The traditional multilevel growth model consists of two steps: 1) one score is calculated to represent the general factor for each child at each time point based on their raw item scores through either classical test theory (CTT) or IRT (item response theory) approaches, and 2) the growth trajectory is modeled based on the overall COR-ST score at each time point. In comparison, the more advanced approaches, MLIRT and MIML growth models, model directly using item-level information (item scores), which simultaneously estimate item-level parameters, change over time, and effects of child predictors.

Digital Object Identifier (DOI)

https://doi.org/10.13023/ETD.2016.477

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