Policymakers, advocates, and researchers often use data to make decisions about how to expand the availability of pre-K,[1] to better understand pre-K’s effects on academics and social-emotional development, and to target available funding to meet the early education needs of “high needs” communities such as children with disabilities, children involved in the child welfare system, and migrant families. Despite these efforts, many families—especially those who identify with groups that have been historically marginalized by systemic inequities and racism—continue to face barriers to enrolling their children in pre-K programs, which are often designed without these families’ specific needs and experiences in mind. Furthermore, there is great variability in the quality of pre-K programs in which children are enrolled or to which they have access, including ongoing challenges with recruiting and retaining staff due to low wages and unsupportive work environments (e.g., lack of paid preparation time or sick leave). To better address these inequities, decision makers must have access to relevant data that can shed light on inequities.

Currently, federal, state, territory, and tribal leaders lack a cohesive picture of pre-K investments due to the siloed nature of publicly funded pre-K programs and the absence of actionable data needed to improve the equity of experiences for children, families, and workforce members. Different pre-K funding streams, program standards, and reporting requirements make it difficult to capture the information needed to inform policies. For example, in California, the State Preschool Program, Transitional Kindergarten, Head Start, Tribal Head Start, and locally funded pre-K programs each collect different and/or limited information. Without a complete picture of the state pre-K system, policymakers struggle to answer questions about which children and families are (or aren’t) being served, the quality of families’ experiences, and the outcomes of children’s participation.

The Early Childhood Data Collaborative at Child Trends—with funding from the Bill & Melinda Gates Foundation—is developing a System Transformation for Equitable Preschools (STEP Forward with Data) Framework to improve the availability of actionable data. A data framework is a tool that can help pre-K decision makers identify, organize, and connect different types of data into a unified information data system within or across pre-K programs. The Framework will focus on collecting and using data to increase learning opportunities for children who face systemic and historical barriers to accessing high-quality pre-K, such as Black and Hispanic/Latino children and families living in poverty. It will further outline a process for using data to answer essential questions about pre-K policies and practices that limit or advance equity goals through an approach that is assets-driven, applicable across pre-K structures, actionable, and aligned with the broader early childhood system. In addition to generating essential questions, the Framework will provide leaders with recommended metrics and data standards to help pre-K programs answer those questions and monitor and evaluate progress toward key equity goals. Finally, the STEP Forward with Data Framework will be a critical resource for states, territories, and tribal communities as they strive to strengthen and expand their pre-K programs using data.

Over the next two years, we will further develop the Framework with input from a national consortium of community members and experts in pre-K policy, equity, and data systems development. We will also conduct a survey of pre-K administrators about their capacity to implement the Framework and any anticipated challenges.

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Footnote

[1] This blog defines pre-K as a state- or federally funded Head Start or pre-Kindergarten educational program for 3- and 4-year-old children to support the development of language, literacy, math, and social skills prior to school entry. Programs include center-, home-, and school-based settings operated by U.S. and Tribal local governments.