Expanding access to high-quality, affordable early childhood services is key to state efforts to support families' well-being, ensure that children are ready to succeed in school, and sustain a strong economy. Right now, early childhood data is typically housed in different, disconnected state and local systems. State leaders seeking to provide…

State postsecondary education data systems are vital assets for policymakers, researchers, and the public. The State Higher Education Executive Officers Association's (SHEEO) Communities of Practice project builds upon SHEEO's efforts to measure the capacity and effective use of state postsecondary data systems and provides states with…

In 2019, the National Center for Education Statistics (NCES) began exploratory data collection for the School Pension Survey (SPS). The SPS is a new data collection of elementary/secondary school teacher pension data collected at the school district level. The SPS was developed primarily in response to public demand for data on teacher and other…

Intervention studies focused on improving reading outcomes are scarce for postsecondary students with disabilities. Historically, comprehensive transition and postsecondary education programs (CTPs) for students with disabilities focused on employment, living, personal, and social skills over academic instruction. Recently, there is an emphasis to…

Regular attendance is essential to providing students with opportunities to learn. State and local education agencies (SEAs and LEAs) play a crucial role in tracking, measuring, and addressing student attendance. The coronavirus disease (COVID-19) pandemic affected the way that many SEAs and LEAs collect attendance data. This resource highlights…

A commonly used metric for measuring college costs, drawn from data in the Integrated Postsecondary Education Data System (IPEDS), is expenditure per full-time equivalent (FTE) student. This article discusses an error in this per FTE calculation when using IPEDS data, especially with regard to community colleges. The problem is that expenditures…

The COVID-19 pandemic has created an unprecedented challenge for state, district, and school leaders across the country. Whether states and districts mandate or choose an in-person or remote model or a hybrid model, which includes some aspect of virtual learning, ensuring that vulnerable students and teachers have a remote learning option has…

In a time when fewer resources force school leaders to make critical decisions, the data-driven decision-making model continues to offer promise. This research project provides observations about factors used for decision making from 14 district leaders across five Iowa school districts. Placing these factors for decision making within the…

Multivariate count data is ubiquitous in many areas of research including the physical, biological, and social sciences. These data are traditionally modeled with the Dirichlet Multinomial distribution (DM). A new, more flexible Dirichlet-Tree Multinomial (DTM) model is gaining in popularity. Here, we consider Bayesian DTM regression models. Our…

The COVID-19 pandemic has created an unprecedented challenge for state, district, and school leaders across the country. Whether states and districts mandate or choose an in-person or remote model or a hybrid model, which includes some aspect of virtual learning, ensuring that vulnerable students and teachers have a remote learning option has…

This Guide provides universities with a road map to initiate or bolster current efforts to create a robust system for ensuring effective public access to high-quality research data. The Guide aims to assist universities and their senior administrators in crafting consistent and uniform approaches to all aspects of research data management and…

Over the past several years, schools across the nation have seen historic declines in student performance in reading, math, and other academic subjects due to the COVID-19 Pandemic. School closures adversely affected student groups at different rates and further exacerbated long-standing learning gaps. There has been a debate among scholars for…

State and local education agencies across the country face challenges related to understanding and managing their teaching staff to best help students learn. Statewide longitudinal data systems (SLDSs) offer valuable information about teacher labor markets that can be used to analyze supply and demand, inform budget and staffing decisions, and…

To evaluate interim progress toward the State-identified Measurable Result (SIMR), states require access to high-quality data from local education agencies (LEAs) and early intervention service providers. In a review of 2017 Phase III State Systemic Improvement Plans (SSIP), 43 Part C states noted limitations or concerns related to data and…

Many states struggle with collecting reliable and valid data that can be easily analyzed at the state level. This can be particularly challenging in states where schools and districts have local control over the selection of their assessment tools. This state spotlight presents the strategies that the Iowa Department of Education (IDE) used to…