Statistics in Brief publications present descriptive data in tabular formats to provide useful information to a broad audience, including members of the general public. They address simple and topical issues and questions. They do not investigate more complex hypotheses, account for interrelationships among variables, or support causal inferences. We encourage readers who are interested in more complex questions and in-depth analysis to explore other National Center for Education Statistics (NCES) resources, including publications, online data tools, and public- and restricted-use datasets. See nces.ed.gov and references noted in the body of this document for more information.
For the past 15 years, the U.S. Department of Education has awarded funding to states and territories to support the design and development of statewide longitudinal data systems (SLDSs). SLDSs collect, analyze, and use data that span individuals' education experiences from preschool to the workforce. SLDSs are designed to help states, districts, schools, educators, and other stakeholders make datainformed decisions to improve student learning and outcomes.(SLDSs).
Since the SLDS Grant Program began in 2006, robust P-20W+1 SLDSs have allowed researchers, policymakers, and practitioners alike to understand important data relationships that help to determine immediate and long-term impacts of education. For example, does tracking preschool attendance help to predict student kindergarten readiness? Can assessment results predict which students will enroll certification an important factor in students' academic proficiency and success in the workforce? With a fully operational SLDS, state and territory governments can establish more informed education policies, agency leaders can develop more relevant education strategies, and educators can make more datadriven decisions for their students.
Nationwide, states' and territories' data capacity and ability to answer these kinds of important questions remain varied. States' and territories' SLDSs differ along multiple factors, including legislative directives and regulations, funding levels, technical capacity, and organizational design. The SLDS Survey provides standard measures for data capacity, a first step toward understanding the links between conditions in states and territories and their capacity levels.
Understanding impacts of education policy and practice requires datasets and data systems to change and evolve. These needs underscore the importance of having SLDSs that can quickly provide data that will help empower education decisionmakers. Teachers administrators, policymakers, and researchers continually need to respond to new questions about such things as the education and workforce trajectories of students, the availability of qualified teachers, and education program outcomes. Access to education data and the capacity that states and territories have to answer complicated questions is more important than ever.
The SLDS Survey was first administered in the summer of 2017. This annual survey was created to help inventory the current data capacity of states' and territories' SLDSs. It not only focuses on whether a given data type or use is in place, but also explores the development of these data systems and their varying degrees of implementation.
The SLDS Survey asks all states and territories to provide information about the types of data that are included in their SLDSs; how they use SLDS data to inform policy; and the capacity of their SLDSs for automated linking of K–12 student data to other data, including teacher, postsecondary, workforce, Perkins career and technical education (CTE), and early childhood data. To provide a snapshot of current data system capabilities, the survey collects information about states' and territories' goals and intentions regarding their data systems by asking respondents to indicate whether a data system's capacity is in place and operational, in progress toward becoming operational, planned, or not planned.
This Statistics in Brief provides aggregate information about states and territories that connect data from different sources in their SLDSs. In order to explore the types of data they collect, how the data are defined, how the data systems are structured, and how the data are ultimately used, this brief explores the following four study questions that represent a portion of the results collected from the survey.
1 P-20W+ refers to data from prekindergarten (early childhood), K–12, and postsecondary through postgraduate education, along with workforce and other outcomes data (e.g., public assistance and corrections data). The specific agencies and other organizations that participate in the P-20W+ initiative vary from state to state.