Over the past 25 years, schools, social service providers, and other government agencies have adopted modern information systems that capture electronically much more data about students, teachers, and schools than previously. Properly linked across levels (e.g., early childhood, K-12, postsecondary) and systems, this data can support improved educational outcomes in multiple ways. If district and school leaders can gain insights into the success of their students after they graduate, this can help them determine whether their educational program and career guidance is providing proper preparation. Researchers can evaluate whether programs and policies have been implemented and whether they improve the outcomes they intend to. The public can monitor system performance and press for improvements when and where necessary – identifying equity gaps in either inputs or outcomes. Finally, individual students and their families can save time and have more opportunities if properly connected data systems can guide choices and simplify processes across governmental systems – for instance, by automatically transmitting a student's transcript to colleges to which she is applying.
The Data Quality Campaign has noted the promise of linked state systems to ease students’ navigation through college and career pathways, to connect students to needed supports, to help students and job seekers understand pathways into particular fields or jobs, and to allow researchers to determine what works and what does not (2023).
Relatedly, the Gates Foundation and Mathematica have created the Education-to-Workforce Indicator Framework that synthesizes prior research and frameworks to identify a set of critical questions and data points that should be collected to track and improve student pathways through their education and into employment. Collecting such data will allow policymakers and educational system leaders to monitor progress and improve policy with the goal of "advancing educational and economic opportunity for all." (Gonzalez et al., 2022).
Research using data linked across systems can have real impacts on major policies that might not otherwise be attainable. For instance, a research team in Michigan performed an experiment to test whether offering students from low-income families free tuition to the University of Michigan if admitted would increase application rates from these students. The researchers saw a large jump in both application and enrollment rates in the targeted student group (Dynarski et al., 2021; Burland et al., 2023). Partly as a result of the evidence provided by this and other studies, other higher ed institutions across the nation have begun guaranteeing full, blanket scholarships to students whose families fall below a set income level (see, for instance, Krupnick, 2024). But the data requirements to conduct such work are substantial. To conduct this type of research, one needs to be able to connect K-12 data administrative data to social services data to college application data to financial aid data to college enrollment data.
This report focuses on the evolving state education data landscape in California and its ability to meet the needs highlighted above. It highlights areas of substantial improvement since Getting Down to Facts II in 2018 as well as some ongoing gaps and challenges that remain. It will also suggest some potential changes to the state data infrastructure that could advance the ability of state data to support educational improvement and better outcomes for individual students.
