Project Activities
This study is designed to produce a set of descriptive data on WSF implementation and to identify relationships between WSF implementation and student achievement. Researchers will begin by using descriptive analysis to assemble the base level knowledge needed to categorize and test types of WSF models. With that information, researchers will then investigate the relationship between WSF (including different design elements) and student outcomes. The research team will also conduct a comprehensive financial analysis of WSF districts, in order to reveal the degree to which WSF is delivering on its aim of increased equity and resources for poor and at-risk students.
Structured Abstract
Setting
The study includes 25–30 large, urban districts in the United States that are using WSF, as well as 200 non-WSF districts. In addition, researchers will conduct a case study of WSF implementation in California to explore implementation of the model at the state level.
Sample
All local education agencies, schools and students in the WSF and non-WSF districts chosen for the study.
Intervention
The study explores district- and state-level implementation of weighted student funding (WSF) strategies. While WSF is often discussed as if it were a single model, in practice, school systems operationalize WSF in myriad ways, such as varying what student characteristics are weighted in their formulas, the magnitude of weights, the percentage of funds that are funneled through the WSF formula, and the flexibilities that accompany the funds.
Research design and methods
Researchers will conduct a survey of WSF district and school staff on the nature of the WSF, its features, the range of flexibilities awarded to schools, and any barriers facing districts using the financial strategy. Researchers will also collect publicly available school-level and district-level financial data, demographic data, and student achievement data. Researchers will then conduct descriptive and financial analyses of WSF implementation. In addition, researchers will use time series analyses to investigate the relationship between WSF (including different design elements) and student academic outcomes.
Control condition
School districts that do not use weighted student funding models.
Key measures
Measures include school level amount and portion of education funding for poor and at-risk kids, formula weights and types of students identified, and changes in achievement and achievement gaps on state standardized tests.
Data analytic strategy
The study includes descriptive financial analytics and pattern analysis of survey and district indicators. In addition, researchers will conduct time series analyses to examine the relationship between the implementation of WSF (and/or specific features of WSF) and student outcomes; and changes in achievement gaps in California districts before and after the implementation of WSF state-wide (the malleable factor).
People and institutions involved
IES program contact(s)
Products and publications
Products: Researchers will produce study briefs as well as articles for peer-review journals. The research team will also disseminate information to policymakers and practitioners through online mailing lists and the Edunomics Lab website.
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.