The Education Institute of Hawaii (EIH), an independent catalyst for improving public education in Hawaii, is leading a Quality-Controlled Business Intelligence Model (QC-BI Model) project designed to put decision-making information into the hands of principals and stakeholders. The downstream effect of the Every Student Succeeds Act (ESSA) is more fiscal transparency and expanded scope and access to quality detailed financial data. Data for FY16 and FY17 will be analyzed.
At the core of this QC-BI Model project is an overlay tool and process. The tool and process enable data integration, analysis and reporting. The purpose of this project is to show that a simple, low cost overlay tool and process can deliver highly useful fiscal data, with context, to support empowered principals and interested stakeholders. Per pupil fiscal data will be available by school, by fund, by program, by function, by source of funding, by object, and by cascading organizational levels.
The EduAnalytics Team will deliver an easy to use model designed for the purpose of research by principals, stakeholders and other decision-makers. The model will include the ability for end-users to research various aggregations of FY16 and FY17 school-level data, and to explore how funding dollars cascade down to classrooms. The goal is to assure that teachers have adequate resources, and principals are empowered with sufficient fiscal facts and context to exercise their empowerment.
EIH attempted to partner with the Department of Education (HIDOE) and Superintendent of Schools on this demonstration project, but they declined. So, EIH has submitted a freedom of information request to obtain needed data for this fiscal project. EIH's project is well underway with more than 280,000 data elements loaded. As of 3/13/2019 the finance data have not yet been received from HIDOE. Also see the "Take 5" web page for a description of the ESSA challenge.
Most, if not all, educational, governmental and commercial leaders in Hawaii, and parents, care about student success and want to be included in a new ESSA-inspired leadership dynamic. That refreshed desire to contribute to student achievement is being demonstrated through initiatives to improve HIDOE transparency, empower local schools, link students to jobs, leverage national best practices aligned with local cultural values, and innovate.
Teachers and students in classrooms benefit because once the detail of how funding cascades down through the education system is known, principals and central administrators can make more informed decisions and set higher priorities for classroom needs. Because the model will include 100% of funding and expenditures, there will also be benefits to managers in charge of non-instructional functions as well.
EduAnalytics is currently seeking one or multiple sponsors for an analysis of Pennsylvania public school revenues. The analysis will include funding data for all 500 public school districts and all public charter schools. The financial data will be intersected with poverty data to shed light on funding equity and the extent to which funding is "progressive" or "regressive"
Due to regulatory changes, use of the Free and Reduced Price Lunch participation metric is no longer an accurate measure of poverty. For this analysis, EduAnalytics will use the U.S. Census Bureau's Small Area Income and Poverty Estimates (SAIPE) program data. For more information, see: https://www.census.gov/programs-surveys/saipe.html
EduAnalytics will deliver an easy to use Excel model designed for the purpose of research by any stakeholder. The model will include pertinent "live" tables and graphics, which enable users to select and explore various aggregations of school districts and charter schools. EduAnalytics can accommodate additional reporting on special areas of interest to sponsors.
"Progressive" refers to a funding result whereby a school district with greater poverty receives greater funding per pupil. "Regressive" refers to a funding result whereby a school district with lower poverty receives greater funding per pupil. What is the overall progressive/regressive tendency in PA by school district, by county, and by region?
The analysis will explore district-to-district equity, district-to-charter equity, and charter-to-charter equity. Student demographic enrollment data will be included as context for equity considerations. One-hundred percent of funding from all sources and all accounting funds will be analyzed in a manner whereby data can be dis-aggregated by source.
The analysis informs fact-based decision-making and understanding regarding funding issues. The intended beneficiaries include: Sate Legislators, the Governor's office, district and charter school administrators, other K-12 public education stakeholders, students, and taxpayers.