Lessons from the Trenches of Applied Data Science
The Pennsylvania State System of Higher Education (PASSHE) asked Civilytics to build an equity-focused tool to identify high schools for recruiting freshmen to system universities. This tool uses only publicly available information to give PASSHE schools the information they need to develop recruitment and marketing campaigns.
FRAIS Gives users tools to interactively explore the number of college-ready students across the United States including the ability to filter and sort by race and ethnicity, geography, and academic selectivity.
Using GAMMs for flexible estimation
An open community for education data analysts.
Train your team in R with exactly the content you need, and none of the stuff you don't.
Concept paper on how to leverage predictive models to improve the feedback and function of the statewide dashboard and education information system.
A RD study of ELL student reclassification and its effect on future outcomes.
The Wisconsin Dropout Early Warning System I co-developed the award-winning Wisconsin Dropout Early Warning System (DEWS) during my time working at the Wisconsin Department of Public Instruction. DEWS is a machine-learning application built on the state longitudinal data system at DPI. It uses hundreds of thousands of records that are mandated to be submitted to the department for various accountability and reporting purposes, analyzes them, and return to schools a prediction of on-time high school graduation for their students in grades 5-9.
A how-to on developing an early warning system at scale used by educators.
A doctoral thesis examining the democratic nature of school board elections in Wisconsin.