Identifying High School Students Who May Not Graduate on Time

Fellows: Kerstin Frailey, Ruobin Gong, Siobhan Greatorex-Voith, Reid Johnson
Data Science Mentor(s): Anushka Anand
Project Manager: Alan Fritzler
Project Partner: Wake County Public Schools, Arlington Public Schools, Vancouver Public Schools

Nearly 700,000 students don’t finish high school each year. To help more students graduate on time, school districts across the country use intervention programs to help struggling students get back on track academically. Yet in order to best apply those programs, schools need to identify off-track students as early as possible and enroll them in the most appropriate intervention. Some forward-looking school districts — such as the Wake County Public School System and the Cabarrus and Kannapolis City school districts in North Carolina, the Arlington Public School District in Virginia, and Vancouver Public Schools in Washington — are exploring data-driven “early warning systems” that can help schools find students in need of extra support.

Building upon our work in 2014 with Montgomery County Public Schools, in 2015 DSSG continued developing a useful and descriptive model that identifies students who may not finish high school on time. Using advanced data science methods, the team produced early warning systems for the partnering districts that can be incorporated into existing district software. The team also performed cross-school analyses to build a system that additional, diverse school districts across the country can use to identify and assist struggling students.

In 2016, we continued to build on this work through our partnership with Ohio’s Muskingum Valley Educational Services Center. You can read about that project here.