Student Integrated Predictive Analytics
Identifying what is the most effective support to in the moment is an ongoing source of education analytics work. All of us that support students in striving towards their post-secondary education goals want to do so in the best way possible. This means using information that is specific, timely, personal, and actionable.
What we do
Regardless of whether a goal is a specific degree or employment in the long-term or focused on persistence in the short-term, a complete picture of the student experience requires data from many sources, including the student themselves. Using past cohorts, SIPA uses these data to develop feedback factors: support factors and risk factors.
The SIPA project supports institutions in organizing and using their data to predict the likelihood students will achieve their established goals. Importantly, this is not limited to quantitative data like academic performance, but other behavioral data like program engagement and off-campus commitments like family and employment. SIPA provides both predictive analytics and a holistic view of the student that utilizes the expertise within the institution and community. The output per student looks like: likelihood of achievement, their areas of strength and support, their risk factors, and suggestions of intervention and encouragement that counselors and other staff can factor into the student experience.