From Prediction to Prevention: A New Approach to Improving Student Attendance

Attendance data should do more than show schools what has already happened. Two students who have missed a similar number of days may face very different attendance risks. New research from Panorama’s Data Science team found that students whose absences are spread across multiple distinct events are more likely to continue missing school than students whose absences happen in one continuous stretch. These patterns can give educators an earlier signal for determining when—and how—students need support. Join Panorama for a conversation about moving from early identification of attendance patterns to effective intervention and consistent follow-through. You’ll also hear how Earlville CUSD 9 built a relationship-centered approach that helped improve high school attendance from 61% to 90%.