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

Thursday, August 20, 2026 | 3:00 ET (60 mins)

Attendance data should do more than show schools what has already happened.

Two students may have missed a similar number of days, but still 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 when determining when—and how—students need support.

This research informed Attendance Forecast, a newly available capability in Panorama Student Success. Attendance Forecast estimates where a student’s attendance may be headed, helping teams prioritize where to investigate and respond.

Join Panorama for a conversation about moving from early identification 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%.

What you’ll learn

• What Panorama learned from analyzing attendance patterns across more than 230,000 students in 400+ schools
• How student absence patterns can reveal future attendance risk
• How Attendance Forecast helps educators identify emerging risk and prioritize support
• Which attendance intervention strategies were associated with stronger results at the elementary, middle and high school levels
• How Earlville CUSD 9 increased high school attendance from 61% to 90%
• How to create a more consistent workflow connecting student data, relationships, interventions, and progress monitoring