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Early Warning Systems
Early Warning Systems (EWS) identify students who are in jeopardy of dropping out of school by analyzing key data to determine which students are most at-risk. Most EWS collect data on three essential early warning elements that research has shown are most predictive of students dropping out—Attendance, Behavior, and Course performance (often referred to as the ABC’s of early warning data):
- Attendance: Missing 20 days or being absent 10 percent of school days;
- Behavior: Two or more mild or more serious behavior infractions;
- Course Performance: Failure in English or math in 6th through 9th grade; a GPA of less than 2.0; two or more failures in 9th grade courses; and failure to pass 9th grade.
What does the Research Say?
It is critical for schools to add a data-based early warning system as a school-wide practice aimed at identifying which students are at risk of dropping out and providing a regular system to guide interventions and monitoring of students.
Core components of effective EWS implementation by the Institute of Education Sciences (IES):
- Train an education team to use the EWS(e.g., administrators, teachers, counselors, mentors, etc.)
- Identify appropriate dropout indicators
- Design and use reports to collect and monitor data
- Connect appropriate interventions to individual student needs
- Evaluate student progress and intervention effectiveness.