Predicting High School Graduation and College Enrollment: Comparing Early Warning Indicator Data and Teacher Intuition

Each year, more districts implement early warning systems (EWS). These EWS predict negative student outcomes, such as dropping out, before they occur. Predictions are then used to match at-risk students to appropriate supports and interventions. Research suggests that these systems are useful in ensuring educators respond to student needs early, generating conversation around specific students at risk of dropping out. However, no research considers what new information teachers gain from having a specific prediction for a student. This article bridges this gap by comparing teacher and EWS predictions of whether students will complete high school and enroll in college. Further, it assesses whether accuracy in teacher judgment stems from additional information not in models—especially related to academic tenacity—and biases like self-fulfilling prophecies. Generally, EWS can provide benefits both as organizational tools and by increasing the precision with which students are identified for supports and interventions.