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

• In Event: Promising Scholarship in Education: Dissertation Fellows and Their Research

Abstract

Each year, more districts implement early warning systems (EWS). These EWSs 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 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.

Author

• James Soland, Kingsbury Center at NWEA