Keeping an eye on students: evidence from a low-cost early alert system

We evaluate an early alert system intervention at a German university, where at-risk students received warning emails based on dropout probability. While the average effect was insignificant, estimates point to heterogeneous responses. Previously active students, particularly in non-STEM fields, reduced exam registrations by up to two courses and modestly improved grades, indicating strategic workload adjustment. Inactive students showed no response, and dropout probability increased slightly in structured programs. Causal forests reveal further treatment heterogeneity. Our findings point towards the importance of pre-treatment academic activity and intervention timing, indicating that warnings must align with student engagement and program structure.

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Publication Details

Journal
Education Economics
Published
2026-07-30
DOI
https://doi.org/10.1080/09645292.2026.2708756
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Keeping an eye on students: evidence from a low-cost early alert system

Johannes Berens, Kerstin Schneider, Leandro Henao, Luis Rumert
Education Economics
Advanced Causal Inference Techniques
article

Keeping an eye on students: evidence from a low-cost early alert system

Johannes Berens, Kerstin Schneider, Leandro Henao, Luis Rumert
article en

Abstract

We evaluate an early alert system intervention at a German university, where at-risk students received warning emails based on dropout probability. While the average effect was insignificant, estimates point to heterogeneous responses. Previously active students, particularly in non-STEM fields, reduced exam registrations by up to two courses and modestly improved grades, indicating strategic workload adjustment. Inactive students showed no response, and dropout probability increased slightly in structured programs. Causal forests reveal further treatment heterogeneity. Our findings point towards the importance of pre-treatment academic activity and intervention timing, indicating that warnings must align with student engagement and program structure.

Education Economics
TH Köln - University of Applied Sciences (DE), RWI – Leibniz Institute for Economic Research (DE), University of Wuppertal (DE), LVR-Klinik Köln (DE)
Bundesministerium für Bildung und Forschung
Quality Education
Openalex Percentile: Top 7%
Advanced Causal Inference Techniques
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