Early warning systems for school dropout prevention

An Early Warning System (EWS) is a tool to improve school retention, transition and completion by identifying students at risk of dropping out. It can be simple and paper-based, or more advanced and AI-powered.

It uses data to flag learners most at risk, especially at key transition points and among marginalized groups. At school level, these insights help parents, teachers and communities provide timely support, including learning assistance, health and mental health services, child protection and social protection. At a subnational level, the data can inform wider strategies such as infrastructure, transport and other measures that address systemic barriers to retention and completion.

An EWS can be integrated with an Education Management Information System (EMIS) – the government’s core system for collecting and managing education data such as enrolment, attendance, progression and school information – allowing dropout risks to be identified and acted on more efficiently at scale.

Why are early warning systems needed? 

School dropout is a critical challenge undermining education access and equity. Dropout is multifaceted, driven by push and pull factors at the system, community and individual levels, including unconducive learning environments, poor education performance, overcrowding, distance, teacher absenteeism, poverty, rurality, child labour, disability, and social and gender norms. Frequent absenteeism, disengagement and low learning levels can all serve as early predictors of dropout risk.