Educational Intelligence (EDU-INT): A New Intelligence Discipline for Predicting Insecurity in Sub-Saharan Africa

Abstract

Education systems experience disruption during armed conflict, but the usefulness of school information for anticipating violence remains insufficiently established. This article defines Educational Intelligence (EDU-INT) as the systematic, ethical collection, analysis, and communication of education-related information to support the anticipation, prevention, and mitigation of insecurity. A targeted narrative review and conceptual synthesis examined fifteen openly accessible research publications, institutional documents, and database resources concerning education, conflict forecasting, early warning, and responsible data management. Sources were assessed for their relevance to indicator selection, observation frequency, temporal ordering, institutional integration, and protection risks. The synthesis supports a plausible relationship between educational disruption and insecurity while distinguishing evidence of conflict affecting education from evidence that schooling indicators predict subsequent violence. Twelve candidate indicators are specified, covering participation, teacher availability, school access, coercion, threats, and damage to essential facilities. A provisional traffic light framework links verified observations to proportionate protective responses without treating uncalibrated scores as probabilities. Public education statistics and conflict event databases provide contextual information and possible outcome measures, but do not supply the daily school records required to validate the proposed framework. No original interviews, retrospective prediction results, or estimated warning intervals are reported. Prospective evaluation should compare models with and without education indicators, preserve the information available at each forecast date, and assess false alarms, calibration, reporting delays, and gender-related differences. EDU-INT therefore represents a proposed analytical specialization whose predictive value requires independent empirical testing. Its contribution is a transparent research framework connecting education monitoring with accountable, effective civilian protection