SPATIAL ANALYSIS OF EDUCATIONAL INEQUALITY: A GEOSPATIAL ASSESSMENT OF PRIMARY SCHOOL DISTRIBUTION ACROSS NIGERIA

This study investigates the spatial distribution and accessibility of primary schools across Nigeria to uncover patterns of educational inequality. Using geospatial techniques, the research evaluates how location affects access to education, particularly in rural and underserved areas. The study employs distance analysis using Euclidean distance to measure proximity between schools and major roads, spatial autocorrelation (Moran’s I) to detect clustering patterns, and two clustering algorithms—K-Means and DBSCAN—to identify regions of high and low school density. Visualization and spatial analysis were performed using GIS and R. Findings reveal significant regional disparities in school access, with many northern areas exhibiting poor road connectivity and dispersed school locations. K-Means produced more structured regional clusters, while DBSCAN was more effective in identifying outliers and isolated schools. The study concludes that geospatial methods offer valuable insights for identifying underserved regions and guiding data-driven decisions to promote equitable access to basic education in Nigeria.