Analysis of Secondary School Infrastructure Distributions in Osogbo Metropolis, Nigeria

This study analysed the geospatial distribution of secondary schools infrastructure in the Osogbo metropolis, Nigeria, with a focus on evaluating accessibility and spatial patterns of school locations. By examining the spatial distribution, travel distances, and clustering of schools, this research offers a novel contribution to the educational planning literature. The data were collected through both primary and secondary sources, utilizing total enumeration for spatial data and a sampling frame of 17,595 students and 452 teachers across 120 public and private secondary schools. Using a balloting approach, at 15%, 19 schools were sampled, followed by a random sampling technique to choose 5% of students and staff, resulting in a total of 906 respondents (880 students and 26 teachers). The analysis, employing Moran's I Index, revealed a value of 0.75 and a p-value of 0.14, indicating a random distribution of schools with a z-score of 1.45, falling within the expected range. The average distance traveled to schools was 1.582 km, reflecting spatial inequities in accessibility. This study provides critical insights for policymakers, emphasizing the need for both public and private stakeholders to ensure equitable distribution and accessibility of secondary schools across Osogbo metropolis.

Authors

Institutions

Publication Details

Journal
Ruang
Published
2024-10-31
DOI
https://doi.org/10.14710/ruang.10.2.60-69
Primary Topic
Religion and Sociopolitical Dynamics in Nigeria
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of Secondary School Infrastructure Distributions in Osogbo Metropolis, Nigeria

Adedotun Samuel Babatunde Babatunde, Olorunfemi Olayiwola, Ogundahunsi Dele Sunday, Gasu Martins Binde et al.
Ruang
Religion and Sociopolitical Dynamics in Nigeria
article

Analysis of Secondary School Infrastructure Distributions in Osogbo Metropolis, Nigeria

Adedotun Samuel Babatunde Babatunde, Olorunfemi Olayiwola, Ogundahunsi Dele Sunday, Gasu Martins Binde, Olayode Christiana
article en

Abstract

This study analysed the geospatial distribution of secondary schools infrastructure in the Osogbo metropolis, Nigeria, with a focus on evaluating accessibility and spatial patterns of school locations. By examining the spatial distribution, travel distances, and clustering of schools, this research offers a novel contribution to the educational planning literature. The data were collected through both primary and secondary sources, utilizing total enumeration for spatial data and a sampling frame of 17,595 students and 452 teachers across 120 public and private secondary schools. Using a balloting approach, at 15%, 19 schools were sampled, followed by a random sampling technique to choose 5% of students and staff, resulting in a total of 906 respondents (880 students and 26 teachers). The analysis, employing Moran's I Index, revealed a value of 0.75 and a p-value of 0.14, indicating a random distribution of schools with a z-score of 1.45, falling within the expected range. The average distance traveled to schools was 1.582 km, reflecting spatial inequities in accessibility. This study provides critical insights for policymakers, emphasizing the need for both public and private stakeholders to ensure equitable distribution and accessibility of secondary schools across Osogbo metropolis.

RuangVol. 10(2)
Osun State University (NG)
Industry, innovation and infrastructure
Openalex Percentile: Top 67%
Religion and Sociopolitical Dynamics in Nigeria
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.