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Detection of hotspots of school dropouts in India: A spatial clustering approach
School dropout is a significant concern universally. This paper investigates the incorporation of spatial dependency in estimating the topographical effect of school dropout rates in India. This study utilizes the secondary data on primary, upper primary, and secondary school dropout rates of the di...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9844897/ https://www.ncbi.nlm.nih.gov/pubmed/36649246 http://dx.doi.org/10.1371/journal.pone.0280034 |
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author | Venkatesan, Raghul Gandhi Mappillairaju, Bagavandas |
author_facet | Venkatesan, Raghul Gandhi Mappillairaju, Bagavandas |
author_sort | Venkatesan, Raghul Gandhi |
collection | PubMed |
description | School dropout is a significant concern universally. This paper investigates the incorporation of spatial dependency in estimating the topographical effect of school dropout rates in India. This study utilizes the secondary data on primary, upper primary, and secondary school dropout rates of the different districts of India available at the Unified District Information System for Education plus (UDISE+) for the year 2020 to contemplate the impact of these dropouts from one region to different regions in molding with promotion rate and repetition rate. The Global Moran’s I, Univariate and Bivariate Local Indicators of Spatial Association, and spatial models are utilized to investigate the geographical variability and to find the possible relationship between dropout rates and the school-level factors at the district level. The outcomes provide clear spatial clustering and precisely highlight the hot zone dropout regions with high repetition and low promotion rates. Based on this study’s results, educational administrators can make evidence-based decisions to reduce dropout rates in hot zones of various regions of India. Furthermore, futuristic studies focusing on linking spatial hot zones with causal factors will add consistent data in assisting policymakers in taking necessary measures to develop a sound education management system. |
format | Online Article Text |
id | pubmed-9844897 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-98448972023-01-18 Detection of hotspots of school dropouts in India: A spatial clustering approach Venkatesan, Raghul Gandhi Mappillairaju, Bagavandas PLoS One Research Article School dropout is a significant concern universally. This paper investigates the incorporation of spatial dependency in estimating the topographical effect of school dropout rates in India. This study utilizes the secondary data on primary, upper primary, and secondary school dropout rates of the different districts of India available at the Unified District Information System for Education plus (UDISE+) for the year 2020 to contemplate the impact of these dropouts from one region to different regions in molding with promotion rate and repetition rate. The Global Moran’s I, Univariate and Bivariate Local Indicators of Spatial Association, and spatial models are utilized to investigate the geographical variability and to find the possible relationship between dropout rates and the school-level factors at the district level. The outcomes provide clear spatial clustering and precisely highlight the hot zone dropout regions with high repetition and low promotion rates. Based on this study’s results, educational administrators can make evidence-based decisions to reduce dropout rates in hot zones of various regions of India. Furthermore, futuristic studies focusing on linking spatial hot zones with causal factors will add consistent data in assisting policymakers in taking necessary measures to develop a sound education management system. Public Library of Science 2023-01-17 /pmc/articles/PMC9844897/ /pubmed/36649246 http://dx.doi.org/10.1371/journal.pone.0280034 Text en © 2023 Venkatesan, Mappillairaju https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Venkatesan, Raghul Gandhi Mappillairaju, Bagavandas Detection of hotspots of school dropouts in India: A spatial clustering approach |
title | Detection of hotspots of school dropouts in India: A spatial clustering approach |
title_full | Detection of hotspots of school dropouts in India: A spatial clustering approach |
title_fullStr | Detection of hotspots of school dropouts in India: A spatial clustering approach |
title_full_unstemmed | Detection of hotspots of school dropouts in India: A spatial clustering approach |
title_short | Detection of hotspots of school dropouts in India: A spatial clustering approach |
title_sort | detection of hotspots of school dropouts in india: a spatial clustering approach |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9844897/ https://www.ncbi.nlm.nih.gov/pubmed/36649246 http://dx.doi.org/10.1371/journal.pone.0280034 |
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