TY - JOUR
T1 - Spatial analysis of millennium educational units in Ecuador and its coverage over poverty areas
AU - Navas, Gustavo Ernesto
AU - Paz, Robinson Llerena
AU - Vaca, Fernando
N1 - Publisher Copyright:
© 2019, Universidad Politécnica Salesiana, Ecuador.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - One of the most influence parameters in poverty is the poor quality of education. The systematic study of poverty is essential to improve the implementation of plans and projects. Since 2005, Ecuador began the’Project to improve education conditions, schooling access and coverage of education’ on high poverty areas through the National Government Educacion2016. This study performs a Spatial Analysis of the above governmental project of Ecuador by the use of free software. This analysis is based in the existence of public educational institutions called’Millennium Educational Units’, whose purpose is to improve academic quality, meet rural student demand and serve historically relegated sectors. It is sought using statistical spatial analysis techniques, supported by a robust relational database such as PostgreSQL for determining their impact area on the population by creating various types of coverage to identify the parishes and the poverty percentage that is being benefited by this educational project, managed to determine that there is a percentage between 77 % and 96 % of UEM, located in areas of extreme poverty.
AB - One of the most influence parameters in poverty is the poor quality of education. The systematic study of poverty is essential to improve the implementation of plans and projects. Since 2005, Ecuador began the’Project to improve education conditions, schooling access and coverage of education’ on high poverty areas through the National Government Educacion2016. This study performs a Spatial Analysis of the above governmental project of Ecuador by the use of free software. This analysis is based in the existence of public educational institutions called’Millennium Educational Units’, whose purpose is to improve academic quality, meet rural student demand and serve historically relegated sectors. It is sought using statistical spatial analysis techniques, supported by a robust relational database such as PostgreSQL for determining their impact area on the population by creating various types of coverage to identify the parishes and the poverty percentage that is being benefited by this educational project, managed to determine that there is a percentage between 77 % and 96 % of UEM, located in areas of extreme poverty.
KW - Millennium educational units
KW - PostgreSQL-PostGIS
KW - Poverty
KW - Spatial analysis
KW - Statistical Spatial Analysis
KW - UEM
UR - http://www.scopus.com/inward/record.url?scp=85072349699&partnerID=8YFLogxK
U2 - 10.17163/lgr.n30.2019.10
DO - 10.17163/lgr.n30.2019.10
M3 - Article
AN - SCOPUS:85072349699
SN - 1390-3799
VL - 30
SP - 111
EP - 121
JO - Granja
JF - Granja
IS - 2
ER -