Exploring the Related Factors in Education Quality through Spatial Autoregressive Modeling with Latent Variables: A Rural Case Study

The principle of education for sustainable development (ESD) is that no child is left behind. Hence, the fourth sustainable development goal (SDG) of the United Nations (UN) emphasizes inclusion and equity in education by focusing on eliminating disparities among regions. This study explores factors...

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Main Authors: Anik Anekawati, Bambang W. Otok, Purhadi, Sutikno
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Education Research International
Online Access:http://dx.doi.org/10.1155/2020/8823186
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spelling doaj-02991c441f0a4a1eaba6ed9d234254c32020-11-25T03:51:58ZengHindawi LimitedEducation Research International2090-40022090-40102020-01-01202010.1155/2020/88231868823186Exploring the Related Factors in Education Quality through Spatial Autoregressive Modeling with Latent Variables: A Rural Case StudyAnik Anekawati0Bambang W. Otok1Purhadi2Sutikno3Faculty of Teacher Training and Education, Universitas Wiraraja, Sumenep 69451, IndonesiaDepartment of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, IndonesiaDepartment of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, IndonesiaDepartment of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, IndonesiaThe principle of education for sustainable development (ESD) is that no child is left behind. Hence, the fourth sustainable development goal (SDG) of the United Nations (UN) emphasizes inclusion and equity in education by focusing on eliminating disparities among regions. This study explores factors related to education quality through modeling in rural areas of Sumenep Regency, in East Java, Indonesia. Currently, only a few kinds of research studies involve spatial data, latent variables and, at the same time, tests of their spillover effects. The modeling herein is the spatial autoregressive model with latent variables (SAR-LVs). The latent variables were estimated using the weighted least square (WLS) method, while the Lagrange multiplier (LM) test was used for spatial dependence testing. The parameters of the SAR-LVs were estimated using two-stage least square (2SLS). The results show that the quality of education is directly influenced by the infrastructure of the schools but not by the socioeconomic conditions of the local communities. The autoregressive spatial coefficient has a significant but negative effect, which shows a negative spillover from districts with a lower quality of education to the ones with a high quality of education. This is due to the students’ competition to get registered for a favorite or good quality school in a particular district, which stimulates the migration of students from its neighboring districts. This reveals the inequality of school quality, since not all students can get access to schools with good quality. Through this study, some recommendations are given as a contribution to achieving the fourth SDG in Indonesia.http://dx.doi.org/10.1155/2020/8823186
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language English
format Article
sources DOAJ
author Anik Anekawati
Bambang W. Otok
Purhadi
Sutikno
spellingShingle Anik Anekawati
Bambang W. Otok
Purhadi
Sutikno
Exploring the Related Factors in Education Quality through Spatial Autoregressive Modeling with Latent Variables: A Rural Case Study
Education Research International
author_facet Anik Anekawati
Bambang W. Otok
Purhadi
Sutikno
author_sort Anik Anekawati
title Exploring the Related Factors in Education Quality through Spatial Autoregressive Modeling with Latent Variables: A Rural Case Study
title_short Exploring the Related Factors in Education Quality through Spatial Autoregressive Modeling with Latent Variables: A Rural Case Study
title_full Exploring the Related Factors in Education Quality through Spatial Autoregressive Modeling with Latent Variables: A Rural Case Study
title_fullStr Exploring the Related Factors in Education Quality through Spatial Autoregressive Modeling with Latent Variables: A Rural Case Study
title_full_unstemmed Exploring the Related Factors in Education Quality through Spatial Autoregressive Modeling with Latent Variables: A Rural Case Study
title_sort exploring the related factors in education quality through spatial autoregressive modeling with latent variables: a rural case study
publisher Hindawi Limited
series Education Research International
issn 2090-4002
2090-4010
publishDate 2020-01-01
description The principle of education for sustainable development (ESD) is that no child is left behind. Hence, the fourth sustainable development goal (SDG) of the United Nations (UN) emphasizes inclusion and equity in education by focusing on eliminating disparities among regions. This study explores factors related to education quality through modeling in rural areas of Sumenep Regency, in East Java, Indonesia. Currently, only a few kinds of research studies involve spatial data, latent variables and, at the same time, tests of their spillover effects. The modeling herein is the spatial autoregressive model with latent variables (SAR-LVs). The latent variables were estimated using the weighted least square (WLS) method, while the Lagrange multiplier (LM) test was used for spatial dependence testing. The parameters of the SAR-LVs were estimated using two-stage least square (2SLS). The results show that the quality of education is directly influenced by the infrastructure of the schools but not by the socioeconomic conditions of the local communities. The autoregressive spatial coefficient has a significant but negative effect, which shows a negative spillover from districts with a lower quality of education to the ones with a high quality of education. This is due to the students’ competition to get registered for a favorite or good quality school in a particular district, which stimulates the migration of students from its neighboring districts. This reveals the inequality of school quality, since not all students can get access to schools with good quality. Through this study, some recommendations are given as a contribution to achieving the fourth SDG in Indonesia.
url http://dx.doi.org/10.1155/2020/8823186
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