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Volume 39, Issue 3 (2024)
GeoRes 2024, 39(3): 309-318 |
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Received: 2024/06/20 | Accepted: 2024/08/11 | Published: 2024/09/20
Received: 2024/06/20 | Accepted: 2024/08/11 | Published: 2024/09/20
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Mohammadtaghi R, Hamidi Toghchi M. Role of School Quality in the Sustainability of Rural Population Settlements; in Isfahan County with a Sustainability Approach. GeoRes 2024; 39 (3) :309-318
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Authors
R. Mohammadtaghi *1, M. Hamidi Toghchi1
1- Department of Human Geography, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran
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Background
The lack of spatial justice and educational services in rural areas of Iran, especially in Isfahan County, has led to migration, decreased quality of life, and population instability. High-quality education can be a key factor in sustainable development and in attracting and retaining rural populations.
Previous Studies
Numerous studies have emphasized the crucial role of equitable access to public services in enhancing rural sustainability and curbing migration. Researchers have linked insufficient access to education in rural areas with spatial and social inequalities, leading to poverty, youth outmigration, and loss of community vitality (Motiei Langroudi & Shamsaei, 2006; Rostaie et al., 2016; Wood, 2023). Others argue that education infrastructure such as schools significantly affects rural resilience and population retention (Babaei et al., 2021; Marre et al., 2020). Studies by Nasiri Zare & Riahi (2021) and Aghajani & Cheshamlos (2021) suggest that improving rural services-especially education-can reduce poverty and migration. Moreover, global frameworks like the SDGs highlight education as a key enabler for sustainable development (UNESCO, 2016). Spatial justice scholars, including Beach et al. (2018), stress that educational inequality is not uniformly distributed but concentrated in marginalized rural areas, exacerbating broader patterns of spatial injustice.
Aim(s)
This study aimed to examine education as an effective tool for attracting and retaining population, with a focus on sustainable development and stability. It investigated the relationship between rural migration and education, as well as how public educational centers influence population attraction in Isfahan County.
Research Type
This research was applied in nature and conducted in Isfahan using a descriptive-analytical method.
Research Society, Place and Time
The statistical population of this study included public schools and migrant households with school-aged children in Isfahan County in the year 2023.
Sampling Method and Number
The sampling method in this study was random. For public schools, using Cochran's formula and based on the number of urban and rural schools, 295 samples were selected (111 questionnaires in rural schools and 184 in urban schools). For migrant households, 384 random samples were also selected using the same formula, based on migration origins and destinations across different districts of the county, and questionnaires were distributed accordingly.
Used Devices & Materials
In this study, data were collected through both library research (including educational data and spatial-geographic information) and field studies (questionnaires). The main data collection tool was researcher-made questionnaires consisting of 45 items based on a 5-point Likert scale. Data analysis was conducted using SPSS version 26 and AMOS version 24 for structural equation modeling and analyzing relationships between latent and observed variables. Additionally, GIS software version 10.8 and Excel tables were used to analyze spatial differences and school distribution patterns.
Findings by Text
Documentary studies in Isfahan County indicate spatial inequality in secondary education. Specifically, out of a total of 146 general and 74 technical-vocational schools, over 75% are concentrated in the educational districts of Isfahan city. Additionally, from the total number of staff (14,342 individuals) and students (37,996 in public and 9,786 in private schools), the shares belonging to the districts of Isfahan city were 90.1%, 94.5%, and 100%, respectively. This indicates a heavy concentration of educational resources and services in the city, which has become a major driver of migration to it (Figure 1).
Figure 1. Distribution of schools, students, and staff in upper secondary schools of Isfahan county
To investigate the causes of migration, 384 questionnaires were analyzed and influencing factors were identified. The geographical factor had no significant impact and was excluded; the most influential factors were educational (coefficient 0.94), managerial (0.79), and educational support services (0.53) (Table 1). The economic factor played a minor role.
Table 1. Factors and indicators of migration in migration-receiving schools in Isfahan city
The structural equation model demonstrated a good fit with RMSEA = 0.069 and CFI = 0.935. Spatial data also clearly confirmed the inequity in the distribution of educational facilities (Figure 1).
Subsequently, the relationship between educational transformation planning and the educational environment was analyzed using Amos software. The results showed that planning had a strong relationship with education (1), management (0.98), and parental involvement (0.93), but no significant relationship with the health component (0.8) (Table 2). Moreover, there was a significant difference between urban and rural areas in the impact of planning (Table 3).
Table 2. Coefficients of the planning and educational environment model
Table3. Impact levels of parameters in urban and rural areas
The analysis of educational equity was also conducted based on the opinions of 295 school principals. The scores of the education, health, management, and participation parameters showed irregular dispersion (with negative Moran indices and p > 0.05) across the county (Tables 4 and 5). Only the management index showed a relatively more uniform distribution (Figure 2).
Table 4. Scores of educational parameters by educational districts
Table 5. Dispersion coefficients of educational environment parameters in schools of Isfahan county
Figure 2. Distribution pattern of management quality in schools of Isfahan county
In the structural model of satisfaction, analysis of 295 questionnaires from families revealed that in Isfahan city, education (0.68) and health (0.29) had a direct impact on satisfaction, whereas in peripheral areas, these effects were 0.94 and 0.83, respectively (Table 6, Figure 3). Management only had an indirect effect through education and health.
Table 6. Regression coefficients of the parental satisfaction model with school affairs in Isfahan county
Figure 3. Structural model of parental satisfaction with school affairs in Isfahan county
The final results indicate that in peripheral areas, household satisfaction with education is significantly lower than in Isfahan city, and there is a meaningful disparity between these two areas. This situation is a major factor in rural migration to the city of Isfahan. The structural model also confirmed this relationship (X² = 43, RMSEA = 0.08, CFI = 0.86, p = 0.000).
Main Comparisons to Similar Studies
The findings of the present study regarding the significant role of educational quality in rural-to-urban migration align with those of Rastgaripour and Mahmoudi (2020), who identified education as a prerequisite for rural economic development. However, in contrast to Yasuri et al. (2016), who focused on spatial disorder, this study directly examined education as a motivating factor for migration. Furthermore, unlike Dadezadeh et al., Nasiri Zare & Riahi, Aghajani & Cheshamlos, Langroudi & Shamsaei, and Ghasemi, who have emphasized facilities and public services, the current research centered its analysis on the role of school principals and the quality of education [Dadezadeh et al., 2021; Nasiri Zare & Riahi, 2021; Aghajani & Cheshamlos, 2021; Motiei Langroudi & Shamsaei, 2006; Ghasemi, 2016]. The findings also correspond with those of Rostmalizadeh (2019), who identify educational processes as drivers of local development and population attraction. Overall, this study, through an analytical and model-based approach, examined the contribution of high-quality education and effective management to the sustainability of rural populations in greater depth.
Suggestions
Based on the findings of the study, it is recommended that the educational quality of rural schools be improved by attracting capable and creative school principals. Education should be considered a prerequisite for economic development and a key factor in rural population retention within policy frameworks. Unlike studies that emphasized public services, this research demonstrated that school management and educational quality have a direct impact on reducing migration.
Conclusion
The educational, health, managerial, and participation parameters exhibit a random or irregular pattern, indicating a lack of uniform distribution across the county. Regarding migration, the educational factor had a greater impact compared to other factors. Contrary to common assumptions, the economic factor showed an inverse relationship with migration.
Acknowledgments: Nothing is reported by the authors
Ethical Permission: No ethical concerns were reported by the authors.
Conflict of Interest: The authors declare no conflicts of interest.
Author Contributions: Razavi MT (First Author), Introduction Writer/]Methodologist (30%); Hamidi Toghchi M (Second Author), Main Researcher/Statistical Analyst/Discussion Writer (70%)
Funding: This research was funded through personal income.
The lack of spatial justice and educational services in rural areas of Iran, especially in Isfahan County, has led to migration, decreased quality of life, and population instability. High-quality education can be a key factor in sustainable development and in attracting and retaining rural populations.
Previous Studies
Numerous studies have emphasized the crucial role of equitable access to public services in enhancing rural sustainability and curbing migration. Researchers have linked insufficient access to education in rural areas with spatial and social inequalities, leading to poverty, youth outmigration, and loss of community vitality (Motiei Langroudi & Shamsaei, 2006; Rostaie et al., 2016; Wood, 2023). Others argue that education infrastructure such as schools significantly affects rural resilience and population retention (Babaei et al., 2021; Marre et al., 2020). Studies by Nasiri Zare & Riahi (2021) and Aghajani & Cheshamlos (2021) suggest that improving rural services-especially education-can reduce poverty and migration. Moreover, global frameworks like the SDGs highlight education as a key enabler for sustainable development (UNESCO, 2016). Spatial justice scholars, including Beach et al. (2018), stress that educational inequality is not uniformly distributed but concentrated in marginalized rural areas, exacerbating broader patterns of spatial injustice.
Aim(s)
This study aimed to examine education as an effective tool for attracting and retaining population, with a focus on sustainable development and stability. It investigated the relationship between rural migration and education, as well as how public educational centers influence population attraction in Isfahan County.
Research Type
This research was applied in nature and conducted in Isfahan using a descriptive-analytical method.
Research Society, Place and Time
The statistical population of this study included public schools and migrant households with school-aged children in Isfahan County in the year 2023.
Sampling Method and Number
The sampling method in this study was random. For public schools, using Cochran's formula and based on the number of urban and rural schools, 295 samples were selected (111 questionnaires in rural schools and 184 in urban schools). For migrant households, 384 random samples were also selected using the same formula, based on migration origins and destinations across different districts of the county, and questionnaires were distributed accordingly.
Used Devices & Materials
In this study, data were collected through both library research (including educational data and spatial-geographic information) and field studies (questionnaires). The main data collection tool was researcher-made questionnaires consisting of 45 items based on a 5-point Likert scale. Data analysis was conducted using SPSS version 26 and AMOS version 24 for structural equation modeling and analyzing relationships between latent and observed variables. Additionally, GIS software version 10.8 and Excel tables were used to analyze spatial differences and school distribution patterns.
Findings by Text
Documentary studies in Isfahan County indicate spatial inequality in secondary education. Specifically, out of a total of 146 general and 74 technical-vocational schools, over 75% are concentrated in the educational districts of Isfahan city. Additionally, from the total number of staff (14,342 individuals) and students (37,996 in public and 9,786 in private schools), the shares belonging to the districts of Isfahan city were 90.1%, 94.5%, and 100%, respectively. This indicates a heavy concentration of educational resources and services in the city, which has become a major driver of migration to it (Figure 1).
Figure 1. Distribution of schools, students, and staff in upper secondary schools of Isfahan county
To investigate the causes of migration, 384 questionnaires were analyzed and influencing factors were identified. The geographical factor had no significant impact and was excluded; the most influential factors were educational (coefficient 0.94), managerial (0.79), and educational support services (0.53) (Table 1). The economic factor played a minor role.
Table 1. Factors and indicators of migration in migration-receiving schools in Isfahan city
The structural equation model demonstrated a good fit with RMSEA = 0.069 and CFI = 0.935. Spatial data also clearly confirmed the inequity in the distribution of educational facilities (Figure 1).
Subsequently, the relationship between educational transformation planning and the educational environment was analyzed using Amos software. The results showed that planning had a strong relationship with education (1), management (0.98), and parental involvement (0.93), but no significant relationship with the health component (0.8) (Table 2). Moreover, there was a significant difference between urban and rural areas in the impact of planning (Table 3).
Table 2. Coefficients of the planning and educational environment model
Table3. Impact levels of parameters in urban and rural areas
The analysis of educational equity was also conducted based on the opinions of 295 school principals. The scores of the education, health, management, and participation parameters showed irregular dispersion (with negative Moran indices and p > 0.05) across the county (Tables 4 and 5). Only the management index showed a relatively more uniform distribution (Figure 2).
Table 4. Scores of educational parameters by educational districts
Table 5. Dispersion coefficients of educational environment parameters in schools of Isfahan county
Figure 2. Distribution pattern of management quality in schools of Isfahan county
In the structural model of satisfaction, analysis of 295 questionnaires from families revealed that in Isfahan city, education (0.68) and health (0.29) had a direct impact on satisfaction, whereas in peripheral areas, these effects were 0.94 and 0.83, respectively (Table 6, Figure 3). Management only had an indirect effect through education and health.
Table 6. Regression coefficients of the parental satisfaction model with school affairs in Isfahan county
Figure 3. Structural model of parental satisfaction with school affairs in Isfahan county
The final results indicate that in peripheral areas, household satisfaction with education is significantly lower than in Isfahan city, and there is a meaningful disparity between these two areas. This situation is a major factor in rural migration to the city of Isfahan. The structural model also confirmed this relationship (X² = 43, RMSEA = 0.08, CFI = 0.86, p = 0.000).
Main Comparisons to Similar Studies
The findings of the present study regarding the significant role of educational quality in rural-to-urban migration align with those of Rastgaripour and Mahmoudi (2020), who identified education as a prerequisite for rural economic development. However, in contrast to Yasuri et al. (2016), who focused on spatial disorder, this study directly examined education as a motivating factor for migration. Furthermore, unlike Dadezadeh et al., Nasiri Zare & Riahi, Aghajani & Cheshamlos, Langroudi & Shamsaei, and Ghasemi, who have emphasized facilities and public services, the current research centered its analysis on the role of school principals and the quality of education [Dadezadeh et al., 2021; Nasiri Zare & Riahi, 2021; Aghajani & Cheshamlos, 2021; Motiei Langroudi & Shamsaei, 2006; Ghasemi, 2016]. The findings also correspond with those of Rostmalizadeh (2019), who identify educational processes as drivers of local development and population attraction. Overall, this study, through an analytical and model-based approach, examined the contribution of high-quality education and effective management to the sustainability of rural populations in greater depth.
Suggestions
Based on the findings of the study, it is recommended that the educational quality of rural schools be improved by attracting capable and creative school principals. Education should be considered a prerequisite for economic development and a key factor in rural population retention within policy frameworks. Unlike studies that emphasized public services, this research demonstrated that school management and educational quality have a direct impact on reducing migration.
Conclusion
The educational, health, managerial, and participation parameters exhibit a random or irregular pattern, indicating a lack of uniform distribution across the county. Regarding migration, the educational factor had a greater impact compared to other factors. Contrary to common assumptions, the economic factor showed an inverse relationship with migration.
Acknowledgments: Nothing is reported by the authors
Ethical Permission: No ethical concerns were reported by the authors.
Conflict of Interest: The authors declare no conflicts of interest.
Author Contributions: Razavi MT (First Author), Introduction Writer/]Methodologist (30%); Hamidi Toghchi M (Second Author), Main Researcher/Statistical Analyst/Discussion Writer (70%)
Funding: This research was funded through personal income.
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