1. Introduction
Educational equity is an important aspect of social equity and is the foundation of social justice [1]. The importance of equity in education has received significant global attention. A consensus has been reached within the academic community that the right to education needs to be protected for everyone, regardless of race, religious belief, color, gender, and socioeconomic status [2].
Over the past 40 years of China’s reform and opening up, the understanding of educational equity has undergone successive changes from an emphasis on equal rights to education to equal opportunities in education, then to a rational allocation of educational resources, and now to the pursuit of fair and quality education [3]. Considerable strides have been made in balancing basic education, and by the end of 2017, the number of counties (cities and districts) that have achieved a basic balance in compulsory education development in China had cumulatively reached more than 2300, accounting for nearly 80% of counties (cities and districts) nationwide [4]. The main social contradiction in China in the new era is the disparity between the people’s growing need for a better life and unbalanced and insufficient development. As an important area of people’s livelihood and the backbone of sustainable socioeconomic development, the unbalanced and insufficient development of education must be addressed. Educational equity has evolved from trying to achieve “literacy” and “universal access” to trying to narrow differences in the quality of supply and understanding how to achieve equity in quality educational resources. At present, the problem of uneven demand for educational facilities and resources is more urgent than the problem of uneven quantity.
County-level administrative units are subjective, self-contained, and flexible in the Chinese administrative landscape [5]. As an overlap between the municipal and rural areas, counties need to implement policies of higher administrative units but also need to refine and implement these policies to a practical level in villages. Studying the equity of China’s educational facilities on a county basis will establish a logical foundation, methodological foundation, and value foundation to achieve more equity and provide a higher quality of equity in education in all of China’s counties.
In the context of China’s new urbanization, the coordinated promotion of rural revitalization is essential to achieve urban and rural coprosperity and to promote modernization [6]. The equitable development of education provides the foundation for the new urbanization. China has entered the middle stage of rapid urbanization [7,8]. Along with the continuous migration of young and middle-aged people from rural areas to cities and towns, a decrease in the population of school-aged children has led to the consolidation of schools for teaching, and schools have shown spatial scarcity in rural areas. High-quality educational resources tend to be concentrated in county towns, giving county residents the advantage of access to high-quality educational resources. However, as the rural population continues to move into the cities, competition for quality education resources in these county cities has intensified. Education resources will continue to be scarce in these county cities, which will deepen the inequality of education in the county areas. The lack of equity in the allocation of education resources between urban and rural areas has become an important factor affecting and limiting the equality of education between urban and rural areas [9,10], seriously hindering the process of achieving social equity in education in China [11].
The topographic fragmentation brought about by soil erosion in the gully areas of the Loess Plateau is serious; the terrain is characterized by thousands of ravines, making it one of the most fragile ecological areas in the world [12,13]. Owing to the fragility of the ecological environment, economic and social development is lagging behind, with urbanization developing slowly compared with that in the plains, with large differences in development levels emerging between urban and rural areas. The special characteristics of the geographic space and the uneven development between urban and rural areas has made the problem of inequitable educational facilities in the counties of the Loess Plateau gully area even more prominent. To date, many studies have examined urbanization in the gully areas of the Loess Plateau in China, but research on the equity of educational facilities in counties with such special topography is lacking.
According to the characteristics of the geographical environment of the Loess Plateau ravine area, we selected Chengcheng County in Shaanxi Province as a typical representative county and constructed a framework to evaluate the equity of educational facilities in the county. The evaluation and analysis framework first explores the fairness of county educational facilities according to three dimensions: equity in supply and demand, in spatial justice, and in quality educational resources. Then, by improving the original model of maximum accessibility equity [14], this framework combines the equity of quality, demand, and spatial accessibility of educational facilities to establish the process of starting point equity, process equity, and outcome equity of county educational facilities. In this study, we evaluated the process of fairness in the starting point, in the process, and in the outcome of educational facilities in the county. We built a framework to evaluate the equity of educational facilities in counties to provide theoretical support for the provision of more equitable educational facilities. Our findings will help governments in China and other countries further optimize the allocation of educational facilities in similar geographical areas.
The remainder of the paper is organized as follows. In Section 2, we discuss the literature with respect to educational facility equity and potential methods. In Section 3, we describe the study area, data sources, and data processing. In Section 4, we describe the construct framework for county educational facilities, the methodology for equity evaluation, and the improved comprehensive equity evaluation model. In Section 5, we present the results of the evaluation of resource equity, spatial equity, and equity in the quality of educational facilities. In Section 6, we discuss our conclusions and recommendations for future research.
2. Literature Review
2.1. Conceptualization of Educational Equity
Educational equity is historical in nature, and its manifestations and modes of governance vary from one era to another, with its meaning changes according to the needs of the times [15]. The efficiency of resource allocation [16] should consider the interests of various groups and respect the basic rights of every resident in the region. Traditional studies on educational equity are based on specific historical conditions, focusing on external material inputs, distributive justice as substantive justice, and scientific indicators for the evaluation of educational equity. Obviously, these conditions are no longer suitable to assess the main disparity in the field of education in the new era of China—that is, “the people’s eagerness to receive quality education and the serious shortage of quality educational resources and their uneven development” [17,18]. Therefore, our understanding of the meaning of equity in education must add “equity in the quality of education” to also include “equity in resources” and “equity in spatial justice”. It is important to emphasize that the term “equity in education” does not mean equality or parity but refers to a means of distribution that is both efficient and fair to the individual while also recognizing differentiation.
2.2. Previous Literature
The issue of equity in education has received widespread attention around the world [19,20,21,22]. The academic community has a long-held consensus that the right to education needs to be protected for everyone, regardless of race, religious belief, color, gender, religion, and socioeconomic status [2]. A recent study by Palmisano et al. confirmed a reduction in the inequality of educational opportunities in 26 European countries for individuals born between 1930 and 1944 and between 1945 and 1954 [23].
The research on equity in education started a little later in China and can be categorized in three periods: theoretical foundation, technological development, and human-centeredness (Figure 1). The theoretical foundation period (i.e., after the 1990s) focused mainly on issues of equity and efficiency, with theories and policies discussed from the perspective of sociological and educational studies. Most scholars tended to oppose educational equity and educational efficiency, as it was difficult to satisfy equity when satisfying educational efficiency [24], with most scholars believing that educational development should be based on the priority of efficiency, taking into account equity. A large number of theoretical discussions and educational policy studies in this period established the foundation for the later geospatial studies on educational equity.
In the 21st century, the study of educational equity entered a period of technological development, with scholars introducing concepts such as spatial equity and accessibility, using geographic information systems (GIS) and other related technological tools [25] to measure educational equity and explore the factors influencing educational equity. As a result, a large number of geographic educational policy studies have been accumulated. Researchers from different disciplinary backgrounds have emphasized the value of studying educational equity from a spatial perspective [26,27,28]. Advances in the use of GIS have also facilitated research in this area. During this period, scholars have focused on two main aspects of educational equity; some scholars have focused on sociodemographic attributes (e.g., age, gender, ethnicity, and income) to examine the equity of residents’ access to public service resources [29,30,31,32], whereas others have analyzed the location and spatial optimization of facilities in terms of spatial accessibility [33,34,35]. The research perspective in this period changed from macro to micro based on 20th-century research, yielding partially quantitative findings and many innovations in research methodology [36,37,38]. Hashem Dadashpoor took a different approach from that of traditional research, attempting to study the spatial inequity measurement (SIM), a comprehensive model of spatial inequality, and exploring the factors that contribute to inequality in public service facilities [36]. According to the SIM model, the study of facility equity is not confined solely to the exploration of geospatial equity but also examines the human perspective, paying special attention to the inequality caused by the mismatch between population needs (demand) and the population currently supported by educational facilities. This approach combines geospatial equity with equity caused by human needs. Wang Fahui et al. conducted a pioneering study on facility equity and proposed the maximal accessibility equality problem (MAEP). This original model includes not only human needs and spatial accessibility but also considers facility supply on the basis of existing research. This model is more sophisticated than Hashem Dadashpoor’s SIM model.
The people-centered period began in the 20th century and has grown gradually as society has developed. The most important factor that needs to be explored in China at present is the equity of county educational facilities based on current needs. Research on the evaluation of the equity of county education is still at a relatively young stage, and this research on the equity of county educational facilities is focused mainly on the period of construction or theoretical feasibility. Many areas require further research, including the following:
The method of selecting evaluation indicators needs to be optimized. Traditional methods of evaluating equity in education usually select the method of extreme difference, variance and standard deviation, and Gini coefficient or establish mathematical models by selecting indicators at all levels and assigning appropriate weights [39]. However, these research methods all have drawbacks to varying extents. Some scholars take the weights of indicators too subjectively, which often leads to the incomparability of the results of indicator measurements. Additionally, their fairness assessment results are detached from space and cannot provide effective guidance to optimize the spatial layout of educational facilities.
The impact of the geographical environment and regional differences on the assessment system is neglected. The shortcomings of China’s educational equity are in the rural and remote areas, and inequitable development between urban and rural areas is a common phenomenon [40]. At present, the allocation of educational resources and overall development of rural education in poor northwest China is unbalanced, which is the root cause of the current inequity in education in China. The assessment system for educational equity in northwest China should not be generalized from the assessment system for educational equity in counties in coastal areas. Literature on educational facilities in counties in the gully areas of the Loess Plateau is lacking. Differences in the equity of educational facilities in this particular geographical region are generally more prominent than in the plains.
3. Study Area and Data Source
3.1. Study Area
Chengcheng County is located in the northeastern part of the Weibei Plateau in Shaanxi Province, adjoining Dali County to the south, bordering Huanglong County to the north, and 186 km from the provincial capital, Xi’an, to the southwest (Figure 2), which is a typical Loess Plateau gully area in Shaanxi Province. The county features three types of landforms, as shown in Figure 3, including low hill areas, loess terrace areas, and loess gullies, which divide the county into “three beams and one plateau”. The Loess Plateau is flat, with a good living environment and a concentration of quality educational facilities, whereas the villages on the beam side are either narrow or steep, with poor external transportation options and lagging village development. These areas have also experienced the most serious population loss. At present, Chengcheng County is still in a period of rapid urbanization, and the characteristics of the rural population gathering in the county are obvious.
3.2. Data Sources
The data on educational facilities come from the education authorities. By the end of 2020, there were 113 primary and secondary schools and kindergartens in the county (9 teaching points under the jurisdiction of the county), including 79 kindergartens, 11 complete primary schools, 11 nine-year schools, 7 junior high schools, and 2 senior high schools. We obtained the spatial information on residential areas and road networks used in the study through spatial big data and field research. Population data were obtained from the seventh census.
4. Methodology
4.1. Construction of an Analytical Framework to Evaluate the Equity of Educational Facilities in Counties
Based on the description of the connotation of educational equity, it is clear that the concept is limited in the extent to which educational resources are spatially distributed in regions in an equal manner [39], as well as the ease of access to educational facilities and equity in terms of access to high-quality educational services. Therefore, we constructed a county-level educational equity framework based on the characteristics of the Loess Plateau ravine region from three dimensions: resource equity, spatial justice, and educational quality equity. The analysis framework was constructed based on the geographical characteristics of the Loess Plateau ravine area (Figure 4). This framework uses the kernel density analysis of supply and demand to illustrate the resource equity of education in the county, measuring the balance between population demand and facility supply on different lands. It uses spatial accessibility to indicate the ease of access to educational facilities by residents in different regions and constructs an evaluation system of education quality equity that includes education-scale and teacher–student ratio indicators to measure the quality of education at different facility sites and to illustrate the spatial differences in education quality. To reflect the equity of county educational facilities in a comprehensive manner, the results of these three dimensions are combined using the modified MEAP model, and the equity of county educational facilities is analyzed through a comprehensive equity index.
4.2. Methodology to Evaluate the Equity of Resources for Educational Facilities
We selected the kernel density analysis method to calculate the kernel density values for the supply and demand of educational facilities. This nonparametric estimation spatial analysis method calculates the density of elements in surrounding neighborhoods [41]. The aggregation data are calculated and estimated through sample data to enable exploration of the distribution of element points in the spatial region. The characteristics of change can reflect the degree of aggregation of element points according to the following formula:
(1)
where k() is the kernel function, h > 0 is the bandwidth, and − is the distance from the estimated point () to the sample ().The demand power of residents for educational facilities is calculated as follows:
(2)
where Di (i = 1, 2, 3,……) is the demand for educational facilities per site; R is the total population; Am is the total residential land area; P is the plot ratio, mi (i = 1, 2, 3……) is the area of each site; and n is the proportion of school-aged children according to statistics for kindergarten (n = 4.93%), primary school (n = 5.62%), and junior high school (n = 5.04%).The supply capacity of educational facilities (Q) is expressed as follows:
(3)
The correction factor (α) is related to the basic characteristics of educational facilities in the county. For example, the educational facilities in the central city of the county always have a school-aged population that is larger than the normative carrying capacity when α = 1.5; alternatively, the lower the value of α, when α = 0.5 in some remote areas.
Formulae (2) and (3) can be substituted into the calculation to obtain the supply kernel density and demand kernel density, respectively. That is to say, we can see the spatial distribution of the elements of supply and demand.
4.3. Spatial Equity Evaluation Method for Educational Facilities
We used raster cost analysis to calculate accessibility to evaluate the spatial equity of facilities. Accessibility is generally defined as the ease of reaching a destination from any point in space, reflecting the spatial resistance that people overcome in the process of reaching the destination [42]. On the basis of the data from three surveys and drawing on existing methods [43], the county’s topography was superimposed, and a weighted average was used to simulate the spatial accessibility of the educational facilities under study by calculating the time cost of reaching the educational facilities in the county from any point. Figure 5 shows the raster cost image obtained by overlaying the topography of the county and the actual situation of the people in the county.
4.4. Evaluation Methods for Equity in Education Quality
After evaluating resource equity and spatial equity, we evaluated equity in education quality. Education quality is refined according to three aspects: education scale, educational facility configuration, and spatial suitability of educational facilities. We used the analytic hierarchy process (AHP)–entropy weighting method [7] to determine the indicators and evaluated educational facility quality according to these three aspects. We then analyzed the evaluation results of education quality in terms of spatial equity. The scale of education includes indicators such as the student–teacher ratio and the number of students; the configuration of educational facilities includes indicators such as the average floor space per student; and the spatial suitability of educational facilities includes the land expansion degree of the educational land area (as shown in Table 1).
4.5. Comprehensive Evaluation Method for the Equity of Educational Facilities in the County
After single-factor evaluation, we improved the MEAP model [36] by adding equity in education quality to the original model’s evaluation of equity in resources and equity in space. We also added an evaluation of the quality of education to the original model. High-quality educational resources are attractive to citizens and affect demand to a certain extent; within a certain range, the better the quality of facilities, the higher the demand for education. Thus, the improved objective function is expressed as follows:
(4)
where Di is the amount of demand at demand point i (Formula (2)), Ai is the accessibility of demand point i, Mi is the facility quality value, and a is the weighted average of the accessibility of each demand point across the study area. The improved model combines resource equity, spatial equity, and distributional equity of facility quality to obtain the facility equity value for the entire county.5. Results
5.1. Evaluation of the Equity of Education Resources in the County
According to Formula (2), we evaluated the fairness of the distribution of educational resources using the supply-and-demand kernel density. We visualized the spatial distribution of supply and demand with the help of GIS and divided it into five levels according to the Jencks natural break method (i.e., very low, low, medium, high, and very high), as shown in Figure 6 and Figure 7.
As shown in Figure 7, quantitatively speaking, the supply-and-demand conflict for educational facilities within the county is concentrated primarily in the center of the county town (“too much demand for the supply to meet”), but the remaining towns show a large outflow of educational demand and a mismatch between the existing supply of educational facilities. Specifically, the overall demand for kindergartens is large, with a supply shortage manifesting within the county, except for about 65.4% of the demand for kindergartens, which is distributed in villages outside the county, with 40% of the villages showing a lack of kindergarten supply. Additionally, 92.8% of the demand for primary schools is concentrated in the county, with about 13,946 students, although the current supply in the county can serve only one-third of the demand. The demand for junior high schools is concentrated almost entirely in the county towns. Supply facilities are set up according to the towns, and other than the county towns, more than 70% of junior high schools have vacant facilities, showing that supply is greater than demand.
Spatially (Figure 6), the supply of educational facilities in the county is distributed in a decreasing pattern of “county center–town center–village”—that is, supply is most abundant in the county center, followed by the town center, and supply is lowest in the village. This gap between county centers and villages is increasing. According to the conversion statistics shown in Figure 6, 79.2% of the educational needs of the towns in the county can be met, 62.1% of the educational needs of the villages cannot be met in the rural areas, and a large difference exists between the supply and demand in the urban and rural areas, as many rural students can go only to the county centers.
For example, the demand for kindergartens is distributed mostly in the countryside, but kindergartens are allocated on a town-by-town basis, with few kindergartens located in the countryside and most concentrated in urban areas.
5.2. Evaluation of the Spatial Equity of Educational Facilities
Through a raster cost weighting analysis and GIS visualization, we analyzed the differences and characteristics of the spatial equity of each educational facility according to the following classification: best accessibility, good accessibility, average accessibility, poor accessibility, and worst accessibility.
Figure 8 shows the three types of terrain in Chengcheng County: gully areas, low mountain hilly areas, and Loess Plateau areas. Loess Plateau areas are terraced plateaus covered by loess, which are loess high terrace plains with a stepped distribution along both sides of the river suitable for construction with good transportation conditions; low mountain hilly areas have the second-best construction conditions; and gully areas have rugged landscapes that are not conducive to agricultural production, with low population concentration, making construction difficult. The accessibility of the county is influenced by the landscape, with obvious geographical differences, and the overall accessibility shows a decreasing pattern of “Loess Plateau area > low hill area > ravine area”.
According to this evaluation, 98.7% of kindergartens, 96.1% of primary schools, and 87% of junior high schools are located in the Loess Plateau area. (Figure 9).
The accessibility of kindergartens in the Loess Plateau area is good, covering more than 82% of the inhabited villages. In contrast, the accessibility of kindergartens in the ravine area is poor, owing to the narrow terrain and the difficulty in building kindergartens, with an average distance to villages in this area of 705.4 m, which is three times the average distance to kindergartens in the county. Accessibility of kindergartens in the low hill area is better than that in the ravine area and second to that in the Loess Plateau area, as it is located in the northern part of the county and has higher terrain. The accessibility of primary schools in the Loess Plateau area is classified as the “average accessibility” of the county, with the nearest distance to school being 495.68 m. The gully area in the western part of the county (Anli town and Yaotou town) is the area with the worst accessibility to primary schools, with the farthest distance to primary schools being 6 km and the average distance to primary schools in the gully area being more than 10 times the average distance to schools in the Loess Plateau area. The average distance to primary school in the gully area is more than 10 times the average distance to schools in the plateau area. The distance to junior secondary schools in the gully area is more than 10 km. Junior secondary schools in the low hills in the north poorly accessible for from the plateau area, owing to the high elevation, whereas the plateau area in the south (Weizhuang and Sizian towns) is divided by the plateau area in the center of the county by gullies, resulting in poor access to educational facilities in the north and south.
5.3. Equity Evaluation of the Quality of Educational Facilities
The results of the comprehensive evaluation of several aspects of educational facilities, including indicators of scale, educational guidance, and spatial suitability indicators, are shown in Figure 10.
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The abundance of educational resources in the county decreases in a gradual manner from the county center to the town center to the village.
Indicative of educational scale (number of classes, student–teacher ratio, and average number of students) measure the abundance of educational resources. The most abundant educational resources are found in the central city, followed by the town centers, such as Feng Yuan. There is a large difference in the richness of educational resources between the county town and the countryside. The indicative indicator for primary school education in the central city averages 24.8 points, whereas the average town averages 8.78 points, and the average village score is only 1.97. The richness of educational resources in kindergartens and junior high schools in the central city is three to eight times greater than that in the average town and village. The average number of kindergarten and junior high school teachers in the county is four to five times that of town and village teachers, and the average number of county teachers in primary schools is five to six times that of town and village teachers. The amount of funds available for running schools in towns and villages differs considerably from the limited educational resources in the county.
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The spatial quality of educational facilities in county towns is poor, and educational facilities are spatially constrained; the spatial scale of educational facilities in townships is large, but the size of the student population is insufficient.
Guiding indicators of education allocation can be used to measure the physical spatial quality of educational facilities (e.g., average student floor space, average student floor area, average student sports halls, and average student outdoor activity space). The guiding indicators are low, and the spatial quality is poor due to the limited land area, large student population size, and small per-pupil floor area of the county’s educational facilities. These educational facilities are spatially confined and crowded and will soon reach capacity limit. As shown in Figure 9 and Figure 10, the guiding index score for kindergarten education in the central city is 1.53, the average guiding index score for primary school education is less than 1/50th of the average score for townships, and the average score for junior high schools is less than half of the average score for townships. This result shows that the spatial quality of educational facilities needs to be improved relative to the highest level of educational resources available in the central city. In contrast, the townships generally have higher configuration guiding indicators but smaller student populations. Junior secondary schools are located primarily in towns. Kindergartens have an average of 208.46 m2 of floor space per pupil, but the average number of pupils is 15, with the smallest classes having only three pupils. Primary schools have an average student area of 30 times the number of urban primary schools, and the average number of students is one-fifth that of the number of urban students.
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Land for educational facilities is more open in the Loess Plateau area of the county, and the educational needs of this area are more easily met.
As shown in Figure 8, the spatial suitability of educational facilities in the county coincides with the county landscape map (i.e., those with higher spatial suitability are all Loess Plateau areas within the county). Spatial suitability is related to the degree of expansion of educational facility sites and the degree of satisfaction of the schooling needs of migrant children on the streets—that is, the more open the site and the higher the degree of satisfaction of the needs of migrant children, the higher the degree of spatial suitability. In terms of spatial openness, the Loess Plateau area of the county is more spatially suitable, as it is easy to expand educational facilities. Regarding the extent to which the schooling needs of migrant children on the streets are met, most of the needs of migrant children in the central city can be met; thus, the spatial suitability of the central city is also higher. In terms of the single indicator of educational self-sufficiency coefficient (i.e., whether educational facilities can meet the schooling needs of street migrant children), a larger number of migrant street children live within the county, and about 72.3% of these children attend educational facilities in the central city. Most of the needs of migrant children in the central city can be met.
Overall, it appears that the quality of education in Chengcheng County is less equitable. First, we found large differences between urban and rural areas, with the county having the best quality and highest abundance of educational resources and the general rural education resources differing significantly. Second, the space available for educational facilities in urban areas is limited, and educational facilities tend to be saturated; facilities within townships have significant vacancies, with about 39.6% of rural primary schools and teaching points currently having fewer than five students. Third, the expansion of land for educational facilities in the Loess Plateau area of the county is higher, and mobile educational needs are more likely to be met (Figure 11).
5.4. Comprehensive Analysis of Equity in Educational Facilities
We used the improved MEAP model to calculate the equity index of educational facilities in the county and to judge the comprehensive fairness of the facilities (Figure 12). Combined with the results of the previous single-factor analysis, the results showed that the fairness of various types of educational facilities in the county underperformed, but the main influencing factors leading to the inequity of each type of facility varied.
The inequity of kindergartens was found to have the highest correlation with supply and demand, with a moderate linear correlation; the total supply of kindergartens can basically meet the demand, but the degree of supply and demand between urban and rural areas varies significantly. Primary school inequity covers about 38.4% of the county area, with this problem of inequity being the most prominent. This inequity is the result of the combined effect of accessibility and the quality of educational facilities. It is more difficult to meet the accessibility needs of villages and towns located in ravine areas, whereas high-quality primary education resources are located in the center of the county, and the quality of education differs considerably from that of towns and villages. The very inequitable category of junior secondary schools accounts for 15.3% of the county area, and its inequity is tied primarily to educational quality (Figure 13).
It is evident that the higher the grade level in the county, the higher the demand for education quality. The decision-making process of rural households is shifting from wanting to maximize economic returns to wanting to maximize comprehensive returns, with education at the core. Increasingly, households are accompanying students to access quality educational facilities.
6. Conclusions
Taking Chengcheng County, a typical Loess Plateau ravine county in Shaanxi, as an example, we constructed a framework to evaluate the equity of educational facilities applicable to the county. The framework is based on natural geographical conditions, incorporates the people’s needs in the current situation in China, adds the equity of educational facilities quality from the perspective of historical educational equity, and individually examines the educational facilities. The three aspects of resource equity, spatial equity, and quality equity of educational facilities were analyzed to explore the factors affecting the inequity of educational facilities in the county. The results show the following:
At present, inequity in the supply and demand of educational facilities in the county is not due to a lack of supply but a supply–demand mismatch in educational facilities. This mismatch is caused by the fact that the urbanization of education is not synchronized with the urbanization of the population in the county. The urbanization of the county has led to more employment opportunities in the central city than in the surrounding areas, with some rural families having parents working in the county’s urban areas and students attending schools nearby. Additionally, driven by education, many rural families have migrated to the central city to accompany their students in pursuit of better education services and facilities. With population growth in the central urban areas of the county, the demand for education has grown; in particular, the demand for quality education has increased sharply, and shortages in quality education facilities and weak schools coexists in the county.
Owing to the geographical environment, the accessibility of educational facilities in the Loess Plateau areas of Chengcheng County is generally good, whereas the accessibility of the ravine areas is poor. Communication within the gully areas is hindered due to difficulties associated with traffic construction as a direct result of the geomorphology. The gully areas also have limited resources to build educational facilities as a result of slow economic development and limited funds for ecological and geographical reasons.
With ongoing development, demand for quality educational facilities has increased sharply, with kindergartens often being located in proximity to primary and junior high schools. People want quality educational facilities, and a phenomenon of school choice is evident in the region. In contrast to the limited quantity of educational facilities, the uneven spatial distribution of the quality of educational facilities is a bigger problem.
In this study, we analyzed three factors that affect the equity of educational facilities: supply and demand, accessibility, and the balanced distribution of educational facilities. However, this study is subject to some limitations, so only preliminary conclusions have been drawn. The causes of inequitable educational facilities in the county are not the same, but a process to explore the specific causes is lacking. Therefore, the combination of a questionnaire survey and spatial analysis, sociological and spatial geography, and spatial changes in students’ school choice behavior, along with county urbanization, should be explored further.
Formal analysis, Q.N.; Investigation, Q.N.; Methodology, Q.N. and P.C.; Software, Q.N.; Supervision, P.C.; Validation, Q.N.; Visualization, Q.N.; Writing—original draft, Q.N.; Writing—review & editing, X.W. and P.C. All authors have read and agreed to the published version of the manuscript.
Not applicable.
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Data is contained within the article.
The authors declare no conflict of interest.
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Enlarge this image.Figure 1. Map of the development of research on equity in education in China.
Enlarge this image.Figure 2. Study area and distribution of educational facilities in Chengcheng County.
Enlarge this image.Figure 3. Topographical map of Chengcheng County.
Enlarge this image.Figure 4. Research framework.
Enlarge this image.Figure 5. Integrated transport time cost raster map.
Enlarge this image.Figure 6. Comparative demand–supply analysis of educational facilities in Chengcheng County.
Enlarge this image.Figure 7. Supply–demand analysis of educational facilities by town.
Enlarge this image.Figure 7. Supply–demand analysis of educational facilities by town.
Enlarge this image.Figure 8. Topography and population map of Chengcheng County.
Enlarge this image.Figure 9. Analysis of the accessibility of educational facilities in the county of Chengcheng.
Enlarge this image.Figure 10. Equity evaluation of the quality of educational facilities.
Enlarge this image.Figure 11. Quality analysis of educational facilities in Chengcheng County.
Enlarge this image.Figure 11. Quality analysis of educational facilities in Chengcheng County.
Enlarge this image.Figure 12. Comprehensive analysis of equity in education facilities in the county.
Enlarge this image.Figure 13. Analysis of the correlation between equity and various factors.
Evaluation index system of the distributed level of educational facilities.
| Target Level | Guideline Level | Indicator Layer | Physical Meaning | Total Weighting |
|---|---|---|---|---|
| Indicators of the scale of education | Number of classes | Reflects the size of the educational facilities | 0.2571 | |
| Average number of students in a class | Reflects the size of the educational facilities | 0.2571 | ||
| Student–teacher ratio | Reflects the size of the teacher resources | 0.0857 | ||
| Guiding indicators for the allocation of educational facilities | Floor space per student | Reflects the degree of crowding in the internal space of the educational facility | 0.1145 | |
| Average floor area per student | Reflects the degree of crowding in the internal space of the educational facility | 0.0887 | ||
| Average student sports hall area | Average of sports fields per person | 0.0508 | ||
| Outdoor area per student | Reflects the level of congestion in outdoor spaces in educational facilities | 0.046 | ||
| Spatial suitability indicators for educational facilities | Land expansion | Site suitability | 0.005 | |
| Educational self-sufficiency index | The extent to which the school’s street meets the schooling needs of migrant children | 0.005 |
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