On equalization of fundamental education in Tibet: a case study on the trend of conditions of primary and middle schools running

Abstract

Based on public data such as the Educational Statistics Yearbook and the National Statistics Yearbook, this paper analyzes the equalization trend of fundamental education in the Tibet Autonomous Region (hereinafter referred to as Tibet), China, using data on running conditions in primary and middle schools in Tibet from 2013 to 2020, and carries out clustering of the rankings of data from China in 2020. The results show that the equalization level of primary and middle education in Tibet has continuously improved from 2013 to 2020. This is evidenced by the increases and improvements in education funding per student, student-teacher ratios, numbers and academic qualifications of teachers, per capita teaching areas and per capita teaching assets. In 2020, the per student education fee in Tibet took the lead in China’s 31 provincial regions, and the student-teacher ratio was close to the national average. Running conditions in primary and middle schools in Tibet still require improvement. This is reflected in the low proportion of full-time teaching staff in primary and middle schools, lack of teachers with senior professional titles in middle schools, area of auxiliary teaching facilities (laboratories, computer rooms, gymnasiums, etc.) in middle schools, and especially in high schools, and shortage of teaching assets (books, computers, multimedia classrooms) in middle schools.

Introduction

As equalization of fundamental public education is a goal pursued by all nations, research on equalization has always been of interest to foreign scholars. According to James Coleman, equality in education includes equality of opportunity, equality of process, equality of results and equality in the impact of education on life (Coleman 1983). Anderson believes that education equality involves: firstly, providing equal education for everyone; secondly, allowing students to reach a unified standard through school education; thirdly, everyone enjoying equal opportunity to realize their potential; and fourthly, provision of opportunities for people to continue their education until their learning conforms to the norms (Anderson 2008). For the OECD, education equality involves fairness and inclusiveness, ensuring that individuals of different genders, status and races receive the basic minimal standard of fair education in different social environments.¹

In research on the equalization of public fundamental education, Chinese scholars have paid more attention to the scale and quality of education. They believe that time and space differences must be considered when formulating policies. For example, fundamental education in different regions within a country is developed in a balanced way, and citizens can benefit from essentially the same educational conditions and quality (Shi and Li 2018). The equalization of compulsory education has been gradual, and since differences between urban and rural areas, regions and schools exist, we should strive for “bottom line equality” of citizens’ compulsory education (Mo 2010). To truly realize equalization of fundamental public education, we should make adjustments when formulating policies in specific times and spaces, and consider actual situations and differences between regions (Lou 2013).

In order to evaluate the equalization of fundamental public education, the World Education Report issued by UNESCO in 2000 proposed a set of five indicators: education supply (funds, human resources), education demand, enrollment/participation, internal performance of education and education output. The OECD proposed the CIPP model, involving context, input, process and products. In 2006, the World Bank issued the Education Development Monitoring System, consisting of education input, education and teaching, education efficiency, education completion and output. Based on China’s basic national conditions, domestic scholars have generally established an education evaluation indicator system from the perspectives of education supply, enrollment and participation, and education output of the UNESCO evaluation system. Specific indicators include teaching area, education funding, teaching assets, student-teacher ratio, teacher education, and enrollment rate. The UNESCO education equalization evaluation system and its relationship with the indicators commonly used by Chinese scholars, as well as those used in this paper, are shown in Table 1. It can be seen that the indicators studied in this paper belong to the education supply category of the UNESCO system.

Table 1 UNESCO evaluation system and its frequently used indicators in domestic evaluation systems

China’s fundamental public education includes pre-school education, compulsory education, high school education, secondary vocational education, special education, continuing education and other public education fields. Each of these is characterized by commonality, inclusivity and fundamentality. As a part of public fundamental education, different views on fundamental education and its connotations exist within the academic community. Nevertheless, the fundamental education mentioned in this paper indicates 9 years of compulsory education plus 3 years of high school education.

As a part of the education evaluation system, “school running conditions” generally refers to areas of various buildings, numbers and qualifications of school staff, teaching assets and values, education funding and so on. They are important prerequisites for achieving equalization of fundamental education, especially in economically backward, rural and remote areas. According to the annual education statistical data published by the Ministry of Education, school running conditions are classified into three categories. The first category is the floor area, including school buildings, teaching (classrooms) and auxiliary facilities (laboratories, libraries, computer rooms, gymnasiums and language labs), administrative rooms (offices, etc.), and living accommodation (teacher dormitories, student dormitories, canteens, bathrooms, etc.). The second category is the amount of assets, including books, computers, and multimedia classrooms. The third category is the total value of fixed assets. However, these belong to the “hardware” category of school running conditions. This paper chooses the indicators of areas of teaching and auxiliary facilities and quantity of assets. In addition, this paper introduced the indicators of “software”, and “funds” are introduced to the school running conditions. The “software” refers to indicators related to STR, including composition of school staff, professional titles, academic qualifications of teachers and education funding.

Using different research methods and data sources, some domestic scholars have studied the equalization of fundamental education in China. According to Lyu, education funding, the urban and rural “dual economy” pattern and the service level of the government are key factors affecting the equalization of education (Lyu and Liu 2010). Xiong and others believe that the main reason for the low level of equalization of fundamental education in Tibet is the difference in economic development levels and education investment between Tibet and the rest of China. The difference in the level of equalization of fundamental education within Tibet is caused by differences in fiscal revenue and expenditure, geographical environment and climate, and educational disparities between urban and rural areas (Xiong and Kai 2012). In order to further promote the equalization of compulsory education in China’s western region, Huang suggests that local “standards for the modernization of compulsory education schools” should be formulated, and that teacher exchange mechanisms should be established to ensure quality of “software and hardware” for compulsory education in relatively poor areas (Huang and Zhao 2014). Wang found that although the central government’s investment in public education services in Tibet was far higher than the national average, the quality of public education services in Tibet still lagged far behind the central and eastern provinces. The development of fundamental education was unbalanced, and the efficiency of capital utilization had to be improved (Wang and Yang 2017). Lan divides the evaluation indicators of national fundamental education services (preschool education, kindergarten, primary school, middle school and technical secondary school) into three levels, ranking the first level indicators (financial input, facility allocation, teacher input and service effectiveness) of 31 provincial regions in China from 2013 to 2017. On an annual basis, Tibet ranked 13th, 12th, 18th, 9th and 9th respectively, showing an overall trend of improvement. In 2017, Tibet ranked second for funding, 15th for facility allocation and teacher investment, and 31st for service effectiveness. The results of clustering education service efficiency show that Tibet is a region with high investment yet low efficiency, mainly caused by the backward indicators of years of education per capita and the proportion of illiterate persons (Lan 2020). Based on data from 290 prefecture level cities in China from 2003 to 2018, Chen’s research found a strong correlation between fundamental public education and economic development. As an important indicator of promoting fundamental public education, the SHUANGJI (“two bases”) program (essentially implementing a nine-year compulsory education and essentially eliminating illiteracy among young and middle-aged people) could help increase the economic growth rate of the western region by 0.997% (Chen and Wang 2021).

Quantitative research on school running conditions in China can be divided into two categories. The first category uses factor analysis to condense information on school running conditions into several common factors according to their relevance, allowing us to focus our research on the main factors. For example, Yang and others believe that the level of school running conditions in rural primary and middle schools can be condensed into three factors: modernized teaching resources, school buildings and school land coverage (Yang and Qin 2020). Zhao and others reduced the dimensions of school running conditions to three factors: fundamental education teaching resources, knowledge expansion teaching resources and modern technology teaching resources (Zhao et al. 2022). Through dimension reduction, Liu obtained three main public factors: the internal factor, the funding factor and the high-level teacher factor (Liu 2021). The second category ranks the importance of school running conditions based on the analytic hierarchy process (AHP). For example, the research of Wang and Zhao found that the educational backgrounds of teachers were the most important indicators in school running conditions in compulsory education, followed by STR, professional experimental equipment and book collection (Wang and Zhao 2011). In this paper, the method of constructing a time domain graph is applied to study the trend of school running conditions for the first time. This can not only reveal its trend of short-term qualitative change, but also predict its range of short-term quantitative change, thus providing guidance for decision-making. Curve fitting is based on the strict use of statistical tools, and the results are highly reliable.

Analysis methodology

Curve fitting involves constructing statistics to test the autocorrelation of sequences. We have used the significance indexes of Analysis of Variance (ANOVA) and the normal distribution of residuals to judge the autocorrelation and curve fitting effect. R² is taken as the standard for selecting the fitting curve.² We applied SPSS to fit curves for school running conditions in primary and middle schools in Tibet from 2013 to 2020 based on time domain. The fitted linear, quadratic, cubic, exponential and other forms of curves represent various trends and variations. The Ljung-Box statistics of all successfully fitted curves in this paper are less than 0.05 when the order is less than 2, the sig. detected by ANOVA and the sig. of curve regression coefficient are less than 0.05, the probability distribution on the P-P diagram of residuals presents an approximate straight line and R² reaches more than 0.8. These test values prove that the constructed curve is statistically significant with 95% confidence. It can be used to study the current trend of school running conditions and predict their short-term changes.

Clustering is a process of classifying numerical data into a specified number of groups according to similarity, with the criterion of similarity being the distance between values. Objects in the same group have high similarity, while objects in different groups have great differences. In this paper, the systematic clustering algorithm of SPSS is used to cluster the data of school running conditions of primary and middle schools in 31 provincial regions in China in 2020, so as to determine the ranking of Tibet. There are three categories of classification. After the final iterative calculation, a category center is obtained for each category, and the region closest to the category center value (squared Euclidean distance) of a category is classified into this category.

Results and discussion

This paper studies the changing trend (from 2013 to 2020) and current status (2020) of conditions of primary and middle schools running in Tibet. The data used in the paper is taken from official resources such as the National Statistical Yearbook,³ the Ministry of Education Statistics⁴and the Educational Statistics Yearbook.⁵ Based on the above data, this paper uses the statistical tool of SPSS to fit the historical trend map of various running conditions in primary and middle schools in Tibet, conducts a cluster analysis of the school running conditions in 31 provincial regions of China in 2020, and analyzes the positioning of different groups in 31 provincial regions.

Low STR means that teachers are adequate in schools. Figure 1 demonstrates that the STR of primary and middle schools showed a rapid decline from 2013 to 2015 before becoming stabilized, and the variation range in primary schools was greater than that in middle schools.

Fig. 1

STR in Tibet (2013-2020)

In 2020, the average STRs of senior high schools were 12.9 for China and 12.34 for Tibet. The STR of Tibet was far from the lowest (Beijing’s was 7.62 and Shanghai’s was 8.74). Among the eight ethnic minority provincial regions, only Qinghai, Xinjiang and Inner Mongolia had STRs lower than the national average. The average STR of junior high schools was 12.73 for China and 11.55 for Tibet. The STR of Tibet was far from the lowest (Beijing’s was 8.68). The average STR of primary schools was 19.18 for China and 14.62 for Tibet. Among the eight ethnic minority provinces and regions, Tibet ranked first.

With the development of primary and middle school education and the increase in students enrolled in Tibet, the total number of school staff increased accordingly. However, the changing trend of different types of school staff (teachers, administrative personnel, teaching assistants and service staff) was different. As shown in Fig. 2, in middle schools, the number of teachers showed a mild linear increase, the number of teaching assistants showed a steep linear increase, and the number of service staff showed a steep linear decrease. In primary schools, the number of teachers showed a linear rise, and the number of service staff showed a quadratic polynomial decline: a steep decline in the initial stage and a slow decline after 2017.

Fig. 2

Number of school staff (2013-2020) (Left) Middle school (Right) Primary school

We conducted SPSS clustering (three categories) according to the proportion of teachers making up all school staff. The results are shown in Tables 2 and 3.

Table 2 Proportion of teachers making up all school staff in 2020 (middle school)

Table 3 Proportion of teachers making up all school staff in 2020 (primary school)

The high proportion of teachers in schools means that the proportion of administrative personnel, teaching assistants and service staff was low. The lack of service and support personnel also means that teachers had to undertake more additional work and a heavier burden.

Table 2 shows that in 2020, the proportion of middle school teachers in Tibet was 97%, the highest in China. This was far from the national average of 89%, the proportion of 79% in Beijing and that of 83% in Shanghai.

Table 3 shows that in 2020, the proportion of primary school teachers in Tibet was 99%, the highest in the country, which was far from the national average of 94%. In terms of the whole country, the regions with low proportions of teachers were Inner Mongolia, Xinjiang and Northeast China. Generally, the proportion of teachers in primary and middle schools in Tibet was irrationally high, which may have affected school operation and teaching quality.

For teachers in Tibet, Fig. 3 shows an increase in those with high academic qualifications and a decrease in those with low academic qualifications. In terms of the number of teachers in senior high schools, there was a linear increase in graduate and undergraduate qualifications, and no significant change for college qualifications. In junior high schools, in terms of the number of teachers, there was a linear increase in those with graduate and undergraduate qualifications, a linear decrease in those with junior college qualifications, and no evident change in those with senior high school qualifications. In primary schools, in terms of the number of teachers, there was a linear increase in those with undergraduate qualifications, a steep decrease in those with senior high school qualifications, a slight increase in those with graduate qualifications, and an initial decrease and then stabilization in those with college qualifications.

Fig. 3

Teachers with different academic qualifications between 2013 and 2020

(Left) Senior high school (Middle) Junior high school (Right) Primary school

Note: The number of undergraduate qualifications is 1/10 of the actual number

To measure the distribution of teachers’ professional titles, we have used the ratios of the number of teachers with intermediate and primary professional titles to the number of teachers with senior professional titles. The low ratio means that the proportion of intermediate and primary teachers was low and the proportion of teachers with senior professional titles was relatively high. The ratios of professional titles of teachers in Tibet (senior high school, junior high school and primary school) in 2020 are shown in Tables 4, 5 and 6.

Table 4 Ratio of professional titles of teachers (senior high school)

Table 5 Ratio of professional titles of teachers (junior high school)

Table 6 Ratio of professional titles of teachers (primary school)

Table 4 shows that the national average ratios of intermediate/senior and primary/senior were 1.31 and 1.33, while those of Tibet were 2.40 and 3.16, the highest in the country. Tibet was the only region in the first category, demonstrating large gaps with Beijing (0.76 and 0.74) and Shanghai (1.42 and 0.93). Therefore, in terms of teacher resources for running conditions of senior high schools, teachers with senior professional titles were very scarce in Tibet.

Table 5 shows that the national average ratios of intermediate/senior and primary/senior were 1.94 and 1.97, while Tibet showed high ratios of 3.44 and 4.82, belonging to the first category alongside Shanxi and Shanghai. Therefore, in terms of teacher resources for junior high schools, teachers with senior professional titles were also scarce in Tibet.

Table 6 shows that the national average ratios of intermediate/senior and primary/senior were 5.0 and 2.87, while those of Tibet were 3.19 and 3.23. This indicates that Tibet’s proportion of senior professional titles was higher than the national average, while its proportion of intermediate professional titles was slightly lower than the national average. To summarize, in terms of teacher qualifications in primary schools, there was no shortage of teachers with senior professional titles in Tibet.

Figure 4 demonstrates that classroom areas in senior high schools decreased from 2013 to 2016, before showing a rapid upward trend after 2017, while the classroom area of junior high school and primary school showed a linear increase from 2013 to 2020. However, the rising slope for primary schools was steeper, indicating a faster rise.

Fig. 4

Areas of classrooms (2013-2020)

(Left) Senior high school (Middle) Junior high school (Right) Primary school

Figure 5 shows that from 2013 to 2020, the areas of laboratories and gymnasiums in senior high schools increased linearly, and the areas of computer rooms, libraries and language labs increased slightly. In the same period, the areas of laboratories in junior high schools increased linearly, the areas of gymnasiums increased exponentially, and the rest showed a slight increase. In the same period, the areas of laboratories, computer rooms and libraries in primary schools increased linearly, those of gymnasiums increased exponentially, and those of language labs rose slightly.

Fig. 5

Areas of auxiliary facilities (2013-2020)

(Left) Senior high school (Middle) Junior high school (Right) Primary school

The clustering results of all 31 regions according to the school building area per student, the teaching (classroom) and auxiliary facilities (laboratory, library, computer room, language lab and gymnasium) area per student in 2020 are shown in Tables 7,8,9, 10 and 11.

Table 7 Clustering of construction area of school building and teaching & auxiliary facilities (senior high school)

Table 8 Clustering of six indicators (senior high school)

Table 9 Clustering of construction area of school building and teaching & auxiliary facilities (junior high school)

Table 10 Clustering of six indicators (junior high school)

Table 11 Clustering of construction area of school building and teaching & auxiliary facilities (primary school)

The national average construction area of school buildings per student and the area of teaching & auxiliary facilities per student are 24.1 and 8.8 square meters. As shown in Table 7, only Beijing belongs to the first category. Tibet (22.4 and 6.7 square meters) belongs to the third category, with its two indicators below the national average. The clustering of the six indicators of classroom, laboratory, library, computer room, language lab and gymnasium area per student in 31 regions are shown in Table 8. Beijing and Shanghai belong to the first category. Tibet is in the third category, meaning that its six indicators are below the national average.

The national average construction area of school buildings per student and the area of teaching and auxiliary facilities per student were 14.62 and 5.97 square meters, respectively. Table 9 shows that Tibet is in the second category, with two indicators of 18.39 and 5.34, which are at the national medium level. Table 10 shows that Tibet is in the third category, and its six indicators are below the national average. To summarize, the area of school buildings, teaching and auxiliary facilities per student in junior high schools in Tibet was at the national medium level.

In primary schools, the national average building area per student and the area of teaching and auxiliary buildings per student were 7.89 and 4.19 square meters, respectively. Table 11 shows that the building area per student in Tibet was 15.31 square meters. This was the highest in China, at close to twice the national average. The area of teaching and auxiliary facilities per student in Tibet was 5.1 square meters, ranking second. For both classroom area and gymnasium area per student, Tibet ranked third in the country. To summarize, Tibet led in area of school buildings, teaching areas and gymnasium areas per student in primary schools.

Figure 6 shows that from 2013 to 2020, all teaching assets of primary and middle schools increased linearly. Of these, computers increased the fastest, followed by multimedia classrooms, and books increased slowly.

Fig. 6

Teaching assets (2013-2020)

(Left) Senior high school (Middle) Junior high school (Right) Primary school

Note: The number of books is 1/1000 of the actual number

The clustering of teaching assets (books, computers and multi-media classrooms) per student in 31 regions in 2020 is shown in Tables 12, 13 and 14.

Table 12 Clustering of teaching assets per student (senior high school)

Table 13 Clustering of teaching assets per student (junior high school)

Table 14 Clustering of teaching assets per student (primary school)

On average, there were 41.16 books, 0.25 computers and 0.04 multimedia classrooms per student for senior high schools in China. Table 12 shows that only Beijing belonged to the first category, with its three indicators far higher than those in other regions. Tibet was in the third category, with its three indicators below the national average.

On average, there were 36.97 books, 0.19 computers and 0.03 multimedia classrooms per student for junior high schools in China. Table 13 shows that Tibet was in the third category, with three indicators of 26.12 books, 0.16 computers and 0.02 classrooms. These indicators were below the national average.

The average numbers of books, computers and multi-media classrooms per student in primary schools in China were 24.05, 0.14 and 0.03, respectively. In Tibet, these three indicators were 18.3, 0.17 and 0.02, respectively. Table 14 shows that Tibet was in the third category.

Figure 7 shows that from 2013 to 2020, education funding per student in Tibet increased continuously. It increased linearly in senior high schools and junior high schools, but increased faster in senior high schools. In primary schools it increased with logarithmic form, increasing rapidly in the early stage, and slowly after 2019. The clustering of national education funding per student in 2020 is shown in Table 15.

Fig. 7

Education funding per student in Tibet (2013-2020)

Table 15 Clustering of education funding per student (RMB)

In 2020, the national average education funding per student for primary schools, junior high schools and senior high schools was RMB 12,330, RMB 17,803 and RMB 18,671 (USD 1761, USD 2543 and USD 2667), respectively. In Tibet, these amounts were RMB 30,080, RMB 35,390 and RMB 42,357 (USD 4297, USD 5056 and USD 6051), respectively, reaching more than twice the national average. The education funds per student were among the top three provincial regions in the country, at the same level as municipalities as Beijing and Shanghai. It can hereby be concluded that a significant amount of public educational funds were invested in primary and middle education in Tibet, especially in primary education.

Conclusion

Between 2013 and 2020, with the support of policies and education funding from central and local governments, the equalization of fundamental education in Tibet was gradually advanced, and the conditions of schools running were continuously improved. This was reflected by the steady drop in the STR in primary and middle schools, the number of teachers and teaching assistants in primary and middle schools showing a linear upward trend, among which the number of teaching assistants in middle schools grew faster, and the number of teachers with higher education degrees, such as postgraduate and university degrees, showing a linear increase, while the number of low academic qualifications decreased. In particular, the number of primary school teachers with only high school education showed a sharp decline, indicating an improvement in teachers’ qualifications. Classroom area per student declined in high schools from 2013 to 2016 before showing a rapid upward trend after 2017. While it showed a linear increase in junior high schools and primary schools, it showed a faster growth rate in the latter. The area of teaching auxiliary facilities per student (laboratories, gymnasiums, computer rooms, libraries, and speech rooms) was on the rise, and the number of laboratories in high schools, junior middle schools, and primary schools rose faster. Teaching assets per student (computers, multimedia classrooms, books) demonstrated a linear upward trend, and the quantity and quality of teaching assets was greatly improved. The average public financial budget for education funding per student showed an overall upward trend. The growth rate of education funding in middle schools became faster in recent years. By 2020, the STR in primary and middle schools in Tibet was close to or lower than the national average, and the average education funding per student of primary and middle school in Tibet reached more than twice the national average, ranking in the top three among the 31 provincial regions in China. The above conclusions are consistent with Lan’s research, which found that in recent years Tibet has invested massively in fundamental education, and facilities and teachers have gradually improved (Lan 2020).

Due to the unique geographical and cultural environment of Tibet, as well as its harsh environment (high altitude, cold weather and remote distance), low population density, weak fundamental educational and lagging economy, in recent years, in order to support fundamental education in Tibet, the Chinese government has implemented many preferential policies other than high educational investment. At present, Tibet benefits from the following special education policies: priority funding support, the “three frees” (food, clothing and school supplies for primary and middle school students), establishment of boarding schools, dispatch of Tibetan aid teachers and education management cadres to Tibet, and the national counterpart support program for Tibetan education (Wang 2018).

While overall school running conditions have been continuously and greatly improved, there are still some deficiencies that require improvement. By 2020, the proportion of supporting staff (teaching assistants, administration and service staff) among all staff in primary and middle schools in Tibet was lower than the national average, with two potential consequences: on the one hand, teachers may have taken on heavier workloads, and on the other hand, school operation and teaching quality may have been affected. In terms of the teachers’ academic qualifications, although the number of highly educated teachers increased on the whole, there is still a shortage of highly educated teachers in middle schools. Although the indicators of school building area, teaching and auxiliary housing area continued to improve, the per student area of Tibetan high schools remains relatively low in the country. In terms of books, computers and multimedia classrooms, although the total number of computers and multimedia classrooms has increased in recent years in a linear trend, the three indicators per student of primary and middle schools in Tibet remain at a low level nationwide.

Policy recommendations on school running conditions for fundamental education in Tibet are as follows: 1) Many indicators of school running conditions for primary education in Tibet have reached or exceeded the national average. At present, the focus is to strengthen support for school running conditions for middle school education in Tibet, especially in senior high schools, and focus on solving the problems of low academic qualifications of middle school teachers, lagging construction of school buildings and shortages of auxiliary facilities and equipment, such as laboratories, computer rooms and multimedia classrooms. Great efforts are required to remedy these weaknesses. In addition, it is necessary to examine the fact that the proportion of teachers to school staff in primary and middle schools in Tibet far exceeds the national average (more than 5 and 8%, respectively) and propose solutions for this issue; 2) We should continue to apply information technology to drive the modernization of education in Tibet. The application of information technology in education has the advantages of reduced costs, fast effects, high efficiency and less time/space limitations. Meanwhile, education informatization plays a positive role in changing educational ideas, promoting teaching reform and accelerating the modernization of education and management methods (Fang et al. 2008). Considering the unique environment of Tibet, ICT (Information and Communications Technology) in education may help overcome geographic constraints and reduce time and money costs. Therefore, primary and middle education in Tibet should adhere to the principal of increasing investment in ICT in education. The concrete measures are as follows: Firstly, it is important to establish a communication system between online learning and other forms of learning to promote the construction of digital campuses. Secondly, it is necessary to develop distance learning resources and build a multi-level, multi-functional and interactive education resource service system. Thirdly, efforts should be made to coordinate the allocation of educational resources among regions, promote sharing of educational resources, establish an educational assistance mechanism between the developed eastern regions and Tibet, and pay special attention to the supporting mechanism of high-quality teacher resources.