Assessing the Modernization of Higher Education in China’s Eight Ethnic Minority Provinces: A Decade-Long Panel Data Analysis (2012–2021)

Abstract

The pursuit of high-quality higher education in ethnic minority regions is of paramount importance in the contemporary era. As China advances towards its distinctive model of higher education modernization, the imperative for a robust evaluation framework for higher education modernization becomes increasingly evident. Achieving synchronized educational modernization across all ethnic groups is not only a persistent and evolving facet of the historical national strategy of “Four Modernizations in Synchronization” but also a critical milestone and salient indicator of concurrent progress in higher education modernization across ethnic minority regions in the present context. From 2012 to 2020, the nation executed a nine-year strategic plan aimed at revitalizing higher education in the central and western regions. This study, employing literature analysis and grounded in the five core functions of universities, utilizes a comprehensive dataset spanning a decade (2012 to 2021) to construct a bespoke evaluation index system for the modernization of higher education in ethnic minority regions. Through quantitative assessments, this study evaluates the trajectory of modernization in higher education development in these regions over the past decade, thereby offering indirect insights into the efficacy of the national initiative to rejuvenate higher education in the central and western regions. The findings indicate a fluctuating yet upward trend in the overall level of higher education development across the eight ethnic minority regions. Nevertheless, substantial disparities persist when compared with other provinces. Notably, Tibet and Guizhou have demonstrated significant growth, with respective growth rates of 5.533 and 4.341. Moreover, an in-depth analysis leveraging the grey GM(1,1) prediction model projects the future developmental trajectories of higher education in ethnic minority regions. To ensure the sustainable advancement of higher education in ethnic minority regions, supplementary policy interventions are indispensable. This entails fostering a conducive environment of resonance and coordinated development between ethnic economies and higher education, thereby nurturing a harmonious relationship that propels progress.

1. Introduction

Higher education, as an important part of the educational system and a cornerstone of Chinese-style modernization, directly furnishes knowledge, technology, and talent essential for economic development. Consequently, quantifying the quality of higher education “supply” and evaluating the level of higher education services to catalyze high-quality economic development have emerged as critical developmental issues [1,2].

For a considerable length of time, a combination of factors such as economic development, geographical environment, and demographic structure has left much room for improvement in higher education in China’s ethnic minority regions. These regions grapple with challenges pertaining to university layout, content development, international exchange and cooperation, and social service capabilities.

The key features of this article are its comprehensive literature analysis and the integration of the five major functions of universities [3]. Building upon this foundation, this article constructs a modern evaluation index system for higher education specifically calibrated for ethnic minority areas. This system quantitatively assesses the level of modernization in higher education development in these regions over the past decade, thereby indirectly reflecting the efficacy of the national initiative to invigorate higher education in the central and western regions of China.

2. Theoretical Review

2.1. Concept of Educational Modernization

In the extant literature, scholars have put forward several seminal viewpoints regarding the definition of educational modernization:

• Educational Modernization as the Enhancement of Educational Modernity: Yuan, L. P. [4] posits that “the essence of educational modernization is the augmentation of educational modernity.” The Chinese Society of Educational Development Strategy further elucidates that educational modernization is the dynamic process by which education incrementally aligns with the imperatives of contemporary societal evolution, thereby catalyzing the progressive escalation of educational modernity.
• Educational Modernization as the Modernization of Educational Form: Li, X. S. [5] conceptualizes educational modernization as the transformative process targeting the modernization of the educational form. This perspective emphasizes the structural and operational changes within the educational system to meet modern standards and expectations.
• Educational Modernization as Human Modernization: Scholars such as Wu, Z. H. [6] and Wu, Y. [7] advocate that educational modernization is fundamentally the process of human modernization. They argue that this modernization entails the enhancement of human modernity and the cultivation of a modernized personality. This viewpoint highlights the role of education in fostering individual attributes and capabilities that are consonant with modern societal norms and values.

2.2. Content, Standards, Features, Theories, Conditions, Value Orientation, or Value Goals of Educational Modernization

In the scholarly discourse on educational modernization, numerous researchers have developed frameworks and theories to delineate its content, standards, features, and goals:

1. Four-Nature Construction: Liu, Z. et al. [8] proposed a construction based on four key aspects, which provides a foundational structure for understanding educational modernization. This framework emphasizes the multifaceted nature of educational modernization, highlighting the interplay between different dimensions such as technological integration, curriculum development, teacher training, and institutional governance.

2. Eight-Characteristics Framework of Educational Modernity: Chu, H. Q. [9] introduced a framework that outlines eight distinct characteristics of educational modernity, offering a detailed analysis of what constitutes modern education. These characteristics include the following:

Technological Integration: The seamless incorporation of modern technology into teaching and learning processes.

Curriculum Relevance: The alignment of educational content with contemporary societal and economic needs.

Teacher Competence: Focusing on the enhancement of teachers’ skills and knowledge to meet modern educational standards, which is crucial for delivering high-quality education.

Student-Centered Learning: The shift from traditional teacher-centered approaches to more student-centered and interactive learning environments.

Institutional Flexibility: The ability of educational institutions to adapt and respond to changing educational demands and technologies.

Quality Assurance: Stressing the implementation of robust quality assurance mechanisms to ensure educational excellence and maintain high standards in teaching and learning.

Internationalization: The engagement of educational institutions in global networks and collaborations.

Social Engagement: The active involvement of educational institutions in addressing societal challenges and contributing to community development.

3. Overall Framework of Socialism with Chinese Characteristics: Pan, X. W. [10] presented a comprehensive framework that integrates educational modernization within the broader context of socialism with Chinese characteristics. This framework highlights the unique approach and value goals of China’s educational modernization efforts, emphasizing the following key aspects:

Political Leadership: The guiding role of the Communist Party in shaping educational policies and ensuring alignment with national development goals.

Economic Support: The provision of adequate resources and funding to support educational modernization initiatives.

Cultural Integration: The preservation and promotion of cultural heritage while integrating modern educational practices.

Social Equity: The commitment to ensuring equal access to quality education for all segments of society, particularly in ethnic minority regions.

Innovative Practices: The encouragement of innovative teaching methods and educational technologies to enhance learning outcomes.

Sustainable Development: The focus on long-term sustainability of educational systems and practices to meet future challenges.

2.3. The Third Aspect Is the Developmental History of Educational Modernization

Scholars including Zhang, Y. T. [11] et al. have conducted a longitudinal review of the trajectory of educational modernization in China, examining it from various temporal perspectives. Their research offers invaluable insights and serves as a crucial reference for charting the future course of our nation’s educational sector.

2.4. The Fourth Aspect Concerns China’s Important Discourse on Educational Modernization

Scholars such as Liu, Y. [12] and Huang, J.J. [13] have focused on Xi Jinping’s relevant discourse on educational modernization. They elaborated, respectively, on the formation conditions, main content, basic characteristics, and contemporary values of Xi Jinping’s important discourse on educational modernization.

2.5. The Fifth Aspect Is the Construction of the Evaluation Index System for Modernization of Higher Education

From the domestic literature amassed, it is discernible that the assessment methodologies for the modernization of higher education encompass three distinct categories: quantitative methods, qualitative methods, and grey clustering methods. An overview of the dimensions utilized in evaluating educational modernization reveals three predominant approaches: the inductive–descriptive approach, the deductive–analytical approach, and the systemic–integrative approach.

2.6. The Sixth Aspect Pertains to the Comparative Study of the Evaluation Index System for the Modernization of Higher Education

A comparative study of the evaluation index system for higher education modernization holds great significance. International comparisons primarily center on the early development models of higher education modernization in Western countries, with a particular focus on the contrasts among the United Kingdom, France, Germany, and the United States. As pioneers in the field of higher education modernization, each of these countries has forged a distinctive development model. The UK’s approach to higher education modernization emphasizes the integration of tradition and innovation, highlighting the parallel advancement of elite and mass education. France is acclaimed for its centralized education management system and its strong commitment to educational equity. Germany’s higher education modernization underscores the close link between vocational education and higher education, which has resulted in the cultivation of a substantial number of high-quality technical professionals. The US model is distinguished by its diversity and flexibility, with a focus on nurturing students’ innovative and practical skills.

Beyond these Western nations, a comparison between the UK and Japan also offers valuable insights. The UK boasts a long-standing education system with a heavy emphasis on academic research and theoretical education. In contrast, Japan’s higher education modernization, while drawing from Western education models and adapting to its unique national conditions, has developed a unique “late-developing exogenous” model. This model is characterized by central government leadership and reflects a transition from passive reform to active development.

By conducting a comparative analysis of the evaluation index systems for higher education modernization in these countries, we can glean useful insights that can inform the development of higher education in other nations. Such comparisons can assist policymakers in formulating and implementing more effective strategies and policies, thereby promoting the progress of higher education modernization on a global scale.

The second part of this study primarily concentrates on regional and provincial comparisons within eastern, central, and western China. This approach allows for a comprehensive analysis of the educational modernization trajectories across different geographical and cultural contexts, providing insights into the diverse pathways and strategies employed in the pursuit of educational modernization.

2.7. The Seventh Aspect Is the Constituent Elements of Higher Education Modernization

These constituent elements not only concretize the connotation of higher education modernization but also guide its developmental goals and directions. The “China’s Education Modernization 2035” initiative sets forth that by 2035 China aims to achieve overall educational modernization, with higher education modernization taking on new epochal significance. Facing new strategic tasks, the key features include the following [14,15]: (1) Promoting the high-level and high-quality universalization of education. (2) Striving to enhance the training of top-notch talents and innovation capabilities. (3) Accelerating the reform of information-based education. (4) Elevating the level of openness in education. (5) Establishing a diversified, personalized, lifelong education system for everyone, thus realizing the goal of modernizing higher education.

Drawing on extant scholarly research regarding the constituent elements of higher education modernization and integrating the strategic task planning delineated in “China’s Education Modernization 2035”, the following five core constituent elements of higher education modernization can be distilled:

• Education Equity and Accessibility: Guaranteeing that high-quality education is attainable for all individuals, irrespective of their background or geographical location.
• Talent Cultivation and Innovation: Nurturing the development of elite talent and fostering innovation capabilities to meet the demands of a knowledge-driven society.
• Information Technology Integration: Embracing and effectively utilizing advancements in information technology to revolutionize and enhance educational methodologies and practices.
• Globalization and Openness: Expanding international collaborations and exchanges to bolster the openness and global competitiveness of higher education institutions.
• Lifelong Learning and Personalized Education: Instituting a lifelong learning framework that accommodates diverse needs and preferences, thereby promoting personalized educational pathways for continuous growth and development.

3. Construction of Evaluation Index System

Upon reviewing the literature, it is evident that in the development of modern higher education in the new era, factors such as “high quality”, “equity”, “social service”, “internationalization”, and “informationization” are embedded in the process of modernization. From these, three major driving forces for promoting the modernization of higher education can be identified. In existing studies, scholars have established a relatively complete evaluation index system for the modernization development level of higher education in ethnic minority regions.

The evaluation index system for the modernization of higher education in ethnic minority regions, as constructed in this paper, is based on the mature experience of relevant research. It adheres to the principles of adaptability to social development, scientific rigor, guidance, representativeness, and objectivity. Departing from the five major functions of universities—talent cultivation, scientific research, social service, cultural heritage innovation, and international exchange and cooperation—and considering the continuity and availability of data, as well as scientific rigor, we constructed an index system to evaluate the level of modernization of higher education in ethnic minority regions [16,17].

This system includes five primary indicators, nine secondary indicators, and 24 tertiary indicators, ensuring a scientifically reasonable and comprehensive evaluation framework (

Table 1. Evaluation indicators of modernization development level of higher education in ethnic minority regions.

Primary Indicator	Secondary Indicator	Tertiary Indicator	Unit	Attribute
Index of High-Quality Input–Output (A1)	Input Indicator	Number of Schools	Unit	+
		Number of Faculty and Staff	Persons	+
		Number of Full-time Teachers	Persons	+
		Ratio of Teachers with Doctoral Degrees in Full-time Teaching Staff	%	+
		Number of Teachers with Senior Professional Titles in Full-time Teaching Staff	Persons	+
		Expenditure on Education	CNY 10,000	+
		General Public Budget for Educational Expenses	CNY 1000	+
		Area of School Property Buildings	Square Meters	+
		Number of Books	Volumes	+
	Output Indicator	Undergraduate Enrollment	Persons	+
		Total Enrollment	Persons	+
		Number of Undergraduate Graduates	Persons	+
		Number of Graduate (Postgraduate) Graduates	Persons	+
Index of Higher Education Equity (A2)	Equal Opportunity	Gross Enrollment Ratio in Higher Education	%	+
	Procedural Fairness	Student–Teacher Ratio	%	−
		Per Capita Education Expenditure per Student	CNY	+
Index of Higher Education in Serving Society (A3)	Talent Assurance	Average Number of University Students per 100,000 Population	Persons	+
	Research Transformation	Income from Patent Ownership Transfer and Licensing	CNY 10,000	+
		R&D Expenditure in Universities	CNY 10,000	+
		Number of R&D Projects in Universities	Item	+
Index of Higher Education Internationalization (A4)	Scientific Research	Number of Scientific Papers Published Abroad	Article	+
Index of Higher Education Informatization (A5)	Infrastructure	Number of Network Multimedia Classrooms	Unit	+
		Number of Computers (Units)/Digital Terminals	Unit	+
	Security System	Value of Information Technology Equipment Assets	CNY 10,000	+

Note: “+” indicates a positive indicator, while “−” indicates a reverse indicator.

) [18,19,20].

The basic data for this study are primarily sourced from authoritative sources such as the “China Statistical Yearbook”, “China Education Statistics Yearbook”, “China Education Expenditure Statistical Yearbook”, and the “China Science and Technology Statistical Yearbook”, as well as data from the National Bureau of Statistics and the Ministry of Education. Spanning from 2012 to 2022, these sources provide high objectivity, reliability, and scientific validity.

To ensure consistency and operability of the data within the index system, the normalization process adopts the method of standardization, specifically utilizing the min–max scaling method to eliminate the influence of dimensions. For positive indicators, ${\mathrm{Y}}_{\mathrm{i}\mathrm{j}}={\displaystyle \frac{{\mathrm{X}}_{\mathrm{i}\mathrm{j}}-\mathrm{m}\mathrm{i}\mathrm{n}{\mathrm{X}}_{\mathrm{i}\mathrm{j}}}{\mathrm{m}\mathrm{a}\mathrm{x}{\mathrm{X}}_{\mathrm{i}\mathrm{j}}-\mathrm{m}\mathrm{i}\mathrm{n}{\mathrm{X}}_{\mathrm{i}\mathrm{j}}}};$ for negative indicators, ${\mathrm{Y}}_{\mathrm{i}\mathrm{j}}={\displaystyle \frac{\mathrm{m}\mathrm{a}\mathrm{x}{\mathrm{X}}_{\mathrm{i}\mathrm{j}}-{\mathrm{X}}_{\mathrm{i}\mathrm{j}}}{\mathrm{m}\mathrm{a}\mathrm{x}{\mathrm{X}}_{\mathrm{i}\mathrm{j}}-\mathrm{m}\mathrm{i}\mathrm{n}{\mathrm{X}}_{\mathrm{i}\mathrm{j}}}}$ where ${\mathrm{X}}_{\mathrm{i}\mathrm{j}}$ represents the j-th index of the i-th system.

In accordance with the Chinese-style modernization process and the views of several scholars such as Wang Shanmai and Li Huiqin, who argue that each indicator is equally important in measuring the level of higher education development, equal weights should be assigned to each indicator.

4. Research Results

4.1. Overall Level of Higher Education Development in Eight Ethnic Provinces Shows a Rising Trend

Data calculations reveal that, from 2012 to 2021, the overall index of higher education modernization in the eight ethnic provinces—namely, Tibet, Inner Mongolia, Qinghai, Xinjiang, Yunnan, Ningxia, Guangxi, and Guizhou—exhibited a fluctuating upward trend, peaking in 2018 at 0.444. The annual growth rate of 0.404 is intimately linked to the national strategy of prioritizing education within the context of Chinese-style modernization development.

Examining the five primary indicators of higher education development in ethnic minority regions, the indices of higher education equity, higher education in serving society, and higher education internationalization have all demonstrated growth [21]. Among these, the higher education equity index has the highest annual growth rate, at 2.331. The secondary indicators, the Higher Education Service to Society Index and the Higher Education Internationalization Index, have growth rates of 1.907 and 1.892, respectively. In contrast, the other two primary indicators, the Higher Education Informatization Index and the Higher Education High-Quality “Input–Output” Index, experienced an overall downward “inverted V” trend during this period, with values of 1.784 and 0.607, respectively. Specifically, the Higher Education Informatization Index increased from 0.497 in 2012 to 0.499 in 2015, then gradually declined to 0.421 in 2021. The Higher Education High-Quality “Input–Output” Index increased from 0.481 in 2012 to 0.499 in 2016, then declined to 0.454 in 2021. Although the decrease in value is not significant, it clearly indicates that both the Higher Education Informatization Index and the High-Quality “Input–Output” Index represent pressing challenges that need to be addressed in ethnic minority regions currently and in the foreseeable future (

Table 2. Measurement of the overall development level of higher education modernization in eight ethnic provinces and regions from 2012 to 2021.

Index	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	Increment
Overall Index of Higher Education Modernization (B1)	0.411	0.407	0.417	0.419	0.425	0.431	0.444	0.423	0.433	0.425	0.404
Index of High-Quality Input–Output (A1)	0.481	0.481	0.482	0.487	0.499	0.497	0.493	0.477	0.453	0.454	−0.607
Index of Higher Education Equity (A2)	0.352	0.325	0.316	0.301	0.319	0.351	0.351	0.341	0.365	0.423	2.331
Index of Higher Education Serving Society (A3)	0.380	0.389	0.408	0.421	0.448	0.472	0.425	0.409	0.422	0.445	1.907
Index of Higher Education Internationalization (A4)	0.347	0.343	0.383	0.388	0.368	0.357	0.460	0.432	0.472	0.384	1.892
Index of Higher Education Informatization (A5)	0.497	0.497	0.497	0.499	0.490	0.480	0.490	0.454	0.451	0.421	−1.784

, Figure 1).

4.2. The Level of Higher Education Development in the Eight Ethnic Provinces and Regions Fluctuates, with Tibet Showing the Greatest Increase and Xinjiang Experiencing the Largest Decline

According to

Table 3. Measurement of higher education modernization development levels in eight ethnic minority provinces from 2012 to 2021.

Year	Tibet	Inner Mongolia	Qinghai	Xinjiang	Yunnan	Ningxia	Guangxi	Guizhou	Average
2012	0.117	0.543	0.212	0.404	0.620	0.276	0.745	0.372	0.411
2013	0.128	0.560	0.194	0.384	0.584	0.247	0.766	0.392	0.407
2014	0.161	0.577	0.150	0.360	0.642	0.198	0.780	0.470	0.417
2015	0.159	0.549	0.146	0.359	0.711	0.209	0.723	0.498	0.419
2016	0.159	0.544	0.154	0.359	0.699	0.203	0.766	0.516	0.425
2017	0.166	0.527	0.158	0.379	0.689	0.230	0.745	0.554	0.431
2018	0.157	0.561	0.147	0.376	0.709	0.265	0.797	0.537	0.444
2019	0.143	0.582	0.134	0.325	0.701	0.231	0.763	0.503	0.423
2020	0.143	0.557	0.165	0.345	0.692	0.237	0.796	0.526	0.433
2021	0.180	0.526	0.186	0.301	0.630	0.242	0.802	0.534	0.425
Average	0.151	0.553	0.165	0.359	0.668	0.234	0.768	0.490	0.423
Increment	5.533	−0.260	−0.627	−2.991	0.367	−0.784	0.925	4.341	0.813

, from 2012 to 2021, Tibet and Guizhou showed significant increases in the level of higher education modernization among the eight ethnic provinces and regions in China, with increments of 5.533 and 4.341, respectively. Guangxi and Yunnan maintained a reasonable growth rate, indicating positive trends in educational development and reflecting the overall effectiveness of education modernization at a macro level.

In contrast, Xinjiang experienced the largest decline, with a decrease of 2.991. The years with the most significant declines were 2018–2019 and 2020–2021, showing decreases of 13.63 and 12.96, respectively.

The index of higher education modernization development in Tibet surged from 0.117 in 2012 to 0.180 in 2021. Several factors contributed to this significant increase [22,23]:

Firstly, the national government has prioritized the educational sector in Tibet, resulting in the substantial allocation of educational resources and funding. This attention has accelerated the pace of higher education modernization in Tibet over the past decade.

Secondly, since 2012, Tibet has been at the forefront of implementing a nationwide 15-year compulsory education system, covering preschool through high school. This initiative has increased the average years of education per person to over 10 years in Tibet.

Thirdly, since 2012, Tibet has enhanced its funding system by extending the “three guarantees” (providing meals, accommodations, and basic learning expenses) and scholarship policies to encompass all children of farmers and herdsmen in preschool and high school education, as well as children from urban families facing financial difficulties. These measures have laid a solid foundation for the development of higher education in the region.

From 2012 to 2021, the level of higher education modernization in Guizhou has shown steady improvement. According to Zou Lianke (2023), education in Guizhou Province is currently undergoing a phase of catching up. The Guizhou government’s “Six Major Enhancements” strategy, which includes substantial improvements in poverty alleviation and five other closely related educational strategies, has been pivotal.

These strategies focus on enhancing educational accessibility, equity, and quality, as well as fostering educational service contributions, development vitality, and openness. With concerted efforts in these areas, the momentum for the development of higher education in Guizhou looks promising (Figure 2).

Based on the modernization level scores of higher education in eight provinces and autonomous regions in ethnic minority regions of China, the development levels of higher education in ethnic minority regions from 2012 to 2021 can be categorized into three levels:

Level 1: The highest modernization development level of higher education (average score > 0.5), including three provinces: Guangxi (0.768), Yunnan (0.668), Inner Mongolia (0.553). These three provinces have relatively good economic development levels, which provide a solid economic foundation for the modernization of their higher education. Additionally, according to the distribution of higher education institutions, the 2021 statistics of regular higher education institutions nationwide indicate that there are 390 such institutions in the eight provinces and autonomous regions inhabited by ethnic minorities, with Guangxi having 85, Yunnan 82, and Guizhou 75. These three provinces and autonomous regions account for 62.05% of the total number of higher education institutions in ethnic minority areas. Higher education serves as a crucial vehicle for promoting social progress and constructing a new development paradigm. Therefore, their relatively high level of modernization in higher education development is evident.

Level 2: A good level of modernization development in higher education (average score between 0.3 and 0.5), including two provinces: Guizhou (0.49) and Xinjiang (0.359). With the implementation of supportive policies from the central government aimed at ethnic minority regions and the improvements in economic development levels, these provinces and autonomous regions have witnessed enhancements in various aspects such as education expenditure, university R&D funding, and the number of multimedia classrooms. These improvements in hardware and software facilities have laid a solid foundation for the modernization of higher education in ethnic minority areas. However, due to factors such as the gross enrollment ratio in higher education and the number of scientific papers published abroad, the indices for the equity and internationalization of higher education are relatively low. This limitation hinders the opportunity for further enhancement in the modernization development level of higher education.

Level 3: A general level of modernization development in higher education (average score < 0.3), including Ningxia (0.234), Qinghai (0.165), and Tibet (0.151). We should acknowledge that Tibet has the lowest modernization index for higher education. In 2021, Tibet’s modernization index for higher education was 0.18, significantly lower than Guangxi’s 0.802. Restricted by factors such as geographical location, higher education models, and economic development levels, the research innovation and internationalization capabilities of universities in these three provinces are limiting factors for the development level of higher education modernization.

4.3. There Is a Significant Difference Between the Modernization Development Level of Higher Education in Ethnic Minority Regions and the National Average Level

Higher education, as a sector requiring significant investment in teaching, research, and personnel, is fundamentally dependent on sustained and effective financial support [24,25]. Consequently, the modernization of higher education is deeply intertwined with economic capacity. Given the notable disparities in geographical location, strategic priorities, resource distribution, and economic development among China’s diverse provinces and regions, a comprehensive analysis of educational progress in ethnic minority areas, compared with other provinces, is essential.

To facilitate a structured scrutiny, this study will examine the indices of higher education development spanning from 2012 to 2021, encompassing all 31 provinces, municipalities, and autonomous regions within China. The objective of this analytical endeavor is to elucidate and provide a more palpable comprehension of the variances in educational evolution, thereby illuminating the distinct pathways and challenges encountered in the modernization of higher education across different regional contexts.

Specifically, to visually illustrate disparities between the eight provinces and autonomous regions inhabited by ethnic minorities and the other 23 provinces, municipalities, and autonomous regions, data from the years 2012, 2015, 2018, and 2021 will be selected for presentation in Figure 3.

Figure 3 illustrates that Tibet, Inner Mongolia, Qinghai, Xinjiang, Yunnan, Ningxia, Guangxi, and Guizhou, the eight provinces and autonomous regions inhabited by ethnic minorities, have lower levels of modernization in higher education compared with the rest of the country. Particularly, Tibet and Qinghai are positioned at the bottom of the 31 provinces, municipalities, and autonomous regions. By analyzing actual data, it can be concluded that there is a close connection between education and economy. The level of modernization in higher education shows a significant correlation with geographical location and economic development level, exhibiting a distinct “east high, west low” pattern.

4.4. Subdivision and Ranking of Higher Education Development Indices in the Eight Provinces in Ethnic Minority Areas

Refer to Figure 4, examining the modernization levels of higher education in Guangxi, Yunnan, and Inner Mongolia from 2012 to 2021 [26,27]:

• Guangxi (2012–2021):

During the observed period, Guangxi has consistently achieved an internationalization index of 1, with an average value of 0.961. The high-quality “input–output” index for higher education stands at 0.934, while the informatization index reaches 0.935. These figures notably exceed those of the developed eastern provinces. However, the equity index for higher education remains the area most in need of improvement.

During the 13th Five-Year Plan period, the research and service capabilities of universities in Guangxi have shown steady improvement. Collectively, these institutions have secured approximately 33,800 research projects across various levels, with a total project funding nearing CNY 5 billion. Leveraging various China-ASEAN talent training centers (bases) and international teaching sites, Guangxi’s universities have trained over 13,000 individuals. Aligned with documents such as the “14th Five-Year Plan for National Economic and Social Development and 2035 Vision Outline of Guangxi Zhuang Autonomous Region” and the “14th Five-Year Plan for the Development of Education in Guangxi Zhuang Autonomous Region”, efforts have intensified to coordinate the scale, structure, talent distribution, quality standards, scientific and technological resources, and financial investment in higher education. By 2025, the gross enrollment rate in higher education across the region is expected to reach 55%.

2.

Yunnan Province (2012–2021):

An analysis of the five indicators of modernization in Yunnan’s higher education development reveals that the “input–output” quality index ranks the highest, with an average value of 0.888. This is followed by the internationalization index and the informatization index, which have average values of 0.861 and 0.804, respectively. Similar to Guangxi, the area requiring the most significant improvement is the equity index of higher education.

The Yunnan Education Modernization 2035 plan highlights the continuous expansion of educational openness in the province. It actively serves and integrates into the construction of the Belt and Road Initiative, enlarging the scope of education’s openness to the outside world. The province has established strategic cooperation with 23 universities. At the same time, Yunnan has established a series of international exchange and cooperation mechanisms and platforms, including the “Yunnan-South Asia Southeast Asia Education Cooperation Forum”, the “South Asia Southeast Asia University Presidents Alliance”, and the China-Shanghai Cooperation Organization Youth Exchange Center. These efforts have attracted around 19,300 international students to study in Yunnan. The goal is to strive for a gross enrollment rate in higher education of over 65% by 2035.

3.

Inner Mongolia (2012–2021):

The five indicators of modernization in Inner Mongolia’s higher education development show relatively balanced performance. Among them, the informatization index and the index for higher education’s societal service function are relatively high, with average values of 0.626 and 0.60, respectively. However, the internationalization index of higher education is the lowest, standing at 0.452. This reflects the comprehensive and coordinated development of higher education modernization in Inner Mongolia, emphasizing the five functional concepts of its universities, which are characterized by strategic, programmatic, and leading features. Through data analysis, it becomes clear that the development logic of Inner Mongolia’s higher education in the new era lies in comprehensive efforts, the simultaneous advancement of the five functions, multiple breakthroughs, and deep progress.

According to Figure 5, from 2012 to 2021, an analysis of the five indicators of modernization in higher education development in Guizhou and Xinjiang reveals that both provinces have achieved relatively high scores in the informatization index and the high-quality “input–output” index for higher education, with mean values of 0.731, 0.493 for Guizhou and 0.685, 0.483 for Xinjiang, respectively. Similar to Guangxi and Yunnan, the aspect that requires the most improvement and enhancement in both provinces is the equity index for higher education.

Reflecting on President Xi Jinping’s two inspections of Guizhou since the 18th National Congress of the Communist Party of China, in 2015 he emphasized the necessity to “forge a new path of development different from the eastern region and distinct from other western provinces.” According to data from the Education Department of Guizhou Province, the province aims to achieve a gross enrollment rate in higher education of 50% by 2025 and to catch up with or even surpass national average levels in key education indicators, positioning itself as a leader in distinctive education.

Similarly, “Education Modernization 2035 in Xinjiang” and the “Accelerating the Implementation Plan for Education Modernization in Xinjiang (2018–2022)” indicate that under the strong leadership of the Autonomous Region Party Committee and with robust support from the central government, Xinjiang aims to achieve various expected indicators of education modernization. This includes increasing investment in education, deepening comprehensive reforms in the education sector, and enhancing the overall level of educational development to establish a higher quality, fairer, and more inclusive education mechanism.

According to Figure 6, from 2012 to 2021, an analysis of the five modernization indicators of higher education development in Ningxia, Qinghai, and Tibet reveals that, in comparison, the equity index for higher education in Qinghai and Tibet significantly exceeds that of Inner Mongolia, Xinjiang, and Guangxi. Specifically, Tibet boasts the highest equity index for higher education, with a mean value of 0.673, followed by Qinghai at 0.633. Educational development in these three provinces is influenced by a confluence of factors including politics, economy, geography, history, and culture, presenting numerous challenges. Historically, leaders of the Party and the state have placed significant emphasis on educational work in these three ethnic minority provinces, enacting various preferential policies to ensure the fairness of higher education.

Concurrently, it is observed that the high-quality “input–output” index, internationalization index, and informatization index of higher education are generally low, with some instances reaching a nadir of 0. As of 2022, the number of higher education institutions offering undergraduate and postgraduate programs stands at 20 in Ningxia, 12 in Qinghai, and 7 in Tibet, which is considerably lower compared with the other five ethnic minority provinces.

4.5. Correlation Analysis Between the Modernization Level of Higher Education in Ethnic Minority Regions and Economic Development

The symbiotic relationship between education and the economy is a classic and vital topic [28]. Achieving high-quality development in higher education has become a focal point for theorists and practitioners in the new era. Higher education serves as a significant driver in shaping the economic development landscape, and the evolving development paradigm demands higher education to evolve with enriched connotations.

According to a correlation analysis between the GDPs of the eight provinces and autonomous regions inhabited by ethnic minorities and the average modernization index of higher education from 2012 to 2021, the correlation coefficient between GDP and the modernization index of higher education is 0.947, indicating a high degree of correlation between the two. Provinces with higher GDP values, such as Guangxi, Yunnan, and Inner Mongolia, also exhibit higher levels of modernization in higher education. Conversely, provinces with lower GDP values, such as Ningxia, Qinghai, and Tibet, demonstrate lower levels of modernization in higher education.

This highlights a beneficial interaction between the high-quality development of higher education and economic growth. They mutually enhance and promote each other, contributing to common development (Figure 7).

5. Trend Forecasting Based on the Grey GM(1,1) Prediction Model

Our study primarily employs the Development Index of Higher Education in eight provinces, autonomous regions, and municipalities inhabited by minority ethnic groups in China from 2012 to 2021 as predictive samples. The GM (1,1) grey prediction model is a method widely used for studying problems with limited data and information scarcity. Therefore, the selection of the grey GM (1,1) prediction model is deemed reasonable.

5.1. Theoretical Background

The GM(1,1) model works by transforming an original data sequence into a monotonic series through a process called Accumulated Generating Operation (AGO). This transformation helps to reveal underlying patterns and trends in the data. The model then constructs a first-order differential equation to describe the system’s behavior, which is solved to generate predictions. Finally, the predicted values are restored to their original form using the Inverse Accumulated Generating Operation (IAGO). The model’s strength lies in its ability to extract meaningful information from small datasets and its flexibility in handling systems with partial information.

5.2. Relevance to Our Study

Given the limited availability of historical data and the complexity of the educational development trends in these regions, the grey GM(1,1) model is particularly suitable. It allows us to effectively analyze and predict trends in higher education development, even with relatively sparse data. The model’s ability to handle uncertainty and its robustness in small-sample scenarios make it a reasonable and reliable choice for our research objectives.

5.3. Grey GM(1,1) Prediction Model

The grey GM(1,1) prediction model is a forecasting method within grey system theory, which is specifically designed to handle systems with incomplete or uncertain information. The “GM” stands for “Grey Model”, and (1,1) denotes a first-order, single-variable model. It is particularly effective for analyzing systems with limited data, making it suitable for scenarios where traditional statistical methods may not be applicable due to data scarcity.

The basic principle is as follows: first, an original data sequence set is assumed:

$${\mathrm{X}}^{\left(0\right)}=({\mathrm{X}}^{\left(0\right)}\left(1\right),{\mathrm{X}}^{\left(0\right)}\left(2\right)\dots \dots {\mathrm{X}}^{\left(0\right)}\left(\mathrm{n}\right))$$

where n represents the number of data points, and a first-order accumulation is performed on x(0) to generate the sequence:

$${\mathrm{X}}^{\left(1\right)}=({\mathrm{X}}^{\left(1\right)}\left(1\right),{\mathrm{X}}^{\left(1\right)}\left(2\right)\dots \dots {\mathrm{X}}^{\left(1\right)}\left(\mathrm{n}\right))$$

$${\mathrm{X}}^{\left(1\right)}\left(\mathrm{k}\right)=\sum \left({\mathrm{X}}^{\left(0\right)}\left(\mathrm{i}\right),\mathrm{k}=\mathrm{1,2}\dots .\mathrm{n}\right)$$

Generating the sequence of adjacent mean values for x(1):

$${\mathrm{T}}^{\left(1\right)}=\left\{{\mathrm{T}}^{\left(1\right)}\left(2\right),{\mathrm{T}}^{\left(1\right)}\left(3\right)\dots \dots {\mathrm{T}}^{\left(1\right)}\left(\mathrm{n}\right),\right\}$$

$${\mathrm{T}}^{\left(1\right)}\left(\mathrm{K}\right)={\displaystyle \frac{1}{2}}{\mathrm{X}}^{\left(1\right)}\left(\mathrm{K}-1\right)+{\displaystyle \frac{1}{2}}{\mathrm{X}}^{\left(1\right)}\left(\mathrm{K}\right),\mathrm{K}=\mathrm{2,3}\dots \mathrm{n}$$

By introducing matrix-vector notation and other calculation processes, the whitening differential equation corresponding to the GM(1,1) grey differential equation is obtained.

$${\displaystyle \frac{{\mathrm{d}\mathrm{x}}^{\left(1\right)}(\mathrm{t})}{\mathrm{d}\mathrm{x}}}+{\mathrm{a}\mathrm{x}}^{\left(1\right)}(\mathrm{t})=\mathrm{b}$$

You can obtain the following formula: ${\mathrm{x}}^{\left(1\right)}\left(\mathrm{t}\right)=\left({\mathrm{x}}^{\left(0\right)}\left(1\right)-{\displaystyle \frac{\mathrm{b}}{\mathrm{a}}}\right){\mathrm{e}}^{-\mathrm{a}(\mathrm{t}-1)}+{\displaystyle \frac{\mathrm{b}}{\mathrm{a}}}$

$${\widehat{\mathrm{x}}}^{\left(1\right)}\left(\mathrm{k}+1\right)=\left({\mathrm{x}}^{\left(0\right)}\left(1\right)-{\displaystyle \frac{\mathrm{b}}{\mathrm{a}}}\right){\mathrm{e}}^{-\mathrm{a}\mathrm{k}}+{\displaystyle \frac{\mathrm{b}}{\mathrm{a}}},\mathrm{k}=1.2\dots \mathrm{n}$$

By inputting the existing series data from 2012 to 2021 into the Grey GM(1,1) prediction model, the predicted values of the Education Development Index for various provinces and regions among the ethnic groups for the years 2022 to 2031 can be calculated (see

Table 4. Prediction of the Higher Education Modernization Development Index for the eight ethnic provinces and regions from 2022 to 2031.

Year	Tibet	Inner Mongolia	Qinghai	Xinjiang	Yunnan	Ningxia	Guangxi	Guizhou
2022	0.192	0.562	0.214	0.316	0.705	0.248	0.796	0.581
2023	0.210	0.560	0.240	0.331	0.712	0.254	0.801	0.598
2024	0.228	0.559	0.266	0.346	0.719	0.259	0.806	0.614
2025	0.246	0.557	0.292	0.361	0.726	0.265	0.811	0.631
2026	0.264	0.555	0.318	0.376	0.733	0.271	0.816	0.647
2027	0.282	0.603	0.344	0.391	0.739	0.276	0.821	0.664
2028	0.300	0.618	0.370	0.407	0.746	0.282	0.826	0.680
2029	0.318	0.641	0.397	0.422	0.753	0.288	0.831	0.697
2030	0.337	0.664	0.423	0.437	0.760	0.293	0.836	0.713
2031	0.355	0.687	0.449	0.452	0.767	0.299	0.841	0.730

). From Table 4, it can be observed that over the next decade, under the sustained attention of the Party towards education and policy-driven initiatives, the level of modernization in higher education development in the eight ethnic provinces and regions will experience a significant surge. Guangxi’s overall modernization level is projected to reach 0.841, while Tibet is anticipated to achieve 0.355.

To ensure the robustness of our conclusions, this study employs two methodological approaches. Firstly, we applied a 1% winsorization to the core variables at both the upper and lower tails to mitigate the potential influence of outliers on the regression results. This data treatment helps to eliminate extreme values that might distort the analysis.

Secondly, drawing upon established research practices, including previous work by Liang Qingqing (the corresponding author), we selected alternative core explanatory variables for robustness testing. Specifically, we used the number of undergraduate students enrolled and the number of postgraduate graduates (with a one-period lag) as substitute variables in the regression equation. These variables have been widely recognized as reliable indicators in similar studies.

The results of these robustness checks consistently support our initial findings, confirming the reliability and stability of our conclusions. Both methodological approaches yield results that are consistent with our primary analysis, thereby strengthening the validity of our research outcomes.

6. Conclusions

Based on preliminary research data, the current weaknesses and key areas for improvement in higher education development in the eight ethnic provinces and regions are summarized in

Table 5. Weaknesses in the current higher education modernization development of the eight ethnic provinces and regions and subsequent advancement paths.

Province	Weaknesses			Key Advancement Paths
Tibet	A4 (0)	A5 (0.001)	A1 (0.013)	1. In response to the low level of internationalization in higher education, amidst the drive for global economic integration and societal informatization, various approaches and methods should be employed to promote the internationalization of higher education. The focus should primarily be on the internationalization of educational resources and educational ideologies.; 2. In response to the relatively low level of informatization in higher education, given the widespread and deep application of modern information technology, initiatives should be accelerated to advance educational informatization. This entails leveraging informatization construction to promote innovation in education and teaching. Measures include establishing educational resource platforms, among others.; 3. To address the low level of equity in higher education, it is essential to highlight equality in educational opportunities, fairness in the educational process, and equity in educational outcomes.; 4. In response to the relatively low level of high-quality “input–output” indices in higher education, it is necessary to increase investment in higher education. This will facilitate the interaction between the modernization of Chinese higher education and the high-quality development of the economy.
Inner Mongolia	A4 (0.452)	A2(0.51)
Qinghai	A3 (0.031)	A5 (0.032)	A4 (0.04)
Xinjiang	A2 (0.201)	A3 (0.298)	A4 (0.322)
Yunnan	A2 (0.152)
Ningxia	A4 (0.162)	A1 (0.175)	A5 (0.198)
Guangxi	A2 (0.177)
Guizhou	A2 (0.156)	A4 (0.348)

. The findings can be categorized as follows:

• Internationalization of Higher Education:
  Significant improvements are needed in Tibet (0), Qinghai (0.04), Ningxia (0.162), Xinjiang (0.322), Guizhou (0.348), and Inner Mongolia (0.452). These regions exhibit relatively low levels of international engagement, which is critical for enhancing global competitiveness and academic exchange.

2.

Equity in Higher Education:

Key regions requiring attention include Yunnan (0.152), Guizhou (0.156), Guangxi (0.177), Xinjiang (0.201), and Inner Mongolia (0.51). Addressing disparities in access and quality is essential to ensure equitable educational opportunities across these provinces.

3.

Informatization of Higher Education:

Tibet (0.001), Qinghai (0.032), and Ningxia (0.198) have been identified as regions with the most pressing need for improvement in digital infrastructure and technology integration. Enhancing informatization is crucial for modernizing educational delivery and expanding access to digital resources.

4.

High-Quality “Input–Output” Efficiency in Higher Education:

Tibet (0.013) and Ningxia (0.175) require targeted interventions to optimize resource allocation and improve the efficiency of educational investments. Strengthening the alignment between inputs and outputs is vital for achieving sustainable development.

5.

Social Service Capacity in Higher Education:

Qinghai (0.031) and Xinjiang (0.298) need to enhance their higher education institutions’ ability to contribute to societal development. This includes fostering partnerships with local industries and communities to address regional challenges and promote economic growth.

To advance coordinated development, it is imperative to construct a comprehensive path that addresses intensity, breadth, depth, and effectiveness across multiple dimensions. This involves not only policy adjustments but also a shift in institutional practices to ensure that higher education systems are responsive to the evolving needs of society [29,30,31]:

In conclusion, these findings highlight the specific areas where targeted policies and investments are needed to address regional disparities and promote the overall development of higher education in these provinces. By focusing on these key areas, policymakers can ensure a more balanced and equitable advancement of higher education across the eight ethnic regions.