The adaptability of discipline structure and industrial structure is the key for higher education to support high-quality economic and social development and improve its contribution ability. Due to the different classification logic between industry and discipline, it is difficult to measure the adaptability directly. By integrating theories of human capital, industrial chain and task model, the industrial categories are grouped into six functional types according to the functional orientation of industrial chain, and then divided into five industries according to patent density and per capita output value: innovation-driven high-efficiency, capital operation high-output, technology application support, labor absorption service and public service guarantee, and the mapping relationship between industry and discipline is established through core task types. On this basis, a theoretical framework of adaptability including three core dimensions of category structure, hierarchical structure and spatial structure and four auxiliary dimensions of policy adaptation, scale adaptation, quality adaptation and guarantee adaptation is constructed, and an index system is given. This framework provides theoretical basis and practical tools for the dynamic adjustment of discipline and major structure.

As generative artificial intelligence becomes embedded in higher education, individual differences in college students’ artificial intelligence literacy warrant attention. Using survey data from 1,364 college students, this study employed structural equation modeling to examine associations among life satisfaction, the overall importance attached to career-decision factors, creative growth mindset, and artificial intelligence literacy, while controlling for demographic, educational-stage, institutional, and disciplinary factors. Life satisfaction, the overall importance attached to career decision factors, and creative growth mindset were positively associated with artificial intelligence literacy; the first two were also positively associated with creative growth mindset. Both statistical indirect associations were significant, and the findings remained stable across alternative specifications. The results indicate that artificial intelligence literacy is associated with students’ current subjective evaluation of life, the importance they attach to career decision factors, and beliefs in the malleability of creativity. Because the data are cross-sectional and same-source self-reports, temporal ordering, causal direction, and mediation require further investigation.

Against the backdrop of China’s strategy to expand high-level opening up in education, international rules constitute an important institutional foundation for regulating cooperation in cross-border higher education and participating in global education governance. Drawing on 25 international rule documents on cross-border higher education issued by international organizations, sovereign states, and non-governmental organizations, this study conducts a textual analysis based on Scott’s three-pillar theory of institutions. The findings show that the international rules governing cross-border higher education form a three-dimensional framework comprising the balancing of governance tensions, the building of institutional trust, and the construction of cross-domain consensus. These three dimensions correspond respectively to the constraining and regulatory mechanism of the regulative pillar, the value-guiding mechanism of the normative pillar, and the meaning-making mechanism of the cultural-cognitive pillar. The existing international rules framework still faces several limitations, including regulatory gaps concerning emerging forms of cross-border education, fragmentation of quality assurance standards, questions about the effectiveness of degree recognition systems, and limited enforceability of the international rules system. Accordingly, China’s participation in the global governance of cross-border education should progressively move from rule alignment toward institutional innovation and the co-construction of international rules.

The establishment of research institutes in Hong Kong by mainland universities represents a novel experiment in cross-border higher education spatial production under the “One Country, Two Systems”framework. This article conceptualizes these institutes as “strategic differential spaces” and employs the “materiality, imagining and social practice” triad from spatial production theory to systematically analyze their inherent logic of spatial generation. The formation of these spaces is rooted in the structural transformation of global knowledge production and the strategic integration of multiple scales. Yet, operating within Hong Kong’s highly legalized and market-driven environment, they confront institutional frictions, including impeded cross-border flows of personnel, funding, and equipment, as well as conflicts in evaluative frameworks and governance cultures. In response, actors continuously reshape the boundaries and operational logics of these spaces through organizational restructuring, hybrid governance, and discursive adaptation. However, the enduring constraints of institutional identity ambiguity and resource dependency continue to impede their sustainable development. Moving forward, it is imperative to establish cross-border institutional articulation mechanisms and deepen their embeddedness in Hong Kong’s local innovation ecosystem, so as to fully actualize their strategic potential.

The information revolution is rapidly permeating various fields of socio-economic development, promoting digital transformation and forming new quality productive forces. It has facilitated and continuously advanced the digital transformation of education, bringing profound changes to the field. Education has entered a new form of development characterized by “maintaining principles while innovating”. On the one hand, digital education brings “innovation” to the existing educational form, enriching and developing modern education; on the other hand, it is “maintaining principles”, safeguarding the fundamentals and grasping the direction for educational development, embodying the dialectical unity of “change” and “unchanging”, inheritance and development, principle and creativity. It presents the commonalities and characteristics of the modern educational system, and gives rise to a new educational form - new quality education. It is a transformation of education to adapt to new quality productive forces, promoting a qualitative leap and improvement in educational services for economic and social development.

This paper begins with the characteristics of AI innovation and the patterns of talent development, clarifying the shift in the underlying logic of cultivating top-notch innovative AI talent and the three critical challenges involved. Through a review and comparison of typical practices in countries such as the United States, the United Kingdom, and France, it then identifies the common approaches adopted by these countries in addressing the challenges above. On this basis, it further reveals the internal mechanism of unconventional cultivation, proposing that the cultivation system be transformed toward hub integration, elastic agility, and ecological synergy, thereby constructing an educational ecosystem that supports the co-evolution of talent development and innovation systems. Grounded in China’s national conditions and institutional strengths, the paper puts forward practical pathways for the independent cultivation of top-notch innovative AI talent, so as to provide a theoretical basis and practical reference for China to accelerate the development of new competitive advantages in AI talent.

Acceleration is a defining feature of modern society. In his theory of social acceleration, Hartmut Rosa classified the various forms of social acceleration and analyzed three engines driving it. Building on this foundation, this paper proposes a theoretical framework of differential structures and, consequently, introduces a new metaphor—the “differential” — to describe the role of university in an accelerating society. This article argues that social structure is not governed by a single, uniform speed; rather, it consists of fixed components, fast and slow sectors, and a “differential” that mediates between them. This “differential” regulates disparities in speed across different sectors, thereby preventing fragmentation within society. In the context of an accelerating society, the university functions precisely as such a crucial “differential”, serving as an intermediary that sustains the connection between fast and slow sectors. To secure its legitimacy within an accelerating society, the university, as a “differential”, must place greater emphasis on the production of knowledge associated with the slow sector and undergo a process of “re-educationalization” and promote public reflection. In doing so, it can provide direction and boundaries for social acceleration, thereby avoiding the slippery slope of disorderly acceleration.

In the process of digitalization of higher education, Global South countries are facing both historical opportunities of technological advancement and structural difficulties. Policy discourse has inherent tension and regional heterogeneity. Employing Critical Discourse Analysis and a postcolonial framework, this study examines 47 higher education digitalization policies from 21 Global South countries. Findings reveal in text analysis the discourse themes focus on digital infrastructure and educational equity, independent talent cultivation, digital sovereignty and discourse power. In discourse practice analysis, regional discourse production presents three models: state-led, internationally dependent, and multi-competitive. In social practice analysis, discourse power structure in digital transformation is marked by the tension between discursive dependence and digital sovereignty. It is argued that China can gather Global South support to co-build an inclusive global digital education governance order through discourse reconstruction, platform collaboration, and independent governance.

Based on survey data from 17,838 graduating Master’s and PhD students (Class of 2025) across 46 Chinese universities, our study operationalizes the boundary into two dimensions: behavioral boundary and guidance boundary. Regarding the behavioral boundary, findings reveal a “Red-Yellow-Green” risk zoning of supervisor behaviors; “sending late-night messages” and “forbidding internships” constitute the Red Zone of unacceptable behavior. Furthermore, a high-quality supervisor-student relationship significantly reduces student rejection of Yellow and Green zone behaviors, but cannot override this Red Line. Regarding the guidance boundary, the supervisor’s role manifests as an “academic core, career support, and humanistic care” trinity. When supervisors additionally act as career planners and life mentors, students’ satisfaction, well-being, and employment rates improve significantly. Finally, the optimal dominance model for co-creation evolves dynamically: from student autonomy (early-stage) to joint consultation (mid-stage) and supervisor gatekeeping (late-stage).

Following the scale expansion during the 14th Five-Year Plan period, Chinese higher education has entered the mid-to-late stage of universalization and now stands at a critical turning point from scale expansion to quality enhancement, from discipline-centered development to national-mission orientation, and from uniform evaluation to classified governance. This paper argues that China’s current challenges are not merely technical problems of management but structural tensions arising from the transition toward a high-participation higher education system. The most pressing issues include institutional barriers to interdisciplinary development, blurred positioning among local application-oriented universities, structural mismatches between talent supply and industrial demand, and the persistence of the “Five-Only” evaluation orientation. Classified development and differentiated evaluation should therefore serve as the central policy lever for the 15th Five-Year Plan period. An agile mechanism for discipline adjustment, an internally driven quality assurance system, and stronger integration of education, science and talent are needed to transform China’s higher education system from scale advantage to substantive strength.

Establishing a scientific categorization-based evaluation system for higher education institutions constitutes the institutional foundation for building a leading country in higher education. Exploring reforms in construction performance evaluation that facilitate “Double First-Class” construction universities to focus on the goal of world-class universities is not only a requirement of the “categorization-based evaluation reform for higher education institutions”, but also a crucial means to guide China’s “Double First-Class” construction universities to consciously serve the national strategy for scientific and technological innovation and enhance their own international competitiveness. Based on a discussion and understanding of the importance of categorization-based evaluation and categorized development models for higher education institutions, as well as their logical interconnections, and following an elaboration on the interpretation of world-class universities and the “two autonomies” mission and responsibility of “Double First-Class”construction universities, this paper proposes that the design of performance evaluation for “Double First-Class” university construction must adhere to three principles: first, to guide “Double First-Class” construction universities toward “improving the quality of independent talent cultivation and producing top-notch innovative talents”; second, to enable them to make outstanding contributions to the nation’s “high-level self-reliance and self-strengthening in science and technology and enhancement of independent innovation capability”; and third, to advance the “modernization of internal university governance”. On this basis, the paper delves into, synthesizes and articulates the key evaluation dimensions and their constituent elements for constructing a construction performance evaluation system for “Double First-Class” university from three major directions: “cultivation of top-notch innovative talents”, “contributions to scientific and technological innovation and research and development（R&D）”, and “modernization of internal university governance.”

China’s high-level research universities are core components of the national strategic scientific and technological strength. However, the technology transfer rate of university scientific and technological achievements remains low, and the transfer cycle is protracted, resulting in insufficient release of innovation value. University-industry collaboration is widely regarded as a critical pathway to cross the “valley of death”, yet its impact on technology transfer outcomes, underlying mechanisms, and optimal organizational forms still lack large-sample empirical support. Based on empirical analysis of over 610 000 patent transfer records from 42 “Double First-Class”construction universities, our findings show that university-industry collaboration significantly enhances the quantity, quality, and speed of technology transfer. The enterprise-led model, deep collaboration, and strong partnerships between universities and leading science and technology enterprises are particularly effective in unlocking synergistic value. University-industry collaboration promotes the transition of research outcomes from the scientific realm to the industrial sector by improving technological advancement, technological depth, legal stability, and commercial value. We recommend strengthening enterprise-led collaborative innovation, establishing long-term and stable university-industry cooperation mechanisms, leveraging the leading role of science and technology flagship enterprises, and facilitating a paradigm shift in university technology transfer from “output-oriented” to “demand-driven”.

Cross-jurisdictional urban clusters higher education hubs, such as the Cascadia Innovation Corridor and the Guangdong-Hong Kong-Macao Greater Bay Area, play a significant role in the global knowledge economy. The construction model of these hubs depends primarily on the interaction between their functional objectives and coordination mechanisms. The Cascadia Innovation Corridor, relying on collaboration among diverse actors and various flexible mechanisms, embodies a “market-driven, ecologically symbiotic” higher education hub model under limited transnational governance. In contrast, the Greater Bay Area, relying on institutionalized co-governance among diverse actors and guidance from national strategies, exhibits a “government-led, strategically coordinated” higher education hub model, while simultaneously facing constraints arising from rule misalignment and collaborative friction caused by institutional disparities. The construction of cross-jurisdictional higher education hubs requires the facilitation of the cross-regional flow of factors such as students, talent, knowledge and innovation, the formation of coordination mechanisms that align with functional objectives, institutional contexts and industrial foundations, and the transformation of institutional differences into resources for regional innovation governance.

Special Admission Plans have expanded opportunities for students from underdeveloped areas to enter key universities, yet “fairness in access” does not automatically lead to“fairness in process and outcomes”. Drawing on the college student transition model, this study uses a transition support program at a top “Double First-Class” construction university as a quasi-experimental setting and adopts a mixed-methods design to examine its mechanisms and practical boundaries. The findings show that: first, students who participated in the program performed significantly better than non-participants in academic preparedness, sociocultural preparedness, and learning engagement, while no significant difference was found in academic performance; the program indirectly influenced grades by improving students’preparedness and learning engagement. Second, the program’s greatest value lay not in academic pre-teaching, but in sociocultural empowerment through decoding implicit university rules and reshaping support networks. Third, due to regional resource disparities, students admitted through special admission plans showed internal heterogeneity in soft skills such as English and programming, making a uniform intervention model prone to a “one-size-fits-all” dilemma. University support systems should therefore shift from homogeneous academic remediation to precisely differentiated cultural navigation and institutional decoding, using sustained support to break down hidden academic barriers.

Based on a multidisciplinary perspective, the similarities and differences between growth and development as well as their measurement methods were discussed, and the concept of higher education development was analyzed. Common development indicator systems, such as the Human Development Index (HDI), Social Progress Index (SPI), Sustainable Development Goals (SDGs), as well as Global Innovation Index (GII), Oslo Manual, European Innovation Scoreboard (EIS), World Competitiveness Yearbook (WCY), and Global Soft Power Rankings, were introduced, along with measurement indicators and results for educational development, and changes in China’s development were also examined. The design rationale, indicator screening and analytical framework for the two primary indicators, eight secondary indicators, and twenty-four observing indicators of the Higher Education Development Index (HEDI) were discussed, as well as data collection, processing, and calculation methods. Recommendations were proposed for result interpretation, public literacy enhancement, and sustained research commitment of HEDI.

Advancing university classification evaluation carries the strategic mission of building a leading country in education and serves as a key pathway for reforming higher education governance mechanisms. Through scientific evaluation, classification systems guide universities in precise positioning, structural optimization, and internal motivation enhancement, thereby addressing the “homogenization” dilemma and driving higher education toward connotative, distinctive, and high-quality development. Currently, profound inherent tensions exist between the value objectives of university classification evaluation and its practical implementation, manifested in three major challenges: insufficient classification criteria, homogenized evaluation indicators, and distorted functional orientations. It is essential to fully leverage policy momentum for classification development, strengthen evaluation system construction to stimulate diversified institutional potential, develop evaluation tools that reflect institutional characteristics, and improve outcome application mechanisms to enhance evaluation effectiveness. These measures will effectively guide higher education from “scale expansion” to “quality-driven specialization”, ultimately achieving the goal of establishing a high-quality higher education system.

Transition efficacy is a core metric for the Pilot Reform Program of Enrollment for Basic Disciplines(PRPEBD). Focusing on the divergence between students’ enrollment motivations and their post-graduation destinations under the Pilot Reform Program of Enrollment for Basic Disciplines, this study conducts an empirical analysis based on follow-up survey data from two cohorts of participants at a pilot university, examining how initial enrollment motivations influence students’ ultimate career trajectories by shaping their intellectual, behavioral, aspirational, and interest-oriented development during their university years. Results show that pathways are highly congruent with motivations: “interest-driven” students transition at significantly higher rates than their “prestige-driven” counterparts. Mediation analysis reveals that this effect is channeled through professional interest, academic performance, and career aspirations, while research participation remains insignificant. These findings suggest that selection should better identify intrinsic motivation and academic interest, and that cultivation should shift from outcome-oriented assessment to process-oriented development to promote substantive rather than merely formal transition.

The four-year engineering technology education (ETE) in the United States. shares remarkable similarities with the vocational undergraduate engineering technology education in China. While ETE is oriented toward cultivating engineering technologists, the labor market presents a starkly different reality. The ambiguous distinction between engineering technologists and engineers has caused many ETE graduates to compete with engineering graduates for similar positions. Additionally, vested interest groups often display professional protectionism, erecting institutional barriers for ETE graduates aspiring to obtain professional engineer licensure. Furthermore, the diminished emphasis on mathematics and science, coupled with the rapid pace of technological change, has led to a remarkable trend of shorter career lifespan in technical roles among ETE graduates. These factors collectively constrain the long-term expansion of ETE in the United States. China should define the objective of vocational undergraduate ETE as application engineers, promote the effective alignment between ETE and the professional engineer licensure system, and strengthen mathematics and science courses.

The rise of Artificial Intelligence (AI) has exposed a certain predicament of the traditional university education model. Although many universities have introduced AI-related courses, and some have made them compulsory, these courses are still often taught through standardized pedagogies inherited from the industrial age. As a result, knowledge marked by generation, openness, and nonlinearity is delivered through an industrial framework shaped by linearity, uniformity, and control. This contradiction may be described as the paradox of AI education, or, metaphorically, as “horse-drawn carriages pulling steam engines.” Student silence, disengagement, and absenteeism are outward signs of this deeper problem. What higher education now needs is not simply more AI instruction, but a new paradigm of human–AI coexistence: one in which students are recognized as agents of learning, teachers become designers of future learning environments, and education moves from “teaching AI” to “learning with AI.” Only through such a shift can higher education respond to technological change while preserving its humanistic purpose. While AI will undoubtedly transform educational concepts, teaching methods, and assessment, the fundamental mission of the university education remains unchanged. Only is this way can university education truly fulfill its fundamental mission in the AI era.

Promoting the classification reform and development of universities is the core agenda for building a leading country in education. From the perspectives of history, academia, and society, classification development is the inevitable trajectory of higher education evolution. The differentiation of knowledge forms determines the rational basis for the categorized reform and development of universities, and the three attributes of education require categorized development to meet the national strategy and people's expectations. We must promote the classification reform of universities with a systematic thinking, establish a categorized university system, reform the university evaluation system, improve the university incentive system, strengthen the university supervision system, create a policy environment and social atmosphere, and facilitate the implementation and effectiveness of the classification reform and development of universities.

The fundamental orientations of research universities, application-oriented universities, and skill-based universities, along with their specific positioning regarding educational levels, service directions, disciplines, and specialties, do not exist in isolation or fragmentation. Instead, they form an inherent unity grounded in knowledge. Unfolding and interacting according to the order of knowledge structure, they assume different roles and fulfill distinct responsibilities and missions within the division of labor in knowledge inheritance, production, innovation, and application. Currently, various forms of “academic drift” pose challenges to university orientation. The underlying causes lie in the hierarchical understanding of knowledge structure, traditional dependency in development paths, identity-driven resource allocation, and a homogenized evaluation system. To overcome this predicament, it is essential to adhere to the principle of knowledge unity. This involves restructuring the categorized evaluation system, establishing goal- and contribution-oriented resource allocation, reshaping the organizational culture of the knowledge division of labor, and constructing a value narrative centered on diverse forms of excellence, thereby achieving differentiated, distinctive, and high-quality development within the higher education system.

Universities are an important part of the national innovation system, and a concentrated intersection of education, science and technology, and talent, it is imperative to promote the integrated development and reform of education, science and technology, and talent in universities. Promoting the construction of new R&D institutions in universities is conducive to promoting the cultivation of practical and innovative talents through industry-academia-research collaboration, advancing organized research and boosting commercialization of scientific and technological achievements efficiently, facilitating the accumulation of top talents, stimulating the vitality of talents, and promoting the integrated development of education, science and technology, talents in universities. In response to the challenges in promoting the construction of new R&D institutions in universities, it puts forward some countermeasures and suggestions in order to better promote the integrated development of education, science and technology, and talents in universities, such as strengthen the top-level design clarify the strategic role of the construction of new R&D institutions in the development and reform of universities; deepen the reform of cultivation mode of postgraduates, and build a highland for cultivating top-notch innovative talents and outstanding engineers; establish support mechanism, incentive mechanism and control mechanisms to promote the professional construction and marketization construction of new R&D institutions; facilitate the flow of innovative resources between universities and new R&D institutions, and promote institutional and cultural innovation in universities.

The construction of an autonomous knowledge system of Chinese pedagogy is an academic proposition arising from a specific spatiotemporal perspective. This constructive process adheres to a macro spatiotemporal vision that integrates Chinese and foreign, ancient and modern perspectives, and proceed as a whole with the development strategy of integrating diverse ideological resources from both China and the past and present, highlighting Chinese characteristics in the tension between local educational realities and global educational civilizations. It achieves inheritance and innovation through cultural development and responses to contemporary issues, and comprehensively promotes innovation in the disciplinary, academic, and discourse systems of pedagogy within the unity of self-discipline and open integration. Ultimately, it shapes an autonomous knowledge system of Chinese pedagogy that possesses both theoretical grounding and an open disciplinary vision, as well as autonomous expression and extensive dialogic capacity.

This study constructs a structural equation model incorporating the interdisciplinary education environment, interdisciplinary learning engagement, and creative thinking to examine the impact of the interdisciplinary education environment on the development of creative thinking among top innovative talents. The findings show that interdisciplinary courses have both significant positive direct effects on creative thinking and indirect effects through curricular and co-curricular interdisciplinary learning engagement. Student-centered teaching has no significant direct effect on creative thinking, but exerts a positive indirect effect by enhancing co-curricular interdisciplinary learning engagement. Organizational support—including emotional support, innovation support, and personality development support—demonstrates differentiated direct and indirect effects on creative thinking. These findings suggest the need to strengthen the alignment between interdisciplinary curricula and teaching approaches, promote the integration of formal and informal learning contexts, and establish a multidimensional and differentiated support system to facilitate the high-quality cultivation of top innovative talents.

Classification-based development of higher education institutions is an important indicator of the maturation of a higher education system. In the process of the formation and evolution of the classification system for university in China, three structural features have become deeply intertwined: a vertical hierarchy based on institutional levels, a horizontal classification rooted in industrial sectors and academic disciplines, and a resource allocation pattern centered on key construction projects. Their interplay has caused institutional classification to gradually devolve into hierarchical ranking in practice. This predicament is jointly shaped by cultural, fiscal, and governance factors: a monolithic standard of success has eroded institutional type identity; a fiscal logic that privileges selectivity over baseline support has undermined equity across types; and homogenized evaluation systems have rendered classification rules persistently ineffective. To make classification operational, fiscal restructuring should serve as the entry point, establishing category-specific funding guarantees and a differentiated appropriation system while advancing type-based performance evaluation and recalibrating governance instruments, so that institutional reform creates a practical foundation for cultural transition and gradually builds a higher education classification system that accommodates diversity and ensures baseline equity.

Drawing on spatio-temporal sociology and using a qualitative longitudinal diary-interview design, this study follows 44 first-year undergraduates from two elite universities over two years to examine the spatio-temporal tensions and divergent trajectories in top-notch students’ high school-to-university transition. The findings show that the transition involves the reconfiguration of cognitive, interactional, and choice spaces, together with a misalignment between institutional and individual time, which places students in a liminal state. Students cross this liminality by reconstructing their individual spatio-temporal order, and their capacity to do so depends on the activation of subjectivity. Three trajectories are identified accordingly: through positive interaction with the institution, students achieve coordination between subjective and objective spatio-temporal orders, cross liminality, and develop subjectivity; when rules are difficult to decode and support is insufficient, students struggle to renew their meaning frameworks, leading to a rupture between subjective and objective spatio-temporal orders, prolonged liminality, and suspended subjectivity development; under performance competition, students carry over their high school inertia, resulting in a mismatch between subjective and objective spatio-temporal orders, an “adaptation trap,” and unactivated subjectivity formation. The study thus calls for process-oriented support systems, a more enabling evaluation ecology, and stronger efforts to activate students’ subjectivity.

The “loose coupling” phenomenon in traditional industry–education integration has constrained the effectiveness of practice-based education for engineering graduate students. As a practice platform doubly embedded in both academia and industry, supervisor-led academic spin-off provide a new observational setting for examining the mechanisms through which practice-based education is realized. Based on 653 questionnaires, this study analyzes the educational effectiveness of supervisor-led academic spin-off as internship platforms for engineering graduate students. The findings show that, compared with internships in ordinary enterprises, supervisor-led academic spin-off are significantly associated with higher levels of knowledge and skills and with some forms of research output, indicating a certain platform advantage. Distinct participation-role differentiation also exists within the platform, which can be classified into three types: peripheral participants, technically oriented participants, and comprehensive participants; these different roles are associated with differentiated educational outcomes. In addition, educational effectiveness is further shaped by factors such as opportunity allocation, output rules, participation boundaries. So, improving the quality of practice-based training for engineering graduate students should go beyond platform construction and place greater emphasis on platform governance, particularly in task allocation, supervisory mechanisms, and participation pathways.

Against the backdrop of the deep advancement of education digitalization strategies, revealing the intrinsic mechanisms of the deep integration of artificial intelligence and higher education is essential for building a high-quality intelligent education ecosystem. Based on STS theory and the TOE framework, this study extracts five conditional variables: technological autonomy, leadership impetus, organizational synergy, application coverage, and ecological openness, while classifying integration levels according to the SAMR model. By employing fsQCA on 53 “AI + Higher Education” typical application scenarios recognized by the Ministry of Education, this paper explores the causal mechanisms driving the digital transformation of higher education. The findings indicate that the six configurations generally follow two modes: “Organization-Driven Transformation” and “Technology-Ecology Symbiosis”. Accordingly, it is proposed to establish a top-level strategy of mutual construction between organizational change and technological empowerment, build a borderless and open intelligent landscape, and precisely match transformation pathways based on resource endowments, so as to construct a high-quality intelligent education ecosystem featuring human-machine collaboration, co-creation, and sharing.

Since the early 21st century, in response to the challenges of globalization and socio-economic transformations, the European Union (EU) has actively promoted the institutional transformation of entrepreneurship education in higher education institutions from a spontaneous, selective and fragmented approach to an organized, universal and standardized model. From a broad perspective, economic and technological changes have driven shifts in educational philosophies and institutional arrangements. Through continuous adjustments to the positioning, objectives, and competence frameworks of entrepreneurship education, the European Commission has developed a multi-level, networked, and systemic framework. Overall, this restructuring is characterized by a focus on key priorities, the removal of structural bottlenecks, and the strengthening of institutional support mechanisms.During this process, higher education institutions have advanced educational approaches, training models, and quality assurance practices, enhancing talent development through integrated entrepreneurship education ecosystems. Drawing on the EU’s experience, this paper suggests that China may consider deepening organizational restructuring, establish a coordinated entrepreneurship competence framework, and strengthen faculty professional development. It further suggests enhancing innovation capacity and promoting knowledge transfer. These efforts aim to support high-quality entrepreneurship education aligned with the goals of building a modern socialist country.

Interdisciplinary integration has emerged as a critical imperative for technological innovation and talent cultivation. Grounded in the dual logic of knowledge boundaries and control inherent in disciplines, this study employs Basil Bernstein’s concepts of classification and framing to deconstruct the dynamics of integration. The analysis reveals that interdisciplinary practice entails a structural shift from “strong” to “weak” classification—signifying increased permeability across disciplinary borders—and a transition from “strong” to “weak” framing, reflecting a diversification of control over knowledge production. Based on these dimensions, four ideal types are proposed: institutionalized multidisciplinary coordination, spontaneous multidisciplinary cooperation, institutionalized fusion innovation, and emergent frontier exploration. It reveals the evolutionary logic of Interdisciplinary integration, moving from a simple combination to a deep collaborative creation. The study concludes that advancing interdisciplinary integration requires not the dissolution of existing disciplines, but the navigation of the embedded agency paradox, thereby sustaining a productive tension between institutional stability and epistemological innovation.

Postdoctoral fellows are a strategic force in promoting the construction of an educational and technological powerhouse. Based on the analysis of policy documents, academic literature, official reports, and other materials, from the perspective of historical institutionalism, it is believed that since the establishment and implementation of China’s postdoctoral system in 1985, the postdoctoral funding policy has gone through the elite funding stage under national unified funding (1985-1992), the diversified funding stage under scale expansion (1993-2007), the strategic precision funding stage under quality orientation (2008-2015), and the diversified collaborative funding stage under system reconstruction (2016 to present). The policy function has shifted from emergency talent supplementation to serving the national innovation strategy, resource allocation has shifted from planned supply to performance incentives, the governance system has shifted from national monopoly to central, local, unit and social co governance, and the value concept has shifted from affairs management to supporting career development. Further research will reveal the logic of policy changes from macro level deep structure, meso level path dependence, and micro level dynamic mechanisms. In the future, we should strengthen the guidance of central finance, establish a tiered and precise funding system, and strengthen the institutional support for the career development of postdoctoral fellows, in order to promote the high-quality development of postdoctoral funding policies.

Research universities are an important component of the Carnegie Classification of Institutions of Higher Education in the United States, and its classification method has been continuously improved and refined in various updates. Before the 2021 edition, the classification of research universities was included in the basic category; the 2025 edition renamed the Basic Classification as the 2025 Institutional Classification, while adjusting the classification of research universities to a separate category of Research Activity Designations, with corresponding optimizations and adjustments to the classification methods and standards. The new classification, while retaining the two core indicators of “number of research doctorates awarded” and “research expenditure” to distinguish three types of research universities, has dozens of additional indicators, helping to accurately present the actual development status of each research university from multiple perspectives. It is recommended to scientifically plan the development scale of China’s research universities, thoroughly evaluate the feasibility of core classification indicators such as the number of doctoral degrees awarded and research expenditures, objectively establish basic standards for independent classification, and set up several observation indicators to build a multi-dimensional research university classification system with Chinese characteristics.

Educational evaluation is pivotal to building a strong nation in education, and classification framework holds strategic significance for comprehensive reform. China’s graduate education classification evaluation has undertaken valuable explorations but still faces challenges such as blurred classification ontologies and mismatched functions. This study constructs an “Adaptive-Ecological Classification”(AEC) Framework for Evaluation, grounded in systems thinking and the foundational logic of “ontology-driven, goal-oriented, and institutionally coordinated” classification evaluation. It proposes a practical pathway comprising macro-level ecological planning, meso-level value-oriented guidance, and micro-level standard system construction, providing theoretical underpinnings and practical guidance for building an autonomous classification evaluation ecosystem.

Based on large-scale student survey data, this study explores the underlying mechanisms by which AI influences college students’innovative thinking within curricular environments characterized by varying levels of “challenge” and “support”. The findings reveal that learning engagement acts as a bridge in enabling AI to foster innovative thinking. Specifically, AI exerts its effects indirectly primarily by stimulating deep cognitive and emotional engagement, and its efficacy is shaped by the curricular environment. The curricular environment exhibits a dual moderating logic of “amplification” and “substitution”: a “high challenge–high support” environment strengthens the “amplification” pathway mediated by learning engagement, whereas environments deficient in either challenge or support highlight the “substitution” pathway. The educational value of AI is not an intrinsic attribute but is co-constructed by the curricular environment through the synergy of challenge and support.

The typology method is grounded in Weber’s ideal type paradigm, constructing concepts to generate typologies that facilitate empirical analysis and comparison, thereby achieving the goal of explanatory understanding of social actions and their cultural meanings. This method is particularly well-suited to educational research, which is characterized by its humanistic objectives, heterogeneous subjects, and complex contexts. However, typology method is frequently misapplied in current educational studies. This paper systematically examines the paradigmatic tradition of Weberian ideal types, the typology method derived from it and its distinction form taxonomy. It proposes two distinct analytical approaches of typology: “typology as understanding” and “typology as explanation”. The conceptual features, technical procedures, and practical applications of these approaches are thoroughly discussed. The study aims to provide methodological guidance for the application of typology in educational research, offering an analytical pathway that balances theoretical advancement with real-world complexity. It seeks to enhance methodological reflexivity in Chinese educational research while providing robust conceptual tools for the explanatory understanding of educational phenomena and practices, promoting the research of iconic concepts and original theories in China’s educational research.

Against the backdrop of digital transformation in vocational education, the explicitation of tacit knowledge has emerged as a crucial issue for enhancing the quality of skilled talent cultivation. The essence of tacit knowledge explicitation lies in achieving multiple transformations: from tacit knowledge to formalized knowledge, from experiential knowledge to conceptual understanding, and from implicit information to explicit encoding. In practice, tacit knowledge explicitation faces numerous challenges, including epistemological misunderstandings, technical limitations and integration difficulties at the implementation level, fragmentation of meaning construction at the pedagogical transformation level, and institutional and mechanistic barriers at the environmental level. In this regard, it is necessary to construct a digitally-supported multidimensional framework for knowledge identification and extraction, innovate tacit knowledge representation strategies in digital teaching material design, and establish quality assurance and continuous updating mechanisms for digital teaching material development.