Based on a survey of university teachers from undergraduate universities across the nation, this study adopts latent profile analysis to investigate the typological characteristics, work performance, and intervention strategies related to job burnout among university teachers in China. The results reveal four latent types of job burnout: low burnout (62.1%), relatively high burnout (27.1%), low sense of achievement (5.8%), and exhaustion(5.0%). Among these, teachers with low burnout demonstrate the best work performance, followed by those with a low sense of achievement, while those categorized as exhausted and relatively high burnout exhibit poorer performance. Organizational emotional support, organizational instrumental support, research pressure, teaching pressure, and the pressure of balancing teaching and research significantly predict different types of teacher burnout. Universities should provide tailored organizational support for teachers of various burnout types, reform teacher evaluation systems to enhance the sense of achievement in teaching, and improve the classification management system to alleviate the pressure of balancing teaching and research.

The ongoing statistical analysis and tracking of academic hotspots in higher education research papers over the past 20 years provide crucial support and reference for accelerating the high-quality development of higher education. A study on 23 of the most influential education journals reveals an imbalance in the output of higher education research papers among different types of institutions. Public undergraduate universities dominate as the main contributors, with a significant proportion of publications coming from “Double First-Class”construction universities. High-contribution institutions account for a large share, while other types of institutions show low participation. Meanwhile, diverse institutions such as education administrative departments, educational research institutions, and overseas institutions are actively engaged in higher education research, demonstrating strong openness and integration.Based on keyword frequency analysis and expert opinions, the top ten academic hotspots in higher education research for this year have been identified. An analysis and assessment of their research progress, key viewpoints, and trends have been conducted.

Article 37(3) of the Academic Degrees Law serves as a catch-all provision for revoking academic degrees, covering both academic and non-academic grounds. By linking revocation grounds to the conditions required for initial degree conferment, the clause allows any breach of those conditions to potentially trigger revocation proceedings. However, actual revocation is warranted only when the conduct constitutes a “serious violation”. For academic misconduct, a “serious violation” must satisfy all three criteria: (a) the conduct falls within a category that university rules deem disqualifying for degree conferment; (b) the offending research output has been publicly disseminated; and (c) the conduct involves ghost-writing, plagiarism, or other forms of academic dishonesty of comparable severity. Serious non-academic breaches involve violations of the political or moral prerequisites for degree conferment. A serious political breach must constitute a crime of a political nature under the Criminal Law. A serious moral breach must violate either the Criminal Law or the Public Security Administration Punishments Law and be morally reprehensible. Crucially, revocation is justified only when such misconduct infringes upon the legal interests protected by the Academic Degrees Law, as manifested by causing significant negative social impact or seriously damaging the university’s reputation.

To uncover the multifaceted reasons behind the delayed graduation of doctoral students and its complex implications, an analysis of survey data from 2024 national academic degree doctoral graduates was conducted. The findings reveal: Firstly, there are significant differences in the reasons for delayed graduation among doctoral students of different background, the rigid requirement of paper publication generally aggravates the delay risk of all kinds of doctoral students. Secondly, many of those who delay graduation for meeting the needs of supervisor’s research project are passive delays; although their research output surpasses that of on-time graduates, they show notable disadvantages in the development of academic ability and academic interests. Thirdly, those who delay graduation to pursue higher-quality research or for overseas exchange are mostly active delays, achieving quality of academic training beyond that of on-time graduates. Based on these findings, it is recommended to reduce the paper publication requirements for doctoral students and strengthen the quality assurance mechanisms for dissertation research in doctoral education, incorporate delayed graduation of doctoral student into supervisor evaluation standard properly and improve their quality of supervision, implement a flexible educational system and provide long-term research support for top-notch innovative doctoral students.

Artificial intelligence technology poses fundamental challenges to the traditional teacher-student centered educational structure and urgently requires the construction of new educational models. The five element education model of “teacher-student-AI-environment-culture” proposes that the educational logic in the intelligent era should shift from traditional binary teaching between teachers and students to a multi element collaborative interactive network. The five element education model is student-centered with AI at its core. By reshaping learning methods, teaching methods, environmental ecology, and cultural atmosphere, it cultivates students’ core competencies of the “eleven abilities”—such as innovation and creativity—that enable them to master and surpass AI. Based on the previous exploration of Beijing Institute of Technology, this model provides an effective practical path for cultivating top-notch innovative talents in the era of intelligence.

Promoting the deepening application of artificial intelligence in university teaching is a crucial issue facing the digital transformation of higher education in China today, and it urgently needs to be explored in depth. Based on this, the study adopts a perspective shifting from “AI exclusion” to “AI empowerment”. By clarifying the concepts of “AI exclusion” and “AI empowerment”, it reveals that “AI exclusion” specifically manifests as ideological exclusion, institutional exclusion, organizational exclusion, and knowledge exclusion. These forms of exclusion follow diverse generative logics rooted in cognitive ideologies, policy systems, organizational structures, and knowledge transmission. In response to the real dilemma of “AI exclusion”, these orientations promote paradigmatic innovation across four dimensions: ideology, institutions, organizations, and knowledge. To eliminate “exclusion” and achieve “empowerment”, this study proposes a four-in-one integrated action pathway: “innovative theory + institutional establishment + organizational regeneration + contextual transformation”, aiming to deepen the application of artificial intelligence in university.

Significant achievements have been made in commercializing scientific and technological (S&T) achievements in Chinese universities. However, on the incentive mechanism, it needs to be seriously summarized in the experience and practices of reform and innovation, so as to further improve relevant policies, and accelerate the reform of three systems, such as individual column management of the transformation of service S&T advances, the evaluation of technology transfer talents and professional titles, and the investment of residual funds from horizontal scientific research projects for the transformation of S&T advances. The incentive mechanism reform of S&T advances transformation should be further people-oriented, such as asset management should pay more attention to the special characteristics of intangible assets by S&T advances, evaluation reform should further strengthen categorized assessment, horizontal research funding reform should further expand the autonomy of S&T personnel, and comprehensive reform of universities should further unclog blockages of incentive mechanism, so as to effectively solve the problems of some universities and their accomplisher of S&T advances being afraid to transfer, unwilling to transfer, and lacking funds to transfer.

In the era of digital transformation, Generative Artificial Intelligence (GenAI) has become an important tool for enhancing research efficiency; however, its specific impact on research output remains underexplored. Based on survey data from the 2024 national doctoral graduate survey, this study investigates the effects of GenAI on the research output of doctoral students using propensity score matching and inverse probability weighted regression adjustment methods. The results indicate that GenAI usage increases doctoral students’ total research output by 6.5% and international publications by 6.9%. The effect is particularly prominent for publications in top-tier journals, with a net effect of 16.5%. However, factors such as gender and age constitute major barriers to GenAI adoption, limiting some doctoral students from reaping the full technological dividends. Furthermore, heterogeneity analysis reveals that the benefits of GenAI use vary significantly across different disciplines and academic environments. For doctoral students with insufficient mentor guidance, although GenAI promotes the output of the total number of papers and international publications, it fails to yield significant benefits for top-tier journal publications. Accordingly, this study recommends the systematic integration of GenAI into doctoral training systems, the development of intelligent resource-sharing platforms, and the strengthening of ethical norms and fairness safeguards. These measures aim to promote the rational application of the technology and the equitable sharing of digital dividends, thereby fostering the high-quality and sustainable development of doctoral education.

To seek a solution to the problem of delayed graduation of doctoral students, this paper analyzes the trend and influencing factors of delayed graduation of doctoral students in China and the United States from an international comparative perspective. The results show that both the rate of recent doctoral students’ postponement and the cumulative postponement rate in China have been rising slowly. Nearly one-third of the current doctoral students are postponement doctoral students, and it is estimated that over 60% of the graduating doctoral students will be postponement doctoral students. The duration of study for doctoral students in the United States has remained at a high level, but it has slightly declined in recent years. From the perspective of influencing factors, the transformation of knowledge production models and the misalignment of the logic of doctoral student training, as well as the expansion of doctoral student enrollment and the imbalance of the training environment in departments and colleges, have shaped the macro background. The disintegration of students with academic culture, relationship networks, and departmental systems has constructed the micro picture. The above factors jointly induce a deviation between the training of doctoral students and the laws of advanced knowledge production, and thus lead to a gradual increase in the rate of delay. To alleviate the current situation of delayed graduation of doctoral students, China urgently needs to improve in the reform of the academic system, the construction of the diversion mechanism and the academic support for doctoral students.

China’s talent cultivation models demonstrate typological diversity and complex evolutionary paths. From the dual tension perspective of “local-international” and “traditional-innovative”, the talent cultivation models of Chinese universities can be identified as four ideal types: “international academic inheritance”, “international innovation leading”, “local cultural preservation” and “local innovation priority”. These types have a dynamic, interactive evolution driven by multiple factors such as disciplinary development needs and national policy guidance. Talent cultivation models in Chinese universities should balance global competition and local adaptation, as well as knowledge accumulation and innovative breakthroughs, to achieve the functional and strategic positioning of China’s higher education development.

With the rapid development of Generative Artificial Intelligence (GAI) technology, China has entered a new stage of high-quality development. While enhancing production efficiency across industries, the application of GAI has also introduced educational risks. In higher education, the involvement of Artificial Intelligence Generated Content (AIGC) in academic theses has increasingly been criticized for enabling academic misconduct such as ghostwriting, plagiarism, and fabrication. Based on an analysis of GAI’s underlying architecture, generative AI is essentially a logical computing tool devoid of autonomous intent. Research on generative AI should adopt an instrumentalist perspective. In reality, AIGC’s involvement in academic theses does not equate to other person’s writing, but its improper citation practices and inherent flaws may lead to plagiarism and fabrication. Based on the reality of anomie in the integrity of a comprehensive ban, the governance of AIGC should be shifted to standardized use. At the institutional response level, the following measures should be prioritized: strengthen explicit labeling mechanisms for GAI; clarify the verification obligations of degree applicants regarding AIGC; implement strict evaluation criteria by degree review committees to ensure academic integrity.

The development of an original philosophy and social science textbook system with Chinese characteristics is an inevitable requirement for accelerating the construction of high-quality textbook and high-quality education systems, is an era demand for achieving a systematic leap from a large country to a leading country in education. The proposal of original philosophy and social science textbooks and textbook system with Chinese characteristics is underpinned by contemporary, historical, and practical logic. Accentuating “Chinese characteristics” is the defining feature of the new era philosophy and social science textbook system. Highlighting originality is a hallmark of high-level philosophy and social science textbooks in the new era. The essence of original philosophy and social science textbooks with Chinese characteristics is distinguished innovative textbooks characterized primarily by independent and original innovation. To achieve a systematic leap towards an original philosophy and social science textbook system with Chinese characteristics in the new era, it is necessary to grasp the overall direction of ideological leadership, practice orientation, innovation drive, and systems integration.

Based on panel data from 56 institutions involved in the first round of China’s “Double High-Level Plan” from 2020 to 2023, this study employs a fixed-effects model and interaction-effect analysis to examine the enabling and inhibiting effects of digital transformation on industry-education integration. The findings indicate that digital transformation significantly enhances integration effectiveness through technological efficiency and resource consolidation; however, the marginal benefits exhibit an inverted U-shaped relationship, where excessive digitization can result in resource redundancy and weakened collaboration. The dispersion of professional structures and delays in technological infrastructure represent primary inhibitors, undermining the enabling effects through resource fragmentation and organizational inertia, respectively. Significant regional heterogeneity is observed, with institutions in the central and western regions displaying prominent “late-mover advantages”, while eastern institutions show diminishing returns. Therefore, digital initiatives should adhere to an optimal threshold to avoid the risks associated with over-digitization, coordinate technology investments with dual-qualified faculty training, and leverage enterprise collaboration and capability iteration to strengthen the technology-human synergy. Furthermore, professional structures should be dynamically optimized, infrastructure upgrades accelerated, and differentiated regional strategies adopted to establish complementary gradients and mitigate constraints stemming from resource fragmentation and organizational inertia.

The continuous analysis of vocational education research papers and hotspots over a decade provides important support for accelerating the high-quality development and construction of independent knowledge system of Chinese vocational education. A statistical review of research papers published in 27 education journals reveals that public undergraduate universities contribute a significantly higher proportion of publications than public vocational (junior college) institutions. “Double First-Class” construction universities and “Double High-Level Plan” colleges stand out as major contributors to vocational education research performance. In terms of regional distribution, the eastern region demonstrates a significantly higher volume of publications and greater institutional research participation than other regions. Research hubs have gradually formed, along with influential institutions and research communities with strong academic leadership in the field of vocational education. The research hotspots in vocational education exhibit a degree of continuity and show dynamic interactions with national policies, social issues, and higher education research. Based on a comprehensive analysis of keyword frequency, this study identifies the top ten academic hotspots in vocational education research for 2024 and provides an in-depth examination of the research progress, key perspectives and future research trends.

High school academic Olympiads have played a significant role in selecting and cultivating top innovative talents. Based on a three-year longitudinal dataset from a university participating in China’s Pilot Reform Program of Enrollment for Fundamental Disciplines (PRPEFD), this study used a mixed-method approach combining quantitative and qualitative research to compared the college development of Olympiad-trained and non-Olympiad students across three dimensions: academic performance, research engagement, and competency development. The study reveals that: Olympiad students significantly outperformed their non-Olympiad peers in academic performance and research participation in their freshman and sophomore years, though this advantage diminished gradually. Olympiad students also rated themselves higher in learning ability, communication skills, and self - efficacy, with the gap widening as grades progressed. Among students admitted through the PRPEFD, those with and without Olympiad experience showed no significant difference in academic performance but had a notable disparity in research participation. Building on empirical support for Olympiad-based admission policies and exceptional enrollment mechanisms under the PRPEFD, this article proposes refining discipline-specific selection criteria across institutional tiers, complemented by compensatory mechanisms for students from under-resourced regions, to establish a merit-based selection ecosystem that balances scientific rigor and inclusiveness.

The “student-centered” teaching management of undergraduate colleges and universities adheres to the center of students’ development, and promotes the realization of the main value of students, meets the learning needs of students and pays attention to the learning effect of students. Through the “triangular mutual evidence”, the study summarizes it into six dimensions, 29 elemental indicators, and takes the students of eight undergraduate colleges and universities in Jiangsu Province as the object to carry out the survey of “students’ needs in teaching management of undergraduate colleges and universities”, and uses the KANO model to analyze and optimize the method to calculate the Better-Worse coefficients of the corresponding indexes, and disperses the indexes in the establishment of a two-dimensional quadrant diagram. Based on this, it is proposed to solve the “urgency”, prioritize to meet the necessary needs of students for teaching management, pay attention to the “hope”, focus on improving the expectations of students for teaching management, and alleviate the “difficult worries”, and optimize students’ charismatic demand for teaching management in a targeted manner.

The Industry-University Collaboration (IUC) mechanism serves as a critical to alleviate the structural contradictions in talent cultivation between supply and demand. Based on a mixed-methods research utilizing AI-driven large language models, this study systematically explores the current situation and restrictive factors of enterprises’ deep engagement in IUC. It finds that a structural contradiction lies in the asymmetry of IUC engagement. Qualitative text analysis finds that, this contradiction primarily stems from four restrictive factors: systemic delay of teaching and research productivity in university, absence of protection for industries’ rights, inadequacy of incentive mechanisms, and information flow bottlenecks. Quantitative analysis confirms that the above factors exert significant cooling effects on enterprises’ engagement in IUC. Addressing these challenges, it is necessary to break the constraints of the higher education evaluation system, clarify the enterprises’ rights and responsibilities in IUC, establish multi-dimensional incentive mechanisms, to stimulate enterprises’ enthusiasm and promote effective IUC.

Top innovative talents are the core force underpinning national original innovation capacity and high-level technological self-reliance. At present, China’s integrated cultivation of top innovative talents is mainly led by secondary schools, with limited exploration extending downward to primary education and insufficient mechanisms effectively linking upward to higher education. Universities generally remain in a “post-hoc receiving” role within the talent selection and cultivation chain. Taking the role transformation of universities in integrated cultivation as a point of departure, this study draws on the cases of the United States, Germany, and Singapore to systematically examine their institutional designs and operational mechanisms in early identification, curriculum articulation, research practice, and teacher development. Based on the practical challenges facing China, the study proposes targeted suggestions: universities should shift away from a “relay-style” logic of education and reshape their mission within the national talent ecosystem; they should build tiered cooperation mechanisms to enhance the capacity of ordinary secondary schools; they should take the lead in establishing professional support systems for teachers engaged in cultivating top innovative talents; and they should strengthen their hub function to construct cross-stage collaborative governance platforms for talent cultivation.

With the accelerated process of digital transformation in higher education, the tension between traditional university teaching evaluation models and the digitalized educational paradigm has become increasingly prominent, placing higher demands on the construction of teaching evaluation systems in universities. Against this backdrop, fully exploring the functional potential of artificial intelligence in university teaching evaluation has emerged as a crucial pathway for promoting evaluation reform. From the perspective of the “technology-education” relationship, the current application of artificial intelligence in teaching evaluation still faces numerous challenges. The root cause lies in the ineffective mutual construction between technology and education, which in turn limits the effectiveness of evaluation practices. Therefore, this study proposes a practical pathway of “technology-education” co-construction to enhance the practical efficacy of AI-based teaching evaluation in higher education. It seeks to build a process-oriented “teaching-learning-evaluation” system through the dimensions of coordination, synergy, and mutual regulation between technology and education, thereby facilitating the deep integration of artificial intelligence into university teaching evaluation and constructing a system that aligns with the demands of higher education in the new era.

Evaluation and quality assurance in higher education play an important role in promoting quality awareness, clarifying quality concepts, reinforcing quality norms and promoting quality construction. However, it is also faced with the tension between uniformity and diversity, normativity and autonomy, authority and utilitarianism that comes with standardisation. Its roots lie in scientism and its cult of quantification. In response, there has been a postmodern turn towards de-indicatorisation of evaluation, with a focus on the integrity, diversity and development of the object of evaluation, a look at the life activities of the object of evaluation itself, and an emphasis on the building of a culture of educational evaluation and quality assurance. The excellent tradition of Chinese educational evaluation is instructive for the postmodern turn in higher education evaluation and quality assurance, which should be creatively inherited and innovatively developed.

By analyzing relevant documents from 36 initial pilot universities, this paper summarizes the current state of transition operations from two perspectives: “how to transit” and “where to transit”. The findings indicate that pilot universities have developed unique transition methods that align with policy requirements and their own contexts. However, there is a need to guard against oversimplifying the transition. Although diverse transition pathways are offered within policy constraints, there is still a need to enhance the guidance of students’ development choices. While the importance of effective linkage between academic stages is recognized, a complete plan for subsequent training is yet to be established. Universities should integrate selection and cultivation in the transition process, deepen the exploration of multi-path, highly adaptive transition practices based on disciplinary characteristics and talent cultivation principles, strengthen coordination among relevant entities, ensuring good quality in every step.

As a key area in the new round of institutional reform, institutional reform in universities serves as the fundamental focus for accelerating the modernization of university governance systems and capabilities. To reveal the internal mechanisms of higher education institution reform, this study adopts the grounded theory approach to analyze 40 typical cases of institutional reform initiatives in universities, thereby summarizing and refining the practical logic behind these reforms. The research findings indicate that such reforms are driven by practical issues such as operational inefficiency and excessive institutional expansion. They require systematic implementation through synchronized streamlining of administrative bodies and staffing, strengthening departmental restructuring and integration, centralized management, and digital transformation process redesign. This aims to reduce organizational structures and staffing quotas, achieve systematic and holistic governance, and prioritize risk mitigation, steady progress, job transfers, and faculty governance capacity enhancement as safeguard mechanisms. Consequently, it is necessary to further establish an overall action framework for institutional reform in universities, explore scientific decision-making foundations for institutional streamlining and optimization, and implement a relatively flexible and adaptive organizational reform model through supportive organizational culture and humanistic care.

Relying on artificial intelligence and other technological means, smart education has not only transformed the use of teaching tools in higher education but also revolutionized the entire spectrum of higher education including educational concepts, teaching methods, and even the educational form. However, the rapid development of technology has given rise to a practical dilemma in higher education research where technological advancements outpace the establishment of a clear pedagogical theoretical foundation. This situation manifests in three specific challenges: ideological conflicts between technology-driven paradigms and education-centric principles; integration difficulties in pedagogical model transformation; assessment mechanism hysteresis. This study therefore proposes a theoretical framework integrating cross-disciplinary insights to explore the pedagogical foundations of smart education applications in higher education. We construct a complex ecosystem for smart education that is:philosophically grounded in educational paradigms, operationally implemented through pedagogical models, spatially enabled by learning environments, innovatively driven by research methodologies, sustainably oriented toward green education initiatives. This system provides a theoretical basis for intelligent technologies to realize the educational concept of “large-scale personalization”, the teaching management model of “data-driven instruction”, the learning scenario of “all-time, all-space, and all-knowledge learning”, and the research paradigm of “human-machine intelligent collaborative innovation”, thereby achieving sustained, effective and healthy development of higher education.

The categorical development of professional master’s programs and academic master’s programs often encounters practical dilemmas, exemplifying a classic phenomenon of?academic drift. While existing explanations for academic drift—such as theories of?institutional change,?organizational resources, and?status competition—offer foundational insights, this study supplements them through analytical inference of a case study. We propose that the?border paradox—the inherent tension between academic aspiration and institutional boundaries, manifested as the interplay of “boundary-crossing” and “boundary-maintaining”—serves as an intrinsic driver of academic drift. Specifically, professional master’s programs must balance professionalism and academic research. However, the academic aspiration inherently seeks to transcend disciplinary boundaries, potentially leading to academic drift at the student level. To address this, it is imperative to distinguish the distinct academic orientations of professional and academic master’s programs, ensuring their effective categorical development. Simultaneously, moderate permeability between these boundaries should be acknowledged to foster interdisciplinary synergy.

In the era of Big Science, interdisciplinary doctoral training driven by collaboration among diverse knowledge producers has emerged as a critical trend in U.S. research universities’ educational reform. Through cross-boundary integration of independent entities, U.S. research universities and national laboratories have built a fractal innovation ecosystem based on knowledge production mode Ⅲ have developed synergistic organizational frameworks underpinned by innovative partnerships. These frameworks emphasize the co-creation of interdisciplinary platforms and resource-sharing mechanisms for talent, funding, and infrastructure. Key practical strategies include integrated collaborative training programs, rotational training models spanning multiple institutional phases, and project-driven research practicums. Together, these approaches forge an interdisciplinary doctoral education paradigm distinguished by its fusion of theoretical rigor and applied practice. The U.S. experience provides instructive lessons for China. Guided by the national reform agenda integrating education, science, and talent development, China should advance the convergence of research and education to establish institutionalized collaboration mechanisms between elite research universities and national laboratories, thereby accelerating the cultivation of top-notch innovative talents.

Breaking the “Western path dependence” in cultivating top-notch innovative talents and establishing an independent cultivation mechanism for top-notch innovative talents with Chinese characteristics have become key breakthroughs in achieving high-level scientific and technological self-reliance and self-strengthening. To promote the independent cultivation of top-notch innovative talents in China, it is necessary to further rationalize the theoretical logic of policy support, so as to achieve the enhancement of autonomy from “external introduction” to “strengthening self-sufficiency”, the innovative positioning from “passive catching up” to “leading the sprint”, and the differentiated development from “uniformity” to “precise classification”. However, in the practical process, there are still many difficulties in relevant policy support, including homogenization of support, insufficient attention to the differences among different types of talents; intermittent support, the policy continuity throughout the entire process of talent cultivation needs to be improved; fragmented support, the collaborative education synergy among multiple subjects is insufficient; passive support, the dynamic mechanism of independent innovation is not sound. To promote the adaptation of relevant policies, we must adhere to the thinking of precise governance, and facilitate the diversified development of top-notch innovative talents through classified support, integrated support, collaborative support, and special support.

In the face of the external pressure of the transformation of the digital society, and the internal requirements of the innovation and development of higher education, UK’s Joint Information Systems Committee (JISC) launched a digital well-being oriented “Digital Capabilities Framework”. This framework set out professional solutions to improving the digital capabilities for students, teachers, administrators and others in Higher Education Institutions (HEIs) from both individual and organisational perspectives. To effectively enhance the overall digital capacity building of HEIs, JISC gave full play to the synergistic development of professional development standards and digital competence frameworks, and integrated digital competence development activities into the teaching and learning and administrative management of HEIs. An overview of the introduction and implementation of the JISC digital capabilities framework revealed distinctive features that focuses on the growth needs of all people, while paying attention to the individual needs of stakeholders. In the process of digital transformation, we should build digital capabilities, re-examine the relationship between technology and people, and rethink the integration of technology and education.

In the process of transformation of China’s science and technology from “following” to “leading”, the impact of laboratory research direction on the training of doctoral students needs urgent attention. Based on the mixed case study, it is found that when the laboratories conduct pioneering research, doctoral students can develop cutting-edge-oriented creativity, but the risk of failure of pioneering research is extremely high, and once failed, doctoral students can’t be able to obtain academic performance; when the laboratories conduct exploratory research, doctoral students can also develop innovative capability, but it is difficult to ensure academic performance; when the laboratories conduct routine research, it is difficult for doctoral students to fully develop innovative capability, but they can achieve high academic performance. Under the excessive performance-oriented talent evaluation and selection system, doctoral students who don’t fully develop innovative capability are more likely to be selected. Accordingly, the excessive performance-oriented selection criteria should be eliminated, the innovative value should be taken as the basic guide in selecting and evaluating reserve talents, and the project funding should be appropriately leaned towards doctoral students engaging in pioneering and exploratory research.

The digital competency level of university teachers is an important indicator to measure the success of digital transformation in colleges and universities, which is deeply influenced by teachers’ subjective level. Through a questionnaire survey of 853 teachers in 21 universities in 13 provinces, it is found that both formal and informal perceived social support can positively promote the digital competence of university teachers, and the promotion effect of formal perceived social support is more significant. In addition, psychological empowerment and technology acceptance play an important mediating role in the relationship between perceived social support and digital competence of college teachers. In order to accelerate the improvement of digital competence of empowering university teachers, it is suggested to strengthen the overall planning of resources to build a comprehensive “formal support” social network, create an emotional support atmosphere to create a symbiotic “informal” social support ecology, deepen psychological empowerment and accurately support “technologically disadvantaged” university teachers, and improve the transformation efficiency of social support resources.

Higher vocational education holds a significant position in China’s educational system, and the high-quality technical and skilled talents it cultivates contribute to economic and social development. Based on data from the Chinese College Graduate Employment Survey (CCGES) and the Statistical Data of Education Funding from 2009 to 2019, this study finds that public education financial investment can significantly enhance the starting salary of vocational college graduates. This conclusion remains valid even after addressing endogeneity by constructing an instrumental variable based on the per-student funding system in vocational colleges established in 2014. The mechanism behind this impact lies in the fact that public education financial investment enriches institutional resources, improves the education quality, and facilitates better major-job congruence for graduates. The increase in public education financial investment particularly benefits graduates from low-economic-capital families and has a more pronounced effect in schools located in financially constrained regions of western and central China. The findings of this study highlight the effectiveness and equity of public education financial investment, as well as its positive implications for promoting high-quality employment.

Promoting the reform of faculty employment systems in Chinese universities is not only an essential institutional requirement for the connotation-based development of higher education, but also an imperative in building a modern university system. This paper analyzes the academic and professional attributes of university faculty, clarifying the conceptual foundations of faculty employment systems and emphasizing the central role of tenure. Tracing the development of China’s university faculty employment system through four stages—incubation, initiation, promotion, and development—the study draws on theories of new institutionalism, academic career lifecycle, motivation, and stakeholder engagement to explain the logic behind the evolution and implementation of these systems. It also identifies a trend of value distortion in current practices, driven by excessive emphasis on instrumental rationality and performance metrics. To restore the normative values of China’s faculty employment system, the paper proposes a multifaceted strategy: upholding the threefold goals of identification, motivation, and safeguard; improving five interrelated subsystems—position structuring, recruitment, evaluation, incentives, and exit mechanisms; defining three institutional standards—contract duration, ranks, and recruitment boundaries; and clearing two governance pathways—democratization and legal safeguards.

As a primary programmatic vehicle for cultivating top-notch innovative talents in basic disciplines in China, the Plan for Strengthening Basic Disciplines manifests diverse policy implementation practices. Through constructing an integrated analytical framework of “institutional logics-organizational resources” and conducting qualitative research at a pilot university, this study reveals that departments implementing the Plan generally adopt multiple strategies: promoting undergraduate research system innovation through experimental approaches, negotiating integrated training transitions via flexible adaptation strategies, exploring curriculum integration through selective implementation methods, and refining talent cultivation programs through strict compliance approaches. However, when confronted with high institutional logic conflicts or insufficient organizational resources, these departments face implementation dilemmas including diminished innovation, goal displacement, suspended execution, and mechanistic compliance. Future reforms should focus on four key improvements: Enhancing university governance structures and optimizing organizational resource allocation; Expanding policy implementation frameworks while establishing collaborative supply mechanisms; Reconciling institutional logic tensions alongside innovating resource integration mechanisms; Promoting multi-stakeholder collaboration through building dynamic iterative mechanisms.

While generative artificial intelligence accelerates educational transformation, it simultaneously precipitates urgent legal challenges and ethical dilemmas. The research findings reveal that college students exhibit significant behavioral tendencies toward the improper use of GenAI. This trend has precipitated a systemic crisis in traditional pedagogical models centered on knowledge dissemination, with courses such as ideological and political education and humanities general education experiencing the most significant erosion of their foundational values. The structural imbalance between technological openness and ethical governance, insufficient teacher support coupled with intensified peer competition, and escalating academic pressure alongside proliferating burnout emerge as pivotal drivers of GenAI improper use. Risk perception in technology usage can effectively mitigate opportunistic tendencies under stressful conditions, while substantially enhancing the intervention efficacy of teacher support. The risks associated with the use of GenAI can be mitigated through the following approaches: establishing a new educational model of human-machine collaboration, creating ethical constraints for technology applications, strengthening teachers’ AI-ready leadership, and promoting a paradigm shift in the educational evaluation system.

The Scholarship of Teaching and Learning (SoTL) among college instructors is vital for advancing teaching and learning reforms and enhancing the quality of talent cultivation. However, in practice, many instructors’ intentions for SoTL often fail to translate into actions, resulting in an “strong intention-weak behavior divergence”. This study, based on interviews with 21 college instructors, explores the formation, divergence, and evolution of their intentions and behaviors in SoTL. The findings indicate that instructors’ intentions for SoTL are driven by a combination of perception of SoTL, value assessment, and perceived behavioral control. However, SoTL behaviors are not solely a product of intentions, as stronger barriers than motivators, inadequate SoTL planning, and unfavorable contextual cues contribute to the intention-behavior divergence. Instructors’ intentions and behaviors in SoTL evolve dynamically in response to changes in contextual cues. Institutions can optimize contextual cues that are directive, exemplary, resource-driven, and individualized, to help instructors translate their SoTL intentions into actionable plans for meaningful engagement.

With the rise of the group nature of the “Global South”, the global higher education governance system is shifting from the dominance of the north to a new pattern of “joint governance between the Global North and South”. The participation of the “Global South” in the global higher education governance system has mainly gone through four stages: initial participation, regional response, deepening of multilateral cooperation and upgrading of strategic cooperation. In the process, the “Global South” has promoted the institutional innovation of the governance system in the fields of global higher education governance subjects, governance standards, governance certification, and governance sharing through the reconstruction of new rules in the dimensions of quality standards, talent mobility, trade in educational services, and digital education governance. As an important member of the “Global South”, China has played an important role as an exchange negotiator, brand communicator, and experience sharer in the global higher education governance system.

Cultivating innovative engineering talents through interdisciplinary approaches represents a critical initiative for universities to optimize disciplinary structures and pedagogical models responding to technological innovation trends. This study conducts a comparative analysis of interdisciplinary engineering programs at four universities, including Purdue University. Findings reveal that driven by environmental, institutional, and student needs, programs develop dual pathways combining predetermined specializations with student-designed concentrations. They construct a curriculum grounded in the principle of sustainability and built around cutting-edge interdisciplinary courses and capstone projects, implement faculty development through departmental or cross-school collaboration, and achieve governance via advising services, committees, and stakeholder institutions. The study proposes that China's Emerging Engineering Education (NEEE) initiative should promote sustainable interdisciplinary development based on emerging technologies and reshape learning boundaries through holistic engineering perspectives.

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.

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.