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    Digitalization of Higher Education
  • Digitalization of Higher Education
    Artificial Intelligence Empowering the Innovative Development of STEM Education: Insights and Practices
    ZHENG Qinghua
    2025, 41(1): 1-7. https://doi.org/10.16298/j.cnki.1004-3667.2025.01.01
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    STEM education is the fundamental way to cultivate innovative talents, and its importance is further amplified in the era of Artificial Intelligence (AI). As a core driving force for shaping new productive capacities, AI is currently empowering the integration of science and education through disruptive technologies. The essence of AI’s role in empowering STEM education lies in creating new scenarios and developing innovative applications. Currently, six new scenarios—gamified learning, socialized learning, collaborative learning, self-directed learning, problem-driven learning, and project-based inquiry learning—have been created. Furthermore, five major categories of large model applications, including evaluation, management, teaching, classroom learning, and extracurricular learning have been developed. The convergence of STEM education and AI aligns with the inherent cycle of “observing phenomena, identifying problems, asking questions, and solving problems”. Ultimately, the success of this integration depends on teachers. The empowerment of artificial intelligence enables the new IQ of human-machine collaboration to surpass the limitations of human IQ itself.
  • Digitalization of Higher Education
    Algorithmic Administration in University Digital and Intelligent Governance:Logical Essentials, Potential Risks and Order Construction
    HUANG Wenwu1; WANG Jianhua2
    2025, 41(1): 8-15. https://doi.org/10.16298/j.cnki.1004-3667.2025.01.02
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    The empowering potential contained in emerging technologies such as big data and artificial intelligence is driving universities in their era to prioritize improving their governance intelligence as an important task for their future development. The combination of administrative actions and algorithms is driving algorithmic administration in university governance practice, and the algorithmic power demonstrated by it exhibits characteristics such as relationality, technicality, structural nature, and secrecy in the governance process. In the process of digital and intelligent governance in universities, phenomena such as changes and imbalances in the “power rights” empowerment/enabling structure, adjustments and dissolution the legitimate of governance due process triggered by technological simplism, and the formation and dilemma of technological/digital bureaucracy have emerged. To stimulate the governance effectiveness of algorithmic administration in universities, it is necessary to highlight the transformation from information technology popularization to the application of digital intelligence in the governance concept, highlight the incremental logic of algorithmic administration in university digital governance, and achieve the coordinated promotion of power expansion and rights protection in governance actions.
  • Digitalization of Higher Education
    Digital Transformation of University Governance: Generative Logic, Realistic Challenges and Path Selection
    WANG Xiaoxi
    2025, 41(1): 16-23. https://doi.org/10.16298/j.cnki.1004-3667.2025.01.03
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    Under the background of the digital age, digital technology has become an important means to promote the modernization of university governance system and governance ability. Based on the governance dilemmas, digital empowerment and incremental change, the digital transformation of university governance has obtained the generative forces from three dimensions: internal motivation, technical support and value guidance. However, the digital transformation of university governance also faces the coupling deviation between the instrumental rationality of digital technology and the value rationality of university governance, the imperfect security mechanism of digital transformation, and the security risks and compatibility problems in the process of digital technology embedded in the university governance process. Based on this, in the practice of effective integration of digital technology and university governance, a digital thinking mode should be further formed and the top-level design of digital transformation of university governance should be well done. Organizational agility should be improved, and the organizational structure and institutional rules of the university should be optimized; data work should be carried out well, the expected risks of digital technology should be clarified, and the construction of digital infrastructure in colleges and universities and the cultivation of digital capabilities of relevant personnel in the school should be continuously promoted.
    • The Independent Knowledge System of Chinese Higher Education
  • The Independent Knowledge System of Chinese Higher Education
    Deconstruction and Reconstruction: Higher Education System in the Era of Big Science
    WU Daguang1,2; WANG Xingzhao1
    2025, 41(1): 24-31. https://doi.org/10.16298/j.cnki.1004-3667.2025.01.04
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    The era of big science is an important feature of the scientific research paradigm after World War II. The emergence of this era has a specific historical background and is an important factor affecting the development and reform of higher education. It is also a new perspective for examining higher education activities. The shift of higher education from the era of small science to the era of big science is a reconstruction process based on reflection. How to maintain the value and positioning of higher education in the era of big science, how to transform the higher education system, where to go in university reform, and how to cultivate top-notch innovative talents are becoming urgent questions that need to be answered. In the era of big science, it is necessary to redefine the mission and responsibility of higher education, and rethink the forms and values of existence of universities, disciplines, and majors.
  • The Independent Knowledge System of Chinese Higher Education
    Construction and Reflection on the Research Path of Higher Education Based on Middle-Range Theory: Concurrently Discussing the Construction of an Independent Knowledge System of Higher Education
    ZHAO Xiaoli; XUN Yuan
    2025, 41(1): 32-39. https://doi.org/10.16298/j.cnki.1004-3667.2025.01.05
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    Theoretical research and practical research have been separated from each other for a long time, we use the middle-range theory established by Merton and others attempt to build a verifiable, two-way interactive bridge between theoretical and empirical research in the field of higher education. Therefore, we should first clarify the concept and provide the concept system verified by experience for higher education research. Secondly, the problems and events of higher education research should be embedded in specific spatio-temporal situations to investigate their dynamic changing processes. On this basis, the characteristics of different fields are distinguished by the typification of research, and the integration of empirical research and theoretical research is realized. In addition, as a research perspective and methodology, using middle-range theory to analyze higher education research is helpful to promote the construction of independent knowledge system of higher education from the aspects of “localization” “regionalization” and “characterization”.
    • The Learning and Development of Undergraduates
  • The Learning and Development of Undergraduates
    Research on the Digital Competence Level of Engineering Undergraduates and Its Matching the Demands of Enterprises
    TAO Jinhu1; QIE Haixia2; WANG Sunyu1
    2025, 41(1): 40-47. https://doi.org/10.16298/j.cnki.1004-3667.2025.01.06
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    The level of digital competence supply affects the process of intelligent process of the manufacturing industry. Based on the second-order structural equation model, the fuzzy comprehensive evaluation method, etc., a systematic evaluation of engineering undergraduates was conducted. The results show that high-level practical digital competencies are the key to promoting the high-level development of digital competence. These students have a high rating ratio for their abilities in “technical ethics and safety regulations, technology updates and transplantation, and comprehensive foundation of digital abilities”, as well as a low level of digital competence at the practical level. On the comprehensive level of digital competence, there is a trend of “electronic information majors > automation majors > instrument majors > electrical majors > mechanical majors”, and the proficiency ranking of various digital competencies in different professional categories has inherent consistency. The manufacturing industry urgently needs “software and hardware collaborative control competencies, production process management and evaluation competencies”, but the supply level of students is low, presenting an “imbalance state”. In the future, we should further innovate teaching models and processes, optimize curriculum systems and resource construction, and improve the ecosystem for cultivating digital competence.
  • The Learning and Development of Undergraduates
    Research on Inducement Identification and Evolution Mechanism of College Students with Learning Difficulties from the Perspective of Educational Reform in the Digital Age
    JIN Xinquan1; JIANG Qiang2; MA Zhiqiang1
    2025, 41(1): 48-56. https://doi.org/10.16298/j.cnki.1004-3667.2025.01.07
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    Identifying the characteristic inducement risks of learning difficulties among college students amidst the digital education transformation and tracking their development over time are crucial for preventing academic risks. This study develops a framework for identifying the causes of learning difficulties through qualitative interviews and uses dynamic topic analysis to further explicate how these triggers evolve. Consequently, the study highlights three major inducers of learning difficulties, including interaction imbalance exacerbated by technological usurpation, cognitive bias triggered by excessive quantification, and social alienation and isolation fueled by deep-rooted inert habits. And the evolutionary mechanism of learning difficulties involves three stages, namely a sensitive germination period influenced by public opinion bias, a risk elasticity period due to technological risk, and a maturity period from inertial convergence. To effectively tackle the challenges, a multifaceted approach is needed, such as creating a supply-demand matching framework with multimodal knowledge mapping, implementing a learning risk management model based on human-computer collaboration, and establishing a comprehensive supervision system involving multiple stakeholders. These strategies are designed to enhance talent cultivation within higher education.
    • Academic Degree and Graduate Education
  • Academic Degree and Graduate Education
    Embeddedness and Enculturation: A Qualitative Study on the Formation of Academic Identity of Doctoral Students
    LIU Lulu1; SHI Jinghuan2
    2025, 41(1): 57-65. https://doi.org/10.16298/j.cnki.1004-3667.2025.01.08
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    The construction of academic identity is a crucial aspect of doctoral students’ academic growth. Based on a categorical and contextual analysis of interview data from 53 doctoral students, it was found that the formation of academic identity is the result of their self-academic embedding, the enculturation within academic communities, the influence of organizational environments and disciplinary cultures, and the shaping of social contexts. Doctoral students embed themselves in academic communities through participation in academic activities, building academic networks, engaging in academic dialogue, and anchoring academic contributions. Academic communities acculturate doctoral students by providing academic recognition, shaping academic roles, guiding academic values, and nurturing academic character. The organizational environment, disciplinary culture, and social context (e.g., societal needs and employment conditions) play pivotal roles in shaping doctoral students’ academic identity as they integrate into and engage with the academic community.
  • Academic Degree and Graduate Education
    Activation and Reinforcement: The Formation Mechanism of PhD Students’ Autonomous Research Ability
    SHI Yueqi1; XIE Xin2
    2025, 41(1): 66-74. https://doi.org/10.16298/j.cnki.1004-3667.2025.01.09
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    Autonomous research ability is a key quality of high-level top-notch innovative talents, and the formation mechanism of PhD students’ autonomous research ability needs to be revealed urgently. This study found that PhD students’ academic potential, cultivating situational perception, and academic engagement behaviors significantly and positively facilitate their autonomous research ability, and cultivating situational perception and academic engagement behaviors play a chain mediating role between academic potential and autonomous research ability, which facilitates the activation mechanism for the formation of autonomous research ability; the behavioral outcome feedback significantly and positively moderates the promotion effect of cultivating situational perception on academic engagement behaviors, and the more positive the feedback, the more the cultivating situational perception can stimulate PhD students’ academic engagement behaviors, which constitutes a mechanism for strengthening autonomous research ability. To promote the development of PhD students’ autonomous research ability, institutions should strengthen the analysis of students’ personalized characteristics, guide PhD students to fully mobilize their subjective initiative and seek self-development; pay more attention to the different developmental needs of PhD students, and provide high-match and differentiated academic guidance; and create a stimulating and supportive cultivating situation, so as to optimize the experience of PhD students’ academic participation.
  • Academic Degree and Graduate Education
    The Application Status and Impact of Artificial Intelligence Generated Content in Postgraduate Academic Writing in China
    CAI Fen; JIA Xiao; SHEN Wenqin
    2025, 41(1): 75-82. https://doi.org/10.16298/j.cnki.1004-3667.2025.01.10
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    With the widespread use of Artificial Intelligence Generated Content (AIGC) tools in academic writing, the impact on postgraduate students in China warrants attention. An analysis of survey data from 14 817 postgraduates reveals that doctoral students have a stronger demand for using AIGC tools to assist in academic writing compared to master’s students. Postgraduates from “Double First-Class” construction universities, those studying in engineering, higher academic years, and those with extrinsic motivations for pursuing studies or perceiving a strong utilitarian publication atmosphere among peers are more likely to use AIGC tools for writing assistance. Postgraduates primarily utilize AIGC tools to assist in searching for materials related to their research topics and translating/refining the language expression in their papers. Postgraduates who use AIGC tools for coursework, translation, or refinement are more likely to recognize the positive impact of these tools on their research efficiency, but their use in research design may hinder the development of academic writing skills. Based on these findings, it is recommended that universities improve academic evaluation standards, and strengthen the development of academic ethical norms and usage skill training for AIGC tools.
    • Research and Exploration
  • Research and Exploration
    The Key to the Transition of New Quality Productive Forces: The Driving Path and Threshold Effect of the Transformation of Scientific and Technological Achievements in Universities
    ZHANG Tianxue; XU Zhitong; MA Yinqi
    2025, 41(1): 83-91. https://doi.org/10.16298/j.cnki.1004-3667.2025.01.11
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    Based on provincial panel data from 2012 to 2021, this study explores the impact mechanism of the transformation of scientific and technological (S&T) achievements in universities on the development of new quality productive forces. The results show that such transformation drives the development of new quality productive forces, mediated by talent agglomeration and regional innovation and entrepreneurship. Industrial structure upgrading and high-tech industry agglomeration exert positive moderating effects. Moreover, university-industry collaboration and government support exhibit threshold effects with increasing marginal returns, while an optimal range of financial development is identified. Accordingly, efforts should focus on promoting the coordinated development of scientific, digital, and green productive forces, creating a high-quality ecosystem to comprehensively support the transformation of S&T achievements in universities. Strategic industrial layout adjustments should proactively guide and absorb the spillover of achievements, addressing barriers to industrialization. A combination of measures integrating S&T transformation with deep university-industry collaboration should be employed to identify the optimal financial support range for enhancing new quality productive forces. Finally, a differentiated support system for the transformation of S&T achievements in universities should be established to encourage regionally differentiated development.
  • Research and Exploration
    The “Crisis” of Aesthetic: Rethinking on the Problems of Aesthetic Conceptions Among College Students
    ZHANG Xianlu
    2025, 41(1): 92-100. https://doi.org/10.16298/j.cnki.1004-3667.2025.01.12
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    The research and practice of aesthetic education in universities are paying more attention to the cultivation of aesthetic conceptions among college students. Adopting qualitative research method and conducting semi-structured in-depth interview method, this study explores the problems and causes of aesthetic conception among college students. Research has found that there are still four problems with the aesthetic conceptions of college students: shallow understanding of aesthetic values; the pan entertainment-oriented choice of aesthetic ways; the contradictory pursuit of aesthetic standards and the one-sided understanding of aesthetic types. The deep-seated reasons for the above-mentioned problems mainly include three points: lack of aesthetic literacy, lack of peaceful state of mind, and negative effects of social media. The way to solve the above difficulties lies in the comprehensive curriculum construction to enhance aesthetic literacy, creating an aesthetic atmosphere to cultivate a peaceful state of mind, and correctly utilize the new advantages of technology empowered the cultivation of aesthetic conception.
    • Education Rule of Law
  • Education Rule of Law
    Reflection on the Social Supervision Mechanism for the Quality of Degree Theses: Based on Article 31 of the Degree Law
    JIN Chao
    2025, 41(1): 101-108. https://doi.org/10.16298/j.cnki.1004-3667.2025.01.13
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    Article 31 of the Degree Law has added a clause on degree quality assurance, requiring degree conferring institutions to “timely disclose relevant information and accept social supervision” in order to ensure the quality of degree conferring, however, the most crucial mechanism for social supervision of the quality of academic dissertations is essentially lacking in China. At present, not only have degree conferring institutions not chosen to actively accept social supervision by promoting the disclosure of their degree theses, but public libraries and commercial databases are also difficult to become platforms for the public to supervise the quality of degree theses. Establishing a social supervision mechanism for the quality of degree theses is not only an inherent requirement for public as taxpayers participation in financial performance evaluation, but also helps to make up for the shortcomings of existing mechanisms for supervising the quality of degree theses. Therefore, it is necessary to first promote instant open access to degree these, secondly establish a unified platform for open access to degree theses by the National Library, and finally improve the system for reporting academic misconduct in degree theses. In the future, Article 31 of the Degree Law should further improve the social supervision mechanism for the quality of degree theses.