Seeking effective governance is the common goal of the shared governance of modern universities. In the information age, there are problems such as “isolated data-islands” and insufficient trust among governance bodies in the shared governance of universities. The fusion of “blockchain and block-data” is the mutual support of their technology and the cores of their concepts, showing a partially decentralized or multi-centered, interconnected, open and shared structure, which is similar to the shared governance of universities in structure and complements each other in practice. The fusion of blockchain and block-data can help solve the problem of university data sharing from the level of information technology, put the responsibilities of different governance bodies, departments or institutions of universities on the chain, make different governance bodies jointly participate in shared governance, enhance mutual trust, facilitate scientific evaluation, promote evidence-based decision-making, and improve the scientific nature of university decision-making. The results of decision-making also provide directions for newer or deeper data-sharing or data-aggregation, and responsibilities of multiple governance bodies on the chain, realizing a closed loop of “data sharing and responsibilities on the chain-information symmetry and mutual trust-scientific evaluation-evidence-based decision-making”, therefore improving the governance process of universities. While blockchain and block-data drive the effective shared governance of universities, they also face challenges such as the lack of relevant professional and technical talents, how to realize the good interaction between information technology and bureaucracy, and unknown data and information security issues.

Educational equity is one of the key and challenging issues in education. The traditional “one to many” teacher-student relationship often fails to provide disadvantaged students with optimal value-added development, which can not bridge educational gaps. As a new subject emerging in education, artificial intelligence (AI) technology holds the potential to provide learners with precise feedback through adaptive learning models, thereby empowering high-quality personalized learning processes and overcoming the impact of learners’ ascribed factors and foundational differences in learning conditions, enhancing the role of acquired factors, so as to promote educational equity. The realization of this vision depends on the full and balanced development of the three key subjects—teachers, students, and AI. However, in practical terms, issues such as the the big data models, computational power and algorithm differentiation of AI, variations in teachers’ TPACK levels and disparities in students’ feedback literacy can all lead to feedback imba-lances in personalized learning supported by adaptive learning models, which fails to meet the interests of the “least beneficiaries” and triggers a backlash against edu-cational equity. To this end, efforts should focus on four aspects: establishing a concept of inclusive technology supply, providing teachers with technical pedagogical training, emphasizing the improvement of students’ feedback literacy, and constructing supporting technology policy supervision systems, so as to prevent the risk of artificial intelligence technology backlashing against educational equity.

China is currently in a critical period of digital transformation in education and the implementation of a new round of compulsory education curriculum reform. Research on teachers’ classroom teaching behavior in the digitalization process holds political, strategic and educational value attributes. This study systematically explains the origin of teachers’ classroom teaching behavior and the transformation of teachers’ classroom teaching behavior through technological evolution based on the historical field. Through literature research, content analysis, and in-depth interviews, the research reveals practical dilemmas in this field. In terms of theoretical construction, there is a scarcity of comprehensive improvement models oriented towards core competencies in technology-enhanced environments. In terms of content interpretation, there is a lack of in-depth analysis of teaching behaviors throughout the entire process. In terms of relationship characterization, there is insufficient coupling logic in systematically analyzing influencing factors. In terms of practical progress, there is poor universal effectiveness of systematic evidence-based practical strategies. In this regard, path selection should be made from four aspects: theoretical logic, relational logic, action logic, and transformation logic, in order to better promote the high-quality development of classroom teaching in the digital age.

The process of digitalization of education challenges the realization of the right to education of the digitally disadvantaged. In the collection, analysis and application of educational data, the inequalities embedded in the social structure and the characteristics of digital technology combine to limit the realization of the right to education of the digitally disadvantaged，which not only reduces their ability to participate in the process of digitalization of education，but also generates new discriminatory and disciplinary effects. The right to education is a fundamental right guaranteed by the Constitution, with the dual attributes of “subjective right” and “objective law”. Taking into account the characteristics of the digitalization of education, and oriented by the demands of the digitally disadvantaged in terms of equality and freedom of education, it is necessary to implement the State’s obligation to respect, protect and pay for the right to education of the digitally disadvantaged. The State should recognize the disadvantages of the digitally disadvantaged at the normative level, promote the digital transformation of education in a targeted manner, and construct a legal protection system in which legislation, administration and the judiciary converge to provide relief in an orderly manner, so as to ameliorate the disadvantages of the digitally disadvantaged in terms of their material resources, abilities and awareness through the State’s provision of assistance to the digitally disadvantaged.

The digital transformation of education refers to the use of digital technology to empower education and shape a new form of education under the value of serving learning. The digital transformation of education implies the action metaphors of advancing the transformation work in problem-driven and demand-driven approaches, shaping the foundation of transformation through the two-way connection of technology integration and data empowerment, constructing the transformation focus through digital technology serving learners’ learning, and forming transformation safeguards through the synchronous organizational and cultural changes. The need to transcend the characteristics of the educational information era lies in changing the carrier of “reproduced knowledge” through “resource-teaching-teacher”. It involves breaking through “quality-equity-innovation” to update the cognition of “reproduced knowledge”, focusing on the instrumental application of information technology to strengthen the value orientation of “reproduced knowledge”, and shifting towards “reconstructing learning” supported by digital technology. “Reconstructing learning” takes improving learning quality as its value orientation and technology combination evolution and mutation creation as its theoretical principles. Its practical implications point to the application of digital technologies in high-quality learning. It can promote the concept of serving efficient knowledge dissemination to serving high-quality learning, construct new learning theories from “knowledge reproduction” to learning engineering solutions, shape new learning forms from teaching interaction to the integration of multiple subjects, establish new learning content generated from online learning content to digital learning ecosystem, and promote it from serving teaching and learning to serving students’ comfortable learning experience and upgrading digital governance.

Knowledge production is an important force driving the progress of human society, and the transformation of the knowledge production models has a profound impact on the development direction of education. From the perspective of historical materialism, the development of material technology is the fundamental driving force for the evolution of knowledge production. To this end, this study uses the transformation of technological social forms as the clue for analysis, with media technology and the industrial revolution as the main markers, systematically sorting out the historical context of the transformation of knowledge production models, analyzing the new phenomena of knowledge production in the information age, and revealing that the historical trend of the transformation of knowledge production models is from the emergence of individuals to the emergence of collective intelligence. On this basis, the study, based on the theory of complex systems, analyzes the five main characteristics of the emergence of collective intelligence: contextual complexity, spatial openness, subject diversity, mode coordination, and non-linear effects. Finally, the article summarizes the value and implications of the emergence of collective intelligence for educational reform and innovation at the micro-level of curriculum form, the meso-level of supply mode, and the macro-level of educational ecology, in the hope of providing theoretical reference for educational reform and innovation.

Artificial intelligence is driving a transformation in knowledge production from traditional inductive-deductive models to data-driven and algorithm-generated systems. This shift profoundly alters the way knowledge is generated, organized, and validated, while also reshapes subject cognition and application logic. Although this transformation enhances the dynamism and interconnectedness of knowledge, it also poses new challenges in terms of reliability, ethical standards, and equity. Education systems must adapt to this trend, evolve from static knowledge transmission to dynamic competence development, promote human-machine collabo-rative teaching, increase algorithmic transparency, and safeguard data privacy to mitigate inequities in technology use. To support the sustainable development of intelligent education, this study proposes to make systematic adaptation across four dimensions: reconstructing value rationality, innovating instrumental rationality, optimizing distributive justice, and strengthening ethical governance, and build an educational ecology that integrates technology and humanities. Future research should focus on the evolution of knowledge verification mechanisms, the cultural adaptability of educational assessments, and the operationalization of ethical principles into practical guidelines, so as to promote the coordinated development of cognitive expansion and human well-being in the process of intelligent education.

The global educational knowledge production has long been constrained by an unequal international landscape, manifesting in disparities of both “quantity” and “quality”. The former is manifested in the overwhelming advantage of developed countries and dominant languages in the number of articles published and cited in the international academic community, while the latter is reflected in the monopoly of Western research, paradigms and theories in research and application, forming an unequal division of labor in the educational knowledge production and obscuring the diversity of local educational knowledge. Behind this is the power structure inherent in language, compelling scholars from the Global South to conform to dominant languages and discourses at the expense of the precision and vibrancy of their native languages. The rise of large language models (LLMs) presents a technological opportunity to lower barriers and facilitate the participation of scholars from the Global South in knowledge production in their native languages. However, technical risks and challenges such as “non-neutrality” “incompleteness” “lack of depth” “ambiguity” and “errors” cannot be overlooked. In response, this study proposes the construction of an “Inclusive Community for Global Educational Knowledge Production” and the initiative of the “Speak in Tongues” project. By advocating for cross-cultural collaboration and data sharing to optimize LLM training, as well as emphasizing technological empowerment and critical reflection, the study seeks to achieve pluralistic, equitable, and sustainable development in global educational knowledge production within the process of decolonization.

Practical teaching is the key instructional design of the vocational education teaching system， and the practical teaching form is the dynamic characte-ristics of the practical process in which the relevant teaching elements are combined together in a specific way. With the comprehensive integration of digital technology， the teaching subject， teaching objective， teaching content， teaching environment and other teaching elements in vocational education practical teaching， as well as its organization， have undergone digital transformation， so that the contradiction between supply and demand of practical teaching and the interaction of the subjects have been fundamentally changed. On this basis， practical teaching will give rise to personalized practical teaching forms based on student needs， flexible practical teaching forms based on mixed supply， investigative practical teaching forms based on human-computer dialogue， and caring practical teaching forms based on human-computer collaboration. At the same time， in order to guarantee the smooth reformation of practical teaching form， it is also necessary to accelerate the digital upgrade of practical teaching elements， build a multi-modal teaching big data digital platform， improve the adaptability of teachers’ digital teaching， and establish and improve the digital ethics security assurance system.

As the driving force of educational reform, digital technology has already participated in the deep texture of teacher identity mobility. As a typical individual living in the digital era, contemporary teachers’ identity shaping is influenced by multiple subjective and objective factors. Taking the digital transition of teacher’s identity as a clue, we understand the era presentation of their identification mode from the two flow processes of relational transformation and social transformation of teachers’ digital identity. In this sense, the digital identity of contemporary teachers contains a dual representation of self coding and mirror image of others, which is a dynamic interweaving of educational norms and individual imagination. The construction of digital identity is a process of pursuing a higher level of self understanding and transcendence, and is self integration in the digital context. In the context of the digital transformation of education, the contemporary challenge faced by teachers is not only the substitution of digital technology for self-identity, but also how to understand the significance and limits of technological change in classroom teaching, professional development, and student growth, change the framework constraints of traditional role concepts, and thus achieve self-remodeling in the transformation of digital identity.

Science education is the key junction of education, science and technology, and talents, and plays an important role in promoting the development of new quality productive forces in knowledge foundation, innovation drive, talent cultivation, and other aspects. Starting from the system theory of “element-structure-function”, the mechanism of science education in promoting the development of new quality productive forces lies in the fact that science education promotes the linkage of elements of new workers, new labor materials, and new labor tools, providing technical support, paradigm guidance, and talent security for the future industrial structure upgrade, thus realizing the common vision of high-quality development. To promote the development of new quality productive forces through science education, it is necessary to shape new production relations that are in line with the development of new quality productive forces, strengthen the effective connection between science education and the new quality productive forces system, optimize the construction of science education discipline system, cultivate high-level new workers through the deep integration of industry, education, research, and application, establish the concept of “big science education”, and promote a virtuous cycle of education, science and technology, and talents with a high-quality science education system.

The development of new quality productive forces and the basic education curriculum reform are mutually driven by liberating and cultivating new quality talents. The new quality productive forces forward inherent innovation requirements, sustainable development concepts, and international competition response needs for the basic education curriculum reform; the basic education curriculum reform provides indirect but fundamental support for the new quality productive forces by shifting from training test takers to liberating innovators, developing fair, ba-lanced, and green ecological education, and aligning with international curriculum reform trends. For the connotation of basic education curriculum reform, the industrial development direction and liberation characteristics of new quality productive forces guide the vertical and horizontal integration and focus on student in curriculum system; its departure from traditional paths guides the orientation of literacy in curriculum objectives; its technological revolution guides the advancement of curriculum content from digitalization to digital intelligence; its high-quality and efficient characteristics guide the curriculum implementation relying on teacher’s professional grasp of “what can and cannot be done” of intelligent technology. At present, the possible practical paths include exerting the innovation and foresight of curriculum theory research in response to the innovation of new quality productive forces, exploring the green attributes of the curriculum reform system in response to its greenness, implementing AI plus curriculum reform in response to its intelligence, promoting the integration of resources from all parties in response to its high efficiency, and building the core literacy of new quality teachers in respond to its li-berating nature.

Top-notch innovative talents are the key elements and positive variables in the development of new quality productive forces. Cultivating and bringing up top-notch innovative talents is the only way to develop new quality productive forces. The cultivation of top-notch innovative talents is subject to the development needs of new quality productive forces, but it also determines the development level of new quality productive forces. The top-notch innovative talent training system needs to be reformed based on the development requirements of new quality productive forces, highlighting the upgrading of talent training specifications generated by “creative ability”, paying attention to the adjustment of the educational content structure of “interdisciplinary integration” and strengthening the innovation of integrated teaching mode in “Industry-University-Research”. However, at present, the supply of top-notch innovative talents training theory is insufficient, the training direction has not yet accurately targeted the development of new quality productive forces, and the training process is “vertical and horizontal”. Therefore, it is necessary to follow the growth law of top-notch innovative talents and design an “advanced” training target system for top-notch innovative talents; According to the requirements of the development of new quality productive forces, the curriculum and teaching system for cultivating top-notch innovative talents should be constructed; Strengthen multi-agent collaborative education, and build an integrated practice system in “Industry-University-Research” to meet the needs of the development of new quality productive forces.

New quality productive forces and the Chinese educational moderni-zation are the strategic drivers and fundamental supports for building a strong country and rejuvenating the nation. There is a logical interdependence and unity between new quality productive forces and the Chinese educational modernization. The bidirectional interaction logical mechanism between the two lies in their inherent consistency. The Chinese educational modernization is the key support for promoting the development of new quality productive forces, and the new quality productive forces are the core driving forces for accelerating the Chinese educational modernization. The strategic value of the two-way mutual construction of new quality productive forces and Chinese educational modernization lies in promoting the great cause of building a strong country and national rejuvenation, achieving common prosperity for all people, unleashing the innovative vitality of talents and promoting scientific and technological innovation and industrial revolution, and accelerating the construction of a strong country in education, science and technology, and talents. To achieve the two-way mutual construction of new quality productive forces and Chinese educational modernization, we should return to the essence of productive forces development, focus on aspects, such as labor purpose, laborers, labor materials, labor objects and labor methods, and lead the exploration and practice of Chinese educational modernization with new quality productive forces, and support the development of new quality productive forces with Chinese educational modernization.

In recent years, with the increasing demand from society for teachers, teachers have been under tremendous pressure. The particularity of teacher work leads to conflicts between their roles as “parents” and “teachers”, thus the identity of teachers as parents must be given important attention. What kind of pressure do teachers face in parent-child education? How do they turn these pressures into motivation? Focusing on this core issue, this study starts from the perspective of “work-family enrichment” and uses grounded theory from qualitative research as a methodological tool. Through interviews with 17 teachers from a public complete high school in Z City, Guangdong Province, the current situation and transformation mechanism of parent-child education for middle school teachers from the perspective of work-family enrichment are revealed, and a benign psychological interaction model of parent-child education for middle school teachers is preliminarily constructed in order to promote teachers’ better self-development and educate their children, which is also beneficial for schools to provide guidance and suggestions for teachers’ mental health.

The rapid development of AI technology continues to blur the boundaries between humans and machines, while empathy, a core trait distinguishing humans from machines, will face severe challenges in technology-dependent intelligent societies, including weakened emotional connections, diminished collaborative capabilities, and a lack of values education. Grounded in the question of “how do humans differ from AI”, this study adopts an interdisciplinary perspective integrating design and educational technology to systematically construct pathways for empathy cultivation in intelligent societies. By analyzing the historical evolution of empathy across philosophy, psychology, and design disciplines, we reveal its core characteristics as a unity of “emotion, cognition and behavior” and identify its four key values in intelligent societies: 1) safeguarding the essence of humanity; 2) fostering cross-cultural understanding; 3) implementing learner-centered concept; and 4) guiding future professional talent development. Based on design thinking, this study proposes empathy cultivation path: 1) Building integrated instructional models rooted in design thinking; 2) Internalizing empathy through the process framework (discovery, immersion, connection and detachment); 3) Uncovering implicit needs using the co-design iceberg model; 4) Optimizing educational practices through the four-layer sensitivity (human, design, technology and collaboration); and 5) Establishing a five-tier empathy cultivation ecosystem (culture, mindset, methodology, method, tools and technologies). The research provides systematic solutions to address emotional deficits in intelligent society, offering theoretical foundations and practical guidance for educational technology developers, policymakers, and educators to build human-AI collaborative educational paradigms.

The 2024-2035 master plan on building China into a leading country in education explicitly proposes the strategic goal of “establishing an important education center with global influence”. The world’s important education center is a center of educational thought innovation, a source of educational reform, a center of high-quality educational development, and a center of educational science research. From the two-way orientation at the national level and the city level, through the construction of an evaluation index system, a multi-dimensional evaluation of the world’s important education centers is conducted to look for the deficiencies and gaps in China’s educational development. Focusing on education strategic planning, the education center city construction, and education high-quality development, and enhancing the level of education internationalization, competitiveness and influence, based on the socialist country and with the capital Beijing city as the core, we will build a national education center city system, carry out scientific planning and the whole advancement, and speed up the construction of an important world education center.

Teacher supply is the relevant institutional arrangement made for the generation and allocation of teachers, an important educational resource and its supporting resources, reflecting the overall consideration of relevant entities in regulating teacher supply, and directly affecting the quality of teacher staff construction. In recent years, the field of deep integration of digital technology and education has been continuously expanding and accelerating, leading to the disruption of traditional education and teaching processes, resulting in qualitative changes in the teacher supply. Digital technology provides new opportunities and challenges for the innovation in teacher supply, but also poses new challenges. In the digital era, there are two dimensions of practical difficulties in teacher supply: “quality gap” and “quantity imbalance”. Digital means should be used to ensure interactive optimization of teacher source supply, to promote quality and efficiency of teacher institutional supply through digital transformation, and rely on digital education to ensure accurate matching of teacher factor supply, thus providing strong support for the realization of digital empowerment of teacher supply.

The rapid development of generative artificial intelligence (AI) technology is reshaping the global educational landscape, sparking widespread interest in its potential applications within teaching, learning, and academic research. Currently, higher education institutions in China generally lack systematic response strategies and standardized management frameworks. To explore how universities can effectively address the opportunities and challenges posed by generative AI, this study selects ten leading American universities as case studies, systematically examining their approaches in policy frameworks, teaching practices, and risk management concerning generative AI applications. The study reveals three main characteristics in the strategies of top American universities: first, they emphasize on building a systematic regulatory framework, utilizing a combination of “general regulations + specific policies” to implement classified policies; second, they adhere to a teaching-centered, technology-empowered philosophy, with comprehensive reforms in curriculum innovation, teaching models, and assessment methods; third, they establish a robust risk management system, ensuring normative application of technology through clearly defined responsibilities, strengthened data security, and intellectual property right protection. Based on the findings, this paper proposes three recommendations for Chinese universities in their application of generative AI: building a standardized application system to ensure technological use efficacy; deepening teaching integration and innovation to enhance talent cultivation quality; and strengthening risk control measures to protect educational data security. These insights aim to serve as valuable references for Chinese universities in advancing educational innovation, improving teaching quality, and upholding academic integrity in the era of artificial intelligence.

In the era of intelligence, the large-scale, long-term and multi-dimensional student behavior performance data generated by learning have become the soil of new learning evaluation. To guide the effective application of technology in learning evaluation, this research focuses on the transformation of learning evaluation ideas and the effectiveness of technology-enabled learning evaluation. By organizing relevant terminology of learning evaluation, it is found that the concept of learning evaluation evolves from “assessment of learning” to “assessment as learning”, and learning-oriented evaluation, and teaching-learning-assessment as a whole, have become important educational evaluation concepts. This research further explores the pathways of integration and innovative applications of technology in learning assessment, and then applies the CIPO model and meta-evaluation ideas to construct a meta-evaluation model of the effectiveness of technology-supported learning evaluation, and takes process evaluation as an example to explore the meta-evaluation model of the effectiveness of technology-supported process evaluation. At the same time, in order to maximize the effectiveness of technology, it is necessary to pay attention to the ethical problem of technology use in the evaluation process and put forward corresponding countermeasures. The research is expected to provide reference for the current reform of learning evaluation.

The transformative opportunities that Generative Artificial Intelligence (GenAI) may bring to teaching practices have attracted widespread attention from various sectors of society. However, there is still a lack of systematic research on the specific impact of GenAI on teaching practices, especially from the perspective of teachers. Since ChatGPT originated in the United States, its higher education system has been among the first to be affected. In this context, many top universities have quickly responded by providing resource support and policy guidance for educators to explore innovative uses of GenAI in teaching. As these explorations deepen, teachers have accumulated valuable practical experience and shared their teaching cases online, offering a key opportunity to reveal the impact of GenAI on teaching through practice-based narratives. Through in-depth analysis of 100 teaching cases, two primary pathways for GenAI’s application in education were identified: optimizing existing processes and driving innovative transformation. Based on the above pathways, six typical types of GenAI-driven teaching scenarios were further identified: customized resources for local practice, alternative feedback with machines, enhanced connections with teachers and peers, situational simulation for authentic learning, accelerated learning process, and creation through iterative interactions with GenAI. These pathways and scenarios collectively showcase GenAI’s multifaceted impact on teaching and underscore the diversity and complexity of its application methods in education.

At the critical stage of digital transformation in higher education, digital learning has become an increasingly vital role in the learning and development of college students. Evaluating and researching digital learning ability, as well as analyzing the current characteristics of college students’ digital learning ability, can provide a scientific basis for improving their digital learning levels and the quality of talent cultivation in universities. This study was based on a random survey among a provincial key university to assess college students’ digital learning ability. The total 2,041 valid responses were collected via the online questionnaire and analyzed with the spider web model. The main findings are: in terms of mindful agency, students demonstrate a robust sense of digital learning, yet there is room for enhancement in managing processes and feelings; regarding creativity, they show an adventurous spirit, but the imagination, intuition and playfulness in digital learning need to be enhanced; concerning sense-making, students have strong skills in know-ledge construction, yet they should improve their abilities to extract and relate information; in curiosity, optimism and hope, students exhibit a strong desire for know-ledge and learning conviction, but their interest in digital learning easily diminish in the face of challenging learning tasks; regarding learning reciprocity, students show a strong awareness of communication and collaboration, but lack a sense of belonging to digital learning communities; concerning openness to learning, students display a degree of resilience, but their autonomy in dealing with digital learning difficulties and setbacks is relatively weak. Accordingly, it is necessary to cultivate college students’ consciousness of reflection and attribution in digital learning to develop their mindful agency and openness to learning; develop digital courses for the development of creativity; encourage college students to change their digital learning methods and thinking patterns to improve their sense-making; stimulate college students’ curiosity towards digital learning challenges for enhancing their intrinsic learning motivation; and establish a digital community of inquiry to enhance college students’ reciprocal learning experiences.

The national requirements and deployment for the integrated reform of the education, science and technology, and talents system and mechanism imply the underlying logic of promoting the comprehensive support for the construction of a socialist modernized country through the integration of the three. In the institutional perspective, the promotion of the integration of the three is a process in which the country deepens the reform of the education, science and technology, and talents system and mechanism. Through continuous improvement of institutional design, it constructs a collaborative system of “education, science and technology, and talents” from the central to local levels, forming a new pattern of integrated planning of the three undertakings, integrated formulation of policies, integrated deployment of operations, and integrated allocation of resources. In reality, factors such as the policy effects of institutional adjustments, inertia of existing policies, collaborative barriers to resource allocation, fragmented departmental management, and cognitive differences in practical operations are intertwined and coupled to form multiple constraints on the integrated reform of the three systems and mechanisms. The key to solving the problem lies in strengthening the integration of the three at different levels of the central and local governments to promote institutional supply, and making good use of the new national system that integrates the allocation of resources and elements from the three.

The university idea is a constructive philosophical concept that leads universities to find their goal positioning and value attributes, highlighting the rational thinking that human beings have been striving for and the way of searching for the origin of the university. However, the classical university concept has limitations such as advocating elitism, confining the imagination of universities and ignoring the development demands of non-elite universities. Because of the inability to deeply perceive the meaning of ontological existence, the diffuse identity forces non-elite universities to embark on the path of imitation. At the stage of universal higher education, ordinariness as a university idea is the philosophical basis for non-elite universities to seek institutional identity. This paper clarifies the misinterpretation of the concept of ordinariness and elaborates the possibility of ordinariness as a possible university philosophy based on the dimensions of epistemology, axiology and practice. Being ordinary does not require non-elite universities to be willing to yield to utilitarian reality, but rather it means fundamentally affirming the ontological value of non-elite universities, transcending the path dependence of university development, and building a diversified and integrated development pattern, so as to achieve first-class and excellence in professional fields.

Disciplinary integration education serves as a strategic response to the paradigm shift in knowledge production and the cultivation of versatile, innovative talents, exerting profound structural transformative effects in the pursuit of building a strong country in education. It emerges as an intrinsic driving force for enhancing the adaptability, innovation, and accessibility of the educational system. This paper proposes the “Superstructure Triad” theoretical framework centered on “Object-Relation-Meaning”, accompanied by the “Five New” concepts: firstly, a new framework grounded in knowledge ecology, complex learning theories, and cognitive science, establishing a dynamic disciplinary cluster governance model, and optimizing discipline structure to facilitate systematic interdisciplinary integration; secondly, a new discourse reconstructing theoretical expression and conceptual system through structured knowledge fusion models, leveraging intelligent technologies to dynamically reorganize knowledge structures and increase educational openness and adaptability; thirdly, new thinking integrating holistic, systematic, and creative thought processes, creating interdisciplinary cognitive development systems and multimodal learning environments to enhance knowledge transfer and complex problemsolving competencies; fourthly, new value defining the structural roles of disciplinary integration education in knowledge production, innovation development, and educational equity, thus promoting the construction of a strong country in education with an interdisciplinary collaborative mechanism; lastly, a new ecology optimizing educational governance structures through enhanced interdisciplinary curricula, collaborative teaching teams, intelligent learning environments, and dynamic evaluation-feedback systems, thereby strengthening knowledge innovation capacity and facilitating educational paradigm evolution mechanism.

With the advancement of student evaluation reform, the deep integration of core competencies and curriculum teaching, as well as the comprehensive implementation of comprehensive quality evaluation, have pushed the evaluation that promotes students’ all-round development into a new stage. At the same time, it is also faced with multiple difficulties and challenges, such as barriers between different student evaluation systems, difficulties in resolving the tension between policies and practices, and mutual constraints between technological limitations and the use of results. Under the trend of educational digital transformation, there is an urgent need to integrate the content, data, and technology of student evaluation from different policy perspectives to construct a comprehensive, specific, and normalized digital integration framework for student evaluation. The key to realizing the digital integration of student evaluation lies in fundamentally changing evaluation concepts, breaking down traditional fragmented evaluation logic, strengthening evaluation models based on educational and teaching processes, and establishing standards and norms for digital evaluation. Looking ahead, the continuous promotion and improvement of digital integration evaluation is expected to bridge the gap between policy formulation and practical operations, enabling student evaluation to return to its essence of fostering talent, and driving the achievement of educational equity through digital evaluation.

To address the challenge of deciphering “what” constitutes the relationship between teachers and intelligent machines in human-machine collaborative teaching, it is essential first to clarify its essential characteristics, forms, and deve-lopmental processes. In classroom settings, intelligent machines serve as extensions of teachers’ capabilities, with their relationship embodying the fundamental characte-ristic of subject-object integration. The forms of interaction between teachers and intelligent machines encompass four categories: alterity relationships, hermeneutic relationships, background relationships, and embodied relationships. These forms reveal the distinct roles played by intelligent machines and teachers in orchestrating the “symphony” of human-machine collaborative teaching. At the initial stage of relationship formation, the teacher-machine dynamic manifests as a tool-oriented commensalism. During the developmental and deepening phases, it evolves into a competitive amensalism and subsequently a partner-based mutualistic symbiosis, respectively. To foster the healthy development of teacher-machine relationships and harmonize their collaborative “symphony” in education, efforts should focus on three key areas: implementing value-sensitive design for intelligent machines, establishing a human-machine moral community, and strengthening algorithm auditing mechanisms.

Artificial Intelligence Generative Content (AIGC) has swiftly brought the relationship between humans and technology from “human-machine collaboration” to a new stage of “human-AIGC collaboration”. The instrumental and passive response characteristics of technology are gradually diminishing, while its intelligence and subjectivity are increasing, altering the modes of human-technology interaction. This transformation has also restructured the current seven-element blended teaching system into an eight-element human-AIGC collaborative teaching system, incorporating intelligent agents. AIGC is not only an independent element within this system but also influences the relationships between the elements: it forms four stable yet heterogeneous types of “teacher-student-AIGC” triadic structures, making the roles and functions of the three agents more diverse and dynamic. The cultivation goals, due to the job revolution brought about by AIGC, should become more embodying the concept of outcome-based education (OBE), shifting the educational philosophy from “teaching knowledge” to “teaching students how to collaborate with AIGC to maximize learning benefits”. Teaching objectives will focus more on developing the “composite brain” that promotes human-AIGC collaboration capabilities, fostering high-order capabilities that integrate individual internal brain with AIGC external brain, such as language, critical thinking, innovative thinking, problem-posing, problem-solving, logical reasoning and so on. Teaching content and resources, empowered by AIGC, will dynamically generate, expand, create, and customize based on teaching standards, content, teacher and student indivi-duality, and teaching needs, exhibiting richness, appropriateness, and novelty. In teaching activities, AIGC will simultaneously exhibit its instrumental and agent nature, and construct a teaching activity selection framework integrated with AIGC based on knowledge classification theory. The teaching environment will become more multimodal, personalized, and ubiquitous, yet this personalization and ubiquity cannot rely solely on AI for decision-making. Human teachers must recognize differences between students from the perspective of affordance theory and teach according to individual aptitudes. In terms of teaching evaluation, the granularity of evaluation will become more refined, with significant improvements in precision and depth, enabling more immediate, customized, and accompanying feedback for each learner.

In the global wave of educational digital transformation, the in-depth application of educational big data has emerged as a core driver for enhancing governance efficiency. However, challenges related to data privacy protection have become increasingly prominent. As the tension between data openness and privacy protection intensifies, striking a balance between innovation and risk has become a critical issue in global education governance. This study delves into the core challenges of privacy protection in higher education data, systematically analyzes 102 data privacy policies from 100 world-class universities to provide insights for constructing a localized data governance framework in China. World-class universities achieve a balance between data value and privacy protection by implementing comprehensive coverage of the data lifecycle, diverse positioning of data subjects, and dynamic coordination of core elements. The study further proposes that higher education data governance should prioritize legal compliance, precision, transparency, technological integration, and adaptability, offering important references for advancing educational digitalization strategies and innovative governance models.

The online learning community with virtual space as the scene and members’ independent interaction has become an important way of knowledge sharing and learning in the “Internet+” era. Taking the WeChat group of the online course “Internet + Education: Dialogue between Theory and Practice Ⅶ” as an example, based on the interaction data of members, using the social network analysis method and the dynamic community discovery method, this paper explores the characteristics and evolution rules of the social network structure of the online learning community from the three levels of the whole, the part and the node. The results show that: The interaction behavior of community members shows periodic fluctuation changes, and the social network structure shows good self-growth; In terms of subgroup evolution, the social network structure shows an evolutionary trend from loose to local aggregation; At the node level, the social network shifts from the structural relationship mainly supported by community organizers to the spontaneous formation of structural relationships by learners. It is found that reciprocity, closure effect and mediating effect have significant positive effects on the evolution of relationship network. Then, suggestions are put forward to promote the benign development of community from three aspects: promoting the interaction of community members, attaching importance to the guidance and cultivation of nodes, and improving the evaluation mechanism of community interaction.