As digitization creates new opportunities for educational transformation, it is imperative to rely on digital technology to deepen the reform of teacher team construction. Based on evidence and centered on people, digital evidence-based teaching and research integrates empirical wisdom with digital technology in a man-machine collaborative way, and promotes the comprehensive, personalized and lifelong development of teacher. The technology-influenced subject, evidence and situation together constitute the basic structure of digital evidence-based teaching and research, which has the humanistic concept of data-driven teacher developmental evaluation, the value concept of conducting personalized improvement at scale, the process concept of evidence-oriented teaching and research diagnosis and decision-making, and the complementary concept of experience and evidence. To promote the efficient implementation of digital evidence-based teaching and research, it is necessary to carry out training to enhance teachers’ digital literacy and evidence-based awareness, improve the platform to form a teaching and research community to promote the balanced development of teacher education, create an evidence-based cultural field to implement the two-way transformation of theory and practice, and pay attention to the evaluation and monitoring of digital evidence-based teaching and research in order to ensure the overall quality.

The deep integration of artificial intelligence in the field of education not only brings about the first-order effects of direct changes in organizational behavior, but also brings the second-order effects of the accumulation and use of data resources in the field of education and data shaping of the subject of educational activities. The impact of the second-order effects can be very profound. Therefore, in order to ensure the integration of artificial intelligence into educational activities and maximize the development of education, the relationship between machine and human in educational activities should be thought about from the perspective of “Receptacle-Forms-Telos”. This entails establishing ethical guidelines for the development of artificial intelligence as an educational “Receptacle” based on the Three Laws of Robotics, formulating design and usage norms for algorithms grounded in the theory of justice as the educational “Form”, and devising shared principles for artificial intelligence based on the educational “Telos” of holistic human development. These efforts aim to regulate, guide, and transcend technology through the lens of education.

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.

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.

Having a deep integration of theory and practice during the teacher education, evidence-based teacher education has become a development tend in teacher education. The key part is to rely on evidence to establish evidence-based teacher education practices.

Evidence here refers to the information carrier for effective teacher education. In the era of intelligence, the evidence optimization of evidence-based teacher education needs AI and other technologies to give full play to the advantages of technology in helping evidence production, selection and use and forming a “crowd intelligence” effect on the use effect. The “human-machine cooperation” will differentiate the scientific nature, functionality and corresponding cases of evidence to form a dynamic semantic link that can be infinitely expanded and optimized, and thus realize the “evidence-man-case” integration, which will keep optimizing evidences in specific practice cases. The construction of teacher education running mechanism needs the application of intelligent technology to develop content optimization, scope expansion and connection optimization of evidence, coupled with the supporting conditions such as algorithms, memory and usage feedback. Based on this, a technical implementation architecture of evidence intelligent evolution is designed to provide a feasible reference framework for evidence management and platform optimization in evidence-based teacher education.

With the promotion of education digitization strategy, blended teaching practice has become more common at present, but there is still a lack of consensus and in-depth theoretical analysis on some of its basic problems, which causes confusion in practice and affects the teaching quality. This paper examines blended teaching from the continuous spectrum of offline teaching to online teaching, and divides it into enhanced off-line teaching, alternating balanced teaching and enhanced online teaching. Using technology phenomenology and cognitive load theory as tools to analyze students’ learning experience, the characteristics of online teaching and the limits of skill acquisition are discussed in layers. Then the basic problems of blended teaching design are discussed, and the design strategies are put forward from the perspectives of making full use of data, overcoming low embodiment and low risk, and controlling cognitive load levels.

The construction of comprehensive education for a strong country in education is required in the new era. Promoting the construction of a strong country in education with the concept of comprehensive education is a practical requirement for the construction of a lifelong learning education system for all people, an urgent need to improve the quality of independent training of high-level talents, and an inevitable pursuit for the all-round improvement of educational governance capacity. The connotation of the construction of comprehensive education for a strong country in education lies in the gradual enhancement of the comprehensive strength of education, educational innovation capacity, talent cultivation and education service contribution capacity, educational governance capacity, international competitiveness and influence of education through the establishment of a comprehensive, intelligent, autonomous, collaborative and open concept of comprehensive education. In order to construct the comprehensive education for a strong country in education in the new era, we should build a comprehensive education system and condense the Chinese plan for the construction of a strong country in education; optimize the mechanism for selecting and cultivating top-notch and innovative talents, and construct a talent highland for the construction of a strong country in education; reshape the concept of systematic education governance, and outline the spectrum of the governance of the construction of a strong country in education; coordinate and promote the in-depth fusion of education and technology, and open up the digital race track for the construction of a strong country in education; promote a balanced, fair, and inclusive education, and stimulate the endogenous impetus for the construction of a strong country in education.

With the rapid development of technology, the world is rapidly entering the digital era. International organizations and countries have gradually realized the necessity of cultivating students’ digital literacy, and constructed frameworks to guide the direction of talent cultivation. China also attaches importance to the cultivation of students’ digital literacy, but has not yet constructed a special framework to cultivate digital talents. Therefore, this study compares eight major international digital literacy frameworks for students in the first level dimension, then found that the main dimensions include of “Citizenship”“Operations”“Information”“Communication”“Content Creation”“Problem Solving”“Safety”“Learning and Development”, and most of them are divided into difficulty levels according to each literacy dimension. Based on this, the suggestion of dimensions is converted locally with reference to China’s national conditions and policy points, and finally consist of 8 first-level dimensions and 33 second-level dimensions. At the same time, based on the Taxonomy of Educational Objectives, this study suggests that digital literacy framework for students is divided into foundation, intermediate, advanced and highly specialised four levels of difficulty, forming a framework system of four levels and six segments. And the division of difficulty corresponds to different stages, so as to facilitate the development of digital literacy for students at different stages of age and ability level.

As one of advanced productive forces, information science and technology has become an important pillar of social and economic development. The rapid innovation of new technologies such as Internet, big data, cloud computing, artificial intelligence and blockchain has promoted the digital transformation of social eco-nomy and given new tasks to school information science and technology education. In order to meet the needs of social development and students’ growth, digital literacy and skills oriented information science and technology curriculum needs to focus on key capabilities, and realize the development from “information literacy” to “digital literacy and skills”, from “technical tools” to “combination of science and technology”, from “imitation exercise” to “discipline practice”, from “summative evaluation” to “value-added evaluation”, strengthen the combination of “learning by doing”, “learning by using” and “learning by creating” in theme activities to improve students’ digital literacy and skills.

The core value system of educational evaluation reform in the new era shares similar value expectations with the socialist core value system. Inspired by the socialist core value system, the core value system of educational evaluation reform in the new era responds to the judgement value, discovery value and improvement value from the three aspects of functional positioning, temporal span and practical logic. This paper summarizes the following value factors: the CPC’s leadership, fostering virtue through education, spirit of the times, openness and sharing, key breakthroughs and overall promotion. The value factors are transformed into the value concept of educational evaluation reform in the new era, which is adhering to the CPC’s overall leadership and putting people first as the main line of thought, constructing an evaluation system that meets the requirements of the times, embo-dies innovation and development, and represents Chinese characteristics, as well as a scientific supporting evaluation mechanism. It is divided into three major levels of value, namely the value concept as the logical starting point, the value goal as the value direction, and the value principle as the technical support. Based on this logical framework, it puts forward four directions: ideological leadership, putting people first, Chinese characteristics and ecological symbiosis, to comprehensively promote the reform of educational evaluation in the new era.

The digitalization of education is a crucial aspect of global education governance, with international organizations playing a key role in advancing global governance of digital technology. They lead, regulate, and guide the legitimate pathways for the empowerment of education through digital technology. However, due to the differences in development backgrounds, historical missions, and conceptual visions among these organizations, the UNESCO, the OECD, the World Bank, and the European Union have exhibited unified central concerns in the realm of global educational technology governance while also showcasing the power dynamics. These are mainly reflected in three aspects: the discursive battles over global welfare and strategic interests, the governance system struggle between soft governance and hard interventions, and the value pursuit contest between humanitarian and utilitarianism. Investigating the power dynamics of international organizations in global governance of educational technology is of significant importance for China to understand and grasp the current complex pattern of technology governance intertwined with power.

The digitization of education is a historical process, which will undergo the stages of conversion, transformation, and wisdom. From the perspective of development, with the concepts of connection, content, and cooperation (3C), digitization of education gathered platform facilitates connection and organizational connectivity, enhanced resource development and quality supervision, and empowered cross-border collaboration and transnational cooperation, thereby facilitating China’s overall leap from the conversion stage to the transformation stage. The new stage is faced with the new strategic opportunities and challenges. Hence, there is an acute need for new development philosophy to steer the new stage. The principles of integrated, intelligent, and international (3I) have emerged in response. Regarding the relationship between “3I” and “3C”, despite the disparities in their development goals and construction tasks, they are inherently coherent. The “3I” constitutes an upgrade, expansion, and deepening of “3C”. Guided by “3I”, China is taking actions by developing and aggregating platform resources and data on a larger scale, integrating intelligent technology more deeply into education system, and conducting international exchanges in digitization of education at a higher level. The aim is to achieve enhanced services, higher-quality applications, and more effective cooperation, promoting the expansion and quality improvement of digital education. Looking ahead, it is imperative to grasp the fundamental trend of the explosive growth of digital technology, adhere to the main thread of digitization of education leading and supporting the construction of a strong country in education, and persist in deepening the national digitization of education strategic action under the guidance of “3I”, in order to continuously propel China from the transformation stage towards the wisdom stage.

The general cultivation mode is an exploration of the localization of general education in Chinese first-class universities for cultivating interdisciplinary talents. Based on a questionnaire survey of 863 undergraduates from three C9 universities, it was found that the students’ “interdisciplinary learning engagement” (learning initiative, strategic learning, scientific research participation) and “interdisciplinary learning outcomes” (disciplinary vision and knowledge understanding, interdisciplinary learning strategy application, cooperation and communication abilities) are quite good on the whole. The former has a positive effect on the latter, and “interdisciplinary cognition” plays a moderating role between learning engagement and learning outcomes. Better interdisciplinary cognition promotes interdisciplinary learning outcomes in two dimensions: learning strategy and scien-tific research project participation. Research shows that freshmen education should strengthen interdisciplinary cognitive content, learning methods, and thinking abilities. In addition, undergraduate scientific research training should also be incorporated into the curriculum system of the general cultivation mode.

Digital technology is the core driving force for skilled workers to build a better life, but the uncontrolled abuse of digital technology can easily overstep the traditional boundary of the stable relationship between human beings and technology, and make skilled workers fall into the dilemma of reverse domestication of digital technology. Based on Borgmann’s philosophical view of technology, digital technology, while empowering and transforming the work world, life world and spiritual world of skilled workers, is also likely to lead to an imbalance in their “human-technology” relationship, presenting a focal alienation pattern of de-skilling, interaction alienation, and pan-entertainment, and trapping them in an “involuted” work world, a “colonized” life world and a “barrenized” spiritual world. In order to resist the risk of technological alienation, vocational education should take the initiative, pay attention to the sustainable development of skilled workers, contribute to the socialization process of skilled workers, lead the reshaping of values of skilled workers, and help skilled workers grow into advanced skilled talents who can adapt to the development of the digital era and lead to a better technological life.

Academic plagiarism in higher education has shown a trend of alienation and escalation in the GAI era. Reviewing the historical evolution of the concept of plagiarism and the means of regulating it as a result of several major technological innovations, technology has been both an promoter and a game-changer. The existing concept of plagiarism has certain obstacles in adapting to the misuse of AIGC. The copyright law, the academic degree law and the student integrity policy of higher education have failed to provide clear normative guidelines, and the traditional similarity detection techniques and ideas are stretched to the limit. The policy makers of higher education should give priority to the technocracy path, and construct specific rules for regulating the use of AIGC in higher education through identification technologies such as generative digital watermarks, with the most basic principle of transparency in the use of AIGC as the core.

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 far-reaching impact of the digital revolution on educational ecology is gradually emerging，and it will also have a profound impact on and participate in the process of modernization of educational governance. Digital governance，because of its dual characteristics of “comparison” and “controllability”，better conforms to the real demands of educational governance that needs easy and measurable evaluation. However，there is still a gap between the model of digital governance and the ideal state of “good governance” in education. By comparing digital governance with the five levels of “democracy，rule of law，effectiveness，responsibility and transparency” of good governance，we find that there are problems in digital governance，such as reaching consensus，lacking legitimacy，ignoring public welfare，unclear division of rights and responsibilities，and insufficient transparency. For this reason，the article explores the transformation of educational governance mode from “digital governance” to “good governance” based on the five in one of “the rational formation of common will，the legal development of digital governance，the emphasis on the public product attribute of education，the clear distribution of rights and responsibilities，and the open and transparent collaborative supervision mechanism”. It conforms to the inherent pursuit of the modernization of educational governance for good governance，and realizes the beautiful vision of good education governance order.

Connectivism holds that the learners are the knowledge producers and the knowledge production depends on learners’ social interactions, but its specific affecting mechanism remains unclear. Based on the connectivism and complex system theory, this study builds a model of factors affecting knowledge contribution in connectivist learning (SOA model) from three dimensions of connecting support, connecting opportunity and connecting ability, and selects nine conditional variables including facilitators’ attention, feedback, role model, interaction objects’ heterogeneity, identity disclosure, community size, initiative, social attraction and altruism. Furthermore, to reveal the combined effects of social interaction factors on the quality of individual knowledge contribution in connectivist learning, 10,598 interactive data from the first Chinese cMOOC are collected and analyzed through the fuzzy qualitative comparative analysis method (fsQCA). The findings are as follows: 1) There are three driving patterns of high-quality knowledge contribution, self-oriented, open altruistic and facilitator dependent; 2) High-quality knowledge contribution needs feedback incentive, role model and individual social attraction; 3) Facilitators’ attention or role model, initiative or altruism are the core conditions for high-quality knowledge contribution. This study not only provides an analysis model of factors affecting knowledge contribution in connectivist learning, but also further reveals the specific effect mechanism of the social interactions to knowledge contribution, which can help the researchers and cMOOCs designers understand the knowledge contribution behavior of learners, and give references to design the incentive mechanism and learning support to stimulate the learners’ high-quality knowledge contribution.

From the dual dimensions of perception and power, digital learning space promises a constantly evolving and wonderful utopian learning landscape. However, in this ideal learning world, highly developed digital technology and learning activities are mutually constructive, deeply changing various relationships in the learning process, including the separation and alienation between the reality of digital learning and its supposed essence or real connotation, resulting in the alienation phenomenon of digital learning space, which is mainly manifested in the rootless identity caused by the alienation of subject identity, the invisible visual trap caused by the transparency of embodied interface, and the phantom binding of the learning “landscape” caused by the difficulty in distinguishing the false from the false. These phenomena of value alienation make the learning space become a “heterotopia” regulated by digital technology, which seriously hinders the realization of its lear-ning value. In order to recover the educational value of digital learning space, it is necessary to make joint efforts from the following three aspects: rethinking the existence of human subject and realizing the re-recognition of subject identity; avoiding the risk of interface temptation and enhancing the self-consciousness of technology embodiment; and beyond the delusional illusions of the landscape, finding the true value of learning, in order to better realize the value of digital learning space.

As digital natives, Generation Z are highly engaged in Internet usage. Based on data from the China Family Panel Survey (CFPS) 2020, this study uses a multi-categorical ordinal logistic regression model for analysis. The results show that there is a usage gap among Generation Z with different family status. In addition, the impact of Internet usage on academic performance varies according to stage and prior grade rankings. Specifically, Internet usage has class and performance heterogeneity, in other words, the higher the social and cultural capital of the family and the higher the academic ranking, the more inclined to learn by the Internet. Internet learning effectively promotes university academic performance, while it is not significant for secondary school academic performance; Internet entertainment shows a wide range of significant negative effects, among which the effect on secondary school academic performance is stronger, but there is a time effect on university academic performance. Therefore, in order to effectively promote educational outcomes by information technology, it is necessary to build a digital enhancement learning environment, supervise by home-school cooperation and guide individuals to cultivate online learning ability and enhance self-control.

Education, science and technology, and talents are the fundamental and strategic support for Chinese path to modernization, which is determined by the status and role of education, science and technology, and talents in the process of modernization. In different stages of modernization development, modernization in the catching-up period and modernization after completion, the role and performance of education, science and technology, and talents are different. Chinese path to mo-dernization is still in the process of development, and scientific and technological innovation occupies a dominant position among the three. From the past reforms of education, science and technology, and talents separately to the current integrated reform of education, science and technology, and talents, the common point is to obey and serve the national development strategy and economic system reform. The difference is that the goal of the separate reforms is to adapt to the transition from the planned economic system to the market economic system, and to develop a big country in education, science and technology, and talents. The current integrated reform is a multiplier effect of the three. It is necessary to build a strong country in education, science and technology, and talents in the integrated reform, and at the same time, build a system and mechanism to support comprehensive innovation in the integrated reform to improve the overall efficiency of the national innovation system.

Since the beginning of the 21st century, the returns to education in China’s labor market have shown a declining trend, yet the competition for indivi-dual educational investment, exemplified by the phenomenon of the “Shang An Re”, has become increasingly fierce. In the context of China’s segmented labor market, does education primarily fulfill a productive function through the formation of human capital or a screening function via credential signaling? This article analyzes data from nine waves of CGSS. The findings provide stronger support for the “weak screening” theory. However, wage premiums in the public sector are primarily driven by the screening function of education, whereas the non-public sector relies more on the productive function of education. Heterogeneity analyses reveal that as work experience increases, the screening function of education in the public sector gradually diminishes, while the productive function of education in the non-public sector also gradually declines. The dynamic changes in the screening function of education reflect the tension in the public sector between emphasizing educational signals and the diminishing reliability of these signals over time. Gender heterogeneity analyses indicate that the educational functions for male workers align with the overall sample findings across different sectors, whereas no significant effects are observed for female workers. This, to some extent, highlights the potential existence of gender discrimination in the current labor market. Based on these findings, it is recommended to enhance the practical value of education to promote a shift from “credential-based education” to “competence-based education”. Additionally, breaking down inter-sectoral educational signal barriers is essential to facilitate the free flow of talents in the labor market. Lastly, enabling women to transform their educational advantages into career advantages.

Education tracking is a crucial structural education system that plays a significant role in national development and public welfare. It encompasses various stratified designs, including vocational-academic tracking, model schools, ability-based classes, and differentiated instruction, all of which are closely tied to educational equity and social mobility. This study analyzes data from 78 countries/regions in PISA 2022. First, principal component analysis was employed to construct an education tracking index, revealing that nearly 60% of the participating countries/regions had an education tracking index below 0.4, suggesting that education tracking is not a universally adopted practice. Additionally, within the same country/region, in-school tracking and inter-school tracking are generally not implemented concurrently. Secondly, employing Latent Profile Analysis (LPA), the typologies of educational tracking across countries and regions were classified into four distinct profiles: high-tracking, late-tracking characterized predominantly by between-school differentiation, late-tracking characterized predominantly by within-school differentiation, and low-tracking. Finally, utilizing simple linear regression and fixed-effects models, the analysis examined the significant exacerbating effects of educational tracking on educational inequality. The findings revealed that between-school tracking systems are the principal contributors to the intensification of educational inequality, whereas within-school tracking exhibits a comparatively lower potential risk in exacerbating educational inequality. A comparison with the PISA 2018 data from four Chinese provinces and municipalities reveals that China’s education tracking is relatively advanced internationally, characterized by a coexistence of moderate inter-school tracking and high in-school tracking. Future designs of education tracking could consider the following aspects: strengthening industry linkages, reducing the proportion of inter-school tracking; promoting the integration of vocational and academic education, creating flexible and interconnected educational pathways, and alleviating parental anxiety; advancing the standardization of education, and promoting the balanced development of inter-school educational resources.

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 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.

Utilitarianism ethics takes “the greatest happiness of the greatest number of people” as its basic tenet and expresses the public moral ideal. However, a kind of vulgar utilitarianism, which encourages people to weigh the advantages and disadvantages and pursue their own selfish interests, is increasingly penetrating into the school, making the school move towards utilitarianism in the value guidance of quick success and instant benefit. Utilitarian education puts the goal of education beyond itself by turning needs into desires, and gives up the value ideal of education in the individualized competition and the pursuit of progress. Education is simplified to mechanical training and learning to repetitive work. The fundamental problem of utilitarianism education is the “spiritual” problem, which makes individual freedom of will impossible by encouraging students’ natural desires. Students become spiritual wanderers in an atomized world through the deconstruction of the educational entity. At the same time, in the separation of thinking and will, and in the disconnection of knowledge and action, the spirit becomes a thinking spirit that cannot move towards reality. On the one hand, the spiritual reconstruction of school education needs to recognize the spiritual turn, so as to regard education as an indivi-dual’s spiritual process; on the other hand, the method of spiritual reconciliation is needed to realize the inner unity of children’s natural desires and free nature, special individuals and universal entities. At the same time, it is also necessary to promote the spiritual return of school education in knowledge, morality, art and other contents, so as to truly make the school a spiritual world in pursuit of truth, goodness and beauty.

Generative artificial intelligence（GenAI） profoundly impacts the social division of labor and career patterns, driving the reshaping of societal knowledge and a rapid evolution in the perception of talent. The challenge for higher education is how to keep pace with the progress of the times and the new changes in the labor market structure, deepen the implementation of the fundamental task of cultivating people with moral integrity, meet the new demands for talent cultivation, and actively innovate in order to better promote student development. This is not only the current reality faced by higher education but also a practical problem that urgently needs to be solved. This study is theoretically guided by Astin’s framework of institutional influence and higher education evaluation. Through collating application guidelines of GenAI released by 38 world-class universities and by applying grounded theory and hierarchical clustering methods, it is found that the characteristics of the application of GenAI to empower students’ development in world-class universities manifest as attaching importance to the starting point, respecting differences, focusing on the process, and emphasizing development. Based on their own development positioning, universities present three types of differentiated attitudes towards the application of GenAI: strategic layout, defensive response, and targeted integration. Additionally, a series of scenarios such as standardized application, intelligent study companions, and high-awareness learning have been constructed. Based on the above forward-looking international experiences, it is proposed that universities in China deepen the exploration of their paths from three aspects: enhancing the cognition of functional value, detailing the guidance of the policy framework, and intensifying the creation of application scenarios.

Influenced by Aristotle’s classification system of knowledge, Western philosophy has historically prioritized theoretical knowledge, suppressing and marginalizing the role of media technology for more than 2,500 years. This intellectual trend has similarly affected historical and educational research. Since the early 20th century, the continuous emergence of new media technologies has prompted significant shifts in historical studies. Since the 21st century, the rapid development of the Internet and artificial intelligence has introduced unprecedented challenges to educational development. The needs of the times call for educational historians to carry out “technological dimension of educational change history research”. Building on the transformative trends in the 20th-century historical research, this paper proposes a new paradigm for studying the history of educational change from a technological perspective. Key areas of focus include the technological origins of education, technology and human cognitive development, media technology as a “metacognitive” tool, historical data collection and analysis, and collaborative models of academic research communities. From the long-term perspective on educational reform, the overall trends of future educational development will likely encompass: at the individual level, fostering students’ multimodal literacy; at the institutional level, adjusting curriculum structures to support lifelong learning by establishing a “knowledge coordinate system”; and at the societal level, reconstructing the human knowledge map and supporting the operation of an intelligent society.

Technology in the intelligent era is profoundly changing and shaping various aspects of educational life, forming an educational landscape and social reality where technological tools are compared with various elements in education. People gradually acknowledge the superiority of using technological tools in educational practice, making them not only an extension of human organs in education, but also increasingly showing their “replacement” role in various elements of education. This has further led to the “Promethean shame” in the field of education from the perspective of Gunther Anders’ post humanism, that is, the shame that “humans are not as good as machines they create”. Exploring the phenomenon of “obsolescence” in education under the context of technological “substitution” is not to deny technology, but to use universal skepticism as a philosophical method to guide people to rationally seek a technological reshaping path based on the essence of education, and to correct, break through, deepen, and surpass it, in order to help “technology that is increasingly detached from human control” return to promoting the sanctity and charm of spiritual fulfillment and building a better life.

The construction of a modernized powerful country must be based on, guided by, and driven by the modernization of higher education, and the modernization of higher education must be based on the internationalization of higher education as a necessary path choice. Therefore, the internationalization of higher education is of great significance to the construction of an educationally powerful country and a modernized powerful country. The internationalization of higher education requires higher education institutions, especially world-class universities, to achieve this through strengthening exchanges and cooperation with various countries, especially with higher education powers, therefore, the construction of world-class universities must become an open system through internationalization to absorb the successful experience of international higher education, stimulate the vita- lity of academic ecological organization, and enhance international competitiveness. Based on the answers to the internationalization of higher education and its relationship with the construction of Chinese modernization, and why the internationalization of higher education is important to the construction of world-class universities, this article proposes and explains the internationalization action options in the process of building world-class universities, starting from the fact that the construction of world-class universities must strengthen the rationality of international development and actively put it into action in running schools, that it must choose a diversified action model for the internationalization of higher education, and that the internationalization of higher education must focus on improving academic competitiveness.

Vocational education is a type of education with the same important status as general education. Based on this value judgment, the compensation based on equality for vocational education is on the basis of equal concerns and focuses on the fairness of the development effect of vocational education. Vocational education in the “lack” state should be compensated to achieve the same important status as general education. In reality, the educational evaluation system, the distribution of educational resources and public opinion have all objectively caused the realistic dilemma of “unequal” status between vocational education and general education. As a correction of the “unequal” status, the compensation based on equality is the balance of rights and obligations for the educated group of vocational education, the just care for the educated group of vocational education, and the deserved rights and interests of vocational education type attributes.

Mainstream learning analytics focuses on instrumental rationality, such as data collection, analysis and mining, and algorithmic modeling, while the value rationality research on how to use learning analytics has been overlooked. As a result, there is a significant imbalance between instrumental rationality and value rationality on the development and utilization of educational data elements. Therefore, this study conceptualizes the value rationality goal of learning analytics, which is referred to as “actionable insights”. Then, the connotation of actionable insights is clarified, the conceptual structure of actionable insights is constructed, the narrative features of actionable insights are characterized, and the analytical reasoning processes and design strategies that support the generation of actionable insights are proposed. The study argues that actionable insights represent meaningful knowledge or information that can be acted upon by end-users from learning analytics, including four hierarchical components: factual, interpretive, reflective and actionable insights. To effectively support the generation of actionable insights, it is recommended to adopt user-centered participatory design methods, incorporate the design concept of data storytelling, and integrate educational theories or learning constructs when designing and developing learning analytics systems.

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.

Technology-empowered educational assessment is not only a key pathway and an important breakthrough for deepening educational assessment reforms, but also an inevitable choice for accelerating the high-quality development of education. Technology-empowered educational assessment can be divided into four developmental stages. Each stage shows its own significant characteristics and also reveals the practical dilemmas faced by technology-empowered educational assessment in the implementation process. Therefore, scenario-based assessment should be a new trend in the current stage of intelligent assessment. Based on the explanation of the connotation and features of scenario-based assessment, researchers believe that the “Evidence Centered Design” (ECD) theory can be introduced into scenario-based assessment, and a scenario-based assessment design framework can be constructed based on the three core elements of learner model, evidence model, and task model. Finally, taking the assessment of normal university students’ intelligent educational literacy as an example, the article proposes a scenario-based assessment design path consisting of four interconnected stages: learner model, authentic task model, process data model, and assessment analysis model, aiming to provide support and reference for the design and implementation of intelligent assessment.

Implementing accurate financial grants for students from economically disadvantaged families is an important policy tool for preventing poverty and achieving the Common Prosperity Goal. Using the China Education Panel Survey data and the causal identification design formed by random student-classroom assignment, this paper estimates the spillover effect of the “one subsidy” policy for students from economically disadvantaged families at elementary and secondary school. We found that the “one subsidy” has a significant positive spillover effect on the academic performance of unsubsidized students in the class. The accurate identification of economically disadvantaged families has a significant impact on the spillover effect of “one subsidy” policy. Formation of this spillover effect which is closely related to the learning interaction and interpersonal communication among students depends a lot on accurate identification of poverty. The results of mechanism analysis show that the learning effort level of students, interpersonal relationship between classmates, and the integration and cohesion of class can significantly be promoted by subsidies for students from economically disadvantaged families. The implementation of this targeted subsidy contains great economic value which can be an important starting point and effective means to promote common prosperity in the new development stage. In the future, we should further lower the threshold of educational subsidies for policies of poverty alleviation, improve the level of accurate identification for students from economically disadvantaged families, and implement differential subsidies according to the poverty degree of students’ families.

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.

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.

The contradiction between humans and intelligent machines is the main contradiction in today’s and future human society. The relationship between humans and intelligent machines has become the main relationship in education. In order to resolve the contradiction between humans and intelligent machines, we need to cultivate new intelligent individuals from the perspective of the man-machine relationship and promote the education revolution in the era of artificial intelligence. The new intelligent individual is someone who can compete with artificial intelligence, live in harmony with it, possess the ability to interact and coexist with intelligent machines, have practical skills in interacting with intelligent machines, and can achieve the integration and symbiosis of human intelligence and artificial intelligence. To cultivate this new type of intelligent people, it is necessary to break prejudices, expand boundaries, and enter daily life through practice, including the curriculum standards system, curriculum system, textbook system, teaching and research system, and evaluation system.

China’s education evaluation standards mainly consist of two parts: laws and policies. However, there are “congenital deficiencies” in both aspects, such as outdated evaluation purposes, unified evaluation subjects and single evaluation standards. As the emerging intelligent education model gradually comes into reality, what kind of adaptive change should be made to the evaluation purpose, subject, and standard, in the educational evaluation norms has become the focus of relevant education legislation and policy formulation. In order to further promote the reform of education evaluation in the new era, combined with the technical characteristics and development trends of intelligent education, the evaluation purpose of China’s education evaluation standards should shift from “diagnostic tool” to “individualized teaching”; the evaluation subject should shift from government to “government+education+social third party”; and the evaluation standard should change from “extensive” to “meticulous”.

“Listening to the Voices from the Window Outside” is one of the ten major actions in the New Education Experiment. This paper aims to comprehensively summarize and deeply reflect on the theoretical research and practical exploration of the “Listening to the Voices from the Window Outside” action in the New Education Experiment, and devise new ideas and measures for this action to set out again, thus driving the New Education Experiment forward and helping the teachers and students involved in the experiment to listen to the voices from the window outside more scientifically and effectively, return to the world of life, and live a happy and complete educational life. This will enable the New Education Experiment to contribute wisdom and strength to the construction of a socialist modernization strong country in education in the new era.