There exists a “high support-low conversion” phenomenon in top-talents cultivation, with its core crux lying in “response failure”. This study aims to explain this practical dilemma theoretically. Rooted in local practical experience, this paper proposes a “Support–Response–Development” (S-R-D) analytical framework. further subdivides support indicators into three dimensions—cognitive, autonomous, and contextual—while employing response indicators as mediating variables, attempting to establish a bridge between cultivation support and student development. This framework aims to provide a novel tool and theoretical underpinning for the improvement of top-talent cultivation programs in China. Applying this analytical framework, this paper conducts a thick description of talent cultivation reform programs such as the Special Class for the Gifted Young and the Basic Science Top-Notch Student Training Program 1.0, preliminarily revealing the dynamic and complex relationship between cultivation support and student development, and offering improvement insights for addressing the “response failure” problem in cultivating top-notch students.

Early identification constitutes a pivotal stage in cultivating top innovative talents, bearing directly on the effectiveness of the innovation-oriented talent supply system. As China’s largest mechanism of educational selection, the college entrance examination (CEE) system, anchored in standardized testing and holistic admissions, plays an essential role in identifying talented students. Using longitudinal survey data of “Double First-Class” universities, this study systematically examines the validity of the CEE system in identifying talented students. The results reveal that although standardized CEE scores provide an initial screening signal for students’ academic performance, innovation-related capabilities, and academic aspirations, their validity in identifying talented students with outstanding comprehensive competence remains limited. Further analysis indicates that a combined selection system integrating standardized examinations with holistic admissions significantly enhances identification precision. Moreover, talented students’ development resists a linear interpretation based on initial conditions and instead follows a dynamic, stage-contingent, and context-dependent process. Instructional quality, close student-faculty interaction, and academic involvement during college emerge as decisive factors in talent formation. These results broaden the theoretical perspective on early identification and offer concrete implications for reforming the CEE and strengthening autonomous talent cultivation systems.

The identification, cultivation and evaluation of top innovative talents constitute a complex system integrating biological potential, social emotion and cultural personality. From the perspective of multidisciplinary, top innovative talents exhibit differentiated core traits: in terms of potential, their distribution features a dichotomy between the all-rounded and the specialized; in terms of emotion, their attributes fall into two categories of the opinionated and the easy-going; in terms of personality, their types are divided into the composed and the passionate. By further constructing a three-dimensional interactive talent type matrix of potential, emotion and personality, top innovative talents can be subdivided into eight combined types. At present, the identification dimensions of top innovative talents lack adequate integration, which compromises the accuracy of trait assessment; cultivation approaches lack targeted design, which impairs the adaptability of personalized development support; evaluation perspectives are rather one-sided, which reduces the validity of talent value measurement.It is necessary to establish a type-oriented precise identification system, develop personalized cultivation approaches adapted to different talent types, and adjust a diversified evaluation scheme with type synergy, so as to improve the practical paths for the differentiated and high-quality development of all types of top innovative talents.

Since its implementation, the mathematics-based exceptional admission policy under the Strengthening Basic Disciplines Plan has attracted considerable public attention, yet empirical evidence evaluating its policy rationality and practical effectiveness remains scarce. Drawing on administrative data from ten cohorts of undergraduate students at a pilot university participating in the Strong Foundation Plan, this study examines the predictive validity of College Entrance Examination (Gaokao) mathematics scores for students’ undergraduate developmental outcomes, with particular attention to disciplinary heterogeneity. The findings indicate that Gaokao mathematics scores significantly predict the likelihood of becoming “high-achieving students” and “sustained high-performing students,” but exhibit limited effectiveness in identifying “top-tier students.” The predictive effects of mathematics scores vary across disciplines. Specifically, mathematics scores significantly predict high-achieving students in science and engineering majors, and also significantly predict whether high-achieving students in science and humanities fields develop into sustained high-performing students. Moreover, the predictive effect of mathematics scores demonstrates a threshold pattern. Students scoring above 130 are more likely to become high-achieving and sustained high-performing students; scores above 140 show stronger predictive power for identifying high-achieving students; and scores above 145 exhibit the strongest predictive validity for sustained high-performing students. These threshold effects exhibits significant disciplinary heterogeneity. Overall, the effectiveness of the mathematics-based exceptional admission policy provides empirical evidence to inform the optimization of selection mechanisms for cultivating outstanding innovative talent in foundational disciplines.

In the era of artificial intelligence, education is undergoing profound transformation, with curriculum culture at the core of this change. As a new cultural driving force in the new era of education, artificial intelligence technology is gradually propelling the structural transformation of curriculum culture through its technological platforms, core functions, and effects. This transformation manifests itself in several ways: curriculum culture, while maintaining its goals of empowerment and transmission-innovation, is shifting toward a learning revolution centered on cognition and development; while carrying curricular knowledge and activities, it is transitioning toward a classification of knowledge that balances internalization and external storage; the subjects of curriculum culture are increasingly emphasizing human-machine synergy alongside national and individual dimensions; and curriculum culture management is moving from standardized and autonomous models toward an evaluation paradigm that emphasizes interaction and inspiration.In response to the transformation of curriculum culture in the intelligent era, it is essential to prioritize the cultivation of digital literacy to equip individuals with the awareness and capabilities necessary for participating in learning revolution. This can be achieved by optimizing strategies for curriculum resource allocation and innovating paradigms for curriculum activities to support the restructuring of knowledge classification and organizational forms. Additionally, a human-centered and harmonious process of regulation should be upheld to preserve the humanistic spirit in curriculum evaluation. Ultimately, these efforts aim to realize a seamless integration of technology and humanism, efficiency and warmth, and intelligence and ethics.

With the rapid advancement of digital technology, textbooks in China are undergoing a transformation from static, linear print formats to dynamic, interactive digital media. However, the current digital transformation of textbooks largely remains at a superficial level of electronization and intellectualization, overlooking the more fundamental need to reconstruct the discourse system of textbooks. According to the first principles of textbook design, the digital transformation of textbook discourse is essentially a negotiation and adjustment between technical logic and the meta-determination of textbooks in knowledge theory, politics, and education. Based on a critical examination of Western textbook discourse styles, the stylistic characteristics of Chinese textbook discourse are trending toward a digitally structured presentation centered on academic principles, a standardized digital adaptation guided by curriculum standards, and an immersive digital expression enriched by cultural context. In terms of value orientation, it is essential to adhere to digital humanism by advocating for human-centeredness, the co-construction of meaning, and humanistic care. Regarding narrative models, three representative types can be identified: problem-oriented inquiry narratives, data-driven evidence-based narratives, and cross-media collaborative narratives. These address the inherent demands of the digital transformation of textbook discourse from the perspectives of cognitive approaches, modes of thinking, and mechanisms of expression. In the realm of transformation practice, it is necessary to prudently address potential risks of discourse power restructuring and technological alienation that may arise during the process of digital transformation. These include the structural challenge posed by algorithmic recommendation to the authority of textbook discourse, the technological erosion of the dialogical nature of textbook discourse through intelligent interaction, and the unidirectional narrowing of meaning generation in textbook discourse resulting from data-driven presentation. In summary, through a systematic exploration of the stylistic features, value orientations, and potential pathways of the digital transformation of Chinese textbook discourse, this paper aims to provide theoretical references for constructing a textbook system that is value-oriented, culturally grounded, and responsive to the needs of the times.

The explosion of generative artificial intelligence (GenAI) marks a fundamental rupture in the human cognitive ecology, driving education through a profound transition from a “retrieval paradigm” to a “generative paradigm.” Relying on probabilistic computation and the deep semantic simulation of natural language, GenAI has substantially taken over the power of representational production at the ontological level. This deep externalization of representation, coupled with the algorithmic mediation of educational practices, will lead to a systemic imbalance in life perception, meaning comprehension, emotional connection, and subject construction within the educational field. Consequently, this tears open deep chasms while simultaneously implying the potential for de-anthropocentrism. Faced with this “crisis,” both traditional representationalism and naive non-representational theories reveal a poverty of explanatory power. Based on Gilles Deleuze’s philosophy of “differential becoming” and Jacques Derrida’s theory of “différance,” this paper constructs a theoretical framework of “generative intertwining,” demarcating the boundary between the “probabilistic repetition of algorithms” and the “differential becoming of life.” In the dialectic of alignment and flight, education does not reject representation and AI; rather, it integrates machine-generated generality as its underlying substrate. Furthermore, as a technology of différance, education should respond to the gap of understanding by using differential narratives to defer judgments of meaning; bridge the gap of life by recalibrating sensory anchors to extend bodily judgment; traverse the gap of emotion by activating affective generation through aesthetic encounters in aesthetic education; and ultimately respond to the gap of subjectivity by reforming evaluation mechanisms to regather the responsibility dispersed by algorithms and reconstruct the nomadic subject.

To address the structural mismatch between talent supply and demand in local undergraduate institutions during the intelligent era, and aligned with the strategic requirements of the Outline of the Plan for Building a Leading Country in Education (2024–2035), this study aims to construct a quality evaluation system that dynamically responds to external demands. Adopting the CIPP model as the theoretical framework, the study comprehensively integrates Python crawler technology, Grounded Theory, and policy text analysis to mine multi-source data, thereby reconstructing the core competency profile required in the intelligent era. The Delphi method was employed to screen indicators, and the Intuitionistic Fuzzy Analytic Hierarchy Process (IFAHP) was introduced to scientifically assign weights to the system, which comprises 4 primary, 14 secondary, and 42 tertiary indicators. The results indicate that Product evaluation holds the highest weight (0.396) within the system, identifying hard technical skills and the industry-education integration mechanism as critical determinants of talent cultivation quality. The constructed evaluation system facilitates a paradigm shift from experience-based judgment to data-driven evidence, providing methodological support and quantitative tools for resolving the structural dilemma of “employment difficulty” versus “recruitment shortage,” while enhancing the quality of talent supply and regional service capabilities.

Under China's strategic framework of integrated advancement in education, science and technology, and human resources, the employment of engineering graduates serves as a critical link connecting talent, technology, and industry. Based on the data from Chinese College Graduates Employment Survey (2009—2025), this study conducts a multidimensional post-stratification weighting analysis of engineering graduates and finds that their employment settlement rate followed a fluctuating pattern of first rising and then falling, peaking at 89.3% in 2017 before declining to 72.6% in 2025. Institutional employment consistently remained the dominant post-graduation destination, while the proportion pursuing further education peaked at 30.4% in 2021 and then declined. In terms of employment quality, engineering graduates exhibited a pattern of sustained improvement followed by a phase of adjustment: the nominal starting salary of institutionally employed engineering graduates reached 5,497 yuan in 2023 before falling to 5,036 yuan in 2025, while the proportion reporting job satisfaction rose to 81.4% in 2019 and then dropped to 74.2% in 2025. With regard to employment structure, manufacturing remained a major sector for engineering graduates, while construction; the production and supply of electricity, heat, gas, and water; and information transmission, software, and information technology services consistently ranked among the leading industries. State-owned enterprises and private enterprises were the principal employers, and professional and technical personnel remained the predominant occupational category. Spatially, employment was concentrated mainly in eastern China, while the shares absorbed by central and western China became more balanced, and the proportion employed in county-level and below grassroots locations increased. Overall, major-job matching and skill matching remained relatively high, and job preferences gradually shifted toward a balance between developmental considerations and concerns for stability. School type, educational attainment, and the alignment between major and interest are identified as crucial factors influencing engineering graduates’ employment outcomes.

Home-school collaboration is governed by current educational laws. Based on the three legal relationships between schools and students: education and being educated, management and being managed, and protection and being protected, schools and parents have formed four pairs of rights and responsibilities in the collaborative educational process. These pairs include: “guidance on family education” and “cooperation in education”, “notification and information disclosure” and “cooperation in intervention”, “communication, consultation and identification” and “cooperation and participation”, and “cooperation in arrangements” and “notification, suggestion and supervision”. To address the predicament in the adjustment of existing legal norms and respond to the legislative requirements of “school leadership” and “parental initiative”, a legal system for collaborative education that encompasses home-school collaboration should be constructed in the compilation of the Education Code. Meanwhile, the legal regulatio of home-school collaboration should be continuously improved in the application of current laws.