Search Results (152)

Global climate change has emerged as a critical challenge for human society in the 21st century. As hubs of population and economic activity, urban and rural areas are increasingly exposed to complex and compounded disaster risks. To systematically evaluate the role of educational intervention in climate adaptability capacity building, this study employs a case study approach, focusing on the “Climate Change Adaptation Education and Teaching Alliance Program” launched in Taiwan in 2014. Through a comprehensive analysis of its institutional structure, curriculum, alliance network, and practical activities, the study explores the effectiveness of educational innovation in cultivating climate resilience talent. The study found that the program, through interdisciplinary collaboration and a practice-oriented teaching model, successfully integrated climate adaptability content into 57 courses, training a total of 2487 students. Project-based learning (PBL) and workshops significantly improved students’ systems thinking and practical abilities, and many of its findings were adopted by local governments. Based on these empirical results, the study proposes that urban and rural planning education should be promoted in the following ways: first, updating teaching materials to reflect regional climate characteristics and local needs; second, enhancing curriculum design by introducing core courses such as climate-resilient planning and promoting interdisciplinary collaboration; third, enriching hands-on learning through real project cases and participatory workshops; and fourth, deepening integration between education and practice by establishing multi-stakeholder partnerships supported by dedicated funding and digital platforms. Through such an innovative educational framework, we can prepare a new generation of professionals capable of supporting global sustainable development in the face of climate change. This study provides a replicable model of practice for education policymakers worldwide, particularly in promoting the integration of climate resilience education in developing countries, which can help accelerate the achievement of UN Sustainable Development Goals (SDG11) and foster interdisciplinary collaboration to address the global climate crisis. Full article

Under the background of “Emerging Engineering Education”, promoting reform in the practical teaching of Agricultural Hydraulic Engineering is a crucial task for cultivating water conservancy professionals with sustainability competencies in the new era. This study addresses current issues in the practical education of Agricultural Hydraulic Engineering, including fragmented practical content, disjointed tiered training, superficial teaching models, and simplified assessment methods. Guided by the Outcome-Based Education (OBE) concept and incorporating sustainability education principles, and integrating the distinctive features and course orientation of the university’s programme, this study implements a multidimensional practical teaching reform characterized by “three level–four integration–five dimension–three objective” framework in Agricultural Hydraulic Engineering. This reform has achieved significant outcomes: teaching quality has been notably enhanced, with students demonstrating substantially improved practical and innovative capabilities, earning over ten national and provincial competition awards in the past two years. Faculty teaching research capabilities have strengthened, resulting in multiple provincial-level teaching reform projects and top-tier course approvals. The proportion of courses achieving a satisfactory level of target attainment stands at 66.7% of the total practical courses. Graduate and employer satisfaction rates reached 96.2% and 100%, respectively. The results demonstrate the strong applicability and effectiveness of this multidimensional practical teaching model in fostering talent equipped for sustainable water conservancy development, providing an important reference for practical teaching reforms in agricultural universities during the new era. Full article

Artificial intelligence (AI) has significantly influenced higher education, accelerating the arrival of College 4.0. Given its core mission of cultivating talent through teaching, understanding how AI can empower teaching in higher education is crucial. Utilizing second-hand survey data from the Zhejiang Provincial Department of Education, this study empirically diagnoses the status of AI-empowered teaching in higher education across 81 universities, 4085 faculty members, and 24,095 students, by descriptive statistical analysis. The results reveal critical structural misalignments. At the institutional level, while 94% of universities have formulated AI plans, a severe disciplinary imbalance exists, with science and engineering accounting for 60.1% of specialized courses compared to only 4.5% in agriculture and medicine. At the faculty level, a “high cognition, low practice” gap is evident; although willingness is high, 96% of instructors lack significant industry practice experience. At the student level, a substantial misalignment appears between the demand for AI skills and educational supply. Based on these findings, we propose targeted strategies for optimizing resource allocation and establishing cross-boundary teacher training systems to promote AI-empowered teaching to achieve sustainable higher education. Full article

The widespread application of Generative Artificial Intelligence (Gen-AI) is transforming educational practices and driving pedagogical innovation. While cultivating higher-order thinking (HOT) represents a central educational goal, its achievement remains an ongoing challenge. Current evidence regarding the impact of Gen-AI on HOT is relatively fragmented, lacking systematic integration, particularly in the analysis of moderating variables. To address this gap, a meta-analysis approach was employed, integrating data from 29 experimental and quasi-experimental studies to quantitatively assess the overall impact of Gen-AI on learners’ HOT and to examine potential moderating factors. The analysis revealed that Gen-AI exerts a moderate positive effect on HOT, with the most significant improvement observed in problem-solving abilities, followed by critical thinking, while its effect on creativity is relatively limited. Moderation analyses further indicated that the impact of Gen-AI is significantly influenced by experimental duration and learners’ self-regulated learning (SRL) abilities: effects were strongest when interventions lasted 8–16 weeks, and learners with higher SRL capacities benefited more substantially. Based on the research findings, this study proposed that Gen-AI should be systematically integrated as a targeted instructional tool to foster HOT. Medium- to long-term interventions (8–16 weeks) are recommended to enhance learners’ problem-solving and critical thinking abilities. At the same time, effective approaches should also be explored to promote creative thinking through Gen-AI within existing pedagogical frameworks. Furthermore, individual learner differences should be accounted for by adopting dynamic and personalized scaffolding strategies to foster SRL, thereby maximizing the educational potential of Gen-AI in cultivating innovative talents. Full article

Background: Cultivating core literacy in physical education (PE) is increasingly recognized as crucial for talent development in higher education. Although diverse assessment tools exist for various literacies, none specifically evaluate the core literacy of the PE discipline among Chinese university students. This study aimed to develop and validate a scale for assessing this core literacy. Methods: An initial item pool was developed through a comprehensive literature review and in-depth expert interviews. Following three rounds of Delphi expert consultation (n = 15) and a pilot test, five items exhibiting insufficient discriminative power or conceptual redundancy were removed, yielding the final Chinese University Students’ Physical Education Core Literacy Assessment Scale. The scale was administered to 1008 university students. Its reliability and validity were examined through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Results: The finalized scale contains 43 items across three dimensions. Model fit indices were excellent: χ²/df of 1.252, RMSEA of 0.016, CFI of 0.934, TLI of 0.992. Conclusion: The newly developed scale proves to be a valid and reliable instrument for measuring core PE literacy among Chinese university students. Full article

Against the backdrop of great power strategic games, countries around the world have been continuously intensifying their control over the trade of critical metals, including tungsten, in order to seize the commanding heights of scientific, technological, and economic development, which has led to increasingly fierce competition in the global tungsten industry chain and supply chain. Although China is endowed with abundant tungsten ore reserves, its tungsten industry chain remains dominated by mid-to-low-end products, with low added value and limited pricing power in the international market. Therefore, it is of great significance to clarify the export competitiveness level of China in each link of the tungsten industry chain and to identify the influencing factors for improving the overall competitiveness of the industrial chain, which will enhance China’s international status and assist in formulating sustainable tungsten resource management strategies. Based on the industrial chain perspective and the trade data of typical products at various stages of the tungsten industry chain from 2008 to 2022, this study first selects the World Market Share Index, Trade Competitive Advantage Index, and Revealed Comparative Advantage Index to quantitatively depict the export competitiveness of the overall, upstream, midstream, and downstream sectors of China’s tungsten industry chain, and a horizontal comparison is conducted with major global tungsten resource trading countries. Secondly, the entropy weight method is adopted to further comprehensively evaluate the competitiveness level of various countries. Finally, the potential influencing factors of the overall export competitiveness of the tungsten industry chain are explored in accordance with Porter’s Diamond Model, and a fixed-effect model is used to perform regression analysis on the panel data. The research findings show that China has strong export competitiveness in the midstream and downstream sectors of the tungsten industry chain, while its export competitiveness in the upstream tungsten ore sector is relatively weak. The level of education, human capital, educational expenditure, gross national product, and trade openness all have a significant positive impact on the export competitiveness of tungsten resources. Greater efforts should be made in China to cultivate high-end talents in the tungsten industry. Moreover, innovation in green technologies and products should be encouraged, and international cooperation should be deepened, to improve the efficiency of the entire industrial chain so that stable and green long-term competitiveness in the tungsten industry can be achieved. Full article

This study proposes a novel structure-preserving algorithm for the Ginzburg–Landau equation (GLE) by combining the Fourier pseudospectral method with the Exponential Average Vector Field (EAVF) scheme. The proposed numerical framework strictly preserves the energy dissipation property of GLE systems, as validated through theoretical analysis and numerical experiments on solitary wave dynamics. Compared to conventional methods such as the average vector field approach, the EAVF-based scheme demonstrates superior computational efficiency, including faster convergence and enhanced stability under larger time steps, enabling accurate long-term simulation of strongly nonlinear GLE systems. Furthermore, this research incorporates a pedagogical innovation through its implementation within an undergraduate innovation project. By adopting a “problem decomposition–code verification–modular development” training model, students engage in the full cycle of algorithm design, implementation, and validation. This practice-oriented approach significantly enhances students’ competencies in scientific programming, complex problem-solving, and research-oriented thinking, providing an effective paradigm for synergizing advanced computational research with talent cultivation in STEM education. Full article

This study takes the Phoenix Mosque (fenghuangsi 凤凰寺) in Hangzhou as a representative case to explore the localization patterns and profound cultural connotations of colour application in Chinese Islamic architecture. The findings reveal that the architectural colour scheme of the Phoenix Mosque not only skillfully integrates traditional Islamic symbolism with Chinese cultural aesthetics but also emphasises simplicity and purity in its overall design, vividly reflecting the unique Jiangnan (Lower Yangtze) regional aesthetic distinct from other styles of Chinese Islamic architecture. This distinctive chromatic system carries significant implications for cultural heritage preservation, artistic aesthetics, and tourism development. However, it also faces multiple challenges, including insufficient preservation techniques, risks of cultural misinterpretation, and a shortage of specialised professionals. In response, this study systematically proposes a set of comprehensive strategies that combine scientific conservation and technological innovation, deepen cultural education and communication, and strengthen talent cultivation and academic research. The aim is to provide robust theoretical foundations and practical pathways for the preservation, inheritance, and innovative development of colour traditions in Chinese Islamic architecture. Full article

New quality agricultural productivity is essential for advancing agricultural modernization, consolidating and expanding achievements in poverty alleviation, and driving rural revitalization. However, leveraging this productivity to facilitate industrial upgrading and support the transition of smallholder farmers remains challenging. This paper constructs a tripartite evolutionary game model involving the government, agricultural enterprises, and farmers within the policy framework of new quality agricultural productivity. By applying evolutionary game theory, we analyze the strategic interactions among policy implementation, farmer welfare, and the development of new quality agricultural productivity. Equilibrium analysis reveals that the government, as a regulatory actor, should provide appropriate subsidies to agricultural enterprises and farmers, undertake initial infrastructure improvements, diversify subsidy instruments, establish special incentives for agricultural technology innovation, and increase investment in cultivating new agricultural talent. Agricultural enterprises, as dynamic agents, should adopt proactive and systematic transformation strategies. Furthermore, they need to strengthen benefit-linked mechanisms with farmers to ensure sustained collaboration. Full article

This paper addresses the core issue of the imbalance between supply and demand for high-level medical–engineering integration talents under the “Healthy China” strategy in the AI+ era. Based on human capital theory and innovation capital theory, it constructs a six-dimensional collaborative theoretical model for the cultivation of medical–engineering integration postgraduates, driven by high-quality employment and guided by innovative financial capital. This model breaks through the disciplinary barriers and institutional constraints of traditional postgraduate education and for the first time creates a knowledge graph curriculum system for medical–engineering interdisciplinary studies. It also establishes a multi-dimensional evaluation index system that integrates the appreciation of innovation capital and the premium of human capital. Through the case of the six-dimensional collaborative research and development and transformation of intelligent medical equipment by our research group, the feasibility and promotion value of this new paradigm for future postgraduate education have been fully verified. Full article

In response to the dual challenge of global agricultural greening and digital transformation, it is imperative for agricultural colleges and universities in China to restructure talent cultivation models to support the development of sustainable and intelligent agriculture. This study combines literature analysis, case studies, and questionnaire surveys to identify misalignments between the current agricultural education system and industry needs. Focusing on educational objectives, curricula, practical training, and faculty expertise, the authors propose a novel four-dimensional collaborative cultivation model, “Objectives–Curriculum–Practice–Faculty”. This model centers on interdisciplinary course clusters (e.g., agricultural artificial intelligence and blockchain traceability), industry–academia-integrated training platforms (e.g., smart agriculture innovation centers), and a Dynamic Adjustment Mechanism (DCAM). To support the implementation of this model, this study advances policy recommendations from three perspectives. First, governments should accelerate reforms by providing special funding support and formulating legislation on industry–academia integration. Second, universities must establish early-warning response mechanisms. Third, enterprises must participate in developing education on ecosystems. This paper establishes both a theoretical framework and a practical pathway to transform agricultural education, offering significant referential value for global agricultural institutions adapting to technological revolutions. Full article

Addressing Artificial Intelligence (AI) faculty deficiencies in higher education, this paper develops the AI+ Dual-qualified Teacher Capability Ecology Model (AI-DTCEM) based on Capability Ecology Theory. The model is developed after a thorough analysis of the current state of new engineering talent cultivation in universities and the innovative practical abilities required in the AI+ environment. This paper proposes an implementation framework characterized by “three-dimensional collaboration, four-tier progression, and five-element drive.” Additionally, it uses the collaborative education project involving Hangzhou Normal University, Zhejiang University, and Hangzhou Ruishu Technology Co., Ltd. as a backdrop to introduce a deep collaborative education model, showcasing the theoretical and practical achievements of this project. Using NetLogo as the simulation platform, this paper designs a 96-month system dynamics experiment to compare and analyze the outcomes of four scenarios: the baseline experiment, the AI-enhanced experiment, the policy-driven experiment, and the comprehensive optimization experiment. This study reveals the following findings: (1) Policy-driven initiatives are crucial for the successful construction of dual-qualified teacher teams, with the policy-driven scenario achieving the highest overall skill level (9.332). (2) The application of AI technology significantly enhances teacher skill development, resulting in AI skill improvements ranging from 116.6% to 163.4%. (3) The comprehensive optimization scenario (utilizing a collaborative mechanism) achieves systemic advantages, realizing a 100% dual-qualified teacher ratio. However, this comes with diminishing marginal returns on investment. This research provides a theoretical foundation, quantitative analysis, and practical pathways for developing dual-qualified teacher teams in the AI+ era. Full article

This study examines how policy incentives enhance students’ entrepreneurial mindset and agility through industry–academia collaboration. Unlike prior research that often adopts institutional or industry perspectives, this paper foregrounds the experiences of students as the primary beneficiaries of entrepreneurship education policies. Drawing on survey data from 528 students across Taiwan and Malaysia, the study tests a comprehensive conceptual framework incorporating professional engagement, curriculum design, and skill development as mediating mechanisms. Using structural equation modeling, the findings show that policy incentives exert strong direct and indirect effects on entrepreneurial outcomes, although some mediating pathways are contingent on the quality of engagement. By positioning student perspectives at the center of analysis, this study contributes to understanding how policy support translates into experiential learning and entrepreneurial agility. Implications are drawn for educators, policymakers, and students, with suggestions for refining collaboration structures and fostering student-centered entrepreneurship ecosystems. Full article

This study proposes a novel curriculum framework for Smart Breeding 4.0 to address the interdisciplinary talent gap in sustainable agriculture. Responding to the limitations of traditional agricultural education, the curriculum was developed through an analysis of emerging technological trends and industry needs. It is structured around four integrated modules: (1) Foundational Theory, tracing the evolution to data-driven breeding; (2) Technology Integration, combining AI and blockchain for precision breeding; (3) Practical Innovation, using real-world platforms for simulation projects; (4) Ethics and Policy, cultivating responsibility through case studies. Teaching emphasizes project-based learning with open-source tools, while assessment combines exams, data analysis, and innovation proposals. Explicitly aligned with key UN Sustainable Development Goals (SDGs), this conceptual framework provides a foundational model for agricultural universities worldwide. The primary contribution of this paper lies in its systematic design; future research will focus on empirical validation through pilot implementation. Full article

Architectural design stands as a highly knowledge-intensive field, with designers serving as the linchpin for its premium development. China’s construction industry is now navigating a transitional phase of slower growth, where a misalignment in designer capabilities significantly obstructs the nation’s shift from being a mere “construction giant” to becoming a true “construction powerhouse”. Based on the spatial mismatch model and Geodetector, this study empirically analyzes the mismatch relationship among designers and its influencing factors using panel data from 31 provinces in China from 2013 to 2023, and proposes strategies for cultivating architectural design talents. Findings reveal that China’s architectural designers exhibit spatial supply imbalance, and complex trends in designer allocation-simultaneous growth and decline coexist. China exhibits diverse types of architect mismatch: 22.58% of regions are in a state of Positive Mismatch, and 12.90% experience Negative Mismatch. In over one-third of regions, the architectural design talent market can no longer self-correct architect mismatch through market mechanisms, urgently requiring collaborative intervention policies from governments, design associations, and enterprises to address architect supply–demand governance. For a smooth transition during the transformation and upgrading of the construction and design industries, the architectural design talent market should accommodate frictional designer mismatch. The contribution of designer mismatch varies significantly, with factors such as innovation, industrial structure, and fiscal self-sufficiency exerting more direct influence, while other factors play indirect roles through dual-factor enhancement effects and nonlinear enhancement effects. The insights from the analysis results and conclusions for future designer cultivation include fostering an interdisciplinary teaching model for designers through university–enterprise collaboration, enhancing education in AI and intelligent construction literacy, and establishing an intelligent service platform for designer supply–demand matching to promptly build a new differentiated and precise designer supply system. Full article