Search Results (346)

This study examines the relationship between national open educational resource (OER) policies and Sustainable Development Goal 4 (SDG4) outcomes across 187 countries between 2015 and 2024, with particular attention to the moderating role of artificial intelligence (AI) readiness. Despite widespread optimism about digital technologies as catalysts for universal education, systematic evidence linking formal OER policy frameworks to measurable improvements in educational access and completion remains limited. The analysis employs fixed effects and difference-in-differences estimation strategies using an unbalanced panel dataset comprising 435 country-year observations. The research investigates how OER policies associate with primary completion rates and out-of-school rates while testing whether these relationships depend on countries’ technological and institutional capacity for advanced technology deployment. The findings reveal that AI readiness demonstrates consistent positive associations with educational outcomes, with a ten-point increase in the readiness index corresponding to approximately 0.46 percentage point improvements in primary completion rates and 0.31 percentage point reductions in out-of-school rates across fixed effects specifications. The difference-in-differences analysis indicates that OER-adopting countries experienced completion rate increases averaging 0.52 percentage points relative to non-adopting countries in the post-2020 period, though this estimate remains statistically imprecise (p equals 0.440), preventing definitive causal conclusions. Interaction effects between policies and readiness yield consistently positive coefficients across specifications, but these associations similarly fail to achieve conventional significance thresholds given sample size constraints and limited within-country variation. While the directional patterns align with theoretical expectations that policy effectiveness depends on digital capacity, the evidence should be characterized as suggestive rather than conclusive. These findings represent preliminary assessment of policies in early implementation stages. Most frameworks were adopted between 2019 and 2022, providing observation windows of two to five years before data collection ended in 2024. This timeline proves insufficient for educational system transformations to fully materialize in aggregate indicators, as primary education cycles span six to eight years and implementation processes operate gradually through sequential stages of content development, teacher training, and institutional adaptation. The analysis captures policy impacts during formation rather than at equilibrium, establishing baseline patterns that require extended longitudinal observation for definitive evaluation. High-income countries demonstrate interaction coefficients between policies and readiness that approach marginal statistical significance (p less than 0.10), while low-income subsamples show coefficients near zero with wide confidence intervals. These patterns suggest that OER frameworks function as complementary interventions whose effectiveness depends critically on enabling infrastructure including digital connectivity, governance quality, technical workforce capacity, and innovation ecosystems. The results carry important implications for how countries sequence educational technology reforms and how international development organizations design technical assistance programs. The evidence cautions against uniform policy recommendations across diverse contexts, indicating that countries at different stages of digital development require fundamentally different strategies that coordinate policy adoption with foundational capacity building. However, the modest short-term effects and statistical imprecision observed here should not be interpreted as evidence of policy ineffectiveness, but rather as confirmation that immediate transformation is unlikely given implementation complexities and temporal constraints. The study contributes systematic cross-national evidence on aggregate policy associations while highlighting the conditional nature of educational technology effectiveness and establishing the need for continued longitudinal research as policies mature beyond the early implementation phase captured in this analysis. Full article

The transition to Outcome-Based Education (OBE) in engineering demands instructional tools that bridge theoretical knowledge and practical engineering competencies. However, traditional Learning Management Systems (LMS) primarily function as static resource repositories, lacking the semantic structure necessary to support deep learning and precise competency tracking. To address this, this study developed a three-layer domain Knowledge Graph (KG) for Structural Geology and integrated it into the ChaoXing LMS (a widely used Learning Management System in Chinese higher education). A semester-long quasi-experimental study (N = 84) was conducted to evaluate its impact on student performance and specific graduation attribute achievement compared to a conventional folder-based approach. Empirical results demonstrate that the KG-integrated group significantly outperformed the control group (p < 0.01, Cohen’s d = 0.74). Notably, while performance on rote memorization tasks was similar, the experimental group showed marked improvement in identifying and solving complex engineering problems. LMS log analysis confirmed a strong positive correlation (r = 0.68) between graph navigation depth and academic success. KG effectively bridged the gap between theoretical knowledge and practical engineering applications (e.g., geohazard analysis). This research confirms that explicit semantic visualization acts as vital cognitive scaffolding, effectively enhancing higher-order thinking and ensuring the rigorous alignment of instruction with engineering accreditation standards. Ultimately, this approach promotes sustainable learning capabilities and prepares future engineers to address complex, interdisciplinary challenges in sustainable development. Full article

Within the global sustainable development agenda, Sustainable Development Goal 4 (SDG 4) highlights improving the accessibility, quality, and learning experience of technical and vocational education and training (TVET). In China, students in vocational colleges often face greater disparities in academic preparation and access to educational resources than their peers in general higher education. Although artificial intelligence (AI) can provide additional learning support and help mitigate such inequalities, there is little empirical evidence on whether and how Gen-AI usage is associated with vocational students’ learning experiences and emotional outcomes, particularly academic anxiety. This study examines how Gen-AI usage is related to academic anxiety among Chinese vocational college students and explores the roles of class engagement and teacher support in this relationship. Drawing on Conservation of Resources (COR) theory, we analyse survey data from 511 students using structural equation modelling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The SEM results indicate that Gen-AI usage is associated with lower academic anxiety, with class engagement mediating this relationship. Teacher support for Gen-AI usage positively moderates the association between Gen-AI usage and class engagement. The fsQCA results further identify several configurations of conditions leading to low academic anxiety. These findings underscore AI’s potential to enhance learning quality and experiences in TVET and provide empirical support for advancing SDG 4 in vocational education contexts. Full article

The rapid growth of China’s prepared food industry has created new opportunities for industrial upgrading, but it has also intensified concerns regarding product quality, supervision gaps, and the long-term sustainability of governance structures. In response to these challenges, this study develops a tripartite evolutionary game model involving local governments, enterprises, and consumers, and further integrates a Markov chain framework to capture stochastic disturbances and long-run state transitions. This dynamic–stochastic modeling approach enables an examination of how collaborative supervision evolves under varying regulatory intensities, compliance costs, and consumer reporting costs. The results show that (1) multi-actor collaborative supervision substantially increases firms’ incentives to operate honestly and reinforces positive feedback loops between regulators and consumers; (2) excessive regulatory, compliance, or reporting costs weaken system stability and reduce policy effectiveness; (3) aligning regulatory intensity with penalty mechanisms accelerates the system’s convergence toward a stable equilibrium, balancing industrial development with food safety objectives; and (4) Markov chain simulations confirm the robustness and long-term stationarity of the governance system. Overall, this study provides a dynamic and evidence-based framework for designing sustainable and resilient regulatory mechanisms in the prepared food industry. The findings offer practical guidance for advancing Sustainable Development Goals (SDGs) 3, 12, and 16 through improved food safety, responsible production, and stronger institutional governance. Full article

This study analyses the integration of Generative Artificial Intelligence (GenAI) in agro-environmental higher education in Ecuador, focusing on its contribution to sustainable digital transformation aligned with Sustainable Development Goals (SDGs) 4 and 9. The research was conducted at the Faculty of Agricultural and Environmental Engineering (FICAYA) of Universidad Técnica del Norte (UTN) using a quantitative, cross-sectional, and analytical design. A validated digital survey grounded in established technology-acceptance frameworks—the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) was administered to 94% of the student population, showing satisfactory internal consistency (Cronbach’s α = 0.87). Data was analysed using descriptive statistics and multivariate techniques, including Principal Component Analysis (PCA) and k-means clustering. The results obtained in Microsoft Forms^® indicate that ChatGPT-5 is the most widely used GenAI tool (54.2%), followed by Gemini (11.9%). Students reported perceived improvements in academic performance (62.5%), conceptual understanding (74.6%), and task efficiency (69.1%). PCA explained 67% of the total variance, identifying three latent dimensions: effectiveness and satisfaction, institutional access and support, and ethical concerns versus operational benefits. Furthermore, k-means clustering (k = 2) segmented users into two distinct profiles Integrators, characterised by frequent use and positive perceptions, and Cautious Users, exhibiting lower usage and greater ethical or technical concerns. Overall, the findings highlight GenAI as a catalyst for sustainable education and underline the need for institutional and ethical frameworks to support its responsible integration in Latin American universities. Full article

The rapid advancements in Educational Technology (EdTech) and e-learning necessitate a critical focus on the principles of sustainability to ensure compliance with and the achievement of Sustainable Development Goal 4 (SDG 4), quality and lifelong education, conceived by the United Nations (UN) [...] Full article

(1) Background: Rubus geoides Sm., a native species of southern Patagonia, faces increasing threats due to climate change and anthropogenic land-use changes. Historically widespread, its distribution has become restricted by overgrazing, urban expansion, extractive industries, and direct harvesting from natural populations driven by interest in its nutraceutical potential since the first European settlements. (2) Methods: To assess its resilience and conservation prospects, we analyzed the morphological variability, genetic diversity, and population structure, complemented by species distribution modeling under past and future climate scenarios. (3) Results: Our findings reveal moderate genetic differentiation and private alleles in specific populations, alongside significant variation in flowering phenology. Paternity analysis indicates a tendency toward self-pollination, although this conclusion is constrained by the limited number of microsatellite markers employed. These results suggest post-glacial dispersal patterns and highlight the species’ potential for expansion under certain climate scenarios. (4) Conclusions: This study provides critical insights for biodiversity conservation and sustainable land management, directly aligned with the UN Sustainable Development Goals SDG 15 (Life on Land). Indirectly, this study contributes to SDG 2 (Zero Hunger) by highlighting the importance of threatened species that hold value for human consumption and food security. Land-use changes, particularly mining and green hydrogen industry settlements, may represent stronger limitations to species expansion than climate change itself. Full article

This study identifies key determinants shaping countries’ Sustainable Development Goals performance and develops classification models for predicting country group membership based on the SDG Index. The research addresses the urgent need to optimize development policies amid limited resources and the approaching 2030 Agenda deadline. Using data from 154 countries (2024), the analysis reveals that key SDG determinants are fundamentally method-dependent: discriminant analysis identified Goals 10, 6, 15, and 5 as most influential for differentiating countries by SDGI level, while Random Forest identified Goals 4, 9, and 2 as the most important predictors. This divergence reflects fundamentally different analytical perspectives—linear contributions to group separation versus complex nonlinear interactions and synergies between goals—with critical policy implications for prioritization strategies. Correlation analysis demonstrates that sustainable development dynamics operate differently across development stages: high-development countries show strongest associations with technological advancement and institutional capacity, while low-development countries exhibit compensation effects where basic infrastructure provision occurs alongside lagging human capital development. The discriminant model achieved 94.08% overall accuracy with perfect classification for extreme SDGI categories, while the Random Forest model provides complementary insights into interactive pathways. The scientific contribution lies in demonstrating that perceived variable importance depends on analytical framework rather than representing objective reality, and in providing validated classification tools for rapid assessment in data-limited contexts. These findings offer actionable guidance for evidence-based resource allocation and policy prioritization in the critical final years of SDG implementation. Full article

The health and operational continuity of emergency responders are fundamental pillars of sustainable and resilient disaster management systems. These personnel operate in high-risk environments, exposed to intense physical, environmental, and psychological stress. This makes it crucial to monitor their health to safeguard their well-being and performance. Traditional methods, which rely on intermittent, voice-based check-ins, are reactive and create a dangerous information gap regarding a responder’s real-time health and safety. To address this sustainability challenge, the convergence of the Internet of Things (IoT) and wearable biosensors presents a transformative opportunity to shift from reactive to proactive safety monitoring, enabling the continuous capture of high-resolution physiological and environmental data. However, realizing a field-deployable system is a complex “system-of-systems” challenge. This review contributes to the field of sustainable emergency management by analyzing the complete technological chain required to build such a solution, structured along the data workflow from acquisition to action. It examines: (1) foundational health sensing technologies for bioelectrical, biophysical, and biochemical signals; (2) powering strategies, including low-power design and self-powering systems via energy harvesting; (3) ad hoc communication networks (terrestrial, aerial, and space-based) essential for infrastructure-denied disaster zones; (4) data processing architectures, comparing edge, fog, and cloud computing for real-time analytics; and (5) visualization tools, such as augmented reality (AR) and heads-up displays (HUDs), for decision support. The review synthesizes these components by discussing their integrated application in scenarios like firefighting and urban search and rescue. It concludes that a robust system depends not on a single component but on the seamless integration of this entire technological chain, and highlights future research directions crucial for quantifying and maximizing its impact on sustainable development goals (SDGs 3, 9, and 11) related to health, sustainable cities, and resilient infrastructure. Full article

Urban health, well-being, and equity—core objectives of Sustainable Development Goals (SDGs 3, 10, and 11)—have become key themes in contemporary urban planning research and landscape research. While existing studies focus predominantly on quantitative assessment, environmental exposure, and human mobility, the historical origins of health-oriented urban green space planning remain insufficiently explored. Focusing on Lingnan area as a representative case, this research investigates the emergence of public green space in late Qing cities and its early contributions to urban health and spatial governance. Through a systematic examination of American and British Gardens at the Thirteen Factories in Guangzhou, the planned public green space system of the Shameen concession, and the municipal greening practices of neighboring Hong Kong and Macao, the study further analyzes Zhang Zhidong’s tree-lined boulevard project along Changdi avenue as a key instance of localized institutional adaptation. Drawing on late-Qing and Republican newspapers, nineteenth-century Western travelogs and reports, historical and contemporary studies and photo albums, the study finds the following: (1) the American and British Gardens marked the earliest emergence of health-oriented urban green space in Lingnan area; (2) the systematically planned green space network of the Shameen concession constituted a prototypical form of health-oriented urban green space planning; (3) the botanical gardens, street-tree systems, public parks, and institutionalized management practices in Hong Kong and Macao exerted a strong regional demonstrative influence on Guangzhou; (4) the street-tree planting along Changdi Avenue represented a localized absorption of foreign planning paradigms and marked the institutionalization of municipal greening in Guangzhou. Although these early practices did not yet form a modern healthy city planning framework at that time, they played a crucial role in improving urban sanitation, enhancing public space quality, and shaping urban order. By tracing the historical trajectory from transnational demonstration to local adaptation and institutional consolihdation, this study provides new insights into the historical foundations of health-oriented urban planning in China and contributes a long-term perspective to contemporary debates on healthy cities and nature-based urban interventions. Full article

The influence of the digital economy on green technological innovation is essential for the attainment of Sustainable Development Goals (SDGs). Based on panel data from 30 Chinese provinces between 2011 and 2023, this study establishes a dual fixed-effects model to investigate how the digital economy affects green technological innovation, considering both quantity and quality. It innovatively explores the roles of high-tech industry agglomeration, high-tech talent agglomeration, and their synergistic agglomeration. This study reveals the following: (1) The digital economy has a significant promotional effect on both the quantity and quality of green technological innovation, and this finding has been consistently verified through an array of robustness tests. (2) Mechanism results show that high-tech industry agglomeration, high-tech talent agglomeration, and their synergistic agglomeration all have a “multiplier effect”, but the impact intensity of synergistic agglomeration is less than that of single agglomeration. (3) Further exploration of the threshold effect of synergistic agglomeration shows that, concerning the quantity of green technological innovation, a higher level of synergistic agglomeration corresponds to a stronger promotional effect. In terms of quality, the promotional effect reaches its peak after the degree of synergistic agglomeration crosses the first threshold and weakens after crossing the second threshold. (4) Heterogeneity analysis reveals that the positive impacts of the digital economy on green innovation are more pronounced in Eastern and Central China than in its western regions. Moreover, a lower environmental regulation intensity favors innovation quantity, while a higher intensity promotes quality. Additionally, the facilitative effect is the strongest in regions where greater attention is given by the government to green development. This study offers practical insights for sustainable global development, particularly in the context of developing nations. Full article

This paper presents an innovative approach to the design of intelligent software architecture for Digital Library Systems (DLSs) and the evaluation of this in the context of sustainable education. By leveraging Artificial Intelligence (AI) technologies, global cooperation and best practices in Software Engineering, we propose the design of a model that enhances the management, access and usability of digital libraries. Our framework introduces intelligent services for decision-making processes, research activities, and personalized learning experiences. Through global collaboration, our architecture aims to contribute significantly to achieving Sustainable Development Goal 4 (SDG4), ensuring inclusive and equitable education worldwide. Full article

Digital technologies have transformed how information is accessed and shared; however, individuals with disabilities continue to face significant barriers in engaging with educational content. The shift to electronic formats presents an opportunity to promote inclusion by integrating accessibility features. Accessible e-books are essential for fostering equitable participation in learning environments, supporting lifelong learning, and aligning with global sustainability goals such as SDG 4 (Quality Education) and SDG 10 (Reduced Inequalities). While international frameworks like the Web Content Accessibility Guidelines (WCAG) advocate for accessible publishing, significant gaps remain. This paper presents a Systematic Literature Review (SLR) aimed at examining the role of accessibility features in shaping the quality, usability, and affordability of e-books. Based on well-defined guidelines, we defined and executed an SLR protocol, identifying 1618 studies in seven different scientific databases. At the end of the review process, we selected 74 studies to answer four research questions related to the accessibility features employed by e-books and their reading platforms. By synthesizing existing evidence, this review highlights barriers, best practices, and strategic pathways to inform educators, publishers, and policymakers. Ultimately, this study advocates for the development of inclusive and sustainable digital content ecosystems that meet the diverse needs of all learners. Full article

This study examines how social media use relates to university students’ digital self-perception within the framework of sustainable education and the Sustainable Development Goals (SDGs 3 and 4). A quantitative, cross-sectional design was applied to a sample of 261 undergraduate students from CES Don Bosco (Madrid, Spain), with a response rate of 24.4%. Participants (75.1% women; age range 18–44) completed a 36-item instrument developed for this study. An Exploratory Factor Analysis (EFA) identified three dimensions with adequate internal consistency—social comparison and influence on self-image, approval seeking and digital authenticity, and digital dependence and anxiety—while two additional dimensions showed insufficient reliability and were considered exploratory only. Non-parametric analyses (Spearman’s rho and Mann–Whitney U) revealed significant associations between earlier digital initiation, longer daily connection time, and higher scores in comparison, approval seeking, and digital dependence. Women reported higher levels in these dimensions, although effect sizes were small to moderate. Because the design was correlational, these results do not imply causality. The findings offer preliminary empirical support for an analytical model of digital self-perception and highlight the importance of integrating emotional and critical dimensions of digital competence into higher education to promote students’ digital well-being. Full article

Promoting the coupled and coordinated development of new-type urbanization and rural revitalization is important for achieving high-quality and sustainable growth in China. This study follows a people-centered and coordinated development approach and is aligned with the Sustainable Development Goals (SDGs). It builds a comprehensive evaluation framework for the two systems and measures and interprets their coupling and coordination. On this basis, and under the background of China’s territorial spatial planning, the study draws implications for land and spatial governance. The core of the study is to answer the following questions: What are the spatiotemporal patterns of the coupling coordination level between new-type urbanization and rural revitalization in China from 2014 to 2023? How has the coordination of their development speed evolved? What are the main sources of regional differences? Which factors are the key drivers that promote coordinated development between the two systems? The main findings are as follows. (1) The national coupling coordination degree increases steadily. Spatially, there is a pattern of “eastern region leading, central and northeastern regions catching up, and western region showing internal divergence”. This pattern is consistent with differences in development intensity and accessibility across regions. (2) From 2019 to 2023, the coordination of development speed improved in most provinces. A few developed or special provinces show short-term mismatch, which may reflect timing gaps between land-use controls and the provision of public services. (3) Gaps between regions are the main source of overall differences, and there is a trend toward convergence. This is in line with interregional equalization and the narrowing of efficiency gaps. (4) Well-being of residents, social development, and digital innovation are the core driving forces. Digital inclusive finance and the intensity of parcel delivery services also provide important support. There are clear interaction effects among the driving factors, and these effects are stronger in areas where planning improves accessibility and reduces transaction costs. Full article