Search Results (8,194)

Generative models can generate art within a single modality with high fidelity. However, translating a work of art from one domain to another (e.g., painting to music or poem to painting) in a meaningful way remains a longstanding, interdisciplinary challenge. We propose a novel approach combining a multi-agent system (MAS) architecture with an ontology-guided semantic representation to achieve cross-domain art translation while preserving the original artwork’s meaning and emotional impact. In our concept, specialized agents decompose the task: a Perception Agent extracts symbolic descriptors from the source artwork, a Translation Agent maps these descriptors using shared knowledge base, a Generator Agent creates the target-modality artwork, and a Curator Agent evaluates and refines the output for coherence and style alignment. This modular design, inspired by human creative workflows, allows complex artistic concepts (themes, moods, motifs) to carry over across modalities in a consistent and interpretable way. We implemented a prototype supporting translations between painting and poetry, leveraging state-of-the-art generative models. Preliminary results indicate that our ontology-driven MAS produces cross-domain translations that preserve key semantic elements and affective tone of the input, offering a new path toward explainable and controllable creative AI. Finally, we discuss a case study and potential applications from educational tools to synesthetic VR experiences and outline future research directions for enhancing the realm of intelligent agents. Full article

Indoor Air Quality (IAQ) in educational environments is a critical determinant of students’ health, well-being, and learning performance, with inadequate ventilation and pollutant accumulation consistently associated with respiratory symptoms, fatigue, and impaired cognitive outcomes. Conventional monitoring approaches—based on periodic inspections or subjective perception—provide only fragmented insights and often underestimate exposure risks. Artificial intelligence (AI) offers a transformative framework to overcome these limitations through sensor calibration, anomaly detection, pollutant forecasting, and the adaptive control of ventilation systems. This review critically synthesizes the state of AI applications for IAQ management in educational environments, drawing on twenty real-world case studies from North America, Europe, Asia, and Oceania. The evidence highlights methodological innovations ranging from decision tree models integrated into large-scale sensor networks in Boston to hybrid deep learning architectures in New Zealand, and regression-based calibration techniques applied in Greece. Collectively, these studies demonstrate that AI can substantially improve predictive accuracy, reduce pollutant exposure, and enable proactive, data-driven ventilation management. At the same time, cross-case comparisons reveal systemic challenges—including sensor reliability and calibration drift, high installation and maintenance costs, limited interoperability with legacy building management systems, and enduring concerns over privacy and trust. Addressing these barriers will be essential for moving beyond localized pilots. The review concludes that AI holds transformative potential to shift school IAQ management from reactive practices toward continuous, adaptive, and health-oriented strategies. Realizing this potential will require transparent, equitable, and cost-effective deployment, positioning AI not only as a technological solution but also as a public health and educational priority. Full article

Humanity is opening up to cosmos in all its dimensions and areas of knowledge. In this context, Paraguay, due to its multicultural uniqueness and two official languages (Spanish and Guaraní), represents an emblematic example of how legends, traditions and its rich mythology are important in their sociocultural translation to space. They coexist as a link between the past and the future. Guarani traditions, mythology, their relationship with nature and their translation into cosmos are amazing and complex aspects of indigenous cultural heritage, which are still present in many Paraguayan initiatives. This article compiles and integrates the cultural information about this topic, which is dispersed in different sources, and frames it in its corresponding context. Likewise, it unequivocally confirms how this intangible heritage is crucial as a living roadmap and a contemporary challenge that should be preserved as it guides individuals, communities and initiatives to implement earth and space science and education. Guaraní cultural heritage offers valuable insights into how indigenous worldviews continue to shape contemporary ecological and cultural practices in our modern intersection pathway to the cosmos. Full article

Background/Objectives: Youth-onset type 2 diabetes (Y-T2D) incidence and severity rose during the COVID-19 pandemic, particularly during periods of widespread public health restrictions—including, but not limited to, virtual learning, stay-at-home orders, closure of recreational facilities, and limitations on in-person healthcare access. This study assessed incidence, severity, and remission rates of Y-T2D following the return to in-person education, focusing on cases diagnosed while such restrictions were in place. Methods: A retrospective chart review was conducted at a pediatric tertiary care center (2018–2024) to identify new Y-T2D diagnoses. We compared incidence rates, disease severity at diagnosis, and remission outcomes before and after the period of comprehensive public health restrictions, defined locally as March 2020–August 2021, during which virtual learning was implemented. Results: Incidence declined from 13.2 to 6.3 cases/month after the major restrictions were lifted. Youth diagnosed after the restrictions period had lower rates of diabetic ketoacidosis (7.1% vs. 20.9%, p < 0.001) and severe hyperglycemia (HbA1c 9.1 ± 2.5% vs. 10.1 ± 2.3%, p < 0.001). Among those diagnosed during the restriction period, 11.1% achieved remission within three years. Remission was associated with lower baseline HbA1c (OR = 9.52, 95% CI: 2.2–41.7, p = 0.003), metformin use (OR = 7.0, CI: 1.9–26.3, p = 0.004), GLP-1 receptor agonist use (OR = 5.8, CI: 1.3–24.4, p = 0.018), and lower likelihood of insulin therapy (OR = 19.5, CI: 2.3–166.7, p = 0.007). Conclusions: The reduction in Y-T2D cases after the lifting of pandemic-related restrictions highlights the impact of pandemic-related environmental changes. Low remission rates—especially among underserved youth—underscore the urgency of early screening, prompt intervention, and equitable access to pediatric diabetes care, and highlight the need to consider the metabolic health impacts of future prolonged public health measures. Full article

Inclusive education represents a central pillar of social sustainability, demanding a nuanced understanding of the factors shaping students’ attitudes toward people with disabilities. Grounded in the social–relational model of disability—which conceptualizes disability as the interaction between individual characteristics and environmental barriers—this study examined the effects of emotionally valenced video stimuli (positive, negative, neutral), gender, and tolerance level on university students’ attitudes, using a randomized quasi-experimental design with repeated measures. The intervention was implemented entirely online to ensure consistency and accessibility. A total of 179 undergraduate students from the National University of Science and Technology Politehnica Bucharest (Romania), aged 20 to 23 years (M = 21.4, SD = 1.6), participated in the study, which lasted approximately two weeks. Participants completed pre- and post-intervention assessments, including the Elementary Tolerance Scale and a 25-item Attitude Scale combining strengths-based descriptors with stereotype-consistent items used diagnostically to detect bias (without endorsing such framings). Results revealed a significant main effect of video type, F(2,176) = 10.07, p < 0.001, with higher post-test scores for the positive condition (M = 93.82) compared to the negative (M = 85.88) and neutral (M = 82.67) conditions. Gender (p = 0.033) and tolerance level (p = 0.034) also emerged as significant moderators. We explicitly reject deficit-oriented terminology, contextualizing its use solely for diagnostic and analytical purposes; wherever possible, affirming, strengths-based, and socially grounded language is prioritized. These findings highlight the value of brief, emotionally tailored interventions for fostering inclusive attitudes in higher education and emphasize the importance of ethically curated, co-designed educational materials and measurement practices grounded in dignity and human rights. Ethical Note (Content Warning): The study adopts a social–relational, human-rights perspective on disability. Deficit-based narratives were analyzed exclusively as subjects of critique and are not endorsed. Descriptions of the “negative” stimulus were deliberately minimized to reduce potential harm and included only for scientific transparency. Negative-valence questionnaire items reflect prevalent stereotypes and were used solely as diagnostic indicators of bias. Future research should prioritize collaborative co-creation with scholars and advocates with disabilities and employ ethically curated, inclusive stimuli. Full article

Climate change is one of the most pressing environmental challenges of our time, with consequences that extend far beyond temperature rise. Its impacts include extreme weather events, sea level rise, biodiversity loss, and disruptions to food and water systems, all of which threaten ecosystems and human well-being. Addressing this crisis requires a broad understanding and engagement from society. However, climate change denial persists, often amplified through online platforms, slowing down effective action. Universities can play a critical role in this context, not only as spaces where scientific knowledge is produced and shared, but also as institutions that train future leaders to respond to environmental crises. In this study, we examined the prevalence of climate change denial among members of a Portuguese public university and explored its relationship with gender, religion, and political orientation. We collected 89 responses and analyzed the data. The findings indicate that individuals with right-leaning political views, certain religious affiliations, and male respondents were more likely to deny climate change. These results highlight the need for targeted educational approaches that address specific audiences, fostering a better understanding of the scientific and environmental realities of climate change, and ultimately promoting informed action toward sustainability. Full article

Computational thinking (CT) is recognized as a core competency for the 21st century, and its development is shaped by multiple factors, including students’ individual characteristics and their use of information and communication technology (ICT). Drawing on large-scale international data from the 2023 cycle of the International Computer and Information Literacy Study (ICILS), this study analyzes a sample of 81,871 Grade 8 students from 23 countries and one regional education system who completed the CT assessment. This study is the first to apply a predictive modeling framework that integrates two machine learning techniques to systematically identify and explain the key variables that predict CT and their nonlinear effects. The results reveal that various student-level predictors—such as educational expectations and the number of books at home—as well as ICT usage across different contexts, demonstrate significant nonlinear patterns in the model, including U-shaped, inverted U-shaped, and monotonic trends. Compared with traditional linear models, the SHapley Additive exPlanations (SHAP)-based approach facilitates the interpretation of the complex nonlinear effects that shape CT development. Methodologically, this study expands the integration of educational data mining and explainable artificial intelligence (XAI). Practically, it provides actionable insights for ICT-integrated instructional design and targeted educational interventions. Future research can incorporate longitudinal data to explore the developmental trajectories and causal mechanisms of students’ CT over time. Full article

This article presents a qualitative analysis of GAVIN, a Blockchain-based system for educational information management that is fully compliant with the General Data Protection Regulation (GDPR). This system was designed to address the challenges of academic credential verification and recovery in a context where academic certificate issuance and verification is highly fragmented, with institutions operating isolated systems that hinder efficient verification and facilitate the proliferation of fraudulent documents. The GAVIN model introduces a multi-blockchain architecture aimed at recognition of formal, non-formal, and informal learning, guaranteeing compliance with GDPR. After completing the design and development of a functional prototype, this study discusses its qualitative evaluation by means of a validation workshop with diverse stakeholders from the education sector, using pre- and post-workshop questionnaires grounded in the Technology Acceptance Model (TAM). Results indicate a strong perceived usefulness and significant potential to improve current credentialing processes. However, concerns were raised regarding implementation feasibility, associated costs, the need for official standardization, and the importance of establishing robust governance and sustainable business models. This study offers valuable insights into the challenges and opportunities of blockchain adoption in education, providing guidance for future development and policy-making. Full article

This article formalizes AI-assisted assessment as a discrete-time policy-level design for iterative feedback and evaluates it in a digitally transformed higher-education setting. We integrate an agentic retrieval-augmented generation (RAG) feedback engine—operationalized through planning (rubric-aligned task decomposition), tool use beyond retrieval (tests, static/dynamic analyzers, rubric checker), and self-critique (checklist-based verification)—into a six-iteration dynamic evaluation cycle. Learning trajectories are modeled with three complementary formulations: (i) an interpretable update rule with explicit parameters $\eta$ and $\lambda$ that links next-step gains to feedback quality and the gap-to-target and yields iteration-complexity and stability conditions; (ii) a logistic-convergence model capturing diminishing returns near ceiling; and (iii) a relative-gain regression quantifying the marginal effect of feedback quality on the fraction of the gap closed per iteration. In a Concurrent Programming course ($n=35$), the cohort mean increased from 58.4 to 91.2 (0–100), while dispersion decreased from 9.7 to 5.8 across six iterations; a Greenhouse–Geisser corrected repeated-measures ANOVA indicated significant within-student change. Parameter estimates show that higher-quality, evidence-grounded feedback is associated with larger next-step gains and faster convergence. Beyond performance, we engage the broader pedagogical question of what to value and how to assess in AI-rich settings: we elevate process and provenance—planning artifacts, tool-usage traces, test outcomes, and evidence citations—to first-class assessment signals, and outline defensible formats (trace-based walkthroughs and oral/code defenses) that our controller can instrument. We position this as a design model for feedback policy, complementary to state-estimation approaches such as knowledge tracing. We discuss implications for instrumentation, equity-aware metrics, reproducibility, and epistemically aligned rubrics. Limitations include the observational, single-course design; future work should test causal variants (e.g., stepped-wedge trials) and cross-domain generalization. Full article

In the US, research suggests that racial disparities exist in the prevalence of postpartum depression (PPD) and postnatal anxiety (PNA), with Black mothers experiencing PPD and PNA at a higher rate than their white counterparts. As a result, research that attempts to understand the antecedents of PPD and PNA in Black mothers may have value to the development of better interventions to reduce both in this subpopulation. Theory suggests that race-related stress (RRS) may be a contributing factor to PPD and PNA symptoms among Black mothers. RRS is defined as the stress associated with racism and discrimination encountered by Black women in their daily lives. In the current study, to test the relationship of RRS to PPD and PNA, we surveyed (N = 79) Black mothers who recently gave birth. The survey consisted of the Index of Race-Related Stress (IRRS), the Edinburgh Postnatal Depression Scale (EPDS), and the Postpartum Specific Anxiety Scale (PSAS-RSF), along with items capturing income, education, mental health status, and the number of children per mother. Income and mental health status, education, and the number of children per mother were used as covariates in a multivariate regression model with IRRS scores as the independent variable and EPDS and PSAS-RSF scores as twin dependent variables. These covariates were selected because of their established relationship with PPD and PNA. The data was analyzed using structural equation modeling. The results indicated that the model provided good fit to the data, (X² = 6.32, df = 9; p = 0.707; RMSEA = 0.00 [90% CI: 0.000, 0.097]; CFI: 1.0). Moreover, IRRS scores were significantly correlated with both PPD symptoms (β = 0.45; p < 0.001) and PNA symptoms (β = 0.3837, p < 0.001), respectively. Such results suggest that future research into the role race-related stress plays in the development of PPD symptoms and PNA symptoms may have value in the reduction in both among Black mothers. Full article

A growing international consensus holds that science education must advance beyond content coverage to cultivate robust understanding of the Nature of Science (NoS)—how scientific knowledge is generated, justified, revised, and socially negotiated. Yet naïve conceptions persist among students and teachers, and effective, scalable classroom strategies remain contested. This narrative review synthesizes research and practice on games and playful activities that make epistemic features of science visible and discussable. We organize the repertoire into six families—(i) observation–inference and discrepant-event tasks; (ii) pattern discovery and rule-finding puzzles; (iii) black-box and model-based inquiry; (iv) activities that dramatize tentativeness and anomaly management; (v) deliberately underdetermined mysteries that cultivate warrant-based explanations; and (vi) moderately contextualized games. Across these designs, we analyze how specific mechanics afford core NoS dimensions (e.g., observation vs. inference, creativity, plurality of methods, theory-ladenness and subjectivity, tentativeness) and what scaffolds transform playful engagement into explicit, reflective learning. We conclude with pragmatic guidance for teacher education and curriculum design, highlighting the importance of language supports, structured debriefs, and calibrated contextualization, and outline priorities for future research on equity, assessment, and digital extensions. Full article

This study investigates the effectiveness of a virtual reality (VR) simulation for teaching the hand lay-up process in composite manufacturing within mechanical engineering education. A within-subjects experiment involving 17 undergraduate mechanical engineering students compared the VR-based training with conventional physical laboratory instruction. Task performance, cognitive load, and learner perceptions were measured using procedural accuracy scores, completion times, NASA-TLX workload ratings, and post-task interviews. Results indicated that while participants required more time to complete the task in VR, procedural accuracy was comparable between VR and physical labs. VR significantly reduced mental, physical, and effort-related demands but elicited higher frustration levels, primarily due to navigation challenges and motion discomfort. Qualitative feedback showed strong learner preference for VR, citing its hazard-free environment, repeatability, and step-by-step guidance. These findings suggest that VR offers a viable and pedagogically effective alternative or complement to traditional composite-manufacturing training, particularly in contexts where access to physical facilities is limited. Future work should examine long-term skill retention, incorporate haptic feedback for tactile realism, and explore hybrid models combining VR and physical practice to optimise learning outcomes. Full article

The relationship between intelligence and creativity has remained a focus of research for nearly 75 years. The primary objective of this study was to examine the current state of research on creativity in the context of giftedness and to identify prevailing trends. This study employed a bibliometric analysis of scholarly articles on the subject in English. The findings offer a comprehensive overview of the performance metrics, intellectual structure, and emerging trends within the literature on creativity in giftedness. Prominent journals, articles, institutions, countries, and authors were identified. Moreover, trends and network structures related to research topics were revealed. One of the most striking findings regarding the performance analysis of the studies was that the US is the most successful country in many areas such as citation frequency, institutional contributions, and author productivity. A significant insight from the trend analysis was the noticeable absence of technology-related topics such as artificial intelligence and machine learning, despite their growing relevance in educational research. That is why these areas are recommended for future investigation. Full article

This research examines the professional aspirations of teenage girls attending secondary school in a Brazilian state and how they perceive potential careers in Science, Technology, Engineering and Mathematics (STEM). STEM remains a masculinised field, not only due to the predominance of men but also because of enduring cultural representations that associate it with exceptional academic performance and highly technical competencies. In response, various educational intervention initiatives have sought to challenge these assumptions and promote the inclusion of girls and women in STEM. This article discusses an intervention carried out in four public schools as part of a project led by the Centre for Informatics at the Federal University of Paraíba. The project collected quantitative and qualitative data on subject preferences, professional expectations and perceptions of STEM among teenage girls. A mixed-methods exploratory approach was adopted to analyse the data and therefore to contribute to understand better the specific challenges of implementing such interventions in socioeconomically disadvantaged contexts, which remain underrepresented within the Women in STEM scholarship. The findings illustrate how social and financial constraints shape these young women’s career aspirations, intensifying both the desire for economic stability and the pursuit of personal fulfilment. At the same time, many perceive the future as uncertain and regard STEM as difficult to access, frequently associated with anxiety surrounding core science subjects. This article contributes to ongoing debates on gender and STEM education, offering insights into the Brazilian context and outlining considerations for the development and refinement of future school-based interventions. Full article

In-school–out-of-school collaborations are increasingly recognized as a key mechanism for enriching STEM education. Guided by conceptual frameworks on boundary crossing and STEM learning ecologies, this scoping review maps and synthesizes findings from 470 studies and 469 programs published between 2014 and 2024, focusing on how such partnerships are reported, structured, and distributed across educational contexts. Approximately 73% of the programs reported some form of collaboration, although often in general terms. The most common forms included shared infrastructure, recruitment coordination, and personnel involvement. More pedagogically grounded forms, such as curricular alignment and co-development of instruction, were rarely described. Collaboration patterns varied across program types, durations, subject areas, and participant target groups. A typology of seven collaboration categories was developed to organize the findings. Notable gaps include the near-total absence of collaboration in medicine-related programs and the underrepresentation of research from low- and middle-income countries. Although collaboration is frequently mentioned, it is seldom described in enough detail to support systematic analysis or theoretical insight. The review recommends more precise definitions, stronger reporting practices, and enhanced theoretical engagement with collaboration as a pedagogical and systemic component of STEM education. The proposed typology provides a foundation for more coherent future research and comparative studies. Full article