Search Results (2,817)

The rapid advancement of Artificial Intelligence (AI) technologies has significantly transformed teaching, learning, and research practices within higher education institutions (HEIs). Although a growing body of literature has examined the application of AI in higher education, existing studies remain fragmented, often focusing on isolated tools or outcomes, with limited synthesis of best practices, core functionalities, and implementation challenges across diverse contexts. To address this gap, this systematic review aims to comprehensively examine the best practices, functionalities, and challenges associated with the integration of AI in HEIs. A comprehensive literature search was conducted across major academic databases, including Google Scholar, Scopus, Taylor & Francis, and Web of Science, resulting in the inclusion of 35 peer-reviewed studies published between 2014 and 2024. The findings suggest that effective AI integration is supported by best practices, including promoting student engagement and interaction, providing language support, facilitating collaborative projects, and fostering creativity and idea generation. Key AI functionalities identified include adaptive learning systems that personalize educational experiences, predictive analytics for identifying at-risk students, and automated grading tools that improve assessment efficiency and accuracy. Despite these benefits, significant challenges persist, including limited knowledge and skills, ethical concerns, inadequate infrastructure, insufficient institutional and management support, data privacy risks, inequitable access to technology, and the absence of standardized evaluation metrics. This review provides evidence-based insights to inform educators, institutional leaders, and policymakers on strategies for leveraging AI to enhance teaching, learning, and research in higher education. Full article

Sepsis is a life-threatening syndrome characterized by marked clinical heterogeneity and complex host–pathogen interactions. Although traditional mechanistic studies have identified key molecular pathways, they remain insufficient to capture the highly dynamic, multifactorial, and systems-level nature of this condition. The advent of high-throughput omics technologies—particularly integrative multi-omics approaches encompassing genomics, transcriptomics, proteomics, and metabolomics—has profoundly reshaped sepsis research by enabling comprehensive profiling of molecular perturbations across biological layers. However, the unprecedented scale, dimensionality, and heterogeneity of multi-omics datasets exceed the analytical capacity of conventional statistical methods, necessitating more advanced computational strategies to derive biologically meaningful and clinically actionable insights. In this context, artificial intelligence (AI) has emerged as a powerful paradigm for decoding the complexity of sepsis. By leveraging machine learning and deep learning algorithms, AI can efficiently process ultra-high-dimensional and heterogeneous multi-omics data, uncover latent molecular patterns, and integrate multilayered biological information into unified predictive frameworks. These capabilities have driven substantial advances in early sepsis detection, molecular subtyping, prognosis prediction, and therapeutic target identification, thereby narrowing the gap between molecular mechanisms and clinical application. As a result, the convergence of AI and multi-omics is redefining sepsis research, shifting the field from descriptive analyses toward predictive, mechanistic, and precision-oriented medicine. Despite these advances, the clinical translation of AI-driven multi-omics approaches in sepsis remains constrained by several challenges, including limited data availability, cohort heterogeneity, restricted interpretability and causal inference, high computational demands, difficulties in integrating static molecular profiles with dynamic clinical data, ethical and governance concerns, and limited generalizability across populations and platforms. Addressing these barriers will require the establishment of standardized, multicenter datasets, the development of explainable and robust AI frameworks, and sustained interdisciplinary collaboration between computational scientists and clinicians. Through these efforts, AI-enabled multi-omics research may progress toward reproducible, interpretable, and equitable clinical implementation. Ultimately, the synergy between artificial intelligence and multi-omics heralds a new era of intelligent discovery and precision medicine in sepsis, with the potential to transform both research paradigms and bedside practice. Full article

Education systems worldwide face a growing pressure to align with Sustainable Development Goal 4.7 by embedding Education for Sustainable Development (ESD) into school life. This study examines how primary school headteachers in Cyprus interpret and enact sustainable leadership to advance ESD within a small, highly centralised system. Drawing on sustainable and distributed leadership theories and a whole-school lens, the study employed semi-structured interviews with ten headteachers from diverse regions (urban, rural, and semi-rural). Reflective thematic analysis identified four patterns: (1) leaders sought a strategic integration of ESD into planning and culture; (2) empowerment and participation were pursued through teacher working groups, student eco-councils, and community partnerships; (3) systemic constraints, a rigid curriculum, limited autonomy, and scarce professional development produced a policy–practice gap; and (4) leaders relied on adaptive, collaborative micro-practices to sustain momentum. The findings suggest that, in Cyprus, sustainable leadership operates as a values-based stewardship enacted through ‘quiet activism’. The study highlights implications for leadership development, such as reflexivity, systems thinking, and ethical reasoning, as well as policy design, such as time, autonomy, and structured support for whole-school ESD, in small-state contexts. Full article

Background/Objectives: The growing number of older adults with complex healthcare needs increases demand for homecare services, while a shrinking workforce often lacks skills for advanced tasks. Digital health is seen as a promising tool to address these challenges. This study explored Swedish homecare professionals’ perceptions of the potential use of digital twins in daily work. Methods: Four focus group discussions were conducted with 31 homecare professionals; two groups each in one urban/rural and one rural municipality. Data were analyzed using inductive content analysis. Results: Three main themes emerged: (i) Perceptions of digital twins as support for older adults, including needs-based, individualized care and proactive support enabling preventive measures; (ii) Perceptions of digital twins as support for professionals, including a better work environment through streamlined tasks and flows and enhanced planning and assessment; and (iii) Concerns about digital twins, focusing on ethical and social issues and limited understanding, which were related to monitoring aspects, the importance of physical visits, and how the technology works. Conclusions: Digital twins are perceived by professionals to have the potential to improve homecare services by supporting both older adults and professionals; however, further research is needed to address concerns and practical implications. Full article

Aquaculture has grown rapidly worldwide and has become a key source of food and employment opportunities. However, its expansion faces environmental, health, reproductive, and technological challenges that threaten its long-term sustainability. In this context, biologists play a crucial role in promoting sustainable practices and integrated management of aquaculture systems. This article reviews their main contributions to animal health, genetic improvement, assisted reproduction, and resource conservation. They also highlight their leadership in applying advanced technologies, including biotechnology, nanotechnology, and genetic engineering. Moreover, this study explores emerging research trends and emphasizes the importance of interdisciplinary training to address the evolving demands of the sector. This underscores the need to strengthen collaboration between science, technology, and public policy to ensure sustainable aquaculture. Enhancing the role of biologists is essential for overcoming current challenges and advancing efficient, ethical, and environmentally responsible aquaculture systems that meet global demand. Full article

Generative artificial intelligence (GenAI), particularly large language models (LLMs) such as ChatGPT and DeepSeek, is transforming healthcare by enhancing clinical decision-making, education, and patient interaction. This exploratory study compares the responses of ChatGPT (GPT-4.1) and DeepSeek-V2 against 90 final-year physiotherapy students in Greece on the quality of the responses to 60 clinical questions across four rehabilitation domains: low back pain, multiple sclerosis, frozen shoulder, and knee osteoarthritis (15 questions per domain). The questions spanned basic knowledge, diagnosis, alternative treatments, and rehabilitation practices. The responses were evaluated for their relevance, accuracy, clarity, completeness, and consistency with clinical practice guidelines (CPGs), emphasizing conceptual understanding. This study provides novel contributions by (i) benchmarking LLMs in physiotherapy-specific domains (low back pain, multiple sclerosis, frozen shoulder, and knee osteoarthritis) underrepresented in prior AI-health evaluations; (ii) directly comparing the LLM written response quality to student performance under exam constraints; and (iii) highlighting the improvement potential for education, complementing ChatGPT’s established role in physician decision support. The results indicate that the LLMs produced higher-quality written responses than students in most domains, particularly in the global response quality and the conceptual depth of written responses, highlighting their potential as educational aids for knowledge-based tasks, although not equivalent to clinical expertise. This suggests AI’s role in physiotherapy as a supportive tool rather than a replacement for hands-on clinical skills and asks whether GenAI could transform physiotherapy practice by augmenting, rather than threatening, human-centered care, for its potential as a knowledge support tool in education, pending validation in clinical contexts. This study explores these findings, compares them with the related work, and discusses whether GenAI will transform or threaten physiotherapy practice. Ethical considerations, limitations, and future directions, including AI voice assistants and AI characters, are addressed. Full article

Background: Artificial intelligence (AI) is transforming medical practice, enhancing diagnostic accuracy, personalisation, and clinical efficiency. However, this transition raises complex ethical challenges related to transparency, accountability, fairness, and human oversight. This study examines how the literature conceptualises and distributes ethical responsibility in AI-assisted healthcare. Methods: This semi-systematic, theory-informed thematic review was conducted in accordance with the PRISMA 2020 guidelines. Publications from 2020 to 2025 were retrieved from PubMed, ScienceDirect, IEEE Xplore databases, and MDPI journals. A semi-quantitative keyword-based scoring model was applied to titles and abstracts to determine their relevance. High-relevance studies (n = 187) were analysed using an eight-category ethical framework: transparency and explainability, regulatory challenges, accountability, justice and equity, patient autonomy, beneficence–non-maleficence, data privacy, and the impact on the medical profession. Results: The analysis revealed a fragmented ethical landscape in which technological innovation frequently outperforms regulatory harmonisation and shared accountability structures. Transparency and explainability were the dominant concerns (34.8%). Significant gaps in organisational responsibility, equitable data practices, patient autonomy, and professional redefinition were reported. A multilevel ethical responsibility model was developed, integrating micro (clinical), meso (institutional), and macro (regulatory) dimensions, articulated through both ex ante and ex post perspectives. Conclusions: AI requires governance frameworks that integrate ethical principles, regulatory alignment, and epistemic justice in medicine. This review proposes a multidimensional model that bridges normative ethics and operational governance. Future research should explore empirical, longitudinal, and interdisciplinary approaches to assess the real impact of AI on clinical practice, equity, and trust. Full article

This study diagnoses the level and profile of university lecturers’ digital competence at a Chilean higher education institution, drawing on the DigCompEdu and OpenEdu frameworks. A non-experimental correlational design was used, based on a self-perception questionnaire adapted from the DigCompEdu Check-In tool and administered to 569 lecturers through the Qualtrics platform. The instrument underwent external expert validation and demonstrated excellent internal consistency (Cronbach’s α = 0.96). Results indicate that 44% of lecturers position themselves at the “Integrator” level, 22% at the “Explorer” level, and 19% at the “Expert” level, with three clearly differentiated competence profiles. These findings informed the development of a structured training programme centred on three components: the pedagogical use of digital technologies, the incorporation of open educational practices aligned with OpenEdu, and the strengthening of students’ digital competence. The programme includes modular workshops, mentoring led by high-competence lecturers, and the creation of open educational resources. Overall, the study provides empirical evidence to guide institutional policies and to foster a reflective, ethical, and pedagogically grounded integration of digital technologies in university teaching. Full article

The rapid emergence of generative artificial intelligence (GAI) is reshaping academic work in higher education. While classical technology acceptance models primarily emphasize cognitive and instrumental determinants, the adoption of GAI also raises ethical concerns related to trust in AI systems and the protection of personal and institutional data. To address this gap, this study examines the determinants of GAI acceptance and use among academic staff in Slovenian higher education institutions by applying a UTAUT-based model that integrates trust and privacy. In this study, GAI is conceptualized as a class of text-based generative AI tools commonly used in academic practice, including applications such as ChatGPT, Copilot, Scholar AI, Gemini, Consensus, and similar systems. A quantitative research design was employed, based on a structured online survey administered to academic staff across 20 higher education institutions in Slovenia (n = 201). Data were analyzed using multilevel confirmatory factor analysis and generalized estimating equations. The results indicate that performance expectancy and attitude toward using significantly predict behavioral intention to use GAI (B = 0.49, p < 0.001 for both), while behavioral intention is the primary predictor of actual use behavior (B = 0.93, p < 0.001). Effort expectancy is positively associated with use behavior independent of behavioral intention (B = 0.23, p = 0.012), whereas trust does not show a statistically significant association with use behavior (B = 0.05, p = 0.458) or behavioral intention (B = −0.01, p = 0.840). Privacy exhibits a positive, but non-statistically significant, association with use behavior (B = 0.12, p = 0.058). The findings highlight the relevance of considering both cognitive and ethical factors when examining generative AI adoption in academic contexts and provide initial empirical insights for refining UTAUT-based frameworks in the context of emerging AI technologies. Full article

Forensic anthropology, a specialized branch of biological anthropology, plays a crucial role in the identification of human remains, particularly when conventional methods such as fingerprinting are not applicable. In Ecuador, its relevance has increased in response to challenges such as intentional deaths, forced disappearances, violence, mass fatalities, and migration-related deaths. Despite its growing importance, the field faces significant limitations, including restricted access to advanced technologies, limited training opportunities for local forensic anthropologists, and insufficient resources for research and the application of advanced methodologies for victim identification. This article examines the development and current state of forensic anthropology in Ecuador, emphasizing the urgent need for population-specific standards, the establishment of a national osteological collection, and stronger institutional support. It also highlights the contributions of bioarchaeological research and its potential to enhance forensic practices. By analyzing the challenges of identifying skeletonized human remains and other instances of human rights violations, the study underscores the necessity of advancing forensic anthropology in the country. The article further discusses how interdisciplinary efforts have contributed to forensic knowledge in Ecuador and concludes by emphasizing the importance of ethical guidelines, technological integration, and improved infrastructure to strengthen forensic anthropology as both a scientific discipline and a humanitarian tool. Full article

The slaughter of pregnant sows remains a relevant concern in modern swine production, with prevalence rates reported from 1.5–13% in Europe. Considering fetal sensitivity during late gestation and legal restrictions on transport and slaughter, reliable assessment of fetal age is of considerable practical, ethical, and legal relevance. In this study, 70 pregnancies from low-prolificacy (purebred German Saddleback) and medium-to-high prolificacy genotypes (purebred German Landrace and Duroc × German Landrace hybrids) were repeatedly examined using transabdominal ultrasonography, with a total of 15 examinations per pregnancy. Seven fetometric parameters—rosto-occipital distance, bi-parietal distance, orbital distance, sternum length, thorax diameter, body diameter, and crown–rump length—were measured in vivo, assessing two fetuses per pregnancy and calculating mean values to account for intra-individual variation. Parameter feasibility varied across gestation: during early gestation (gestation days 38 and 40), orbital distance, sternum length, and crown–rump length could be reliably measured; in mid-gestation, all seven parameters were measurable, whereas in late gestation (from gestational day 87 onward), crown–rump length was no longer measurable, and the remaining six parameters remained assessable for gestational age estimation. Crown–rump length (CRL) increased from a median of 3.2 cm (range 1.9–4.2 cm) at day 38 to 16.3 cm (range 14.0–18.2 cm) at day 77, representing the most practical parameter for determining the stage of gestation. Litter size had no significant effect on fetometric growth, except for a weak correlation with thorax diameter at day 77, and parity showed no measurable influence on any parameter. The results show that fetometric values in modern sow genotypes are smaller than those reported in earlier literature, highlighting the need for updated gestational age assessment. These findings provide practical guidance for gestational age estimation, supporting the enforcement of animal welfare legislation and potentially contributing to a reduction in the slaughter of highly pregnant sows. Full article

This study proposes a systematic framework for establishing ethical guidelines for GeoAI (Geospatial Artificial Intelligence), which integrates AI with spatial data science, GIS, and remote sensing. While general AI ethics have advanced through the OECD, UNESCO, and the EU AI Act, ethical standards tailored to GeoAI remain underdeveloped. Geospatial information exhibits unique characteristics, spatiality, contextuality, and spatial autocorrelation—and consequently entails distinct risks such as geo-privacy, spatial fairness and bias, data provenance and quality, and misuse prevention related to mapping and surveillance. Following PRISMA 2020, a systematic review of 32 recent international policy documents and peer-reviewed articles was conducted; through content analysis with intercoder reliability verification (Krippendorff’s α ≥ 0.76), GeoAI ethical principles were extracted and normalized. The analysis identified twelve ethical axes—Geo-privacy, Data Provenance and Quality, Spatial Fairness and Bias, Transparency, Accountability and Auditability, Safety (Security and Robustness), Human Oversight and Human-in-the-Loop, Public Benefit and Sustainability, Participation and Stakeholder Engagement, Lifecycle Governance, Misuse Prevention, and Inclusion and Accessibility—each accompanied by an operational guideline. These axes together form a practical framework that integrates universal AI ethics principles with spatially specific risks inherent in GeoAI and specifies actionable assessment points across the GeoAI lifecycle. The framework is intended for direct use as checklists and governance artifacts (e.g., model/data cards) and as procurement and audit criteria in academic, policy, and administrative settings. Full article

Theologians have a moral responsibility to attend to the grave disorder in which the language of morality currently suffers. I argue that the healing of this disorder involves a morally prescribable disloyalty to the semblance of the virtue of charity. In this paper, I will review the moral blind spots and ethical inconsistencies in how the semblance of the virtue of charity is confused with the actual virtue of charity and is thus actualized inappropriately in today’s society. I will then investigate the virtue of solidarity as a prescription to help repair the potentiality of what the virtue of charity ought to be and look like. In looking to solidarity, I will turn to Ada María Isasi-Díaz’ epistemological concept of lo cotidiano as a means of practicing accountability in virtue theory and virtue practice. First, I will explore mujerista theology as an approach and why it is important to ethically attend to the voices on the margins; then, I will investigate the concept of lo cotidiano as a methodology that centers a commitment of responsibility to the other; lastly, I will turn to the virtue of solidarity and argue how attending to solidarity enhances our call to charity in an authentic and accountable way (A version of this paper was presented at the 2025 Convention of the Catholic Theological Society of America (CTSA) in Portland, Oregon). Full article

Interactive science galleries have transformed how the public engages with science, shifting from object-centred displays to immersive, design-led experiences. This study situates these changes within broader cultural and economic contexts, exploring how design mediates our understanding of science and reflects neoliberal and experiential values. Using archival research, qualitative interviews with museum professionals, and reflective practice, the research examines the evolution of interactive science spaces at the Science Museum in London—The Children’s Gallery, Launch Pad, and Wonderlab. The findings reveal that exhibition design increasingly prioritises entertainment, immersion, and pleasure, aligning with the rise in the experience economy and the influence of corporate models such as Disneyland. While such strategies enhance visitor engagement and accessibility, they risk simplifying complex scientific narratives and reducing learning to consumption. The study concludes that effective science communication design should balance enjoyment with critical inquiry, using both comfort and discomfort to foster curiosity, reflection, and ethical awareness. By analysing design’s role in shaping the “science experience”, this research contributes to understanding how cultural institutions can create more nuanced, thought-provoking encounters between audiences, knowledge, and space. Full article

Background: Role clarity is a persistent challenge among Patient Care Technicians (PCTs), contributing to inconsistent task performance and safety risks. In Saudi Arabia, little is known about PCTs’ understanding of their responsibilities. This study evaluated the impact of a targeted educational program designed to improve PCTs’ role clarity, safety practices, and communication. Methods: A quasi-experimental pre-post study was conducted in September 2025 with 35 PCTs from the Hail Health Cluster. The one-day intervention included lectures, discussions, role-play, and case scenarios. Outcomes were measured using a validated instrument across four domains: role clarity; core clinical tasks and safety; communication and ethics; and objective knowledge. Pre-post changes were analyzed using paired t-tests (Cohen’s d), and subgroup differences in change scores were examined using one-way ANOVA (η²) in SPSS v29. Results: Baseline scores were lowest in objective knowledge (41.4%) and role clarity (62.8%). Post-training, total composite scores improved significantly (+10.88%, p < 0.001, d = 1.63), with the most significant gain in objective knowledge (+19.8%, p < 0.001, d = 0.99). Role clarity showed only a modest, non-significant increase (+3.98%, p = 0.088, d = 0.30). No demographic differences were found. Conclusions: Targeted training was effective in reducing knowledge gaps; however, improving role clarity may require organizational reinforcement beyond brief training. Full article