Search Results (1,939)

With the rapid development in generative artificial intelligence (GenAI) technologies, their application in STEAM education offers new possibilities for promoting interdisciplinary integration of technology and the arts. This study employs a systematic literature review method. Six databases—Google Scholar, Web of Science, PubMed, Taylor & Francis, Springer Link, and Scopus—were searched for publications from January 2021 to January 2026. After independent screening and review by two reviewers, 21 empirical studies out of 424 initial records were included. A comprehensive analysis was conducted using a combination of open and axial coding. The findings indicate that GenAI’s support for artistic creativity in STEAM education is primarily manifested in four dimensions: lowering the threshold for creation to enhance the accessibility of artistic creativity, stimulating interdisciplinary associations to strengthen subject integration, supporting critical artistic recreation to deepen cultural engagement, and building a human–GenAI collaborative creation ecosystem to foster reflexivity. Based on this, the study constructs a GCD (Guiding questioning–Co-refining–Deepening reflection) cyclic instructional framework, providing teachers with an actionable pedagogical pathway for using GenAI to cultivate students’ interdisciplinary artistic creativity across different educational stages. Furthermore, the study systematically analyzes ethical challenges such as technological dependency, cultural homogenization, educational equity, and originality, and proposes corresponding pedagogical strategies to address them. It should be noted that the current body of relevant empirical research is limited in quantity and exhibits substantial heterogeneity, and the GCD framework still requires further classroom-based practical validation. Future research could strengthen empirical longitudinal tracking of longterm effects, deepen the construction of support systems for teachers’ digital literacy, and continue to advance the exploration of ethical, equity, and cultural diversity issues in GenAI-based artistic creativity education. Full article

Background: Knowledge of place-based communities and the lived experiences of diverse citizens such as disabled people are key to making more inclusive sustainable communities. Yet many voices in public planning and community engagement, such as people with disabilities, neurodivergent people, children and young people, are often not heard. Method: Bringing people together requires an artful approach that amplifies diverse voices and stories while enabling solutions through knowledge exchange. In this article we share the art of designing and doing community chats as an inclusive dialogical method. The community chats used The World Café’s principles and framework adapted with inclusive processes, enabling us to explore the concept of planning inclusive communities and, importantly, solutions for them with community members with and without disabilities. Findings: In this article we firstly critique the current tensions regarding community engagement in public planning and participatory research methods, before outlining our approach. This includes outlining in detail our design approach and applied processes for maximising the participation of diverse people with disabilities and chronic illnesses. We offer critical reflections on our key lessons learnt and the non-negotiables in undertaking community chats. Conclusions: By sharing our thinking, approach and lessons learnt, we offer an inclusive adaptive approach to a popular method—the world café—that can be useful to evoke meaningful and empowering knowledge exchanges with diverse people with disabilities to help progress actions towards making communities more inclusive. Full article

As hybrid work arrangements become more established in organisations, the need for effective design and implementation strategies has grown significantly. Evidence indicates that employee wellbeing and engagement in hybrid work environments are declining and this presents a critical challenge for human resource management (HRM) professionals. This presents HRM professionals with a critical imperative of improving wellbeing, while maintaining engagement and productivity at work. This aligns closely with the United Nations’ 17 Sustainable Development Goals, particularly those that promote wellbeing and decent work. Through a systematic synthesis of 78 studies, this research investigates the key determinants of employee engagement and wellbeing in hybrid work contexts. The conceptual framework for this study is grounded in existing theoretical perspectives from the Job Demands–Resources model, Saks Frameworks and wellbeing perspective presented by Guest. The analysis identifies five critical factors that influence engagement and wellbeing outcomes in hybrid work, accompanied by evidence-based propositions for practice. These recommendations encompass: establishing well-equipped workspaces with appropriate flexibility in both location and time; developing organisational culture and leadership through enhanced communication and collaboration mechanisms; strategically allocating jobs and tasks whilst fostering effective networks and collaboration tools and implementing targeted training interventions to mitigate technostress and burnout associated with digital workloads. We advocate for future research to develop comprehensive models, frameworks and wellbeing interventions to guide HRM professionals in addressing these challenges at both the local and global levels. Full article

Background: AI-supported game-based learning (AI-GBL) integrates artificial intelligence mechanisms, including adaptive difficulty adjustment, large language model (LLM) scaffolding, intelligent non-player characters (NPCs), and stealth assessment, into game-based educational environments. Objective: This systematic review synthesizes the empirical evidence on AI-GBL effectiveness, adaptive mechanisms, and intelligent assessment approaches across diverse educational contexts. Method: Following PRISMA 2020 guidelines, 55 peer-reviewed empirical studies (2021–2026) were identified from Web of Science and Scopus databases. Two independent reviewers screened records (κ = 0.89; 100% consensus on disagreements), extracted data using a standardized coding scheme, and assessed methodological quality using a five-criterion rubric. A thematic synthesis approach was adopted due to the heterogeneity of the evidence base. Results: The reviewed studies generally suggest promising positive effects of AI-GBL on knowledge acquisition, intrinsic motivation, and affective engagement under a range of educational conditions. LLM-based scaffolding reduces cognitive load but risks fostering passive dependency; adaptive difficulty adjustment benefits depend critically on the direction and magnitude of adaptation; AI NPCs function as credible instructional partners in both EFL and STEM contexts; stealth assessment achieves AUCs of 0.848–0.913. Challenges include algorithmic bias in assessment models, LLM latency, over-reliance risks, and a near absence of longitudinal evidence. Conclusions: AI-GBL’s effectiveness rests on principled alignment between AI mechanisms and learning theory rather than algorithmic sophistication per se. Equity-by-design approaches and longitudinal evidence constitute the field’s priority research needs. Full article

Background/Objectives: Artificial intelligence (AI) is increasingly transforming cardiology through advanced analytical tools capable of identifying complex patterns across cardiovascular imaging, electrophysiology, and clinical datasets. Machine learning (ML) and deep learning (DL) algorithms are being integrated into echocardiography, cardiac computed tomography (CT), cardiac magnetic resonance imaging (MRI), and electrocardiography (ECG), enabling earlier diagnosis and more personalized cardiovascular care. This narrative review summarizes current clinical and organizational applications of AI in cardiology and discusses emerging concepts related to explainable and trustworthy AI. Methods: A narrative review was conducted according to SANRA recommendations using the PubMed, MEDLINE, Web of Science, and Scopus databases, including peer-reviewed publications from 2015 to 2026 addressing clinical, organizational, and ethical applications of AI in cardiology, with particular emphasis on cardiovascular imaging, electrocardiography, heart failure, digital health, and explainable AI frameworks. Results: Substantial evidence demonstrates that AI-based tools can achieve expert-level performance in cardiovascular imaging interpretation, automated electrocardiographic analysis, and clinical risk prediction. Across multiple cardiovascular settings, AI has been associated with improved diagnostic accuracy, enhanced workflow efficiency, and earlier detection of cardiovascular disease. Predictive models support risk stratification in heart failure and ischemic heart disease, while chatbots and digital health platforms may facilitate patient engagement, remote monitoring, and continuity of care. Despite these advances, important challenges remain, including algorithmic bias, limited transparency, insufficient external validation, data heterogeneity, and barriers to routine clinical implementation. Emerging explainable AI approaches may improve model interpretability, clinician confidence, and the safe adoption of AI-driven decision support systems. Conclusions: Artificial intelligence is rapidly evolving from a research-oriented technology into a clinically relevant component of cardiovascular care. Current evidence indicates that AI can enhance diagnostic performance, improve risk prediction, streamline clinical workflows, and facilitate more personalized management across multiple cardiovascular domains. However, the successful translation of AI into routine practice will depend on robust external validation, transparent decision-making mechanisms, regulatory oversight, and clinician acceptance. The development of explainable and trustworthy AI frameworks represents a critical step toward the safe, ethical, and sustainable integration of AI into modern cardiology. Full article

Background: The convergence of machine learning (ML), gamification, and critical thinking assessment within adaptive educational platforms has accelerated since 2020, driven by large language models (LLMs) and graph neural networks (GNNs). No prior systematic review has jointly addressed all three dimensions, and Central Asian educational contexts remain underrepresented. Methods: Following PRISMA 2020 guidelines, we searched Scopus (n  =  4396) and OpenAlex (n  =  4152) for publications from 2016 to 2026. Quality assessment used the Mixed Methods Appraisal Tool (MMAT 2018; threshold ≥  2), yielding 82 papers. Five research questions addressed ML personalization (RQ1), gamification and engagement (RQ2), critical thinking assessment tools (RQ3), recommendation algorithms (RQ4), and regional applicability in Kazakhstan and Central Asia (RQ5). Results: Transformer-based and GNN models dominate the recent literature (52% of corpus from 2025), with an accuracy of 91–97% for dropout prediction and learning path recommendation under single-institution conditions. Gamification studies report up to 90% student satisfaction; LLM-based critical thinking assessment shows promise but faces validity concerns. Thirteen papers address Central Asian contexts. Conclusions: Significant gaps persist: no integrated gamification–critical thinking framework exists, recommendation systems lack explainability, and Kazakh-language datasets are severely underrepresented. Future research should prioritize multilingual adaptive systems, explainable algorithms, and privacy-preserving federated learning for low-resource contexts. Full article

Renewable energy sources are fast becoming the most cost-effective option for adding new power generation capacity globally. In South Africa (SA), the transition from fossil fuels to renewable energy has steadily gained momentum over the years. However, this transition is beset by complex and multidimensional barriers. This research study analyses and prioritises renewable energy barriers and mitigation strategies in South Africa. The DEMATEL multi-criteria decision-making technique was employed to rank the barriers and assess their cause-and-effect relationships. The findings reveal the top three barrier categories as Agreement, Market, and Knowledge. The study further employed an integrated hybrid CRITIC-TOPSIS technique to prioritise the proposed mitigation strategies for each barrier in a defined category. The results indicate that strengthening local community engagement is the most suitable solution to the adoption of renewable energy in SA. A sensitivity analysis model was conducted to validate the robustness of the results. The findings validate the consistency of the methods, with the ranking of the barriers and mitigation strategies remaining stable under various scenarios. This study presents a context-specific causal analysis of barriers and an objective prioritisation of mitigation strategies in South Africa using an integrated hybrid DEMATEL and CRITIC–TOPSIS approach, providing policymakers and decision-makers with valuable insights to develop strategic plans and policies that address the identified barriers. Full article

Transitional waters—such as estuaries, lagoons, deltas, and coastal wetlands—are dynamic environments where freshwater and seawater interact, forming highly productive and biologically diverse ecosystems. Shaped by temperature and salinity gradients, tidal influence, sediment transport, and nutrient-rich conditions, these habitats support diverse ecological functions. Their structural complexity—including seagrass beds, salt marshes, mudflats, and mangroves—provides essential habitats for many fish species. These areas are crucial for fish life cycles, serving as nurseries, spawning grounds, feeding zones, and refuges from predators. Many commercially important species depend on them during early life stages before moving offshore, making them vital for both commercial and recreational fisheries. Beyond food provision, they deliver key ecosystem services, including water purification, coastal protection, and carbon storage. Research on the fish community of the Ria Formosa lagoon in Portugal since the 1980s highlights long-term changes in the fish community and the dominant role of habitat structure and temporal dynamics. Subtidal seagrass beds support higher fish abundance and diversity than unvegetated areas, acting as key nursery habitats and provide important fish provisioning services. Seasonal variation is also central, driven by recruitment pulses of marine migrants in late winter–spring. Recent pressures on this system have been driven by human activity and environmental change. Seagrass loss reduces nursery and feeding areas, while pollution degrades water quality. Overfishing (including illegal fishing), recreational activities, and aquaculture expansion add stress. Climate warming and invasive species such as Caulerpa prolifera, further disrupt ecosystem balance and threaten biodiversity. Sustainable management—such as habitat restoration, protected areas, and integrated policies—is essential to preserve the ecological and economic value of this unique lagoon. Ongoing research, monitoring, habitat restoration, and stakeholder engagement remain critical for ensuring resilience. Full article

Crafting STEM teaching into meaningful experiences can transform facts into knowledge. Immersive virtual reality (IVR) represents a significant pedagogical disruption, offering novel modalities of engagement with science content, extending beyond passive reception towards enhanced critical inquiry, reflective evaluation, and the cultivation of higher-order thinking skills. This study investigated how 20 Maltese students (mean age 12) adjusted their perceptions and acceptance of IVR when encountering it for the first time in formal STEM education. A quasi-experimental design was employed over six weeks, with data collected through pre- and post-intervention questionnaires. The analytical framework combined the Technological Frames of Reference (TFR) and Technology Acceptance Model (TAM) to capture perceptual snapshots and attitudinal shifts. While IVR initially stimulated enthusiasm, sustained exposure prompted critical reflections on its potential and limitations, particularly in relation to subject relevance, peer communication, and ease of use. Such deliberations are themselves suggestive indicators of reflective engagement. Rather than being demonstrated evidence of cognitive skill development, they are consistent with the early exercise of analytical and evaluative reasoning. These insights underscore the recursive dialog between technology-in-use and user contextualization, revealing how perceptions mature through experience. By examining how young learners engage with emergent technologies, this research highlights education’s role in cultivating adaptability, reflective judgment, and critical thinking capacities—central to innovative pedagogy and support for uncertain futures. Full article

Fire safety in high-rise buildings represents a critical challenge in the United Arab Emirates (UAE), where intensive urbanization, extreme climatic conditions, and multilayered regulatory frameworks impose unique competency demands on architects and Fire Safety Engineering (FSE) consultants. Despite this, no empirically validated competency framework exists that simultaneously addresses both professional groups and is tailored to the specificities of the UAE context. This study aimed to construct and empirically validate such a framework. A three-phase sequential exploratory mixed-method design was employed. In the first phase, a systematic literature review yielded a preliminary set of 69 competency indicators organized within a Knowledge, Skills and Attitudes (KSA) structure. In the second phase, a three-round Delphi technique with an expert panel of 18 specialists validated the set to 62 final indicators. In the third phase, importance–performance analysis (IPA) was conducted on a sample of 250 professionals actively engaged in fire safety projects across four UAE. IPA identified 16 priority competency gaps, most pronounced in digital transformation (BIM, CFD, AI; gap = 1.23), proactive client advisory competencies (gap = 1.21), and regulatory navigation and Civil Defence coordination (gap = 1.00). A counterintuitive finding emerged whereby architects systematically rated competencies higher than FSE consultants across all dimensions (all p < 0.05). Psychometric validation confirmed excellent instrument reliability (Cronbach’s Alpha > 0.95) and a theoretically consistent three-factor KSA structure explaining 70.06% of variance. The developed framework of 62 empirically validated indicators represents the first competency model of its kind for architects and FSE consultants in the Gulf Cooperation Council (GCC) region. Its findings provide a direct empirical basis for curriculum reform, Continuing Professional Development (CPD) programmes, and professional licencing standards in the UAE and across the GCC region. The study makes three original contributions: the first empirically validated UAE-specific competency framework for these professional groups; a methodological combination of Delphi, IPA, EFA, Mann–Whitney, and Kruskal–Wallis not previously applied in fire safety competency research; and empirical confirmation that 74% of indicators required original development or adaptation, demonstrating the limitations of generic international competency models in the UAE context. Full article

Cultural heritage is a critical pillar of identity, social cohesion and continuity within ethnocultural communities. However, the preservation of cultural heritage across Southern Africa is largely constrained by fragmented colonial policy implementation, and limited community engagement. This study critically examines the application of the Evidence-Based Policy and Practice (EBPP) model as a decolonizing framework for sustainable management of cultural heritage. The study conducts a structured scoping review of literature to explore the integration of EBPP with the principles of Collective Benefit, Authority to Control, Responsibility, Ethics (CARE), and the principles of Findable, Accessible, Interoperable, Reusable (FAIR) to support inclusive and ethical governance. The findings of the study reveal that sustainable management of cultural heritage is dependent upon community-led governance, alignment between research, policy, and practice, and strengthening of intellectual property protections. The study identifies persistent gaps in the operationalization of indigenous knowledge policies and highlighted the need for participatory approaches to ensure the long-term sustainability of cultural heritage. The study argues that the integration of EBPP, alongside the principles of CARE and FAIR, significantly enhances accountability, fosters data sovereignty, and supports the decolonization of knowledge systems. Thus, the study makes a significant contribution to the growing global discourse on sustainable development by positioning cultural heritage as a dynamic resource for social transformation. Full article

Environmental sustainability has become a critical priority for higher education institutions, which play a key role in promoting awareness and shaping students’ perceptions of sustainable practices. Understanding students’ awareness and perceptions is essential for evaluating the effectiveness of institutional sustainability initiatives. This study aimed to assess students’ awareness and perceptions of environmental sustainability at Prince Sattam bin Abdulaziz University and to examine the influence of demographic factors and the relationship between awareness and perception. A quantitative cross-sectional survey was conducted among 323 university students. Data were collected using a structured questionnaire measuring environmental awareness (18 items) and perception of sustainability practices (14 items) on a 5-point Likert scale. Composite scores were computed as the means of item responses. Descriptive statistics, independent t-tests, one-way ANOVA, and multivariable linear regression analyses were performed. Students demonstrated a moderate level of environmental awareness (mean = 3.116 ± 0.403) and moderate perceptions of sustainability practices (mean = 2.887 ± 0.199). Environmental awareness was significantly higher among female students and those in science-related disciplines (p < 0.001). Perception of sustainability was significantly associated with field of study and level of study (p < 0.001). In multivariable analysis, gender and field of study remained significant predictors of awareness, while gender, field of study, and level of study predicted perception. A significant but negative association was observed between awareness and perception of environmental sustainability (B = −0.496, p < 0.001). While students demonstrated a moderate level of environmental awareness, perceptions of sustainability practices were inconsistent. The findings highlight the need for enhanced sustainability education and engagement initiatives within universities. Future research should explore how awareness and perception translate into meaningful engagement with sustainability practices. Full article

As the environmental sustainability of blockchain technology becomes a focal point of public and academic debate, understanding how technically engaged communities frame this issue is increasingly important. This study examines 3000 long-form comments from a highly active sustainability-focused Bitcointalk thread to analyze sentiment patterns, recurring arguments, and the linguistic cues associated with community responses to environmental criticism. Using Natural Language Processing (NLP) methods, we apply Valence Aware Dictionary and sEntiment Reasoner (VADER) sentiment analysis to classify the discourse, n-gram extraction to identify dominant thematic expressions, and a Random Forest model combined with SHapley Additive exPlanations (SHAP) to interpret the lexical features most strongly associated with sentiment polarity. The results show a strongly positive and internally consistent discourse structure: 87.63% of comments are classified as positive, while negative and neutral comments are comparatively rare. The dominant themes emphasize energy consumption as a necessary trade-off for network security, while external criticism is frequently reframed or rejected. Explanatory modeling further indicates that negative sentiment is primarily driven by terms associated with climate risk, damage, and reputational concerns when users respond to criticism. Rather than claiming to capture the cryptocurrency ecosystem as a whole, this study presents a localized case study of one Bitcointalk mega-thread and describes it as a highly homogeneous narrative space shaped by recurrent rebuttal and rhetorical reinforcement. The findings offer a focused contribution to understanding how insider communities construct sustainability narratives around blockchain energy use, while also highlighting the need for broader comparative and network-structural research in future work. Full article

Background: Frequent consumption of foods high in fat and sugar (HFS) has been linked to disrupted appetite regulation (via hippocampal dysfunction) and an increased tendency to continue desiring palatable foods, even when physiologically full. While we have previously shown that motivational drive for such foods can persist when full, it remains unclear whether attentional engagement (i.e., the visual attention captured by palatable foods) shows a similar sustained desire to consume palatable foods when full. Understanding whether attention persists is critical, as attention can powerfully shape food choice and overeating. Methods: This study investigates whether habitual HFS intake was associated with the maintenance of visual attention, motivational responses, and food consumption when satiated. Twenty-four adults aged 18–30 years completed a food frequency questionnaire and a bogus taste-rating task once when hungry and again after consuming a standardised meal. Using Tobii Pro Glasses 3 wireless eye-tracking glasses, we measured fixations on real snack foods, and participants rated wanting and liking for each item. Results: Eating a meal significantly reduced total fixations to snack foods, and wanting was more sensitive than liking to physiological state. Fixations were higher for ‘healthy’ snacks compared to ‘unhealthy’ snacks, with this effect more pronounced when participants were hungry. Notably, individuals in the low-fat/low-sugar group showed strong alignment between post-meal decreases in visual attention and decreases in wanting and liking, whereas this coupling was diminished in the high-fat/high-sugar group. Discussion: Extending previous work into the domain of attention, this study reveals diet-related differences in how visual attention interacts with motivational evaluations of food. The disrupted coupling associated with high-fat/high-sugar intake suggests potential alterations in attentional and motivational processes supporting appetite regulation. Understanding how diet shapes these cognitive–motivational interactions provides a valuable foundation for future neurocognitive research on overeating and obesity risk. Full article

Background: Culturally and Racially Marginalised (CaRM) communities in Australia encounter subtle and covert forms of prejudice, commonly referred to as “new racism”. Within healthcare settings, these experiences can shape trust, engagement, and patterns of help-seeking. Mental health nurses are often the first point of contact in care delivery, and their ability to recognise, respond to, and mitigate the impacts of new racism is critical for fostering therapeutic relationships and supporting equitable access. Understanding how CaRM communities perceive the conditions that influence their mental health service use is fundamental for informing more equitable and culturally responsive care. Objective: This study explored the viewpoints of CaRM community members regarding the factors they consider important for addressing new racism in healthcare systems and supporting engagement with mental health services. Design: Q methodology was used to identify statistically derived viewpoints that reflect shared viewpoints about the conditions perceived as critical for addressing the impacts of new racism on mental health service use. Setting: Participants were recruited from culturally and linguistically diverse communities across Australia through community settings, social media, and professional networks. Participants: Thirty-five individuals from CaRM backgrounds completed the Q-sort. Methods: This Q methodology consisted of five steps: (1) set up of the Q-sorting instrument, (2) selection of participants, (3) data collection, (4) factor analysis, and (5) factor interpretation. Results: Three distinct viewpoints were identified: (1) raising awareness of mental health issues within CaRM communities (community-focused), (2) providing visible anti-racism and culturally safe services (service-focused), and (3) recognising and formally addressing new racism within healthcare systems (policy-focused). Conclusions: This study offers the first empirically derived, community-informed set of viewpoints on addressing new racism in Australian mental healthcare. While exploratory, the findings highlight multi-level considerations that are potentially relevant to mental health nursing practice, and may be useful to inform future research, policy development, and service redesign aimed at strengthening cultural responsiveness and equity in mental health systems. Full article