Search Results (1,927)

Artificial intelligence (AI), a transformative force, has revolutionised various aspects of human life and business operations. This has led to a drastic mutation of the career landscape, embedded with vast opportunities as well as challenges, particularly concerning career sustainability (CS). Despite myriad studies on CS, the paradoxical interplay of AI and CS remains underexplored, particularly for expatriates (expats). To address the aforementioned gap, our study incorporates an affordance perspective (AFP), positioning AI as an object and CS as a user context. Specifically, this study investigates whether AI facilitates the orchestration of an enhanced sustainable career within the boundary conditions of knowledge sharing (KS), encompassing both tacit and explicit knowledge pertinent to AI, cultivated through managerial initiatives and employee-driven activities. The study conducted a quantitative survey among 490 expats working in AI-integrated environments in China. The results reveal a curvilinear (U-shaped) relationship between AI and CS, where AI affordance at a moderate level enhances career adaptability and skill development. However, digital affordances become complex beyond a certain threshold, creating several career concerns, such as job insecurity and role ambiguity. Furthermore, the moderating effect of tacit and explicit KS mitigates numerous career disruptions while fostering long-term career growth. The study framed AI as both a tool and a collaborator that illuminates the importance of AI–human intelligence (AI–HI) synergy and knowledge augmentation in navigating digital transitions. Moreover, implications for international career development and human-oriented digital transformation are also discussed. Full article

Pragmatic language is a core component of school-based social participation, yet children with Autism Spectrum Disorder (ASD) and Social Communication Disorder (SCD) frequently experience persistent difficulties in using language appropriately across everyday learning contexts. This study investigated the effectiveness of a culturally adapted, school-based immersive Virtual Reality (VR) learning program designed to enhance pragmatic language and social communication skills among Thai primary school children. Eleven participants aged 7–12 years completed a three-week, ten-session VR program that simulated authentic classroom, playground, and canteen interactions aligned with Thai sociocultural norms. Outcomes were measured using the Social Communication Questionnaire (SCQ) and the Pragmatic Behavior Observation Checklist (PBOC). While SCQ scores showed a small, non-significant reduction (p = 0.092), PBOC results demonstrated significant improvements in three foundational pragmatic domains: Initiation and Responsiveness (p = 0.032), Turn-Taking and Conversational Flow (p = 0.037), and Politeness and Register (p = 0.010). Other domains showed no significant changes. These findings suggest that immersive, culturally relevant VR environments can support early gains in core pragmatic language behaviors within educational settings, although broader social communication outcomes may require longer or more intensive learning experiences. Full article

Systems thinking is not a static concept, but rather a dynamic and evolving paradigm that continually adapts to the challenges of its time, becoming more refined and applicable in different areas, such as education. The main objective of the study is to identify the relationship between academic performance and the pedagogical strategies used to promote systems thinking in undergraduate and graduate students in STEM disciplines (science, technology, engineering, and mathematics). The method used is quantitative research with a non-experimental cross-sectional design. For data collection, a 25-item Likert scale called “STEM Pedagogical Strategies” was used, with an overall Cronbach’s alpha coefficient of α = 0.985. The instrument measures students’ perceptions of the application of five key strategies: problem-based learning, thinking routines, system maps and visual diagrams, design thinking, and system dynamics. The sample consisted of 350 undergraduate and graduate students in STEM fields. The main results show that there is a significant correlation between students’ academic performance and the pedagogical strategies of thinking routines and design thinking. Likewise, the skills developed through systems thinking, as shown in the available literature, would be the basis for fostering collaboration, complex problem solving, and students’ ability to become “systems”. Full article

To maintain power system stability and supply quality when integrating doubly fed induction generator (DFIG)-based wind energy conversion systems (DFIG-WECSs), regulators regularly update grid codes specifying low voltage ride-through (LVRT) requirements. This paper presents a systematic literature review (SLR) on the use of STATCOMs to enhance LVRT capability in DFIG-WECSs. Objectives included a structured literature search, bibliographic analysis, thematic synthesis, trend identification, and proposing future research directions. A PRISMA-based methodology guided the review, utilising PRISMA 2020 for Abstracts in the development of the abstract. The final search was conducted on Scopus (31 March 2025). Eligible studies were primary research in English (2009–2014) where STATCOM was central to LVRT enhancement; exclusions included non-English studies, duplicates, reviews, and studies without a STATCOM focus. Quality was assessed using an adapted Critical Appraisal Skills Programme (CASP) tool. No automation or machine learning tools were used. Thirty-eight studies met the criteria and were synthesised under four themes: operational contexts, STATCOM-based schemes, control strategies, and optimisation techniques. Unlike prior reviews, this study critically evaluates merits, limitations, and practical challenges. Trend analysis shows evolution from hardware-based fault survival strategies to advanced optimisation and coordinated control schemes, emphasising holistic grid stability and renewable integration. Identified gaps include cyber-physical security, techno-economic assessments, and multi-objective optimisation. Actionable research directions are proposed. By combining technical evaluation with systematic trend analysis, this review clarifies the state of STATCOM-assisted LVRT strategies and outlines pathways for future innovation in DFIG-WECS integration. Full article

Amid China’s “Manufacturing Power” push, full-chain digital restructuring in the Guangdong–Hong Kong–Macao Greater Bay Area remains hampered by mismatches among technology, organization, and environment. We therefore explored how shop floor actors perceive and shape this Technology–Organization–Environment (TOE) interplay. Semi-structured interviews with frontline operators, maintainers, and supply chain staff from GBA manufacturers were inductively coded, yielding 36 concepts, 10 categories, and 3 core TOE aggregates that were woven into a grounded model. The analysis shows that industrial internet platforms and smart equipment only create value when matched by flexible shop floor structures, cross-department data protocols, and skilled teams; otherwise, data silos, simulation–production deviations, and “buy-but-not-build” procurement stall adoption. Market pressure for customized, short-lead-time products and divergent municipal pilot policies further intensify the TOE balancing act, particularly for SMEs with weak absorptive capacity. By revealing a grassroots “technology-driven → organization-adapted → environment-adjusted” spiral that is moderated by frontline feedback, the study extends the TOE framework to micro-level, regional innovation theory and offers policy–practice levers for differentiated, cross-city manufacturing upgrading. Full article

Introduction: Nursing educators and clinical leaders face persistent challenges in engaging the next generation of nurses, often characterized by short attention spans, frequent phone use, and underdeveloped communication skills. This article describes the design and delivery of a full-day interactive teaching workshop for nursing faculty, senior clinical nurses, and nurse leaders, developed using a design-thinking approach supported by generative AI. Methods: The workshop comprised four thematic sessions: (1) Learning styles across generations, (2) Interactive teaching methods, (3) Application of interactive teaching strategies, and (4) Lesson planning and transfer. Generative AI was used during planning to create icebreakers, discussion prompts, clinical teaching scenarios, and application templates. Design decisions emphasized low-tech, low-prep strategies suitable for spontaneous clinical teaching, thereby reducing barriers to adoption. Activities included emoji-card introductions, quick generational polls, colored-paper reflections, portable whiteboard brainstorming, role plays, fishbowl discussions, gallery walks, and movement-based group exercises. Participants (N = 37) were predominantly female (95%) and represented multiple generations of X, Y, and Z. Mid- and end-of-workshop reflection prompts were embedded within Sessions 2 and 4, with participants recording their responses on colored papers, which were then compiled into a single Word document for thematic analysis. Results: Thematic analysis of 59 mid- and end-workshop reflections revealed six interconnected themes, grouped into three categories: (1) engagement and experiential learning, (2) practical applicability and generational awareness, and (3) facilitation, environment, and motivation. Participants emphasized the workshop’s lively pace and hands-on design. Experiencing strategies firsthand built confidence for application, while generational awareness encouraged reflection on adapting methods for younger learners. The facilitator’s passion, personable approach, and structured use of peer learning created a psychologically safe and motivating climate, leaving participants recharged and inspired to integrate interactive methods. Discussion: The workshop illustrates how AI-assisted, design-thinking-driven professional development can model effective strategies for next-generation learners. When paired with skilled facilitation, AI-supported planning enhances engagement, fosters reflective practice, and promotes immediate transfer of interactive strategies into diverse teaching settings. Full article

(1) Background: Developing cultural competence and reflective communication skills remains a challenge in nursing education. Traditional teaching methods often provide limited opportunities for safe practice of culturally sensitive interactions in emotionally complex situations. Artificial intelligence (AI)–based patient simulations may offer a scalable approach to experiential and reflective learning. (2) Aim: This study explored the educational potential of AI-based patient simulations in supporting nursing students’ self-assessed cultural competence, reflective awareness, and communication confidence. (3) Methods: A convergent mixed-methods pre–post study was conducted among 24 s-cycle nursing students. Participants engaged in individual AI-based patient simulations with simulated patients representing diverse cultural contexts. Quantitative data were collected using an exploratory cultural competence self-assessment scale administered before and after the simulation. Qualitative data included post-simulation reflection forms and AI-student interaction transcripts, analysed using inductive thematic analysis. (4) Results: A statistically significant increase in overall self-assessed cultural competence was observed (Wilcoxon signed-rank test: Z = 4.05, p < 0.001, r = 0.59), with the greatest improvements in communication adaptability and perceived communication sufficiency. Qualitative findings indicated an emotional shift from uncertainty to engagement, heightened awareness of cultural complexity, reflective reassessment of assumptions, and high perceived educational value of AI simulations. (5) Conclusions: AI-based patient simulations represent a promising pedagogical tool for fostering reflective and communication-oriented learning in culturally complex nursing contexts. Their primary value lies in supporting experiential learning, emotional engagement, and the development of cultural humility, suggesting their potential role as a complementary educational strategy in advanced nursing education. Full article

Objective. The aim of this study was to define a structured competence model for nurses working in gastrointestinal endoscopy in Italy and to assess nurses’ perceptions of the number of procedural repetitions required to acquire and maintain competence across different endoscopic procedures. Methods. A cross-sectional online survey targeted registered nurses working in Italian gastrointestinal endoscopy units. The questionnaire, developed from guidelines and expert consensus, covered demographics, organizational context, and perceived repetition thresholds for 30 procedures. Partial Credit Models (PCMs) estimated acquisition and maintenance thresholds; Differential Item Functioning (DIF) tested differences by self-reported experience level. Results. A total of 332 nurses participated (68.4% female; mean age 47.1 years; mean endoscopy experience 10.1 years). For competence acquisition, most procedures were placed in the 11–30 or 31–50 repetition range, with higher values for complex techniques. Competence maintenance generally required fewer repetitions, but thresholds varied by procedure. Advanced or infrequently performed techniques were perceived as more demanding. More experienced nurses reported higher thresholds, reflecting stricter internal standards. Conclusions. Acquisition and maintenance of gastrointestinal endoscopy competences differ in intensity and frequency requirements, supporting the need for tailored, modular training pathways. Findings highlight the importance of national competence standards, adaptive learning technologies, and structured mentorship to enhance skill development, reduce variability, and promote consistent, high-quality patient care across Italy. Full article

Higher education continues to encounter the challenge of redesigning writing pedagogy beyond the rapid adoption of emerging technologies. This challenge is particularly evident in English writing courses, which play a role in developing students’ writing and research skills in universities across the United Arab Emirates (UAE). While generative artificial intelligence (GenAI) tools offer practical affordances for writing instruction, their growing use has also raised concerns about academic integrity, authenticity, and critical engagement. Although early discourse has focused on the risks and potential of GenAI, there remains a clear dearth of frameworks to guide instructors in designing meaningful and engaging writing assignments. This paper introduces Ai-RACE, an adaptable pedagogical framework for designing purposeful and innovative writing tasks. Grounded in classroom-based insights, principles of writing pedagogy, constructivist and multimodal learning theories, Ai-RACE conceptualises assignment design around five interconnected components: AI integration, Relevance, Authenticity, the 4Cs, and Engagement. Employing a design-focused qualitative approach, the study uses instructional practices and student reflections to examine the implementation of Ai-RACE in writing contexts. Although situated within a specific institutional context, the study offers transferable guidelines for designing writing assignments across international higher education settings. By positioning Ai-RACE as a design heuristic, the study demonstrates its potential in supporting engagement, critical thinking, writing skills and ethical use of AI, and highlights the importance of rethinking writing pedagogy and the professional development in AI- influenced contexts. Full article

This study introduces the Hybrid Hydrological Forecast System (HHFS), a dual-stage, data-driven framework for monthly streamflow forecasting at the Santa Branca outlet in the upper Paraíba do Sul River Basin, Brazil. The system combines two nonlinear regressors, Multi-Layer Perceptron (MLP) and extreme Gradient Boosting (XGB), calibrated through a structured four-step evolutionary procedure in GA₁ (hydrological weighting, dual-regime Ridge fusion, rolling bias correction, and monthly mean–variance adjustment) and a hydro-adaptive probabilistic optimization in GA₂. SHAP-based analysis provides physical interpretability of the learned relations. The regressive stage (GA₁) generates a bias-corrected and climatologically consistent central forecast. After the full four-step optimization, GA₁ achieves robust generalization skill during the independent test period (2020–2023), yielding NSE = 0.77 ± 0.05, KGE = 0.85 ± 0.05, R² = 0.77 ± 0.05, and RMSE = 20.2 ± 3.1 m³ s⁻¹, representing a major improvement over raw MLP/XGB outputs (NSE ≈ 0.5). Time-series, scatter, and seasonal diagnostics confirm accurate reproduction of wet- and dry-season dynamics, absence of low-frequency drift, and preservation of seasonal variance. The probabilistic stage (GA₂) constructs a hydro-adaptive prediction interval whose width (max-min streamflow) and asymmetry evolve with seasonal hydrological regimes. The optimized configuration achieves comparative coverage COV = 0.86 ± 0.00, hit rate p = 0.96 ± 0.04, and relative width r = 2.40 ± 0.15, correctly expanding uncertainty during wet-season peaks and contracting during dry-season recessions. SHAP analysis reveals a coherent predictor hierarchy dominated by streamflow persistence, precipitation structure, temperature extremes, and evapotranspiration, jointly explaining most of the predictive variance. By combining regressive precision, probabilistic realism, and interpretability within a unified evolutionary architecture, the HHFS provides a transparent, physically grounded, and operationally robust tool for reservoir management, drought monitoring, and hydro-climatic early-warning systems in data-limited regions. Full article

Social–emotional development in early childhood lays the groundwork for school readiness, healthy relationships, and long-term well-being. Parents play a pivotal role in this process, shaping children’s emotional awareness, regulation, and social competence through everyday interactions. This literature review synthesizes evidence from 74 peer-reviewed studies to evaluate nine evidence-based parenting interventions targeting parents of preschool-aged children. The programs were analyzed with respect to their objectives, theoretical foundations, components, and the resulting outcomes for both parents and children. Across interventions, consistent benefits emerged in children, including improved emotion recognition, regulation, empathy, and prosocial behavior, as well as reductions in internalizing problems. Parents also gained in confidence and positive discipline practices. Key elements linked to effectiveness included active parent skill-building (such as modeling, role play, and guided practice), structured parent–child interactions, multi-component designs integrating home and school contexts, and flexible delivery formats that adapt to family needs. These findings underscore the critical role of parenting interventions as an evidence-based method to enhance preschoolers’ social–emotional development. Full article

This study examines the effectiveness of an eight-week AI training program aimed at enhancing teacher candidates’ pedagogical competence and AI literacy in rapidly changing and evolving educational environments. As the modern world continues to change and develop, the transformation of education, which is one of the most important elements of our lives, cannot be ignored. Accordingly, the integration of teacher candidates, who constitute key education stakeholders, into technological developments is very important in terms of both efficiency and sustainability. The “parallel–simultaneous design”, one of the mixed research methods in which quantitative and qualitative research methods are used together, was employed. In line with the stated purpose, the study started with a needs analysis conducted with 33 teacher candidates studying in different branches at the faculty of education. As a result of the needs analysis, knowledge gaps, digital skill levels and readiness for integration of artificial intelligence tools in future classrooms were determined. Its application to teacher candidates, instead of teachers in the profession, was determined by the needs analysis. The results indicate that it would be more beneficial to apply the education of the future to the teachers of the future and that they will find it easier to adapt to such training. Accordingly, a pre-test–post-test design was applied to observe how the participants changed, and an artificial intelligence literacy scale was also used. QDA Miner Lite was used for the analysis of the qualitative data, and SPSS 29.0 was used for the analysis of the quantitative data. During the eight-week training, Gamma programs were used for the presentation, Suno for audio, Midjourney for visuals and ChatGPT-4 for a descriptive search in order to provide better quality education to the participants. While practicing with these applications, the aim is to provide more up-to-date education that reveals problem-solving skills that include critical thinking exercises. According to the results, the teacher candidates who expressed that they were undecided or had insufficient knowledge reached a sufficient level in the post-test. In the light of these results, it can be stated that artificial-intelligence-oriented education is effective in developing sustainable pedagogical skills, digital literacy, readiness and professional self-confidence. The study also offers evidence-based recommendations for the design of future teacher training programs. Full article

The article presents an analysis of the mechanisms used by a vocational high school in Bulgaria to develop dual training and implement it sustainably. It focuses on the school management’s leadership role in the network of different stakeholders, demonstrating the importance of this aspect in the entire process of developing dual education. Apart from the case analysis of the Bulgarian vocational high school’s successful implementation of dual learning, the research strategy includes examining regulatory documents, evaluation reports and publications in media and by companies, as well as analyzing the attitudes among key stakeholders. An overview of the challenges facing dual education in Bulgaria is also provided. Based on the case study findings, the factors supporting the implementation and sustainability of the dual system have been identified. We conclude that the long-term development of the dual education model depends on the understanding that the formation of professional skills is a dynamic process, requiring attention to the needs of the local environment, adaptability to current changes and active participation by all stakeholders. The role of school leadership—with regard to both its motivation and activity—has proven to be essential, and therefore it should not be overlooked when creating state incentives to support dual training. Full article

Drought poses a severe threat to grassland biodiversity and ecosystem function. However, quantitative frameworks that capture the interactive effects of drought intensity and duration on productivity remain scarce, limiting impact assessment accuracy. To bridge this gap, we developed and validated a novel hybrid modeling framework to quantify drought impacts on net primary productivity (NPP) across Inner Mongolia’s major grasslands (1961–2012). Drought was characterized using the Standardized Precipitation Index (SPI), and ecosystem productivity was simulated with the Biome-BGC model. Our core innovation is the hybrid model, which integrates linear and nonlinear components to explicitly capture the compounded, nonlinear influence of combined drought intensity and duration. This represents a significant advance over conventional single-perspective approaches. Key results demonstrate that the hybrid model substantially outperforms linear and nonlinear models alone, yielding highly significant regression equations for all grassland types (meadow, typical, desert; all p < 0.001). Independent validation confirmed its robustness and high predictive skill (NSE ≈ 0.868, RMSE = 20.09 gC/m²/yr). The analysis reveals two critical findings: (1) drought duration is a stronger driver of productivity decline than instantaneous intensity, and (2) desert grasslands are the most vulnerable, followed by typical and meadow grasslands. The hybrid model serves as a practical tool for estimating site-specific productivity loss, directly informing grassland management priorities, adaptive grazing strategies, and early-warning system design. Beyond immediate applications, this framework provides a transferable methodology for assessing drought-induced vulnerability in biodiverse ecosystems, supporting conservation and climate-adaptive management. Full article

The performance of New Zealand’s construction companies depends on the adaptability and skills of their workforce. The soft skills of the company’s building professionals are thought to contribute to the delivery of successful construction projects. This pilot study captures the perceptions of the importance of critical soft skills in semi-structured interviews with thirteen Quantity Surveyors (QSs) and fourteen Project Managers (PMs) working in New Zealand. For both cohorts the most important skill is communication, followed by workplace ethics. An exploratory Mann–Whitney U comparison suggests a difference in their ranking of emotional intelligence in interactions with other stakeholders, with PM deeming it more important than QS. Within-cohort Spearman rank correlation shows different patterns of association among soft-skill clusters for QS and PM, offering contextual insight rather than confirmatory inference. After communication and ethics, QS prioritise dispute resolution while PM value project reasoning. A combination of individual traits and practical experience influences the successful transition from a QS role to the broader PM role. The findings are limited by the small sample size but may be useful in professional development courses and recruitment efforts, contributing to a more adaptable and flexible construction workforce. Full article