Search Results (8,993)

This quasi-experimental study examined the effectiveness of Augmented Reality (AR)-enhanced instruction on creativity development in Malaysian Design and Technology education. Forty-six, fifteen-year-old female students were assigned to AR-enhanced (n = 23) or traditional instruction (n = 23) groups for a four-week Mechatronic Design unit. Creativity was assessed using an adapted Torrance Tests of Creative Thinking-Figural (TTCT-F) instrument with expert validation and independent scoring by three raters. Bootstrapped ANCOVA (5000 iterations) controlling for pretest differences revealed significant improvements across all Guilford creativity components in the AR group: Elaboration (F = 27.093, p < 0.001, η² = 0.387), Originality (F = 20.445, p < 0.001, η² = 0.322), Fluency (F = 17.896, p < 0.001, η² = 0.294), and Flexibility (F = 7.593, p = 0.008, η² = 0.150). The differential effect pattern suggests AR operates through multiple mechanisms, primarily socio-constructivist collaborative scaffolding, followed by motivational enhancement and cognitive load reduction. These findings demonstrate AR’s substantial potential for creativity development in Design and Technology education, particularly for collaborative elaboration and generative ideation. However, single gender sampling, brief intervention duration, and quasi-experimental design limit generalizability, warranting future research with diverse populations and extended interventions. Full article

Background: Cyberbullying has emerged as a major public health concern with profound psychological repercussions on the adolescent population. The shift toward virtual communication has fundamentally altered interpersonal dynamics, removing the spatio-temporal barriers of aggression and creating new challenges for mental health. Methods: A systematic review was conducted following PRISMA 2020 guidelines, including a comprehensive update executed in February 2026. Searches were performed across PubMed, EBSCO, Web of Science, and Scopus. The review included observational and experimental studies involving adolescents (aged 10–19 years) reporting clinical mental health outcomes. Methodological quality was assessed using the Joanna Briggs Institute (JBI) critical appraisal tools. Results: Forty-two high-quality articles were selected. Key findings include the following: Prevalence: A median cyber-victimization prevalence of 19.1% was identified, although significant methodological heterogeneity exists with ranges between 2.1% and 88.0%. Clinical Impact: Victims exhibited significantly elevated rates of depression (90%) and anxiety (87%) compared to uninvolved peers. Suicidality: Victimization is a critical risk factor, with suicide attempts reported in 19.0% of victims, compared to 3.0% in aggressors. Vulnerable Groups: Adolescents with autism spectrum disorder (ASD) demonstrated extreme vulnerability, with victimization rates between 64.1% and 68.9%. Additionally, females and LGBTQ+ youth showed a higher risk of symptom internalization and post-traumatic stress. The Role of the Bystander: Observers experienced fear, moral frustration, and helplessness, acting as either passive reinforcers or active upstanders depending on the school climate. Conclusions and Implications: Effective prevention requires a socio-ecological approach that transcends the classroom, integrating families, healthcare centers, and technological platforms. A transition toward modernized cyber-education is recommended, utilizing interactive tools and “serious games” to foster empathy. Full article

The COVID-19 pandemic caused major disruption to healthcare education worldwide, forcing rapid transitions to online learning, interruptions to clinical placements, and heightened uncertainty that profoundly influenced student experiences. Given that academic motivation is a key determinant of learning quality, persistence, and professional identity, this review sought to consolidate global evidence on how the pandemic affected healthcare students’ motivation to study. A systematic search of peer-reviewed literature was conducted following PRISMA-ScR guidelines, identifying studies across medicine, nursing, and allied health programs that reported on changes in motivation and the factors shaping these trajectories. Extracted data were synthesized narratively, with attention to emerging themes such as stress, anxiety, burnout, resilience, gender differences, and the role of professional identity formation. Findings revealed substantial variability: while many students reported reduced motivation due to social isolation, technological barriers, and limited clinical exposure, others described increased drive linked to professional responsibility, adaptability, and resilience. Evidence also indicated gendered differences in motivational patterns, with female students more likely to report stress-related declines. Overall, the pandemic exposed both vulnerabilities and strengths in healthcare student motivation, pointing to the value of educational strategies that promote motivation, resilience, and professional identity development among future practitioners. Full article

Generative Artificial Intelligence (GenAI) has the potential to bring substantial benefits to language education, making it essential to examine how teachers engage with these technologies in practice. This exploratory qualitative case study draws on semi-structured interviews with four in-service upper-secondary English teachers in Norway to examine the factors shaping their engagement with GenAI. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT), the study examined factors shaping teachers’ engagement with GenAI, including performance expectancy, effort expectancy, social influence, and facilitating conditions. Thematic analysis revealed a pattern of selective, context-sensitive use rather than straightforward adoption. While teachers recognised the potential of GenAI to support planning, idea generation, and formative feedback, their engagement was constrained by concerns about assessment validity, academic integrity, privacy, and institutional guidance. The findings suggest that teachers’ use of GenAI is shaped not only by perceptions of usefulness and ease of use but also by trust, assessment considerations, and the availability of clear policy frameworks. By using UTAUT as a qualitative analytical lens, this study contributes to research on technology acceptance and teacher agency by showing how teachers negotiate the use of GenAI in ways that reshape assessment practices and professional roles. The findings point to the need for clear institutional guidance, AI-resilient assessment practices, and targeted teacher education that supports ethical, pedagogically grounded use of GenAI. Full article

The integration of artificial intelligence (AI) into early childhood education presents both opportunities and challenges to longstanding Froebelian pedagogies, particularly regarding child agency and nature-based play. This mixed-methods study explores this tension within the Chinese context. It examines how Chinese Froebelian practitioners perceive the alignment between AI tools and core principles and investigates the strategies they employ to navigate the integration of technology with humanistic educational values. The survey results, from 50 practitioners, revealed that AI can support autonomous and holistic learning, yet significant concerns persisted regarding the displacement of sensory and nature-based experiences. Follow-up interviews uncovered a practitioner-led “dual-track integration” approach, which strategically blends physical manipulation and nature engagement with AI-enabled personalization. Through an iterative dialogue between theory and data, this study develops and refines the “dual-track integration” framework as an empirically grounded, sensitizing model. This framework offers principled strategies for hybrid learning that uphold the developmental primacy of play. Situated within the discourse on Sustainable Development Goal 4 (quality education) and Goal 10 (reduced inequalities), the analysis highlights AI’s dual potential to advance or hinder equity. By examining China’s hybrid position, which combines advanced digital infrastructure with persistent equity gaps, this research highlights the critical role of educator agency and pedagogical design in leveraging AI to advance equitable, high-quality early childhood education. Full article

The integration of artificial intelligence (AI) into online education has transformed the digital learning space, offering new ways to enhance learner satisfaction and engagement. This systematic literature review, covering a five-year span from 2020 to 2025, explores how AI technologies, such as chatbots, intelligent tutoring systems (ITS), sentiment analysis, gaze tracking and predictive analytics, support learner engagement across cognitive, emotional, behavioral, and social dimensions. Drawing from 30 peer-reviewed studies, the current review addresses three central research questions: (1) What aspects of AI positively influence learner satisfaction and engagement in online courses within higher education institutions; (2) What potential challenges from using these technologies may arise; and (3) What research approaches are most commonly used to assess AI’s impact in such learning contexts? The findings highlight that adaptive learning, real-time feedback, and emotion-aware systems contribute positively to personalized learning and motivation. However, concerns persist around data privacy, algorithmic bias, over-reliance on automation, and system usability. Experimental and quasi-experimental designs, as well as machine learning, mixed methods, and survey-based approaches are found to dominate in reviewed studies. Based on these insights, this work offers a foundation for future AI-enhanced learning management systems designed primarily to enhance learner engagement across cognitive, emotional, behavioral, and social domains. Full article

Critical thinking dispositions are essential motivational drivers for intellectual excellence; yet their relationship with socio-emotional traits, such as humour, remains under-researched. This study investigated associations between critical thinking dispositions and the four humour styles (Affiliative, Self-enhancing, Aggressive, Self-defeating) in higher education, controlling for gender, field of study, and academic year. A quantitative, correlational design was used with 382 Portuguese university students who completed the Critical Thinking Dispositions Scale and the Humour Styles Questionnaire. Our results showed that Open-mindedness predicted Affiliative humour, while CT Self-confidence and Cognitive maturity predicted Self-enhancing humour. Truth-seeking inversely predicted Aggressive humour, which was higher in males and students of Science and Technology. Self-defeating humour was uniquely predicted by lower Cognitive maturity. These findings underscore that adaptive humour aligns with reflective thinking, whereas maladaptive styles correlate with traits that may hinder epistemic engagement. These findings underscore that adaptive humour is associated with reflective thinking, whereas maladaptive humour styles correlate with dispositional traits that may impede epistemic engagement; taken together, the results highlight the importance of integrating educational strategies that foster critical thinking dispositions, as such strategies may facilitate the development of more adaptive humour styles. Full article

This study addresses the growing vulnerability of societies to extreme weather events intensified by climate change and explores how Secondary Education can foster sustainability competences aligned with the European GreenComp framework. A mixed-methods design was used, combining a content analysis of 279 curricular units from educational legislation and STEM subjects in Compulsory Secondary Education and Baccalaureate, a questionnaire administered to 190 students, and the design and classroom implementation of a GreenComp-based teaching intervention. The curricular analysis revealed uneven integration of sustainability competences across STEM disciplines, with stronger presence in Biology, Geology and Technology, and limited representation in Mathematics and Physics and Chemistry. Student perceptions showed fragmented understandings of extreme weather events, their causes and consequences, and limited awareness of global frameworks such as the SDGs and COP meetings. The implemented teaching sequence improved students’ knowledge of extreme events, strengthened their recognition of links with climate change, and increased awareness of mitigation, adaptation, and the role of education and political action. Overall, the findings highlight both opportunities and gaps in current curricula and demonstrate the potential of contextualized, inquiry-based STEM approaches to develop sustainability competences and better prepare students to face extreme weather events. Full article

Against the backdrop of intensified global talent competition, the return of overseas talents has become a key engine driving the enhancement of core competitiveness in developing countries. Accurately identifying its critical driving factors is essential for China to address the challenges of talent introduction. This study constructs a hybrid multiple-criteria decision-making framework to systematically explore the influence mechanism of overseas talent return: first, a 15-criterion decision structure covering economic, policy, educational, technological, and social aspects is established via systematic literature review and two-round Delphi expert surveys; second, the grey DEMATEL-ANP technique is adopted to quantify the inter-relationships and relative weights of the criteria and screen and rank the critical driving factors accurately. Empirical results show that the six core driving factors ranked by importance are talent policy support, economic development level, scientific and technological development strength, public service quality, educational resource supply, and attention to science and technology, with significant synergistic interaction effects among these factors. This research provides a scientific decision-making framework and empirical support for developing countries to formulate targeted talent introduction policies and optimize the talent development ecosystem. Full article

Sustainable regional competitiveness is widely recognized as a cornerstone for fostering economic growth, social well-being, and environmental sustainability at the local level. Building upon our previous research, in which we extensively examined the ten factors shaping regional competitiveness, this study continues the investigation by focusing on the same nine factors while replacing environmental considerations with civil protection, utilizing updated literature spanning 2020 to 2025. The study’s time frame was from March 2025 to November 2025. A literature review methodology was adopted, emphasizing critical evaluation rather than a systematic review. Recent studies published within the last five years were analyzed, with particular attention to these ten recognized factors: (1) economy, (2) labor market, (3) poverty and social inclusion, (4) healthcare, (5) educational infrastructure, (6) environmental considerations, (7) transportation infrastructure, (8) science and technology, (9) high-tech industries, and (10) innovation. The key findings of the study emphasize the distinct yet interconnected role of each factor in shaping regional competitiveness. Economic development remains foundational, closely linked with education, causes of death, and sustainability, highlighting that a strong economy alone is insufficient. Labor market dynamics, including youth employment and skills development, are crucial for translating potential into growth, while addressing poverty and social exclusion requires coordinated social and economic policies. Public health indicator reflect societal challenges and helps identify areas where targeted interventions can enhance well-being and productivity. Education strengthens human capital, supports innovation and high-tech industries, and promotes social inclusion, creating the foundation for sustainable regional growth. Environmental issues shape the risks that civil protection must manage, while effective environmental protection reduces the need for emergency response. Transportation infrastructure connects economic activity, Research & Development (R&D), Information and Communication Technologies (ICT) deployment, and innovation, enhancing regional integration. Science and technology, particularly ICT, drive productivity and competitiveness, while human capital plays a central role in the development of high-tech industries, supporting innovation and economic diversification. Finally, innovation underpins the capacity of regions to adapt and maintain a long-term competitive advantage. Overall, this research demonstrates that by retaining the same nine core factors and replacing environmental considerations with civil protection, it is possible to gain new insights into regional competitiveness. Full article

Generative Artificial Intelligence (GAI) is rapidly reshaping pedagogical practices and offering new opportunities to advance sustainability within higher education. This study investigates the extent to which postgraduate students utilize GAI to support Sustainable and Environmentally Responsible Teaching Practices (SERTPs), and examines whether this use varies across demographic, academic, and technological characteristics. A descriptive quantitative design was employed, involving 310 postgraduate students from the College of Education at King Khalid University. Data were collected using a validated and highly reliable instrument measuring five dimensions of GAI-supported sustainable teaching. Descriptive and inferential analyses, including t tests, one-way ANOVA, and LSD post hoc comparisons, were conducted. The findings reveal that postgraduate students demonstrate a moderate overall level of GAI use in advancing SERTPs, with the highest engagement occurring in the promotion of sustainable educational practices. Significant differences were only found in relation to students’ levels of technology use and students’ levels of GAI use, indicating that frequent and sophisticated engagement with AI tools is the strongest predictor of sustainable teaching practices. No significant differences emerged across gender, age, academic department, program level, or specialization. The study highlights the need for targeted training and institutional strategies that enhance students’ AI proficiency, thereby enabling GAI to serve as a catalyst for environmentally responsible and sustainable teaching practices in higher education. Full article

Extended Reality (XR) technologies are increasingly used to create immersive and interactive systems across domains such as education, training, health, and entertainment. As these systems become more complex and multisensory, evaluating user experience (UX) in XR environments requires approaches that go beyond traditional usability assessments and consider perceptual, cognitive, emotional, and interaction-related factors. However, existing UX evaluation efforts in XR often rely on isolated instruments or domain-specific studies, lacking a systematic and reusable evaluation methodology. This paper proposes a human-centered methodology for evaluating user experience in extended reality applications, integrating UX dimensions and XR-specific characteristics into a structured and coherent evaluation process. The methodology is grounded in a multi-phase research process that includes a comprehensive literature review, expert consultation, correlation analysis between UX dimensions and XR features, and formal specification of evaluation phases and activities. Based on this process, the proposed methodology supports evaluators in selecting appropriate UX evaluation methods and instruments according to the characteristics and experiential goals of XR applications. The methodology defines a set of UX dimensions tailored to immersive environments, capturing perceptual, cognitive, emotional, and interaction aspects that are critical for the design and evaluation of adaptive and human-centered XR systems. An expert-based validation was conducted to assess the clarity, usefulness, and applicability of the methodology, leading to refinements in its structure and descriptions. The methodology promotes a human-centered approach by considering user perception, emotional impact, and contextual experience across XR modalities. It additionally contributes to the field by offering a reusable process for UX evaluation in XR, supporting more consistent, transparent, and human-centered assessment practices. It also provides a foundation for future empirical studies and the development of evaluation approaches inspired by natural and adaptive human–environment interactions. Full article

In arid-zone water resource management and water-security assessment, changes in water-body volume are key indicators of water availability and regulation performance. However, arid-zone lakes often lack sufficient bathymetric information to constrain geometry under low lake-level conditions. Shrinkage-driven hydrological disconnection can destabilize extrapolation of water level–storage relationships. This increases uncertainty in quantifying long-term storage changes. Here, we develop a multi-digital elevation model (DEM) hypsometry framework to reconstruct near-monthly lake storage for 1993–2024, recovering storage during low-level periods without bathymetric surveys. Reconstructed changes agree with independent satellite altimetry (r = 0.93 for level and 0.90 for storage), outperforming above-water-only (r ≈ 0.637 for water level) and conventional model-selection base-lines (r ≈ 0.753 for water level). The framework was quantified across three scenarios: expanding lakes, lake systems and reservoirs, and terminally shrinking lakes. For the persistently shrinking Big Aral Sea, under the whole-lake modeling assumption, the Copernicus-based reconstruction provides a cumulative storage change of −214.3 km³, closest to the satellite altimetry estimate of −210.68 km³ among the tested DEMs. In contrast, other DEMs overestimate the 1993–2024 cumulative loss by 66.15–141.01 km³. Sub-lake modeling further adjusts the Shuttle Radar Topography Mission (SRTM)-based cumulative change to −248.38 km³, substantially reducing structural bias caused by lake disconnection. This study provides a transferable technical framework for lake storage reconstruction in arid regions under degraded low lake-level conditions and hydrological disconnection. Full article

Background/Objectives: The rapid expansion of generative artificial intelligence (AI) and large language model-based chatbots has accelerated their adoption in higher education, including nursing. This scoping review mapped the use of AI-based chatbots in nursing education, including curricular domains, pedagogical approaches, educational outcomes, and implementation challenges. Methods: A scoping review was conducted following the Joanna Briggs Institute methodology and reported in accordance with the PRISMA-ScR guideline. Searches were performed across major bibliographic databases and grey literature sources. Quantitative, qualitative, and mixed-methods studies addressing the use of AI chatbots in nursing education or professional training were included. Data were extracted using a standardized instrument and synthesized through descriptive statistics and qualitative content analysis. Results: Sixty-six studies (2019–2025) were included, with significant growth observed after 2023. Most studies employed quasi-experimental designs (37.9%) and were implemented in academic settings (83.3%). Application formats varied across online, hybrid, simulation-based, and classroom models. Reported benefits included improved learning performance, clinical reasoning, and student engagement. Key challenges involved the reliability of AI outputs, academic integrity, data protection, and limited institutional governance. Conclusions: AI-based chatbots represent promising tools to enhance nursing education, particularly when integrated into structured pedagogical strategies with active faculty supervision. Their use can support the development of clinical reasoning, student engagement, and personalized learning. However, methodological heterogeneity, ethical concerns, and governance gaps highlight the need for careful implementation and further rigorous research to ensure safe, effective, and pedagogically sound integration. Full article