Search Results (971)

Digital competence refers to the integration of digital technology in teaching and learning, as outlined in the national curriculum of Estonia for upper secondary schools. This study presents original research findings on Estonian science teachers’ use of digital tools and materials, their digital competence, and the main benefits and challenges they face. The findings emphasize the need for continued professional development, accessible digital resources, and equitable digital infrastructure to maintain Estonia’s leadership in digital science education. A survey of 58 secondary school science teachers revealed that computers (desktops, laptops, and tablets) are the primary digital tools used. The article explores digital literacy advancements in secondary science education, research methodologies used to assess digital tool usage, and key findings from recent studies. However, challenges such as digital equity, technological barriers, and digital fatigue persist. Additionally, discrepancies were found in teachers’ responses regarding digital tool effectiveness, implementation strategies, and perceived barriers. While some teachers reported a successful integration and improved student outcomes, others highlighted difficulties in aligning digital resources with curriculum requirements and pedagogical approaches. Full article

With the advance of digital transformation, the assessment of the environmental impact of digital tools and technologies grows more relevant. Considering the inflated expectations of environmental responsibility in higher education, this study analyses how websites of Polish universities conform to sustainable web design criteria. The sustainability audit employed a methodology encompassing carbon emissions measurement, technical website analysis, and SEO evaluation. The author analysed 63 websites of public universities in Poland using seven independent audit tools, including an original AI Custom GPT agent preconfigured in the ChatGPT ecosystem. The results revealed a substantial differentiation in CO₂ emissions and website optimisation, with an average EcoImpact Score of 66.41/100. Nearly every fourth website exhibited a significant carbon footprint and excessive component sizes, which indicates poor asset optimisation and energy-intensive design techniques. The measurements exposed considerable variability in emission intensities and resource intensity among the university websites, suggesting the need for standardised digital sustainability practices. Regulations on the carbon footprint of public institutions’ websites and mobile applications could become vital strategic components for digital climate neutrality. Promoting green hosting, “Green SEO” practices, and sustainability audits could help mitigate the environmental impact of digital technologies and advance sustainable design standards for the public sector. The proposed auditing methodology can effectively support the institutional transition towards sustainable management of digital infrastructure by integrating technical, sustainability, and organisational aspects. Full article

Marine biomass, particularly from waste streams, by-products, underutilized, invasive, or potential cultivable marine species, offers a sustainable source of high-value biopolymers such as collagen and chitin. These macromolecules have gained significant attention due to their biocompatibility, biodegradability, functional versatility, and broad applicability across health, food, wellness, and environmental fields. This review highlights recent advances in the uses of marine-derived collagen and chitin/chitosan. In alignment with the United Nations Sustainable Development Goals (SDGs), we analyze how these applications contribute to sustainability, particularly in SDGs related to responsible consumption and production, good health and well-being, and life below water. Furthermore, we contextualize the advancement of product development using marine collagen and chitin/chitosan within the European Union’s Blue bioeconomy strategies, highlighting trends in scientific research and technological innovation through bibliometric and patent data. Finally, the review addresses challenges facing the development of robust value chains for these marine biopolymers, including collaboration, regulatory hurdles, supply-chain constraints, policy and financial support, education and training, and the need for integrated marine resource management. The paper concludes with recommendations for fostering innovation and sustainability in the valorization of these marine resources. Full article

Background: Artificial intelligence (AI) and machine learning (ML) have been reshaping maternal, fetal, neonatal, and reproductive healthcare by enhancing risk prediction, diagnostic accuracy, and operational efficiency across the perinatal continuum. However, no comprehensive synthesis has yet been published. Objective: To conduct a scoping review of reviews of AI/ML applications spanning reproductive, prenatal, postpartum, neonatal, and early child-development care. Methods: We searched PubMed, Embase, the Cochrane Library, Web of Science, and Scopus through April 2025. Two reviewers independently screened records, extracted data, and assessed methodological quality using AMSTAR 2 for systematic reviews, ROBIS for bias assessment, SANRA for narrative reviews, and JBI guidance for scoping reviews. Results: Thirty-nine reviews met our inclusion criteria. In preconception and fertility treatment, convolutional neural network-based platforms can identify viable embryos and key sperm parameters with over 90 percent accuracy, and machine-learning models can personalize follicle-stimulating hormone regimens to boost mature oocyte yield while reducing overall medication use. Digital sexual-health chatbots have enhanced patient education, pre-exposure prophylaxis adherence, and safer sexual behaviors, although data-privacy safeguards and bias mitigation remain priorities. During pregnancy, advanced deep-learning models can segment fetal anatomy on ultrasound images with more than 90 percent overlap compared to expert annotations and can detect anomalies with sensitivity exceeding 93 percent. Predictive biometric tools can estimate gestational age within one week with accuracy and fetal weight within approximately 190 g. In the postpartum period, AI-driven decision-support systems and conversational agents can facilitate early screening for depression and can guide follow-up care. Wearable sensors enable remote monitoring of maternal blood pressure and heart rate to support timely clinical intervention. Within neonatal care, the Heart Rate Observation (HeRO) system has reduced mortality among very low-birth-weight infants by roughly 20 percent, and additional AI models can predict neonatal sepsis, retinopathy of prematurity, and necrotizing enterocolitis with area-under-the-curve values above 0.80. From an operational standpoint, automated ultrasound workflows deliver biometric measurements at about 14 milliseconds per frame, and dynamic scheduling in IVF laboratories lowers staff workload and per-cycle costs. Home-monitoring platforms for pregnant women are associated with 7–11 percent reductions in maternal mortality and preeclampsia incidence. Despite these advances, most evidence derives from retrospective, single-center studies with limited external validation. Low-resource settings, especially in Sub-Saharan Africa, remain under-represented, and few AI solutions are fully embedded in electronic health records. Conclusions: AI holds transformative promise for perinatal care but will require prospective multicenter validation, equity-centered design, robust governance, transparent fairness audits, and seamless electronic health record integration to translate these innovations into routine practice and improve maternal and neonatal outcomes. Full article

Information and communication technologies (ICTs) are becoming increasingly important for sustainable rural development through the smart village concept. This study aims to model ICT’s potential for public services management in European rural areas. It identifies ICT applications across rural service domains, analyzes how these technologies address specific rural challenges, and evaluates their benefits, implementation barriers, and future prospects for sustainable rural development. A qualitative content analysis method was applied using purposive sampling to analyze 79 peer-reviewed articles from EBSCO and Elsevier databases (2000–2024). A deductive approach employed predefined categories to systematically classify ICT applications across rural public service domains, with data coded according to technology scope, problems addressed, and implementation challenges. The analysis identified 15 ICT application domains (agriculture, healthcare, education, governance, energy, transport, etc.) and 42 key technology categories (Internet of Things, artificial intelligence, blockchain, cloud computing, digital platforms, mobile applications, etc.). These technologies address four fundamental rural challenges: limited service accessibility, inefficient resource management, demographic pressures, and social exclusion. This study provides the first comprehensive systematic categorization of ICT applications in smart villages, establishing a theoretical framework connecting technology deployment with sustainable development dimensions. Findings demonstrate that successful ICT implementation requires integrated urban–rural cooperation, community-centered approaches, and balanced attention to economic, social, and environmental sustainability. The research identifies persistent challenges, including inadequate infrastructure, limited digital competencies, and high implementation costs, providing actionable insights for policymakers and practitioners developing ICT-enabled rural development strategies. Full article

This study proposes a non-semantic multimodal approach to predict segment access frequency (SAF) in lecture archives. Such archives, widely used as supplementary resources in modern education, often consist of long, unedited recordings that are difficult to navigate and review efficiently. The predicted SAF, an indicator of student viewing behavior, serves as a practical proxy for student engagement. The increasing volume of recorded material renders manual editing and annotation impractical, making the automatic identification of high-SAF segments crucial for improving accessibility and supporting targeted content review. The approach focuses on lecture archives from a real-world blended learning context, characterized by resource constraints such as no specialized hardware and limited student numbers. The model integrates multimodal features from instructor’s actions (via OpenPose and optical flow), audio spectrograms, and slide page progression—a selection of features that makes the approach applicable regardless of lecture language. The model was evaluated on 665 labeled one-minute segments from one such course. Experiments show that the best-performing model achieves a Pearson correlation of 0.5143 in 7-fold cross-validation and 61.05% average accuracy in a downstream three-class classification task. These results demonstrate the system’s capacity to enhance lecture archives by automatically identifying key segments, which aids students in efficient, targeted review and provides instructors with valuable data for pedagogical feedback. Full article

Since the end of the Civil War, Cambodia has pursued economic development to enhance livelihoods, particularly in rural areas, where land is a critical resource. Previous studies have indicated that the country has changed land use and land cover. However, they have not explained how these changes can improve the livelihoods of local communities, thereby mitigating their negative impacts through an asset-based approach. Battambang Province, in the northwestern region, was the battleground until political integration in 1996. Since then, the province has been home to immigrants exploring the lands for livelihood. Thus, this study aims to examine agricultural livelihoods in the villages of Dei Kraham and Ou Toek Thla, located west of Battambang Town. These were selected because of their common characteristics. Adopting a quantitative approach and a sustainable livelihood framework, this study employed stratified random sampling to select 123 families for interviews across three population subgroups: old settlers, new settlers, and young settlers. In situ information was collected using structured questionnaires and analyzed using Kruskal–Wallis tests to assess the livelihood assets underlying the physical, natural, human, financial, and social capital. The statistical analysis results reveal no significant differences (p-value = 0.079) in livelihood assets between the strata at the village level. Meanwhile, significant differences were observed in physical, human, and financial capital between old and young settlers when examining the subgroups (p-value 0.000). The extent of the land resources held by old settlers was associated with household income and livelihoods related to agriculture. Based on livelihood asset scores, nearly half of the new settlers (0.49–0.5) and a quarter of the young settlers (0.47) are vulnerable groups requiring support. The youth will soon face an uncertain future if they do not prioritize education. Full article

In modern medical education, a robust understanding of statistics is essential for fostering critical thinking, informed clinical decision-making, and effective communication. This paper explores the synergistic value of early and continued statistical education for medical students and residents, particularly in relation to the expanding field of sports supplementation and its impact on athletic performance. Early exposure to statistical principles enhances students’ ability to interpret clinical research, avoid cognitive biases, and engage in evidence-based practice. Continued statistical learning throughout residency further refines these competencies, enabling more sophisticated analysis and application of emerging data. The paper also addresses key challenges in integrating statistics into medical curricula—such as limited curricular space, student disengagement, and resource constraints—and proposes solutions including interactive learning, case-based teaching, and the use of public datasets. A unique emphasis is placed on connecting statistical literacy to the interpretation of research in sports science, particularly regarding the efficacy, safety, and ethical considerations of sports supplements. By linking statistical education to a dynamic and relatable domain like sports performance, educators can not only enrich learning outcomes but also foster lasting interest and competence in quantitative reasoning. This integrated approach holds promise for producing more analytically proficient and clinically capable physicians. Full article

The present study focuses on investigating the contribution of puppetry as a pedagogical and psychosocial tool in special education, addressing the literature gap in the systematic documentation of the experiences of special education teachers, concerning its use in daily teaching practice. The main objective is to capture the way in which puppetry enhances the learning, social and therapeutic support of students with complex educational and psychosocial needs. The study employs a qualitative phenomenological approach, conducting semi-structured interviews with eleven special education teachers who integrate puppetry into their teaching. Qualitative data were analyzed using thematic analysis. The findings highlight that puppetry significantly enhances cognitive function, concentration, memory and language development, while promoting the active participation, cooperation, social inclusion and self-expression of students. In addition, the use of the puppet acts as a means of psycho-emotional empowerment, supporting positive behavior and helping students cope with stress and behavioral difficulties. Participants identified peer support, material adequacy and training as key factors for effective implementation, while conversely, a lack of resources and time is cited as a key obstacle. The integration of puppetry in everyday school life seems to ameliorate a more personalized, supportive and experiential learning environment, responding to the diverse and complex profiles of students attending special schools. Continuous training for teachers, along with strengthening the collaboration between the arts and special education, is essential for the effective use of puppetry in the classroom. Full article

The increasing complexity of modern control systems highlights the need for reliable and robust fault detection, isolation, and identification (FDII) methods, particularly in safety-critical and industrial applications. The study focuses on the FDII of multiplicative faults in a DC motor and its electronic amplifier. To simulate such scenarios, a complete laboratory platform was developed for real-time FDII, using relay-based switching and custom LabVIEW software 2009. This platform enables real-time experimentation and represents an important component of the study. Two estimation-based fault detection (FD) algorithms were implemented: the Sliding Window Algorithm (SWA) for discrete-time models and a modified Sliding Integral Algorithm (SIA) for continuous-time models. The modification introduced to the SIA limits the data length used in least squares estimation, thereby reducing the impact of transient effects on parameter accuracy. Both algorithms achieved high model output-to-measured signal agreement, up to 98.6% under nominal conditions and above 95% during almost all fault scenarios. Moreover, the proposed fault isolation and identification methods, including a decision algorithm and an indirect estimation approach, successfully isolated and identified faults in key components such as amplifier resistors (R₁, R₉, R₁₂), capacitor (C₈), and motor parameters, including armature resistance (R_a), inertia (J), and friction coefficient (B). The decision algorithm, based on continuous-time model coefficients, demonstrated reliable fault isolation and identification, while the reduced Jacobian-based approach in the discrete model enhanced fault magnitude estimation, with deviations typically below 10%. Additionally, the platform supports remote experimentation, offering a valuable resource for advancing model-based FDII research and engineering education. Full article

Volcanic islands host exceptional geological features that illustrate complex endogenic processes and interactions with climatic and marine forces, while also being particularly vulnerable to the impacts of climate change. Despite their scientific, educational, touristic, and aesthetic values, such islands remain underrepresented within the UNESCO Global Geoparks (UGGp). This study reviews current volcanic island geoparks and evaluates territories with potential for future designation, based on documented geoheritage, geosite inventories, and geoconservation frameworks. Geoparks are categorized according to their dominant narratives—ranging from recent Quaternary volcanism to broader tectonic, sedimentary, and metamorphic histories. Through an analysis of their distribution, management strategies, and integration into territorial planning, this work highlights the challenges that insular territories face, including vulnerability to global environmental change, limited legal protection, and structural inequalities in access to international resources recognition. It concludes that volcanic island geoparks represent strategic platforms for implementing sustainable development models, especially in ecologically and socially fragile contexts. Enhancing their global representation will require targeted efforts in ecologically and socially fragile contexts. Enhancing their global representation will require targeted efforts in capacity building, funding access, and regional cooperation—particularly across the Global South. Full article

The development of stock markets is pivotal for economic growth, particularly through the mobilization of idle resources into productive investments. Despite recent reforms to enhance Uzbekistan’s capital market, public engagement remains limited. This study examines the behavioral determinants of stock market investment intention and participation among university students, employing the Theory of Planned Behavior (TPB) and Partial Least Squares Structural Equation Modeling (PLS-SEM). The model investigates the influence of digital literacy, financial literacy, social interaction, herding behavior, overconfidence bias, risk tolerance, and financial well-being on investment intention and behavior. A survey of 369 university students was conducted to assess the proposed relationships. The results reveal that risk tolerance, overconfidence bias, and herding behavior significantly and positively affect investment intention, while digital literacy demonstrates a notable negative effect, suggesting caution in assuming technology readiness automatically translates to investment readiness. Investment intention, in turn, strongly predicts actual participation and mediates several of these effects. Conversely, financial literacy, financial well-being, and social interaction showed no significant direct or mediating influence. Additionally, differences according to gender and academic background were observed in how intention translates into behavior. The findings underscore the need for integrated financial and behavioral education to enhance market participation and contribute to policy discourse on youth financial engagement in emerging economies. Full article

Applying language models (LMs) and generative artificial intelligence (GenAI) to the study of Ancient Greek offers promising opportunities. However, it faces substantial challenges due to the language’s morphological complexity and lack of annotated resources. Despite growing interest, no systematic overview of existing research currently exists. To address this gap, a systematic literature review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 methodology. Twenty-seven peer-reviewed studies were identified and analyzed, focusing on application areas such as machine translation, morphological analysis, named entity recognition (NER), and emotion detection. The review reveals six key findings, highlighting both the technical advances and persistent limitations, particularly the scarcity of large, domain-specific corpora and the need for better integration into educational contexts. Future developments should focus on building richer resources and tailoring models to the unique features of Ancient Greek, thereby fully realizing the potential of these technologies in both research and teaching. Full article

Oral tradition stories hold a vital place in language education, offering rich repositories of linguistic, cultural, and historical knowledge. In the Spanish as a Foreign Language (SFL) context, their inclusion provides dynamic opportunities to explore diversity, foster critical and creative thinking, and challenge dominant epistemologies. Despite their pedagogical potential, these narratives remain largely absent from formal curricula, with most SFL textbooks still privileging canonical works, particularly those from the Latin American Boom or European literary texts. This article aims to provide practical guidance for SFL instructors on designing effective, culturally responsive materials for the teaching of vocabulary. Drawing on a methodological framework for material design and a cognitive approach to vocabulary learning, I present original pedagogical material based on a Colombian oral tradition story about the witches of La Jagua (Huila, Colombia) to inspire educators to integrate oral tradition stories into their classrooms. As argued throughout, oral narratives not only support vocabulary acquisition and intercultural competence but also offer students meaningful engagement with the values, worldviews, and linguistic diversity that shape Colombian culture. This approach redefines language teaching through a more descriptive, contextualized, and culturally grounded lens, equipping learners with pragmatic, communicative, and intercultural skills essential for the 21st century. My goal with this article is to advocate for teacher agency in material creation, emphasizing that educators are uniquely positioned to design pedagogical resources that reflect their own cultural realities and local knowledge and to adapt them meaningfully to their students’ needs. Full article

Background/Objectives: Migraine affects approximately 3–10% of school-aged children and up to 28% of adolescents, with prevalence increasing during adolescence. For pediatric specialty providers, increased awareness of this condition may influence patient care. This study examined pediatric dentists’ education, clinical exposure, and perceived knowledge gaps related to pediatric migraine, with the goal of identifying barriers to recognition and referral, as well as informing future training to support accurate diagnosis and interdisciplinary care. Methods: A 28-item electronic questionnaire was distributed to all members of the American Academy of Pediatric Dentistry, including pediatric dentists and postgraduate pediatric dental residents, assessing knowledge, beliefs, clinical experience, and interest in further training regarding pediatric headache/migraine management. Respondents with and without previous training were compared in terms of general understanding using t-tests; a linear regression model analyzed predictors of provider awareness regarding links between oral conditions and headache/migraine. Results: Among 315 respondents, the mean self-perceived awareness score was 2.7 ± 1.3 (on a 0–5 scale). The most frequently identified contributing factors were clenching (73.7%), bruxism (72.4%), and temporomandibular disorders (65.7%). Nearly all respondents (95.2%) reported no formal education on headache/migraine prevention, yet 78.1% agreed on the importance of understanding the relationship between oral health and headache/migraine. Respondents with prior training were significantly more aware (p < 0.001) than those without prior training. Educating families (p < 0.001), frequency of patient encounters with headache (p = 0.032), coordination with healthcare providers (p = 0.002), and access to appropriate management resources (p < 0.001) were significant predictors of providers’ awareness. Conclusions: Pediatric dental providers expressed strong interest in enhancing their knowledge of headache/migraine management, highlighting the value of integrating headache/migraine-related education into training programs and promoting greater interdisciplinary collaboration. Full article