Search Results (4,447)

This systematic literature review investigates how the concept of time is taught and learned in early mathematics education. While young children are commonly expected to learn how to tell time, this review explores what additional aspects should be emphasised to foster a deeper and more sustainable understanding of time. Using the EBSCO database, 36 relevant articles published up to December 2024 were identified. To cover different aspects related to the teaching and learning of time, peer-reviewed scientific articles as well as practice-based reports were included in the search. A majority of the articles focused on clock reading as an aspect of time. The aspects duration, sequencing, and measurement of time also frequently appeared whereas expressions of time, or cross-disciplinary aspects were seldom mentioned. Drawing on the findings, this review proposes a comprehensive framework outlining key aspects that should be included in early mathematics education to support the teaching and learning of time. Full article

The growing concern over environmental sustainability has intensified the focus on consumers’ perceptions of eco-friendly food packaging, especially among younger generations. This study aims to investigate the attitudes, preferences, and barriers faced by Greek university students regarding sustainable food packaging, a demographic considered pivotal for driving future consumption trends. An online questionnaire assessing perceptions, preferences, and behaviours related to sustainable packaging was administered to students, with responses measured on a five-point Likert scale. Three hundred and sixty-four students took part in this survey, with the majority (60%) of them being female. Principal component analysis was employed to identify underlying factors influencing perceptions, and k-means cluster analysis revealed two consumer segments: “Innovatives”, including one hundred and ninety-eight participants (54%), who demonstrate strong environmental awareness and willingness to adopt sustainable behaviours, and “Sceptics”, including one hundred sixty-six participants (46%), who show moderate engagement and remain cautious in their choices. Convenience, affordability, and clear product communication emerged as significant factors shaping student preferences. The findings suggest that targeted educational campaigns and transparent information are essential to converting positive attitudes into consistent purchasing behaviours. This research provides valuable insights for policymakers and marketers looking to design effective sustainability strategies tailored to the student population. Full article

In the context of increasing Artificial Intelligence integration in higher education, understanding the factors influencing university teachers’ adoption of AI tools is critical for effective implementation. This study adopts a perception–intention–behavior framework to explores the roles of perceived usefulness, perceived ease of use, perceived trust, perceived substitution crisis, and perceived risk in shaping teachers’ behavioral intention and actual usage of AI tools. It also investigates the moderating effects of peer influence and organizational support on these relationships. Using a comprehensive survey instrument, data was collected from 487 university teachers across four major regions in China. The results reveal that perceived usefulness and perceived ease of use are strong predictors of behavioral intention, with perceived ease of use also significantly influencing perceived usefulness. Perceived trust serves as a key mediator, enhancing the relationship between perceived usefulness, perceived ease of use, and behavioral intention. While perceived substitution crisis negatively influenced perceived trust, it showed no significant direct effect on behavioral intention, suggesting a complex relationship between job displacement concerns and AI adoption. In contrast, perceived risk was found to negatively impact behavioral intention, though it was mitigated by perceived ease of use. Peer influence significantly moderated the relationship between perceived trust and behavioral intention, highlighting the importance of peer influence in AI adoption, while organizational support amplified the effect of perceived ease of use on behavioral intention. These findings inform practical strategies such as co-developing user-centered AI tools, enhancing institutional trust through transparent governance, leveraging peer support, providing structured training and technical assistance, and advancing policy-level initiatives to guide digital transformation in universities. Full article

Heart failure (HF) is a major global health challenge, characterized by high morbidity, mortality, and frequent hospital readmissions. Despite the advent of guideline-directed medical therapies (GDMTs), the burden of HF continues to grow, necessitating a shift toward comprehensive, multidisciplinary care models. Heart Failure Disease Management Programs (HF-DMPs) have emerged as structured frameworks that integrate evidence-based medical therapy, patient education, telemonitoring, and support for social determinants of health to optimize outcomes and reduce healthcare costs. This review outlines the key components of HF-DMPs, including patient identification and risk stratification, pharmacologic optimization, team-based care, transitional follow-up, remote monitoring, performance metrics, and social support systems. Incorporating tools such as artificial intelligence, pharmacist-led titration, and community health worker support, HF-DMPs represent a scalable approach to improving care delivery. The success of these programs depends on tailored interventions, interdisciplinary collaboration, and health equity-driven strategies. Full article

The naturally occurring radioactive gas radon presents a major public health danger mainly affecting people who spend time in poorly ventilated buildings. The periodic table includes radon as a noble gas which forms through uranium decay processes in soil, rock, and water. The accumulation of radon indoors in sealed or poorly ventilated areas leads to dangerous concentrations that elevate human health risks of lung cancer. The research examines environmental variables affecting radon concentration indoors by studying geothermal installations and their drilling activities, which potentially increase radon emissions. The study was conducted in the basement of the plumbing educational building at the Aristotle University of Thessaloniki to assess the potential impact of geothermal activity on indoor radon levels, as the building is equipped with a geothermal heating system. The key findings based on 150 days of continuous data showed that radon levels peak during the cold days, where the concentration had a mean value of 41.5 Bq/m³ and reached a maximum at about 95 Bq/m³. The reason was first and foremost poor ventilation and pressure difference. The lowest concentrations were on days with increased human activity with measures that had a mean value of 14.8 Bq/m³, which is reduced by about 65%. The results that are presented confirm the hypotheses and the study is making clear that ventilation and human activity are crucial in radon mitigation, especially on geothermal and energy efficient structures. Full article

Understanding the carbon emission efficiency of apple production (APCEE) is critical for promoting green and low-carbon agricultural development. However, the spatiotemporal dynamics and driving factors of APCEE in China remain inadequately explored. This study employs life cycle assessment, super-efficiency slacks-based measures, and a panel Tobit model to evaluate the carbon footprint, APCEE, and its determinants in China’s two major production regions from 2003 to 2022. The results reveal that: (1) Producing one ton of apples in China results in 0.842 t CO₂e emissions. Land carbon intensity and total carbon emissions peaked in 2010 (28.69 t CO₂e/ha) and 2014 (6.52 × 10⁷ t CO₂e), respectively, exhibiting inverted U-shaped trends. Carbon emissions from various production areas show significant differences, with higher pressure on carbon emission reduction in the Loess Plateau region, especially in Gansu Province. (2) The APCEE in China exhibits a W-shaped trend (mean: 0.645), with overall low efficiency loss. The Bohai Bay region outperforms the Loess Plateau and national averages. (3) The structure of the apple industry, degree of agricultural mechanization, and green innovation positively influence APCEE, while the structure of apple cultivation, education level, and agricultural subsidies negatively impact it. Notably, green innovation and agricultural subsidies display lagged effects. Moreover, the drivers of APCEE differ significantly between the two major production regions. These findings provide actionable pathways for the green and low-carbon transformation of China’s apple industry, emphasizing the importance of spatially tailored green policies and technology-driven decarbonization strategies. Full article

Computational Thinking (CT) has been an important concept for the computer science education community in the last 20 years. In this work we performed a systematic review of the literature regarding the computational thinking of children from kindergarten to primary school. We compiled a large dataset of one hundred and twenty (120) studies from the literature. Through analysis of these studies, we tried to reveal important insights and draw interesting and valid conclusions. We analyzed various qualitative and quantitative aspects of the studies, including the sample size, the year of publication, the country of origin, the studies’ design and duration, the computational tools used, and so on. An important aspect of the work is to highlight differences between different study designs. We identified a total of 120 studies, with more than half of them (>50%) originating from Asian countries. Most studies (82.5%) conducted some form of intervention, aiming to improve their computational thinking in students. A smaller proportion (17.5%) were assessment studies in which the authors conducted assessments regarding the children’s computational thinking. On average, intervention studies had a smaller number of participants, but differences in duration could not be identified. There was also a lack of large-scale longitudinal studies. Block-based coding (i.e., Scratch) and Plugged and Unplugged activities were observed in high numbers in both categories of studies. CT assessment tools showed great variability. Efforts for standardization and reaching a consensus are needed in this regard. Finally, robotic systems have been found to play a major role in interventions over the last years. Full article

Background/Objectives: Evidence-based nursing practice (EBNP) is essential in high-acuity settings such as intensive care units (ICUs) and emergency departments (EDs), where nurses are frequently required to make time-critical, high-stakes clinical decisions that directly influence patient safety and outcomes. Despite its recognized importance, the implementation of EBNP remains inconsistent, with frontline nurses often facing barriers to accessing and applying current evidence. Methods: This descriptive, cross-sectional study systematically mapped and prioritized clinical questions generated by ICU and ED nurses at a tertiary hospital in South Korea. Using open-ended questionnaires, 204 clinical questions were collected from 112 nurses. Each question was coded and classified according to the Nursing Interventions Classification (NIC) taxonomy (8th edition) through a structured cross-mapping methodology. Inter-rater reliability was assessed using Cohen’s kappa coefficient. Results: The majority of clinical questions (56.9%) were mapped to the Physiological: Complex domain, with infection control, ventilator management, and tissue perfusion management identified as the most frequent areas of inquiry. Patient safety was the second most common domain (21.6%). Notably, no clinical questions were mapped to the Family or Community domains, highlighting a gap in holistic and transitional care considerations. The mapping process demonstrated high inter-rater reliability (κ = 0.85, 95% CI: 0.80–0.89). Conclusions: Frontline nurses in high-acuity environments predominantly seek evidence related to complex physiological interventions and patient safety, while holistic and community-oriented care remain underrepresented in clinical inquiry. Utilizing the NIC taxonomy for systematic mapping establishes a reliable framework to identify evidence gaps and support targeted interventions in nursing practice. Regular protocol evaluation, alignment of continuing education with empirically identified priorities, and the integration of concise evidence summaries into clinical workflows are recommended to enhance EBNP implementation. Future research should expand to multicenter and interdisciplinary settings, incorporate advanced technologies such as artificial intelligence for automated mapping, and assess the long-term impact of evidence-based interventions on patient outcomes. Full article

Augmented reality (AR), which overlays digital content within the user’s view, is gaining traction across domains such as education, healthcare, manufacturing, and entertainment. The hardware constraints of commercially available HMDs are well acknowledged, but little work addresses what design or interactions techniques developers can employ or build into experiences to work around these limitations. We conducted a scoping literature review, with the aim of mapping the current landscape of design principles and interaction techniques employed in near-field AR environments. We searched for literature published between 2016 and 2025 across major databases, including the ACM Digital Library and IEEE Xplore. Studies were included if they explicitly employed design or interaction techniques with a commercially available HMD for near-field AR experiences. A total of 780 articles were returned by the search, but just 7 articles met the inclusion criteria. Our review identifies key themes around how existing techniques are employed and the two competing goals of AR experiences, and we highlight the importance of embodiment in interaction efficacy. We present directions for future research based on and justified by our review. The findings offer a comprehensive overview for researchers, designers, and developers aiming to create more intuitive, effective, and context-aware near-field AR experiences. This review also provides a foundation for future research by outlining underexplored areas and recommending research directions for near-field AR interaction design. Full article

Quantum sensing based on NV-centers in diamonds has been demonstrated many times in multiple publications. The majority of publications use lasers in free space or lasers with fiber optics, expensive optical components such as dichroic mirrors, or beam splitters with dichroic filters and expensive detectors, such as Avalanche photodiodes or single photon detectors, overall, leading to custom and expensive setups. In order to provide an inexpensive NV-based magnetometer setup for educational use in schools, to teach the three topics, fluorescence, optically detected magnetic resonance, and Zeeman splitting, inexpensive, miniaturized, off-the-shelf components with high reliability have to be used. The cheaper such a setup, the more setups a school can afford. Hence, in this work, we investigated LEDs as light sources, considered different diamonds for our setup, tested different color filters, proposed an inexpensive microwave resonator, and used a cheap photodiode with an appropriate transimpedance amplifier as the basis for our quantum magnetometer. As a result, we identified cheap and functional components and present a setup and show that it can demonstrate the three topics mentioned at a hardware cost <EUR 100. Full article

Background/Objectives: Antibiotic use is common among hospitalized pediatric patients. However, inappropriate use, including excessive use of Watch antibiotics, can contribute to antimicrobial resistance, adverse events, and increased healthcare costs. Consequently, there is a need to continually assess their usage among this vulnerable population. This was the objective behind this study. Methods: The medical records of all pediatric patients (under 12 years) admitted and treated with antibiotics at a Ghanaian Teaching Hospital between January 2022 and March 2022 were extracted from the hospital’s electronic database. The prevalence and appropriateness of antibiotic use were based on antibiotic choices compared with current guidelines. Influencing factors were also assessed. Results: Of the 410 admitted patients, 319 (77.80%) received at least one antibiotic. The majority (68.65%; n = 219/319) were between 0 and 2 years, and males (54.55%; n = 174/319). Ceftriaxone was the most commonly prescribed antibiotic (20.69%; n = 66/319), and most of the systemic antibiotics used belonged to the WHO Access and Watch groups, including a combination of Access and Watch groups (42.90%; n = 136/319). Neonatal sepsis (24.14%; n = 77/319) and pneumonia (14.42%; n = 46/319) were the most common diagnoses treated with antibiotics. Antibiotic appropriateness was 42.32% (n = 135/319). Multivariate analysis revealed ceftriaxone prescriptions (aOR = 0.12; CI = 0.02–0.95; p-value = 0.044) and surgical prophylaxis (aOR = 0.07; CI = 0.01–0.42; p-value = 0.004) were associated with reduced antibiotic appropriateness, while a pneumonia diagnosis appreciably increased this (aOR = 15.38; CI = 3.30–71.62; p-value < 0.001). Conclusions: There was high and suboptimal usage of antibiotics among hospitalized pediatric patients in this leading hospital. Antibiotic appropriateness was influenced by antibiotic type, diagnosis, and surgical prophylaxis. Targeted interventions, including education, are needed to improve antibiotic utilization in this setting in Ghana and, subsequently, in ambulatory care. Full article

Background: Emotional abuse is both prevalent and underrecognized particularly in culturally complex settings like India. Adolescents, being in a critical developmental phase, are especially vulnerable to the long-lasting psychological effects of emotional abuse. This qualitative literature review aims to synthesize findings from primary studies that explore the lived experiences of emotional abuse among Indian adolescents and identify emerging patterns across sociocultural contexts. Method: Electronic databases, including DOAJ, Google Scholar, ProQuest, JSTOR, Pubmed, PsycNet, and SCOPUS, were searched for peer-reviewed articles published in English up to March 2025. Inclusion criteria comprised qualitative or mixed-methods research focusing on emotional abuse among adolescents aged 12–20 in Indian contexts. The Critical Appraisal Skills Programme (CASP) was used for quality assessment. Results: Five major thematic domains were identified across the included studies: (1) Family as a primary site of emotional abuse; (2) Gendered experiences of abuse; (3) Cultural normalization and silence; (4) Psychological and emotional consequences; and (5) Coping and resilience among adolescents. These themes reflect shared experiences of emotional abuse shaped by cultural, familial, and gender-based expectations. Conclusions: This review highlights the urgent need for increased awareness and culturally sensitive interventions addressing emotional abuse in Indian adolescents. The findings suggest that parents, educators, and policymakers must recognize emotionally harmful behaviors and implement prevention-oriented strategies, particularly through non-violent communication and adolescent mental health support frameworks. Full article

Oral health during pregnancy is essential for maternal and child well-being, as hormonal and physiological changes increase women’s susceptibility to oral diseases. Despite the recognized importance of prenatal dental care, adherence to dental services remains a challenge in the public health context. This study aimed to analyze oral health and the use of dental services during pregnancy through the perception of pregnant women. It represents the qualitative phase of a mixed-method study conducted with 25 pregnant women (with and without dental care) receiving prenatal care in the Brazilian Unified Health System (SUS). Participants were selected through saturation sampling, and data were collected via semi-structured interviews, followed by content analysis. The findings revealed four major themes: barriers and facilitators to dental care, changes during pregnancy and oral health. Discomfort from oral changes was a common concern. Barriers included misinformation, fear, cultural beliefs, and service organization. In contrast, facilitating factors were identified, such as care prioritization, support from healthcare teams, health education, and access through SUS. This study concludes that emotional, cultural, and contextual aspects shape the use of dental services during pregnancy. Access through SUS is perceived as an important facilitator, which simultaneously presents organizational weaknesses that need to be addressed. Full article

The rapid emergence of generative AI technologies has sparked significant transformation across educational landscapes worldwide. This study presents a comprehensive bibliometric analysis of GAI in education, mapping scholarly trends from 2022 to 2025. Drawing on 3808 peer-reviewed journal articles indexed in Scopus, the analysis reveals exponential growth in publications, with dominant contributions from the United States, China, and Hong Kong. Using VOSviewer, the study identifies six major thematic clusters, including GAI in higher education, ethics, technological foundations, writing support, and assessment. Prominent tools, especially ChatGPT, are shown to influence pedagogical design, academic integrity, and learner engagement. The study highlights interdisciplinary integration, regional research ecosystems, and evolving keyword patterns reflecting the field’s transition from tool-based inquiry to learner-centered concerns. This review offers strategic insights for educators, researchers, and policymakers navigating AI’s transformative role in education. Full article

In today’s fast-changing world, the higher education system must evolve to enhance the quality of learning and teaching. Fulfilling the role of a university is a major challenge. Universities must implement strategies that place the student at the center of their concerns; so, these strategies must be designed for and by the student. However, the high university dropout rate is one of the current problems faced by many universities. This suggests that there are some issues that hinder the learning process. Several studies have highlighted the advantage of artificial intelligence (AI) technologies in providing explorative and predictive analyses that explain why students are dropping out, with the aim of improving the quality of teaching and providing an integrated learning environment. This paper proposes a framework that predicts student dropout rates using machine learning techniques, based on data collected from various sources. Data collection was carried out between 2022 and 2024. We used a quantitative analysis method employed through a questionnaire distributed to 120 students (aged 18–26) from open access faculties of a Moroccan public university to identify the factors leading to an increase in university dropout rates. We discuss the impact of selected variables, and the findings show that several factors are related to university dropout rates, such as social background, psychological and health problems, insufficient motivation of professors, limited perspective on educational programs, changes in language and teaching methodologies, absenteeism, student attitude, and a lack of interaction between professors and students. Full article