Search Results (2,007)

Background/Objectives: Accurate and accessible perioperative health information empowers patients and enhances recovery outcomes. Artificial intelligence tools, such as ChatGPT, have garnered attention for their potential in health communication. This study evaluates the accuracy and readability of responses generated by ChatGPT to questions commonly asked about breast cancer. Methods: Fifteen simulated patient queries about breast cancer surgery preparation and recovery were prepared. Responses generated by ChatGPT (4o version) were evaluated for accuracy by a pool of breast surgeons using a 4-point Likert scale. Readability was assessed with the Flesch–Kincaid Grade Level (FKGL). Descriptive statistics were used to summarize the findings. Results: Of the 15 responses evaluated, 11 were rated as “accurate and comprehensive”, while 4 out of 15 were deemed “correct but incomplete”. No responses were classified as “partially incorrect” or “completely incorrect”. The median FKGL score was 11.2, indicating a high school reading level. While most responses were technically accurate, the complexity of language exceeded the recommended readability levels for patient-directed materials. Conclusions: The model shows potential as a complementary resource for patient education in breast cancer surgery, but should not replace direct interaction with healthcare providers. Future research should focus on enhancing language models’ ability to generate accessible and patient-friendly content. Full article

This study aims to provide a comprehensive overview of psychological distress among medical students in Spain, a growing concern given the high prevalence rates of anxiety, depression, and burnout reported across multiple medical schools and universities. To assess the scope and key characteristics of this phenomenon, a thorough literature search was conducted in the PubMed, ProQuest, and Web of Science (WoS) databases. Studies published between 2010 and 2024 in peer-reviewed scientific journals, written in English or Spanish, and specifically focused on medical students enrolled in Spanish universities were considered for inclusion. A total of 14 studies were analysed. The findings indicate that psychological distress often emerges early in medical training and tends to intensify as students progress academically. Female medical students are consistently more affected, as most of the studies reviewed indicate that they exhibit higher levels of depressive symptoms, trait anxiety, and perceived stress. Some research also suggests greater levels of burnout among female students compared to their male peers. Key contributing factors include academic overload and dissatisfaction, sleep deprivation, and the use of maladaptive coping strategies. Although awareness of the issue is increasing, available evidence suggests that institutional responses remain limited, and that only a small number of universities have implemented structured mental health programmes. Overall, the results underscore the urgent need for institutional reforms in Spanish medical education to safeguard students’ mental wellbeing. Key priorities include revising curricula, implementing structured emotional support programmes, and ensuring accessible services—requiring coordinated, long-term commitment across academic, healthcare, and policy sectors. Future research should explore longitudinal trends and the effectiveness of targeted interventions. Full article

Background: Thailand is rapidly transitioning into an aging society, creating an intergenerational caregiving gap that strains existing support systems. Objective: This study evaluated the effectiveness of “Young Care,” a community-based intervention designed to enhance youth knowledge, attitudes, and caregiving practices (KAP) toward older adults. Methods: A two-day structured training was conducted in Maha Sarakham Province in 2023 using a pre-post mixed-methods design. Middle and high school students participated in lectures, multimedia sessions, and experiential learning activities related to caregiving. Quantitative data were collected using validated KAP questionnaires, while qualitative insights were obtained from focus group discussions involving students, older persons, caregivers, and local leaders. Results: Post-intervention analysis revealed significant improvements in knowledge and attitudes (p < 0.001), accompanied by increased empathy, caregiving initiative, and a sense of moral responsibility among participants. Conclusions: The initiative fostered formal partnerships among schools, local governments, healthcare providers, and universities through memoranda of understanding. These collaborations enabled budgetary support and outreach to out-of-school youth, positioning “Young Care” as a scalable, youth-centered strategy to address Thailand’s long-term care challenges. Full article

The education sector in Tanzania faces significant challenges, especially in public primary schools. Unmanageably large classes and critical teacher–pupil ratios hinder the provision of tailored tutoring, impeding pupils’ educational growth. However, artificial intelligence (AI) could provide a way forward. Advances in generative AI can be leveraged to create interactive and effective intelligent tutoring systems, which have recently been built into embodied systems such as social robots. Motivated by the pivotal influence of teachers’ attitudes on the adoption of educational technologies, this study undertakes a qualitative investigation of Tanzanian primary school mathematics teachers’ perceptions of contextualised intelligent social robots. Thirteen teachers from six schools in both rural and urban settings observed pupils learning with a social robot. They reported their views during qualitative interviews. The results, analysed thematically, reveal a generally positive attitude towards using social robots in schools. While commended for their effective teaching and suitability for one-to-one tutoring, concerns were raised about incorrect and inconsistent feedback, language code-switching, response latency, and the lack of support infrastructure. We suggest actionable steps towards adopting tutoring systems and social robots in schools in Tanzania and similar low-resource countries, paving the way for their adoption to redress teachers’ workloads and improve educational outcomes. Full article

The growing integration of technology in education has heightened awareness of global risks, such as the spread of disinformation. This awareness is vital for fostering the well-being of individuals, especially teenagers, by promoting critical thinking and responsible digital practices. By cultivating these skills, sustainable education empowers individuals to identify potential threats, protect themselves, and advocate for informed, positive change. As part of a European project, this study aims to analyze the current level of awareness among secondary school students (12 to 17) and their teachers. Differences between both are analyzed in how they deal with disinformation in terms of (1) perceptions, (2) feelings and practices, and (3) knowledge and management. A quantitative approach was adopted for this study, which surveyed 1186 minors and 166 teachers. The analysis was based on non-parametric statistics; the Mann–Whitney U statistic was applied as the appropriate measure for comparing independent samples (teachers and students) with a non-normal distribution (p < 0.05). The results were surprising in that they highlighted that minors were more expert than expected in their use of technology and their awareness of the risks of disinformation. These conclusions make it clear that technological tools have the potential to raise awareness of the dangers of disinformation and improve the sustainability of education. Full article

Paraprofessionals play a crucial role in supporting both teachers and students within a classroom, even though the specifics of their duties vary. While their responsibilities involve supporting student achievement, research has shed light that many paraprofessionals feel unprepared for their responsibilities in the classroom. This study aimed to address a gap in the existing literature by exploring how a professional development program that mirrors the trainings special education teachers receive would impact paraprofessionals and help them feel more prepared for their responsibilities in the classroom. Employing a generic qualitative methodology, this study sought to capture the experiences of 43 paraprofessionals. Data collection involved an online open-ended questionnaire at the start and conclusion of the school year. The study’s outcomes revealed five patterns in the data: (a) paraprofessionals struggled with collaborating with classroom teams at the start of the school year, (b) paraprofessionals struggled with managing student behavior at the start of the school year, (c) professional development was helpful to most of the paraprofessionals, (d) professional development led to better preparedness to address challenging behavior, and (e) professional development led to better preparedness to address the instructional needs of students with disabilities. Following a thorough analysis and synthesis, these patterns were condensed into two general themes: the importance of professional development for paraprofessionals and the importance of presenting the professional development that teachers receive on a continuous basis to paraprofessionals as well. These findings are significant for school leaders and educators, as they highlight the importance of providing professional development to paraprofessionals while supporting students with disabilities. Full article

There has been a widely held view for some time that school teachers and principals need to possess a level of knowledge and understanding of the legal regulation of schools and that of their workers. This study explores the level of understanding of legal matters pertaining to the school environment that independent school teachers hold in Queensland. This level of ‘legal literacy’ is investigated in a qualitative research study that explains the various areas of education law that are known and those that are less understood by such educators. Data was analysed using content analysis methodology, using a coding scale that was created specifically for the purposes of coding the participants’ scenario responses. Overall, it was discovered that the level of legal literacy held by Queensland independent school teachers was alarmingly low. This varied across the myriad topics, but essentially, the educators surveyed did not demonstrate an adequate legal understanding to successfully complete their roles. More education in this area should be made available for educators to better equip them with such an understanding to ensure they know when and how to more capably protect themselves and the children entrusted to their care. Full article

Skipjack tuna constitutes a crucial fishery resource in the Western and Central Pacific Ocean (WCPO) purse seine fishery, with high economic value and exploitation potential. It also serves as an essential subject for studying the interaction between fishery resource dynamics and marine ecosystems, as its resource abundance is significantly influenced by marine environmental factors. Skipjack tuna can be categorized into unassociated schools and associated schools, with the latter being predominant. Overfishing of the associated schools can adversely affect population health and the ecological environment. In-depth exploration of the spatial distribution responses of these two fish schools to environmental variables is significant for the rational development and utilization of tuna resources and for enhancing the sustainability of fishery resources. In sparsely sampled and complex marine environments, geographic similarity methods effectively predict tuna resources by quantifying local fishing ground environmental similarities. This study introduces geographical similarity theory. This study focused on 1° × 1° fishery data (2004–2021) released by the Western and Central Pacific Fisheries Commission (WCPFC) combined with relevant marine environmental data. We employed Geographical Convergent Cross Mapping (GCCM) to explore significant environmental factors influencing catch and variations in causal intensity and employed a Geographically Optimal Similarity (GOS) model to predict the spatial distribution of catch for the two types of tuna schools. The research findings indicate that the following: (1) Sea surface temperature (SST), sea surface salinity (SSS), and net primary productivity (NPP) are key factors in GCCM model analysis, significantly influencing the catch of two fish schools. (2) The GOS model exhibits higher prediction accuracy and stability compared to the Generalized Additive Model (GAM) and the Basic Configuration Similarity (BCS) model. R² values reaching 0.656 and 0.649 for the two types of schools, respectively, suggest that the geographical similarity method has certain applicability and application potential in the spatial prediction of fishery resources. (3) Uncertainty analysis revealed more stable predictions for unassociated schools, with 72.65% of the results falling within the low-uncertainty range (0.00–0.25), compared to 52.65% for associated schools. This study, based on geographical similarity theory, elucidates differential spatial responses of distinct schools to environmental factors and provides a novel approach for fishing ground prediction. It also provides a scientific basis for the dynamic assessment and rational exploitation and utilization of skipjack tuna resources in the Pacific Ocean. Full article

This article investigates the revolutionary potential of AI-powered virtual assistants in augmented reality (AR) and virtual reality (VR) environments, concentrating primarily on their impact on special needs schooling. We investigate the complex characteristics of these virtual assistants, the influential elements affecting their development and implementation, and the joint efforts of educational institutions and technology developers, using a rigorous quantitative approach. Our research also looks at strategic initiatives aimed at effectively integrating AI into educational practices, addressing critical issues including infrastructure, teacher preparedness, equitable access, and ethical considerations. Our findings highlight the promise of AI technology, emphasizing the ability of AI-powered virtual assistants to provide individualized, immersive learning experiences adapted to the different needs of students with special needs. Furthermore, we find strong relationships between these virtual assistants’ features and deployment tactics and their subsequent impact on educational achievements. This study contributes to the increasing conversation on harnessing cutting-edge technology to improve educational results for all learners by synthesizing current research and employing a strong methodological framework. Our analysis not only highlights the promise of AI in increasing student engagement and comprehension but also emphasizes the importance of tackling ethical and infrastructure concerns to enable responsible and fair adoption. Full article

Urban areas are responsible for most of Europe’s energy demand and emissions and urgently require building retrofits to meet climate neutrality goals. This study evaluates the energy efficiency potential of three public school buildings in western Macedonia, Greece—a cold-climate region with high heating needs. The buildings, constructed between 1986 and 2003, exhibited poor insulation, outdated electromechanical systems, and inefficient lighting, resulting in high oil consumption and low energy ratings. A robust methodology is applied, combining detailed on-site energy audits, thermophysical diagnostics based on U-value calculations, and a techno-economic assessment utilizing Net Present Value (NPV), Internal Rate of Return (IRR), and SWOT analysis. The study evaluates a series of retrofit measures, including ceiling insulation, high-efficiency lighting replacements, and boiler modernization, against both technical performance criteria and financial viability. Results indicate that ceiling insulation and lighting system upgrades yield positive economic returns, while wall and floor insulation measures remain financially unattractive without external subsidies. The findings are further validated through sensitivity analysis and policy scenario modeling, revealing how targeted investments, especially when supported by public funding schemes, can maximize energy savings and emissions reductions. The study concludes that selective implementation of cost-effective measures, supported by public grants, can achieve energy targets, improve indoor environments, and serve as a replicable model of targeted retrofits across the region, though reliance on external funding and high upfront costs pose challenges. Full article

This article explores Schipper’s scholarly contributions to the study of dongtian fudi (grotto heavens and blessed lands) and specifically situates this project in its broader intellectual context and Schipper’s own research. While Schipper was not the first to open discussions on this topic, his research in this direction still offers profound insights, such as the coinage of the concept of “Daoist Ecology” and his views on mountain politics. This article argues that Schipper’s work on dongtian fudi is a response to the school of Deep Ecology and its critics, and also a result of critical reflection on the modern dichotomy between nature and culture. In Schipper’s enquiry of dongtian fudi, the “mountain” stands as the central concept: it is not only the essential component of Daoist sacred geography, but a holistic site in which nature and society are interwoven, endowed with both material and sacred significance. Through his analysis of the Daoist practice of abstinence from grain (duangu), Schipper reveals how mountains serve as spaces for retreat from agrarian society and state control, and how they embody “shatter zones” where the reach of centralized power is relatively attenuated. The article also further links Schipper’s project of Beijing as a Holy City to his study of dongtian fudi. For Schipper, the former affirms the universality of the locality (i.e., the unofficial China, the country of people), while the latter envisages the vision of rewriting China from plural localities. Taken together, these efforts point toward a theoretical framework that moves beyond conventional sociological paradigms, one that embraces a total worldly perspective, in which the livelihoods of local societies and their daily lives are truly appreciated as a totality that encompasses both nature and culture. Schipper’s works related to dongtian fudi, though they are rather concise, still significantly broaden the scope of Daoist studies and, moreover, provide novel insights into the complexity of Chinese religion and society. Full article

In alignment with global educational trends, Australia has adopted a pluralistic approach to initial teacher education (ITE), encompassing traditional university-based programs, employment-integrated models and vocational training routes. This diversification of pathways has emerged as a strategic response to persistent workforce challenges, including chronic shortages, uneven distribution of qualified educators, and limited demographic diversity within the profession. Rather than supplanting conventional ITE models, these alternative pathways serve as complementary options, broadening access and enhancing system responsiveness to evolving societal and educational needs. The rise in non-traditional routes represents a deliberate response to the well-documented global teacher shortage, frequently examined in comparative educational research. Central to their design is a restructuring of traditional program elements, particularly duration and delivery methods, to facilitate more flexible and context-sensitive forms of teacher preparation. Such approaches often create opportunities for individuals who may be excluded from conventional pathways due to socioeconomic constraints, geographic isolation, or non-linear career trajectories. Significantly, the diversity introduced by alternative entry candidates has the potential to enrich school learning environments. These educators often bring a wide range of prior experiences, disciplinary knowledge, and cultural perspectives, contributing to more inclusive and representative teaching practices. The implications for student learning are substantial, particularly in disadvantaged communities where culturally and professionally diverse teachers may enhance engagement and academic outcomes. From a policy perspective, the development of flexible, multifaceted teacher education pathways constitutes a critical component of a sustainable workforce strategy. As demand for qualified teachers intensifies, especially in STEM disciplines and in rural, regional and remote areas, the role of alternative pathways is likely to become increasingly pivotal in achieving broader goals of equity, quality and innovation in teacher preparation. Full article

This research investigates topic-based sentiment classification in Greek educational-related data using transformer-based language models. A comparative evaluation is conducted on GreekBERT, XLM-r-Greek, mBERT, and Palobert using three original sentiment-annotated datasets representing parents of students with functional diversity, school directors, and teachers, each capturing diverse educational perspectives. The analysis examines both overall sentiment performance and topic-specific evaluations across four thematic classes: (i) Material and Technical Conditions, (ii) Educational Dimension, (iii) Psychological/Emotional Dimension, and (iv) Learning Difficulties and Emergency Remote Teaching. Results indicate that GreekBERT consistently outperforms other models, achieving the highest overall F1 score (0.91), particularly excelling in negative sentiment detection (F1 = 0.95) and showing robust performance for positive sentiment classification. The Psychological/Emotional Dimension emerged as the most reliably classified category, with GreekBERT and mBERT demonstrating notably high accuracy and F1 scores. Conversely, Learning Difficulties and Emergency Remote Teaching presented significant classification challenges, especially for Palobert. This study contributes significantly to the field of sentiment analysis with Greek-language data by introducing original annotated datasets, pioneering the application of topic-based sentiment analysis within the Greek educational context, and offering a comparative evaluation of transformer models. Additionally, it highlights the superior performance of Greek-pretrained models in capturing emotional detail, and provides empirical evidence of the negative emotional responses toward Emergency Remote Teaching. Full article

The evaluation of open-ended questions is typically performed by human instructors using predefined criteria to uphold academic standards. However, manual grading presents challenges, including high costs, rater fatigue, and potential bias, prompting interest in automated essay scoring systems. While automated essay scoring tools can assess content, coherence, and grammar, discrepancies between human and automated scoring have raised concerns about their reliability as standalone evaluators. Large language models like ChatGPT offer new possibilities, but their consistency and fairness in feedback remain underexplored. This study investigates whether ChatGPT can provide stable and fair essay scoring—specifically, whether identical student responses receive consistent evaluations across multiple AI interactions using the same criteria. The study was conducted in two marketing courses at an engineering school in Chile, involving 40 students. Results showed that ChatGPT, when unprompted or using minimal guidance, produced volatile grades and shifting criteria. Incorporating the instructor’s rubric reduced this variability but did not eliminate it. Only after providing an example-rich rubric, a standardized output format, low temperature settings, and a normalization process based on decision tables did ChatGPT-4o demonstrate consistent and fair grading. Based on these findings, we developed a scalable algorithm that automatically generates effective grading rubrics and decision tables with minimal human input. The added value of this work lies in the development of a scalable algorithm capable of automatically generating normalized rubrics and decision tables for new questions, thereby extending the accessibility and reliability of automated assessment. Full article

At the Michael G. DeGroote School of Medicine, a significant component of the MD curriculum involves written narrative reflections on topics related to professional identity in medicine, with written feedback provided by their in-person longitudinal facilitators (LFs). However, it remains to be understood how generative artificial intelligence chatbots, such as ChatGPT (GPT-4), augment the feedback process and how MD students perceive feedback provided by ChatGPT versus the feedback provided by their LFs. In this study, 15 MD students provided their written narrative reflections along with the feedback they received from their LFs. Their reflections were input into ChatGPT (GPT-4) to generate instantaneous personalized feedback. MD students rated both modalities of feedback using a Likert-scale survey, in addition to providing open-ended textual responses. Quantitative analysis involved mean comparisons and t-tests, while qualitative responses were coded for themes and representational quotations. The results showed that while the LF-provided feedback was rated slightly higher in six out of eight survey items, these differences were not statistically significant. In contrast, ChatGPT scored significantly higher in helping to identify strengths and areas for improvement, as well as in providing actionable steps for improvement. Criticisms of ChatGPT included a discernible “AI tone” and paraphrasing or misuse of quotations from the reflections. In addition, MD students valued LF feedback for being more personal and reflective of the real, in-person relationships formed with LFs. Overall, findings suggest that although skepticism regarding ChatGPT’s feedback exists amongst MD students, it represents a viable avenue for deepening reflective practice and easing some of the burden on LFs. Full article