Search Results (4,271)

Emerging technologies (ETs), such as AI and reality techniques, are reshaping educational measurement. However, existing studies remain dispersed and are rarely synthesized in ways that clarify how ETs participate in the evidentiary work of educational measurement. Guided by PRISMA 2020, we systematically reviewed 933 empirical studies published between 2016 and 2025 in formal educational settings. We coded studies by (a) grain size (micro, meso, macro), (b) Constructing Measures Theory building blocks (construct map, item design, outcome space, measurement model), and (c) ET category. Results showed a strong concentration at the micro level (88.88%) and in outcome space and measurement model work (86.80% combined), indicating that ET-enabled innovation has focused primarily on transforming performances into indicators and modeling those indicators for interpretation and decision-making. Learning analytics and educational data mining, machine learning and deep learning, and automated scoring and feedback systems were the dominant ET clusters. These findings point to an uneven development of ET-enabled educational measurement. Included studies also indicating recurring concerns about transparency, fairness, and governance are linked to the field’s main areas of ET-enabled concentration. We therefore argue for closer alignment among construct claims, evidence, modeling, and intended use, and offer implications for developers, researchers, and education practitioners. Full article

This study proposes and analyzes an integrated framework for monitoring potable water quality and laboratory effluent management in universities, with emphasis on its practical application in a Brazilian public institution. Adopting a qualitative and documentary approach, the research was based on high-impact scientific publications, institutional reports, and environmental databases. The results demonstrate that effective water and effluent governance depends on the interaction of three core dimensions: regulatory compliance, technological innovation, and institutional governance. These elements operate synergistically to ensure transparency, risk prevention, and environmental accountability. The proposed University Laboratory Water Monitoring Framework (UL-WMF) illustrates how universities can transform water control into a managerial and educational tool aligned with sustainability goals. The illustrative institutional application revealed potential for integrating Internet of Things (IoT) and Laboratory Information Management System (LIMS) technologies into environmental management routines, reinforcing universities’ strategic role in achieving global sustainability objectives. Despite relying on secondary data, this study provides a scalable foundation for decision support systems and future empirical validation. The novelty of the University Laboratory Water Management Framework (UL-WMF) lies in its integration of potable water monitoring and laboratory effluent governance into a single operational framework, addressing a gap in the existing literature and offering a model specifically tailored to the context of universities in developing countries. The applied component of the study consists of an illustrative institutional case constructed exclusively from publicly available environmental and governance reports. This illustration serves to demonstrate the operational relevance of the proposed framework, without implying field measurements or primary data collection. Full article

The research aimed to create a hybrid model for assessing the carbon footprint of pilots’ education at a flight school, taking into account the level of implementation of green infrastructure by the educational institution, while excluding indirect emissions from the model. The study implemented an approach that combines fuzzy set theory with expert evaluation methods, utilizing membership functions and convolution mechanisms to incorporate subjective expert assessments into formalized numerical measures. The research was focused on two research questions: Does the proposed hybrid model allow for a practical assessment of a pilot’s carbon footprint during his training? Does the hybrid model provide the ability to automatically determine the level of carbon footprint of an aviation educational institution and generate substantiated recommendations for the strategic management of sustainable development of the educational process? The resulting model enables a quantitative assessment of individual CO₂ emissions during pilot training and provides collective insights into the overall carbon footprint, accounting for the green infrastructure’s level of implementation. The hybrid model was tested and validated using real data from the Technical University of Košice (Slovakia) within the “PILOT” study program (2022–2025). The experimental calculations are based on the Viper SD4, a homogeneous aircraft type. The model is designed to account for multiple aircraft types through weighted aggregation, a feature that can be used in future institutional implementations. These recommendations are practical for managers and specialists at aviation educational institutions, environmental analysts, curriculum developers, and policymakers focused on sustainable development. At the current stage, the model primarily captures direct training-related and institution-level operational emissions, while indirect emissions were included only to a limited extent because of insufficiently available and non-systematically recorded data. Therefore, the proposed framework should be interpreted as an operational decision-support model rather than a full greenhouse gas inventory covering all indirect emission sources. Full article

Despite the growing use of tessellated and patterned façades in contemporary architecture, their thermal performance, particularly in cooling-dominated educational buildings, remains insufficiently quantified, with existing studies largely prioritizing daylighting or aesthetic outcomes over energy-driven thermal behavior. This study aims to systematically evaluate how different tessellated façade geometries and perforation ratios influence thermal performance and cooling demand in a Mediterranean climate, and to identify an optimal façade configuration that balances multiple thermal objectives. Three tessellation typologies—nature-inspired (Voronoi), Islamic geometric, and folded origami-based patterns—were parametrically generated and applied as external shading screens to an educational building. Annual thermal simulations were conducted using Climate Studio to assess four performance metrics: solar heat gain, energy use intensity, hours of overheating derived from operative temperature, and peak cooling demand. A post-simulation, data-driven, multi-objective, decision-support approach was applied using Compromise Programming to systematically evaluate and rank discrete façade alternatives based on multiple thermal performance criteria. Results indicate that all tessellated façades reduce solar heat gain and peak cooling demand relative to the unshaded baseline, with performance strongly dependent on both geometry and perforation ratio. Lower perforation ratios (20%) consistently outperform more open configurations, while Voronoi-based façades achieve the most balanced overall thermal performance across all evaluated criteria and emerging as the top-ranked solution. The study’s novelty lies in its comparative, cooling-focused evaluation of fundamentally different tessellation logics using transparent, decision-oriented optimization rather than subjective comfort indices or computationally intensive evolutionary algorithms. Beyond its specific findings, the research provides a transferable methodological framework for integrating geometry-informed façade design into early-stage decision-making, supporting climate-responsive and energy-efficient educational architecture in Mediterranean and similar climates. Full article

Background/Objective: In Spain, 99% of births occur in hospital settings, and planned home birth is neither funded nor regulated by the Public Health System. Despite growing interest in this birth option, qualitative evidence exploring the experiences of women who opt for a planned home birth after a previous hospital birth remains scarce, particularly in contexts where this practice is not integrated into the healthcare system. This study aimed to explore the perceptions and experiences of Spanish women who opted for a planned home birth following a previous hospital birth, focusing on the reasons that motivated this decision and the care received during the process. Methods: A qualitative descriptive design was employed. Semi-structured interviews were conducted between July and December 2025 with 19 women who had experienced a planned home birth in Spain after a previous hospital birth. Data were analysed using inductive thematic analysis following Braun and Clarke’s approach. The study adhered to the Standards for Reporting Qualitative Research (SRQR). Results: Three main themes emerged: (1) motives related to choosing a planned home birth, including negative hospital experiences characterised by loss of autonomy, medicalisation of birth without consent, and fragmented care; (2) seeking a physiological and humanised birth, reflecting women’s desire for empowerment, control, and a transformative experience, alongside barriers such as lack of professional support and financial burden; and (3) the need to increase visibility and establish regulation, highlighting demands for professional training, dissemination strategies, and integration of planned home birth into the Public Health System to ensure equitable access. Conclusions: Women who opted for a planned home birth after a hospital experience reported highly positive and empowering outcomes. However, the absence of regulation, professional support, and public funding creates significant inequalities. Integrating planned home birth into the Public Health System, educating healthcare professionals, and developing strategies to increase the visibility of planned home births are essential to guarantee women’s right to choose where they give birth. Full article

Artificial intelligence (AI) systems and tools are increasingly reshaping educational practices. This study examines perspectives shared in student-focused online communities on AI’s impact on education, comparing those of computer science (CS) and business students through an analysis of Reddit posts. Using natural language processing (NLP), sentiment analysis, and Latent Dirichlet Allocation (LDA) topic modeling, we analyzed 1108 posts collected from six subreddits. Results reveal distinct thematic focuses: CS students emphasize technical aspects, including programming efficiency, coding assistance, and concerns about job displacement, while business students focus on decision-making enhancement, financial analysis applications, and operational efficiency. Sentiment analysis indicates that the Business/Finance-oriented corpus is slightly more positive than the CS-oriented corpus (51.9% vs. 50.1% positive). The CS-oriented corpus also contains a higher proportion of negative posts (36.0% vs. 33.2%). These differences reflect discipline-specific epistemological frameworks shaping AI perception. The findings provide educators with guidelines for developing tailored AI integration strategies that address discipline-specific concerns and opportunities. This study contributes to understanding how academic background influences perceptions of AI in education, offering insights for curriculum design and policy development. Full article

The return to in-person classes after the COVID-19 pandemic revealed an increase in physical violence among students of secondary school. This article examines the role of the school as a setting that enables students to learn how to coexist with others. Based on an educational qualitative research study conducted in two state-run schools in the Metropolitan Area of Buenos Aires, located in urban poverty contexts, it investigates the effects of COVID-19-induced isolation on school coexistence. The fieldwork involved participant observation, interviews, and analysis of student productions during school workshops. Students and teachers were selected through purposive sampling. The working hypothesis posits that learning to coexist involves not only dealing with conflicting situations but also the need to verbalize them, a practice that schools actively foster. The findings show that, by providing a place where time and space are shared, the school acts as a key mediator, where students’ physical and verbal interactions become essential to reconfiguring relationships among classmates. The study concludes that the school plays a decisive role in transforming conflict into voiced experience, replacing physical aggression with meaningful narratives. Full article

This research-to-practice study presents a design-oriented framework that integrates challenge-based learning (CBL), experiential learning (EL), and authentic assessment (AA) to support competency development in higher education. The framework aligns the stages of CBL (i.e., engagement, investigation, and solution) with Kolb’s experiential learning cycle and core AA principles, including realism, cognitive challenge, and evaluative judgement. Learning activities are structured around real-world challenges that reflect professional practice, enabling a coherent progression from experience to reflection, conceptualisation, and evaluation, and supporting the systematic development and assessment of student competencies. A single case study illustrates the application of the framework in industrial engineering education, implemented across six interdisciplinary modules at a private university in Mexico. Students engaged in process improvement projects within six small and medium-sized enterprises, fostering problem solving, decision making, and evaluative judgement in authentic contexts. The findings indicate that the framework supports the development of problem-solving and communication competencies, demonstrating its design coherence and practical feasibility. The framework provides structured guidance for educators to align learning objectives, activities, and assessments within CBL environments. However, limitations related to pedagogical integration and the single-case design constrain the generalisability of the findings. Future research should explore cross-disciplinary applications, longitudinal competency development, and adaptation to emerging educational contexts. Full article

Objectives: The transition from in-person to online formats for clinical case discussions has transformed the way medical professionals collaborate and share knowledge. The current pilot study investigates the potential impact of this shift by comparing the experiences of specialists and residents who had practiced both online and in-person pituitary tumor boards compared to the experiences of those who only experienced the online format. Methods: A cohort of 15 participants, including 10 specialists and 5 residents, provided insights through structured surveys and free-text responses. Results: The results indicate differences in the perception of the duration and participation dynamics in online pituitary tumor boards between both groups, with online boards facilitating the discussion of more cases. Overall participant engagement was mostly perceived as the same; a subset reported reduced perceived engagement, particularly among senior professionals. Conclusions: These findings highlight how prior experience can affect the perceived effectiveness, level of engagement and duration of online formats, providing valuable hypothesis-generating input for optimizing future medical board meetings. Full article

Secure coding is essential, yet the strategies developers use to detect and mitigate flaws are not well understood. We present an eye-tracking-based approach that captures developers’ visual patterns while reading, coding, and applying security tools. Our framework uses participant-editable stimuli and dynamic environments to reflect authentic coding development. By visualizing gaze transitions and attention shifts, we expose how developers allocate effort during secure coding. By leveraging techniques that reveal gaze transitions, attention levels, and pupil size changes, we are able to gain insight into their behavior. Our study provides a fine-grained, process-oriented account of behavior in CWE-based secure coding educational tasks, uncovering attentional patterns and decision timelines that traditional methods may not capture. These contributions provide a foundation for improving training and understanding developer differences. Full article

Disinformation, amplified by digital platforms and algorithmic distribution systems, represents a growing challenge for media trust, public health communication, and societal stability. This narrative literature review examines disinformation through an integrative psychosocial perspective, focusing on how patterns of exposure interact with individual vulnerability factors—including education, political beliefs, social identity, personality traits, and emotional responses to uncertainty—to influence the processing and acceptance of misleading information. The review synthesises interdisciplinary evidence on how algorithmic amplification and emotionally salient content increase susceptibility to disinformation and shape risk perception, health-related decision-making, and preventive behaviours. Findings indicate that repeated exposure to false or misleading information reinforces perceived credibility through familiarity effects, contributes to declining trust in institutional sources, and intensifies social and political polarisation. Disinformation is therefore conceptualised not only as an informational problem but also as a psychosocial process affecting emotional regulation, cognitive evaluation, and collective responses to crises, particularly in public health contexts. The analysis further highlights a recursive feedback loop in which reduced media trust increases vulnerability to subsequent disinformation, with broader implications for democratic participation and social cohesion. Mitigation strategies discussed include media literacy initiatives, critical thinking education, platform governance, regulatory approaches, and interventions targeting psychosocial drivers of susceptibility. Full article

Background/Objectives: Echocardiography reports are essential diagnostic tools, but their complexity and specialized English terminology frequently hinder comprehension for non-specialists and patients. This study addresses these accessibility gaps by developing a resource-efficient large language model (LLM) system designed to translate and summarize English echocardiography results into Traditional Chinese. Methods: To overcome significant hardware constraints, we utilized Quantized Low-Rank Adapter (QLoRA) techniques and the Unsloth acceleration framework to fine-tune LLaMA-3.2-1B and LLaMA-3.2-3B-Instruct models on a single mid-tier GPU. The system employs a dual-stage inference architecture: the first stage provides technical medical translation for clinicians, while the second stage generates simplified, patient-centric educational summaries to enhance health literacy. Results: Evaluation across multiple metrics, including BLEU, ROUGE, METEOR, and Perplexity, demonstrated that the LLaMA-3.2-3B-Instruct model with the AdamW 8-bit optimizer achieved the most stable validation performance, excelling in semantic coherence and structural consistency. A preliminary qualitative error analysis conducted in the Discussion section further identified clinical nuances, such as terminology simplification and minor hallucinations, underscoring the critical necessity of a Human-in-the-Loop verification procedure. Conclusions: These findings validate the feasibility of deploying cutting-edge medical AI in resource-limited clinical environments. While the results reflect validation-only performance on a specialized dataset, the platform offers a scalable foundation for enhancing clinical decision support and health literacy through accessible, automated medical text processing. Full article

Major depressive disorder (MDD) affects over 330 million people globally, yet up to 30% of patients fail initial pharmacotherapy due to genetic variability in drug metabolism. This narrative review synthesizes evidence on pharmacogenomic (PGx) guided approaches for MDD, emphasizing their integration with POC diagnostics and engineering solutions. Approximately 40–50% of patients carry actionable variants in CYP2C19 or CYP2D6, which govern the metabolism of selective serotonin reuptake inhibitors. Landmark trials (GUIDED, PRIME Care, GAPP-MDD) and meta-analyses demonstrate that PGx-informed prescribing modestly but significantly improves remission and response rates, particularly in treatment-resistant depression. Established guidelines from CPIC and the Dutch Pharmacogenetics Working Group provide actionable recommendations for CYP2D6 and CYP2C19 phenotypes. Emerging POC platforms, including Genomadix Cube and Genedrive, now deliver CYP2C19 results within one hour, supporting rapid clinical decisions. However, psychiatric-specific implementation data remain limited compared to cardiology; current POC devices lack multi-gene capabilities, and most studies underrepresent diverse populations. Persistent barriers include variable reimbursement, limited clinician education, and fragmented electronic health record integration. Future directions include pre-emptive genotyping, expanded multi-gene panels, and embedded clinical decision support. With continued engineering innovation and rigorous validation, PGx-guided care holds promise for reducing the trial-and-error burden and advancing precision psychiatry. Full article

Aging is a complex physiological process influenced by various factors, including individuals’ mental attitude. This interaction between biological vulnerability and psychological resources characterizes the entire life course; however, in older age, it becomes particularly salient due to the higher prevalence of multimorbidity, frailty, functional decline, and existential transitions (e.g., retirement, bereavement, loss of social roles), which intensify the impact of mental outlook on adaptation and quality of survival. Optimism has gained growing attention in clinical practice as a psychological asset associated with better health. This has also encouraged the incorporation of optimism-enhancing strategies into geriatric care. However, encouraging optimism in older patients, although well intentioned, can create ethical tensions in clinical communication, decision-making, and care planning. Sensitivity should be paid to aspects such as education, cultural background and religion within interactions with older adult patients. Uncritical promotion of optimism can undermine autonomy, foster unrealistic expectations, or place emotional burdens on patients who may already feel vulnerable. The appeal of optimism should therefore be balanced with careful ethical consideration. Full article

Objective: Influenza and pertussis vaccines are recommended during pregnancy; however, uptake remains insufficient in many European countries, increasing the risk of preventable infections. Recent recommendations for maternal respiratory syncytial virus vaccination have been endorsed by scientific societies. This study evaluated maternal vaccination coverage, knowledge, attitudes, and factors influencing vaccine uptake among Lithuanian women. Methods: A retrospective cross-sectional online survey was conducted between 4 and 14 November 2025 in Lithuania among women aged 18–55 years with at least one previous pregnancy. The questionnaire contained 29 questions on sociodemographic characteristics, obstetric history, vaccination history, attitudes, and informational sources influencing decisions. Internal reliability was confirmed (Cronbach’s α = 0.83). Descriptive statistics were used to summarize the data. Associations between categorical variables were assessed using the Chi-square test or exact tests (Fisher’s exact or Fisher–Freeman–Halton). Binary and multivariable logistic regression analyses were performed to evaluate factors associated with self-reported vaccination uptake and the relationship between influenza and pertussis vaccination. Odds ratios with 95% confidence intervals were calculated. Statistical significance was set at p < 0.05. Results: A total of 241 women participated. Self-reported vaccination coverage during pregnancy was 28.7% for influenza, 43.8% for tetanus–diphtheria–pertussis, and 4.2% for respiratory syncytial virus. Physician’s recommendation was the strongest predictor: women advised to vaccinate were 17.0 times more likely to receive influenza, 16.5 times more likely to receive pertussis, while RSV vaccination occurred almost exclusively among women who reported receiving a physician’s recommendation. Higher uptake was associated with younger maternal age and university education. Reasons for declining vaccination were avoidance of medical interventions and concerns about safety or side effects. Conclusions: Maternal vaccination coverage in Lithuania remains low despite public funding and national recommendations. Strengthening provider communication, improving information strategies, and integrating vaccination counseling into routine antenatal care may increase uptake and enhance maternal and neonatal protection. Full article