Search Results (274)

The integration of Educational Robotics (ER) into teaching and learning has increased in recent years. While several studies have described the design and use of simulators, no content analysis has systematically documented the features and contribution of simulators in ER. Therefore, a systematic review of eight databases was conducted. From 1200 retrieved articles, 89 met the inclusion criteria. The emerged articles comprised two distinct categories: (a) simulator framework studies—describing tools or platforms (54 articles)—and (b) simulator-based intervention studies—reporting empirical implementations (35 articles). Each article was analyzed by two independent researchers who recorded the design features of simulators, their domain of use, the educational level at which the implementation occurred, intervention characteristics, teacher involvement in the studies, and the skills they tried to promote. Findings showed that simulators were primarily designed for STEM education. Most operated in coding environments, used 3D visualization, and were freely available. Interventions were more frequent at the tertiary level, with fewer at primary and secondary levels. Many empirical studies that used simulators employed small samples in short durations, limiting the generalizability of the findings. Simulator-based practices were mainly linked to programming, problem solving, and computational thinking. Higher-order competences such as collaboration or metacognition were rarely addressed. Finally, most intervention studies reported either no or only moderate teacher involvement. This article aims to be a basis for researchers who study ER implementation and simultaneously serve as a basis for choosing, designing, and adopting ER simulators as teaching tools. Full article

This study examines the effectiveness of the University–Government–Kindergarten Collaboration (UGK) model in training early childhood teacher candidates (TCs), using the Education for Sustainable Development (ESD) framework to assess its role in enhancing TCs’ competencies. Data were collected through a survey of 210 TCs and in-depth interviews with 12 participants. The findings indicate a structural imbalance in UGK: while university–kindergarten collaboration shows some effectiveness, the lack of governmental leadership weakens tripartite synergy. From an ESD perspective, although UGK fosters basic collaborative skills, it does not systematically develop higher-order ESD competencies such as systems thinking, normative awareness, critical thinking, and strategic action. By shifting the focus from institutional to student experience, this study offers a new analytical framework for teacher education models. It concludes that optimizing UGK requires stronger governmental coordination, deeper university–kindergarten cooperation, and explicit integration of ESD core competencies throughout the training system. Full article

Preschool teaching is a highly demanding profession that requires constant socio-emotional attunement and the ability to engage in reflective reasoning. Despite the central role of these skills in effective early childhood education, little is known about whether preschool teachers’ socio-affective and cognitive capacities vary as a function of accumulated professional experience. To address this knowledge gap, we compared the performance of 30 professional preschool teachers with a matched control group of 30 non-teachers on tests measuring emotion recognition, active-empathic listening, interpersonal reactivity, and abstract reasoning. We found that preschool teachers were significantly better on all dimensions of active-empathic listening (sensing, processing, and responding) and better in emotional self-regulation than controls. Moreover, years of preschool teaching experience were positively correlated with emotion recognition, improved listening skills, and more deliberate abstract reasoning strategies. Notably, socio-affective competencies were correlated with abstract reasoning performance within the preschool teacher group. According to these results, long-term professional involvement in preschool teaching enhances socio-affective skills and integrates them with higher-order cognitive processes, both of which are essential for responsive teaching, efficient classroom management, and the development of children’s social and cognitive abilities. Full article

Background/Objectives: The transition to higher education is a critical phase of human development that makes adolescents and young adults particularly vulnerable to mental health problems, such as depression, anxiety, and stress. This study aimed to evaluate the psychometric properties of the Portuguese version of the Depression, Anxiety and Stress Scale-21 Items (DASS-21) among first-year undergraduate nursing students. Methods: A methodological study was conducted with 225 undergraduate nursing students, aged 17 to 18 years, from a higher education institution in central Portugal. Data were collected using the Google Forms platform. Confirmatory factor analysis was conducted to test three competing models: a single-factor model, a three-factor correlated model, and a second-order factor model. Reliability was assessed using composite reliability, and validity was evaluated using average variance extracted and the Fornell–Larcker criterion for discriminant validity. Results: Factor analyses revealed that the three-factor correlated model fit the data best overall, showing superior fit indices compared to the competing models (χ²/df = 2.37; CFI = 0.90; and RMSEA = 0.08; TLI = 0.88 and SRMR = 0.04). Composite reliability was high across all tested models, ranging from 0.84 to 0.94. The analysis of score distributions by category revealed a high prevalence of severe or extremely severe symptoms of anxiety, stress, and, to a lesser extent, depression. A statistically significant association was found between higher symptom severity and prior familiarity with mental illness. Conclusions: The DASS-21 proved to be a valid and reliable instrument for assessing psychological distress in higher education students. These findings underscore the urgent need for mental health programs in higher education institutions that focus on early detection and intervention, particularly for students initiating their studies and those with a history of mental health problems. Full article

This study specifies and validates a three-layer Structural Equation Model (SEM) that accounts for how tourists’ evaluations of destination attributes translate into loyalty; the model is based on UN Tourism’s sustainability pillars. Guided by service-science and Customer Experience (CX) logics, and adopting a Tourist Experience (TX) framework that treats Tourist Experience as a domain-specific case of CX, we define five first-order antecedents—Emotions (EMS), Local Culture (CTL), Authenticity (AUT), Entertainment (ENT), and Servicescape (SVS)—that load onto a higher-order appraisal, Global Perception (GEN), which in turn drives Destination Loyalty (LOY). Using ordinal indicators and a robust diagonally weighted least squares estimator (WLSMV), the model exhibits a good global fit (CFI/TLI = 0.970/0.968; SRMR = 0.049; RMSEA = 0.073 [90% CI = 0.070–0.076]). Standardized effects indicate that GEN is primarily explained by Emotions (β = 0.445, p < 0.001), Authenticity (β = 0.271, p < 0.001), and Servicescape (β = 0.241, p < 0.001), whereas CTL and ENT are not significant when competing with these other predictors. GEN strongly predicts LOY (β = 0.967, p < 0.001), mediating sizable indirect effects from EMS, AUT, and SVS to LOY. The findings corroborate a parsimonious mediational chain in which affective, meaning-related, and infrastructural inputs cohere into a single global appraisal that is proximal to loyalty. Our study provides a decision-focused blueprint for designing emotion-rich, authenticity-protecting, and well-orchestrated servicescapes to enhance GEN and, consequently, LOY; it adheres to established SEM reporting standards and articulates a holistic transactional conceptualization grounded in recent tourism literature. Improvements in GEN reflect not only better experiences but also designs consistent with long-run destination sustainability. Full article

Rapid adoption of digital surveying technologies in construction has highlighted the need for engineering education to equip students with technological competency as well as higher-order problem-solving skills. This experiment explores undergraduate students’ acceptance of emerging surveying technologies and their perceived learning results within a constructivist framework of experiential learning. Thirty-six students in a required construction surveying class interacted with traditional and advanced technologies such as total stations, terrestrial laser scanning, drones, and mobile LiDAR through structured, semi-structured, and unstructured lab activities. Data were gathered based on two post-course surveys: a technology acceptance survey grounded in Unified Theory of Acceptance and Use of Technology (UTAUT) and a self-perceived cognitive learning outcome survey through Bloom’s Taxonomy. Qualitative analysis along with quantitative analysis indicated a gap between technology acceptance and perceived learning gains. Laser scanner had the greatest acceptance scores followed by other advanced tools. Total station (widespread in hands-on lab activities) was perceived to have been most influential in terms of enhancing learning. Lower-order skills were strengthened in structured labs, while higher-order thinking emerged more unevenly in open-ended labs. These findings underscore that the mode of student engagement with technology matters more for learning than the sophistication of the tools themselves. By embedding UTAUT and Bloom’s Taxonomy in an authentic learning environment, this experiment provides engineering educators a mechanism to assess technology-enhanced learning and identifies strategies to facilitate higher-order skills aligned with industry needs. Full article

Understanding the causal relationships between safety factors is essential for successful intervention in industries with intrinsically high-risk environments such as the construction industry. Therefore, the aim of this study is to employ the Interpretive Structural Modeling (ISM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) techniques to analyze and map the interdependencies among various safety-related elements affecting construction safety. According to the results, resource allocation was shown to be the highest-level, most independent element in the analysis, highlighting its function as the primary facilitator of safety initiatives. This strategic commitment directly drives Management Commitment and Competence, which form the core organizational support structure. Mid-level elements that translate management intent into site-level practice include workers’ training, safety motivation, and communication structure. The frequency of safety observations, workers’ involvement in safety decisions, and subcontractor and procurement management—the immediate procedural controls—are then used to assess operational efficacy. Crucially, the most dependent factor was found to be Workers’ Compliance, indicating that frontline safety behavior is the result of efficient management at all higher levels. Therefore, in order to improve overall safety performance in construction, this research emphasizes the importance of improving resource provision and leadership commitment. The outputs of the current study provide an organized, evidence-based roadmap for selecting interventions. Full article

This study evaluated the accuracy and educational potential of three generative AI models, ChatGPT 3.5, ChatGPT 4o, and Gemini 2.5, by addressing pharmacy-related content across three key areas: biostatistics, pharmaceutical calculations, and therapeutics. A total of 120 exam-style questions, categorized by Bloom’s Taxonomy levels (Remember, Understand, Apply, and Analyze), were administered to each model. Overall, the AI models achieved a combined accuracy rate of 77.5%, with ChatGPT 4o consistently outperforming ChatGPT 3.5 and Gemini 2.5. The highest accuracy was observed in therapeutics (83.3%), followed by biostatistics (81.7%) and calculations (67.5%). Performance was strongest at lower Bloom levels, reflecting proficiency in recall and conceptual understanding, but declined at higher levels requiring analytical reasoning. These findings suggest that generative AI tools can serve as effective supplementary aids for pharmacy education, particularly for conceptual learning and review. However, their limitations in quantitative and higher-order reasoning highlight the need for guided use and faculty oversight. Future research should expand to additional subject areas and assess longitudinal learning outcomes to better understand AI’s role in improving critical thinking and professional competence among pharmacy students. Full article

STEM (Science, Technology, Engineering, and Mathematics) is essential for the development of 21st-century skills, particularly in a world driven by technological innovation. However, in vulnerable school contexts, access to meaningful STEM experiences remains limited. This study addresses this issue through the design and implementation of a didactic strategy in a public high school in Bogotá, Colombia, based on two educational resources: the BioSen electronic board, which is compatible with Arduino technology and designed to acquire physiological signals such as electrocardiography (ECG), electromyography (EMG), electrooculography (EOG), and body temperature; and the Space Exploration instructional guide, which is organized around contextualized learning missions. This study employed a quasi-experimental mixed-methods design that combined pre–post perception questionnaires, unstructured classroom observations, and a contextualized knowledge test administered to three student groups. Findings demonstrate that after eight weeks of implementation with upper secondary students, the strategy had a positive impact on the development of 21st-century skills, such as creativity, computational thinking, and critical thinking. These skills were assessed through a mixed quasi-experimental design combining perception questionnaires, qualitative observations, and knowledge evaluations. Unlike the control groups, students who participated in the intervention adjusted their self-perceptions when facing real-world challenges and showed progress in the application of key competencies. Overall, the results support the effectiveness of integrating low-cost biomedical tools with gamified STEM instruction to enhance higher-order thinking skills and student engagement in vulnerable educational contexts. Full article

We propose Federated Entropic High-Order Descent (FedEHD), a drop-in client optimizer that augments local SGD with (i) an entropy (sign) term and (ii) quadratic and cubic gradient components for drift control and implicit clipping. Across non-IID CIFAR-10 and CIFAR-100 benchmarks (100 clients, 10% sampled per round), FedEHD achieves faster and higher convergence than strong baselines including FedAvg, FedProx, SCAFFOLD, FedDyn, MOON, and FedAdam. On CIFAR-10, it reaches 70% accuracy in approximately 80 rounds (versus 100 for MOON and 130 for SCAFFOLD) and attains a final accuracy of 72.5%. On CIFAR-100, FedEHD surpasses 60% accuracy by about 150 rounds (compared with 250 for MOON and 300 for SCAFFOLD) and achieves a final accuracy of 68.0%. In an environmental monitoring case study involving four distributed air-quality stations, FedEHD yields the highest macro AUC/F1 and improved calibration (ECE 0.183 versus 0.186–0.210 for competing federated methods) without additional communication and with only $\mathcal{O}(d)$ local overhead. The method further provides scale-invariant coefficients with optional automatic adaptation, theoretical guarantees for surrogate descent and drift reduction, and convergence curves that illustrate smooth and stable learning dynamics. Full article

We investigate the stability of higher-order skyrmion crystals with large topological charges in the presence of crystal-dependent magnetic anisotropies. Focusing on the competition between two types of bond-dependent anisotropy allowed by $D_{3\mathrm{d}}$ crystalline symmetry on a two-dimensional triangular lattice, we systematically construct a low-temperature magnetic phase diagram using simulated annealing. Our analysis reveals that the stability of the higher-order skyrmion crystal with skyrmion number of two is strongly controlled by the relative sign of the bond-dependent anisotropy to the $D_{3\mathrm{d}}$-type anisotropy: a positive anisotropy, which favors spin oscillations perpendicular to the ordering wave vector, enhances its stability, whereas a negative anisotropy, favoring oscillations parallel to the ordering wave vector, suppresses it and instead stabilizes a topologically trivial double-Q state. We further examine the field evolution of these phases under an out-of-plane magnetic field and show that distinct types of skyrmion crystals with the skyrmion number of one emerge in the intermediate-field regime. These results highlight that the competition between different magnetic anisotropies in crystalline systems is a key factor governing the stability of both zero-field and field-induced skyrmion crystals. Full article

Microorganisms such as methanogenic archaea play a key role in wastewater treatment plants (WWTPs) by breaking down organic matter and pollutants and producing methane, a potential renewable energy source. However, sulphate-reducing bacteria (SRB) compete with archaea for the same substrates under anaerobic conditions, lowering methane production and generating harmful hydrogen sulphide (H₂S). Inhibiting SRB is therefore crucial to enhance methane yield and reduce toxic by-products. By means of manual screening of public databases (KEGG, BRENDA, PDB, PubChem) 12 potential inhibitors of SRB were found. After computational ecotoxicological assessment, four candidates were selected, and one of them experimentally increased methane production, demonstrating that SRB inhibition favours the anaerobic digestion of sludges. In order to further explore new candidates, Quantitative Structure–Activity Relationship (QSAR) models were developed showing reliable predictive performance. These models enabled the virtual screening of COCONUT, a natural product database, identifying 73 potential SRB inhibitors. After an ecotoxicological assessment, five commercially available compounds remained. The identified candidates may reduce competition between SRB and methanogenic archaea, leading to higher methane production and supporting WWTPs in generating their own biogas. This would contribute to a circular economy and help mitigate greenhouse gas emissions. Full article

We have investigated the evolution of CDW states and structural phases in a Cu-deficient Cu_1-δTe (δ = 0.016) by employing high-pressure experiments and first-principles calculations. Raman scattering results reveal that the vulcanite structure at ambient pressure starts to change into the Cu-deficient rickardite (r-CuTe) structure from 6.7 GPa, which then becomes fully stabilized above 8.3 GPa. Resistivity data show that T_CDW1 (≈333 K) is systematically suppressed under high pressure, reaching zero at 5.9 GPa. In the pressure range of 5.2–8.2 GPa, a sharp resistivity drop due to superconductivity occurs at the onset temperature T_C = ~2.0–3.2 K. The maximum T_C = 3.2 K achieved at 5.6 GPa is clearly higher than that of CuTe (2.3 K), suggesting the importance of charge fluctuation in the vicinity of CDW suppression. At 7.5 GPa, another resistivity anomaly appears due to the emergence of a second CDW (CDW2) ordering at T_CDW2 = ~176 K, which exhibits a gradual increase to ~203 K with pressure increase up to 11.3 GPa. First-principles calculations on the Cu-deficient Cu₁₁Te₁₂ with the r-CuTe structure show that including on-site Coulomb repulsion is essential for incurring an unstable phonon mode relevant for stabilizing the CDW2 order. These results point out the important role of charge fluctuation in optimizing the pressure-induced superconductivity and that of Coulomb interaction in creating the competing CDW order in the Cu-deficient CuTe system. Full article

Fluoride contamination in groundwater is a pressing environmental and public health issue, with chronic exposure linked to skeletal and dental fluorosis. Here, we report the synthesis of magnesium oxide nanoparticles via a controlled co-precipitation method employing dimethylformamide (DMF) as solvent and either ammonium hydroxide (MgO-1) or ammonium carbonate (MgO-2) as precipitating agents. The resulting materials were comprehensively characterized using thermogravimetric analysis (TGA/DSC), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and scanning electron microscopy coupled with energy dispersive spectroscopy (SEM/EDS). Additionally, BET surface area and porosity analyses revealed mesoporous structures, with MgO-1 showing a slightly higher surface area (14.12 m² g⁻¹) than MgO-2 (13.87 m² g⁻¹). Both MgO-1 and MgO-2 exhibited high crystallinity, nanoscale particle sizes (81.6 nm and 128.1 nm, respectively), and distinct morphological features. Batch adsorption studies revealed maximum fluoride uptake capacities of 117.6 mg/g (MgO-1) and 94.5 mg/g (MgO-2) at neutral pH, with MgO-1 exhibiting superior performance due to its smaller particle size and higher specific surface area. Fluoride removal remained above 98% between pH 3–9, confirming stability across a wide pH range, with a minor decline at pH 11 due to OH⁻ competition. Adsorption equilibrium data were best described by the Temkin isotherm model, suggesting heterogeneous surface interactions and an exothermic process, while kinetic analyses indicated pseudo-second-order behavior for MgO-1 and pseudo-first-order for MgO-2. Both materials maintained high fluoride selectivity in the presence of competing anions and successfully reduced fluoride in tap water from 2.11 mg/L to below the WHO limits without altering water hardness. These findings underscore the potential of engineered MgO nanomaterials as efficient, selective, and sustainable adsorbents for water defluoridation, offering a promising pathway toward scalable remediation technologies in fluoride-affected regions. Full article

Assessment practices are central to higher education, particularly critical in theory-based programs, where they facilitate the development of conceptual understanding and higher-order cognitive skills. They also support Saudi Arabia’s Vision 2030 agenda, which aims to drive educational innovation. This narrative review examines assessment practices in theory-based programs at a Saudi public university, identifies discrepancies with learning objectives, and proposes potential solutions. A narrative review synthesised peer-reviewed literature (2015–2025) from Scopus, Web of Science, ERIC, and Google Scholar, focusing on traditional and alternative assessments, barriers, progress, and comparisons with international standards. The review found that traditional summative methods (quizzes, final exams) still dominate and emphasise memorisation, limiting the development of higher-order skills. Emerging techniques, such as projects, portfolios, oral presentations, and peer assessment, are gaining traction but face institutional constraints and resistance from faculty. Digital adoption is growing: 63% of students are satisfied with learning management system tools, and 75% find online materials easy to understand; yet, advanced analytics and AI-based assessments are rare. A comparative analysis reveals that international standards favour formative feedback, adaptive technologies, and holistic competencies. The misalignment between current practices and Vision 2030 highlights the need to broaden assessment portfolios, integrate technology, and provide faculty training. Saudi theory-based programs must transition from memory-oriented evaluations to student-centred, evidence-based assessments that foster critical thinking and real-world application. Adopt diverse assessments (projects, portfolios, peer reviews), invest in digital analytics and adaptive learning, align assessments with learning outcomes and Vision 2030 competencies, and implement ongoing faculty development. The study offers practical pathways for reform and highlights strategic opportunities for achieving Saudi Arabia’s national learning outcomes. Full article