Search Results (17,221)

Architectural design stands as a highly knowledge-intensive field, with designers serving as the linchpin for its premium development. China’s construction industry is now navigating a transitional phase of slower growth, where a misalignment in designer capabilities significantly obstructs the nation’s shift from being a mere “construction giant” to becoming a true “construction powerhouse”. Based on the spatial mismatch model and Geodetector, this study empirically analyzes the mismatch relationship among designers and its influencing factors using panel data from 31 provinces in China from 2013 to 2023, and proposes strategies for cultivating architectural design talents. Findings reveal that China’s architectural designers exhibit spatial supply imbalance, and complex trends in designer allocation-simultaneous growth and decline coexist. China exhibits diverse types of architect mismatch: 22.58% of regions are in a state of Positive Mismatch, and 12.90% experience Negative Mismatch. In over one-third of regions, the architectural design talent market can no longer self-correct architect mismatch through market mechanisms, urgently requiring collaborative intervention policies from governments, design associations, and enterprises to address architect supply–demand governance. For a smooth transition during the transformation and upgrading of the construction and design industries, the architectural design talent market should accommodate frictional designer mismatch. The contribution of designer mismatch varies significantly, with factors such as innovation, industrial structure, and fiscal self-sufficiency exerting more direct influence, while other factors play indirect roles through dual-factor enhancement effects and nonlinear enhancement effects. The insights from the analysis results and conclusions for future designer cultivation include fostering an interdisciplinary teaching model for designers through university–enterprise collaboration, enhancing education in AI and intelligent construction literacy, and establishing an intelligent service platform for designer supply–demand matching to promptly build a new differentiated and precise designer supply system. Full article

Surge capacity is the ability to manage sudden patient influxes beyond routine levels and can be evaluated using the 4S Framework: staff, stuff, system, and space. While low-resource settings like Rwanda face frequent mass casualty incidents (MCIs), most surge capacity research comes from high-resource settings and lacks generalisability. This study assessed Rwanda’s hospital surge capacity using a cross-sectional survey of emergency and surgical departments in all referral hospitals. Descriptive statistics, t-tests, Fisher’s exact test, ANOVA, and linear mixed-model regression were used to analyze responses. Of the 39 invited participants, 32 (82%) responded. On average, respondents believed that they could manage 13 MCI patients (95% CI: 10–16) while maintaining routine care, with significant differences between tertiary and secondary hospitals (11 vs. 22; p = 0.016). The intra-class correlation was poor for most variables except for CT availability and ICU beds. Surge capacity perception did not vary significantly by professional category, though less senior staff reported higher capacity. Significantly higher capacity was reported by those with continuous access to imaging (p < 0.01). Despite limited resources, Rwandan hospitals appear able to manage small to moderate MCIs. For larger incidents, patient distribution across facilities is recommended, with critical cases prioritized for tertiary hospitals. Full article

Lassa fever (LF), a severe hemorrhagic disease endemic to West Africa, is primarily transmitted by rodents of the genus Mastomys, particularly Mastomys natalensis, which serve as the main reservoirs of Lassa virus (LASV). There have been reports of high prevalence of LF in Nigeria, and outbreaks tend to be recurrent yet geographically restricted, implying that additional ecological or epidemiological factors influence the distribution of the disease beyond the mere presence of M. natalensis. However, national-scale data on LASV prevalence in rodent populations remain scarce. To address this gap, a targeted small mammal survey was conducted over a four-month period (May to August 2024) in Otukpo Local Government Area (LGA) of Benue State, north-central Nigeria. Rodents and other small mammals were trapped across three purposively selected wards identified as high-risk areas based on prior reports of occurrence of such small mammals in the areas and the informal settlements in which the selected wards were located in in Otukpo LGA. Analysis of the samples revealed no statistically significant variation in LASV prevalence among the study sites, indicating a relatively uniform, low-level exposure risk across the LGA and region. However, a marginally significant difference in LASV detection between plasma and serum samples suggests that sample type and storage conditions may influence serological sensitivity. These findings highlight the importance of refining diagnostic protocols, broadening surveillance to include additional rodent hosts, and integrating ecological data with public health strategies to improve early warning systems and strengthen Lassa fever control efforts. Full article

Students with autism spectrum disorder (ASD) often face difficulties in solving arithmetic word problems, particularly in transitioning from informal counting strategies to more efficient methods based on number facts and formal operations. This study examined the development of problem-solving strategies in a single student with ASD and intellectual disability across two sequential single-case experiments using multiple baseline designs. Study 1 (age 13 years 9 months; 17 sessions) employed Modified Schema-Based Instruction (MSBI) to teach addition and subtraction change problems, while Study 2 (age 14 years 10 months; 18 sessions) utilized the Conceptual Model-based Problem Solving (COMPS) approach for multiplication and division equal-group problems. Success was defined as both correctness of the response and correctly identifying the required operation. Results indicated that the student’s performance improved in all problem types in both studies, with maintenance observed 8 weeks after Study 1 and 5 weeks after Study 2. Instruction effects generalized to two-step addition and subtraction problems in Study 1, and to two-step addition and multiplication problems in Study 2. The findings indicate that both MSBI and COMPS facilitated the student’s shift from informal strategies to efficient operation-based problem solving. Implications for practice include the need for individualized reinforcements, careful adaptation of instruction, and providing teachers with a variety of problems and knowledge of these teaching methods to support students with ASD in developing advanced problem-solving skills. Full article

The widespread integration of artificial intelligence into university academic activity requires responsibly addressing the ethical challenges it poses. This study critically analyses these challenges, identifying opportunities and risks in various academic disciplines and practices. A systematic review was conducted using the PRISMA method of publications from January 2024 to January 2025. Based on the selected works (n = 60), through a systematic and rigorous examination, this study identifies ethical challenges in teaching and research; opportunities and risks of its integration into academic practice; specific artificial intelligence tools categorised according to study approach; and a contribution to the current debate, providing criteria and practical guidelines for academics. In conclusion, it can be stated that the integration of AI offers significant opportunities, such as the optimisation of research and personalised learning, as well as notable human and ethical risks, including the loss of critical thinking, technological dependence, and the homogenisation of ideas. It is essential to adopt a conscious approach, with clear guidelines that promote human supervision, ensuring that AI acts as a tool for improvement rather than for the replacement of intelligent human performance, and that it supports human action and discernment in the creation of knowledge. Full article

This study explores and models the use of MATLAB technology in multimodal learning interactions to address the challenges of teaching and learning statistics in a multinational postgraduate classroom. The term multimodal refers to the deliberate integration of multiple representational and interaction modes, i.e., visual, textual, symbolic, and interactive computational modelling, within a coherent instructional design. MATLAB is utilised as it is a comprehensive tool for enhancing students’ understanding of statistical skills, practical applications, and data analysis—areas where traditional methods often fall short. International postgraduate students were chosen for this study because their diverse educational backgrounds present unique learning challenges. A qualitative case study design was employed, and data collection methods included classroom observations, interviews, and student work analysis. The collected data were analysed and modelled by conceptualising key elements and themes using thematic analysis, with findings verified through data triangulation and expert review. Emerging themes were structured into models that illustrate multimodal teaching and learning interactions. The novelty of this research lies in its contribution to multimodal teaching and learning strategies for multinational students in statistics education. The findings highlight significant challenges international students face, including language and technical barriers, limited prior content knowledge, time constraints, technical difficulties, and a lack of independent thinking. To address these challenges, MATLAB promotes collaborative learning, increases student engagement and discussion, boosts motivation, and develops essential skills. This study suggests that educators integrate multimodal interactions in their teaching strategies to better support multinational students in statistical learning environments. Full article

Anesthesia for children with a current respiratory infection or a history of infection within the last two weeks is always associated with a high risk of respiratory complications. However, this risk decreases significantly when the interval between the last symptoms of the infection and the planned anesthesia and medical procedure is extended to at least 2–4 weeks. The most common adverse events include bronchospasm, laryngospasm, and apnea. For children requiring unplanned procedures—such as emergency, urgent, or immediate general anesthesia—guidelines should be followed to maximize their safety and minimize the risk of complications. Full article

The introduction of emergency remote teaching in university education during the COVID-19 pandemic was not a matter of choice, but an attempt to make education sustainable in times of crisis. However, some research, even before the COVID-19 pandemic, showed that digital inequality caused by the unequal material status of students could have an impact on remote teaching. Also, before the COVID-19 pandemic, some researchers pointed out a new phenomenon, Zoom fatigue, as an accompanying phenomenon of video conferences with potential harm to the physical and mental health of consumers. The aim of this study is to examine the possibility that material status and Zoom fatigue may play the role of a moderator in the attitude of students towards ERT. The sample included 148 students attending education faculties in Serbia. The data obtained were frequencies, percentages, descriptive statistics, χ² test results, t test for independent samples, ANOVA, and linear regression.The results showed that 13% of students find the lack of financial funds for the purchase of an Internet connection with high-speed data flow to be an aggravating circumstance. Moreover, it transpires that Zoom fatigue may play the role of a moderator in students’ attitude towards ERT, particularly concerning the possibility of introducing remote teaching as a permanent form of teaching;in addition, certain aspects of students’ material status, primarily monthly household income, were a significant predictor of Zoom fatigue level on the ZEF scale. Full article

In combination with recent Catholic social teaching, this paper will explore the thought of the philosopher Emmanuel Levinas on the role of ethics in the economy to challenge forms of aggressive profiteering by illusion, deceit or exploitation. Levinas draws upon the Talmud and its teaching on sorcery and on profiting from falsehood as a starting point for his reflections on modern society, reckless market speculation and on the need for the members of society to grow in their mutual responsibility and respect for each other’s unique and incomparable dignity. Levinas’s ethic of generosity calls us to move away from the self-interested model of “greed is good” and to strive for ever-greater justice in our monetary society. Full article

Self-efficacy (SE) enables pre-service teachers to manage learning tasks and solve problems with confidence, which is essential for professional development and for addressing real-world teaching challenges. This study aimed to enhance SE through an integrated approach combining Lesson Study and Community of Practice (CoP plus LS) to better prepare pre-service teachers for classroom practice. Thirteen pre-service teachers in a teaching practicum were assigned to either an experimental group (CoP plus LS, n = 7) or a control group receiving conventional training (n = 6). A mixed-methods design was employed: SE was measured quantitatively using validated questionnaires at three time points (pre-test, post-test, and 8-week follow-up), and qualitative data were collected through semi-structured group interviews. Quantitative results showed that the CoP plus LS group demonstrated significantly greater improvement in SE compared to the control group. Within the CoP plus LS group, SE increased significantly from pre-test to post-test, with scores at follow-up remaining higher than baseline despite a slight decline. Qualitative findings revealed four themes: (1) enhanced classroom management and instructional design, (2) stronger professional identity and commitment, (3) recognition of real-world teaching challenges, and (4) growth through collaborative reflection and learning. Overall, the findings indicate that CoP plus LS effectively strengthens SE among pre-service teachers. Incorporating this approach into teacher education is recommended to enhance psychological readiness and foster sustainable professional growth. Full article

The increasing prevalence of artificial intelligence (AI) in higher education has established the need to examine the implications of specific AI-based technologies. We analyzed students’ perceptions of Packback, an AI-driven discussion board platform, in a large-enrollment undergraduate course at the University of Tennessee, United States. Valid and reliable quantitative survey instruments were used to measure students’ (n = 96) user experience (UX) of Packback and their perceptions of instructors who require the use of AI platforms in their courses. Data were analyzed to determine how students’ personal characteristics, prior use of Packback, and the UX of Packback influence their perceptions of the credibility (competence, goodwill, trustworthiness) of instructors who require the use of AI platforms. Findings indicated that students had an overall favorable experience of the Packback platform, despite moderate variability. For the credibility of instructors who require the use of AI technologies, students reported a moderate-to-high belief of competence, a moderate belief of goodwill, and a moderate-to-high belief of trustworthiness. A significant model was produced to explain the variance in students’ perception of teacher credibility. Female students and students who had more favorable UX were significantly associated with having higher beliefs in instructor credibility. Although the use of AI platforms can improve efficiency in teaching and learning, our data suggest it can also influence students’ perceptions of instructor credibility. Full article

Background: Despite chemotherapy-related toxicities being more likely in older patients, no routine prediction tool has been validated for the UK population. Previous research within the TOASTIE (tolerance of anti-cancer systemic therapy in the elderly) study found a low predictive performance of the Cancer and Aging Research Group (CARG) score for severe chemotherapy-related toxicities. Building on this, the TOASTIE study dataset was used to assess the viability of developing a predictive model with baseline variables and frailty scores for severe chemotherapy-related toxicities in older patients. Methods: All patients from the TOASTIE dataset were included, with the inclusion/exclusion criteria detailed in the TOASTIE protocol. Demographic factors, self-assessment scores, Rockwood Clinical Frailty Score and researcher’s estimated risks of toxicity were assessed for their association with severe chemotherapy-related toxicities. After data partition into 70:15:15 train/validation/test, models were built on the training dataset using logistic regression (LR), LASSO and random forest (RF). Models were optimized with a validation set with LR and LASSO; cross-validation was used with RF. Model performance was assessed with balanced accuracy, NPV and AUC. Results: Of the 322 patients included, the incidence of severe toxicities was 22% (n = 71). Ten variables were statistically significant, albeit weakly associated with severe toxicities: primarily patient-reported factors, Performance Status and high baseline neutrophil count. LR models gave the best balanced accuracies of 0.6382 (AUC 0.6950, NPV 0.8696) and 0.6469 (AUC 0.6469, NPV 0.4286) with LASSO, and 0.6294 (AUC 0.6557, NPV 0.6557) with RF. Conclusions: Models lack sufficiently robust results for clinical utility. However, a high NPV in predicting no toxicity could help identify lower-risk patients who may not require dose reductions, potentially improving overall outcomes. Full article

This study examines the influence of religious socialization on the crises of faith among Turkish youth in Türkiye. Drawing on qualitative interviews with 20 participants, it adopts a process-oriented approach, conceptualizing a crisis of faith not merely as an abrupt disruption but as a gradual process shaped by the complex and sometimes conflicting dynamics within religious socialization. Young individuals are not simply passive agents in the traditionally one-way transmission of faith; instead, they become more autonomous and dynamic as they encounter negative attitudes and behaviors, often leading to a crisis of faith. The analysis highlights the roles of authoritarian parenting, perceived inconsistencies in religious teachings, peer and social media influence, and gender inequalities within patriarchal contexts. The findings suggest that while religious socialization provides an initial framework for faith, it also poses challenges that prompt Turkish youth to re-evaluate or distance themselves critically from traditional religion. Full article

Clinical models inform initial teacher education programs at several sites globally. Such models, and the term ‘clinical,’ along with related but not synonymous evidence-based forms of teaching, are advocated by some and criticised by others. Advocates emphasise an integration of evidence, theory, and research with contextualised clinical judgement that centres on students and teachers. Critics raise concerns over the privileging of ‘scientific’ or ‘medicalised’ ways of knowing that undermine teachers’ professional and moral judgement. This paper draws on focus group data exploring understandings of clinical judgement among 20 teacher educators in a well-established clinical teacher education course. Findings reveal that while there were tensions in the use of ‘clinical’, participants saw value in the language of clinical judgement in teaching. Clinical judgement positioned teaching as a profoundly intellectual activity in which the synthesis and evaluation of observations, research, context, and student learning evidence informed teacher decision making. Findings suggest that, when framed in this way, clinical judgement and clinical teaching models can enhance teachers’ professionalism and confidence in professional decisions. The perspectives of participants reveal an often-overlooked aspect of the clinical teaching debate—the experiences of teacher educators working within such a model. Full article

This study examines GPT usage in university-level programming education, focusing on patterns and correlations in students’ learning behaviors. A survey of 438 students from four universities was conducted to analyze their adoption of AI, learning dispositions, and behavioral patterns. The research aimed to understand the current state of GPT adoption and the connection between student learning approaches and their use of these technologies. Findings show that while a majority of students use GPT applications, the frequency and depth of this engagement vary significantly. Students who favor self-directed learning tend to leverage this technology more for personalized learning and self-assessment. Conversely, students more accustomed to traditional teaching methods use it more conservatively. The study identified four distinct learner groups through cluster analysis, each with unique interaction styles. Furthermore, a correlation analysis indicated that learning orientations, such as Technology-Driven Learning and intrinsic motivation, are positively associated with more frequent and effective GPT use. Full article