Hasil untuk "Education"

Mohammadreza Farrokhnia, S. K. Banihashem, O. Noroozi et al.

ABSTRACT ChatGPT is an AI tool that has sparked debates about its potential implications for education. We used the SWOT analysis framework to outline ChatGPT’s strengths and weaknesses and to discuss its opportunities for and threats to education. The strengths include using a sophisticated natural language model to generate plausible answers, self-improving capability, and providing personalised and real-time responses. As such, ChatGPT can increase access to information, facilitate personalised and complex learning, and decrease teaching workload, thereby making key processes and tasks more efficient. The weaknesses are a lack of deep understanding, difficulty in evaluating the quality of responses, a risk of bias and discrimination, and a lack of higher-order thinking skills. Threats to education include a lack of understanding of the context, threatening academic integrity, perpetuating discrimination in education, democratising plagiarism, and declining high-order cognitive skills. We provide agenda for educational practice and research in times of ChatGPT.

Deborah A. Maranville

A. Astin

S. Schwartz, Vincent Tinto

L. Resnick

D. Keegan

N. Colangelo, G. Davis

K. Tobin

D. Fuchs, L. Fuchs

B. Weiner

Cameron Mccarthy, Warren E. Crichlow

Wilson H. Hammett, James Macinko

Abstract Introduction Existing quantitative studies of violence victimization in Brazil often examine individual demographic and socioeconomic risk factors, limiting insight into how identities can intersect to co-produce vulnerability or resilience. This study uses a nationally representative household survey to investigate how demographic, socioeconomic, and geographic factors intersect to shape the probability of experiencing psychological, physical, and sexual violence among Brazilian adults. Methods Data from the 2019 Brazil National Health Survey was used to created indicators of 12-month experience of three types of interpersonal violence (psychological, physical, and sexual), a measure of any violence and one indicating 2 or more types. Previous literature guided the development of 356 clusters of intersectional identities based on demographic, socioeconomic and other factors. Analyses used the intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) approach based on multilevel analyses of all 356 intersectional strata in addition to individual-level factors. Results Among Brazilian adults, 18.3% (totaling 27,535,272) reported experiencing interpersonal violence and 3.7% experienced more than one type in the past 12 months. Psychological violence (17.4%) was most frequently reported, followed by physical (4.6%) and sexual (0.8%) violence. MAIHDA models revealed that prevalence and risk varied widely across intersectional strata, but that younger age (< 30), being single, living in an urban area, and living with a long-term illness or disability were consistently found in the strata with highest predicted probability of victimization across all types of violence. Being female, being Black, having a college-level education, and being in the lowest wealth tertile were also commonly found in the highest ranked strata across forms of violence victimization. The overall variance attributable to intersectional (as opposed to individual) effects was between 9.3% and 13.0% across different forms of violence, suggesting that risk of experiencing (or reporting) interpersonal violence in this study accumulates largely in additive rather than multiplicative ways. Conclusions This study found that experiences of psychological, physical, and sexual interpersonal violence were patterned by intersecting social and economic inequalities, with higher risk among women, younger adults, Black or Brown individuals, those who are single, urban residents, and people living with long-term health problems. MAIHDA analyses revealed that risk accumulated across overlapping social positions—particularly among young, single, urban Black women with chronic conditions—highlighting the need for violence prevention strategies that address structural drivers of gender, racial, and socioeconomic inequality. Clinical trial number Not applicable.

S. Jayne, S. Jejeebhoy

Y. Cheng, W. Tam

Santu Mondal, Sneha Ray, Aritra Acharyya et al.

This work investigates the application of artificial neural network (ANN)-based regression models to predict the static and dynamic characteristics of GaN impact avalanche transit time (IMPATT) sources in the terahertz (THz) frequency regime. A comprehensive dataset, derived from self-consistent quantum drift-diffusion (SCQDD) simulations of GaN IMPATT structures designed for a wide frequency range from the microwave frequency bands, up to 5 THz, is used to train the ANN models. The models effectively capture the impact of variations in structural, doping, and biasing parameters on device performance. The proposed ANN approach significantly reduces computational time for predicting breakdown characteristics, power output, and conversion efficiency properties of IMPATT sources, achieving similar accuracy to traditional SCQDD simulations while requiring only 7.8&#x2013;20.1% of the computational time. Mean square errors are observed to be on the order of <inline-formula> <tex-math notation="LaTeX">$10^{-4}$ </tex-math></inline-formula>&#x2013;<inline-formula> <tex-math notation="LaTeX">$10^{-6}$ </tex-math></inline-formula>, demonstrating the models&#x2019; high accuracy. Experimental validation shows strong agreement in terms of breakdown voltage, power output, and efficiency, supporting the potential of machine learning to streamline the design and optimization of high-frequency semiconductor devices.

Joanne Huiyi Luo, Xuan Han Koh, Marlinda Ali et al.

Background Community nurses play a crucial role in managing pain, a prevalent yet often inadequately addressed symptom in community settings. Persistent knowledge gaps among healthcare providers contribute to inconsistent pain management, potentially compromising patient outcomes. Objectives This study is designed as a pre- and post-course observational study aiming to assess baseline pain knowledge among community nurses in Singapore and evaluate the effectiveness of an interdisciplinary pain education programme. Methods 43 community nurses completed a pre-course questionnaire assessing self-reported clinical knowledge and objective pain knowledge using the Clinical Pain Knowledge Test (CPKT). Following an interdisciplinary pain education programme, 34 nurses completed the post-course questionnaire. Changes in self-reported clinical knowledge and CPKT scores were analysed, and multivariable linear regression was used to identify predictors of post-course knowledge scores. Results Baseline pain knowledge among community nurses was modest with a mean pre-course CPKT score of 49.1% (±12.8%). Post-course, there was a significant improvement in overall knowledge scores (mean 58.4% ± 14.1%, p < 0.001). While improvements were observed in most CPKT domains, there was no significant change in the application of knowledge in clinical conditions. Less experienced community nurses demonstrated the greatest improvement post-course. Conclusion Structured pain education programmes effectively enhance nurses’ theoretical knowledge, particularly among those with less experience in community nursing. However, translating this knowledge into clinical application remains challenging. Standardised pain education and interdisciplinary training approaches may further strengthen pain management competencies in community settings.

Pâmela Gracielle da Fonseca, António Raposo, Nada Alqarawi et al.

BackgroundFeeding difficulties, such as limited appetite, selective eating, and food phobia, affect caregivers' ability to provide adequate nutrition to children. These issues impact 25%–40% of non-neurodivergent children and up 80% of neurodivergent children.AimThis review examines how family involvement influences the improvement, worsening, or maintenance of feeding difficulties in neurodivergent and non-neurodivergent preschool and school-age children.MethodsAn integrative review was conducted using Embase, PubMed, Scopus, Cochrane Library, Lilacs and grey literature (Google Scholar and Connect Papers). The review focused on randomized clinical trials (RCTs) involving parents or caregivers of children aged 2–10 years, assessing lifestyle or psychological interventions.ResultsFrom 1,257 studies, 885 primary articles were screened. Of the 100 most recent articles on grey literature, 2 met the eligibility criteria after full-text assessment and were therefore included in the review. Thirty-six studies were reviewed in full, leading to 11 RCTs with 630 children aged 1 to 14. Interventions included behavioral education, sensory education, and cooking classes. Findings indicated increased vegetable acceptance in two studies, improved feeding difficulties scores in five, and reduced avoidant/restrictive food intake disorder (ARFID) symptoms in two studies. One study showed no significant differences between control and intervention groups.ConclusionFamily-involved interventions generally produced positive outcomes in managing feeding difficulties. However, methodological variability and the predominance of studies from high-income countries limit the generalizability of these results. Future research should focus on standardizing diagnostic criteria and developing culturally sensitive interventions.

Colin Baker

Nicholas Burnett

M. Murad, Fernando Coto‐Yglesias, P. Varkey et al.