The global pandemic of COVID-19 forced institutions of higher learning to implement emergency remote learning and to change pedagogical approaches to enhance access and success for all students. Students have mixed views about remote learning. The purpose of this study is to examine special educational needs and disabled students' perspectives of remote learning in the United Arab Emirates. The study was conducted using a qualitative case study within an interpretivist paradigm. Thirty-three special educational needs and disabled students were selected to complete an open-ended questionnaire and participate in semi-structured interviews. It was found that students applauded extraordinary convenience and reasonable accommodation they were getting as a result of remote learning. However, post COVID-19, the majority opted for face-to-face instruction as they described it as 'irreplaceable'. The study concludes that students' nature of special needs and disabilities are influential towards their choice of a mode of instruction.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8886201 | PMC |
http://dx.doi.org/10.1007/s10639-022-10962-4 | DOI Listing |
J Clin Monit Comput
January 2025
Department of Electrical Engineering, Eindhoven University of Technology, Groene Loper 3, 5612 AZ, Eindhoven, the Netherlands.
Unobtrusive pulse rate monitoring by continuous video recording, based on remote photoplethysmography (rPPG), might enable early detection of perioperative arrhythmias in general ward patients. However, the accuracy of an rPPG-based machine learning model to monitor the pulse rate during sinus rhythm and arrhythmias is unknown. We conducted a prospective, observational diagnostic study in a cohort with a high prevalence of arrhythmias (patients undergoing elective electrical cardioversion).
View Article and Find Full Text PDFSci Rep
January 2025
College of Electrical and Information Engineering, Beihua University, Jilin, 132013, China.
Remote sensing images often suffer from the degradation effects of atmospheric haze, which can significantly impair the quality and utility of the acquired data. A novel dehazing method leveraging generative adversarial networks is proposed to address this challenge. It integrates a generator network, designed to enhance the clarity and detail of hazy images, with a discriminator network that distinguishes between dehazed and real clear images.
View Article and Find Full Text PDFIntegr Environ Assess Manag
January 2025
Faculty of Fine Arts, Design and Architecture Department of Landscape Architecture, Tekirdağ Namık Kemal University, Tekirdağ, Türkiye.
Wetlands provide necessary ecosystem services, such as climate regulation and contribution to biodiversity at global and local scales, and they face spatial changes due to natural and anthropogenic factors. The degradation of the characteristic structure signals potential severe threats to biodiversity. This study aimed to monitor the long-term spatial changes of the Göksu Delta, a critical Ramsar site, using remote sensing techniques.
View Article and Find Full Text PDFFront Public Health
January 2025
Department of Psychology, Kazimierz Wielki University, Bydgoszcz, Poland.
Introduction: The ongoing COVID-19 pandemic, which began in early 2020, and the outbreak of war in Ukraine in 2022 (a country bordering Poland on the east) have significantly impacted the mental health of young people in Poland, leading to increased rates of depression, anxiety, and other mental health issues. The rising number of individuals struggling to cope with daily stressors, as well as non-normative stressors, may indicate a decrease in the individual's potential, specifically in skills, attitudes, and competencies required to overcome difficulties that they encounter. It can be assumed that for young people, maintaining mental health under the influence of social stressors, such as the pandemic and the ongoing war in Ukraine, depends on the ability to adapt positively, which is the ability of young individuals to adjust to situational demands in a way that allows them to effectively manage those situations.
View Article and Find Full Text PDFThe repetitive observations of satellites provide rich multi-temporal information for coastal remote sensing, making it possible to improve the accuracy of bathymetric inversion through multi-temporal satellite data. This study takes Culebra, Puerto Rico, as the study area and attempts multi-temporal bathymetric inversion using 193 Sentinel-2 images and eight tracks of ICESat-2 ATL03 data. Two widely used machine-learning models, CatBoost and Random Forest (RF), were employed to construct bathymetric inversion models, and the Fusion followed by Inversion (FI) strategy and inversion followed by Fusion (IF) strategy were also compared.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!