ABSTRACT
Emergency Remote Teaching (ERT) is a mode of teaching usually triggered by disasters and pandemics such as the deadly Coronavirus. This study used a self-reported questionnaire to investigate student perceptions, challenges, and coping strategies during ERT at a public university in Ghana. Using a randomly selected sample of 80 students, the study established the relationships between student perceptions and coping strategies, perceptions, and challenges. Out of the 80 respondents, 76 questionnaires were duly completed and were analysed using partial least square structural equation modelling (PLS-SEM). The bootstrapping results indicate that student perceptions of ERT have a significantly positive relationship with their coping strategies, the challenges have a significant negative relationship with coping strategies. However, student perceptions did not significantly correlate with students' challenges. Results recommend that the university put appropriate measures in place to reduce the challenges associated with ERT, which will improve students' perceptions since the pandemic is still raging with a series of waves. Challenges such as lack of access to digital devices and high-speed internet should also be addressed urgently.
ABSTRACT
Background and/or Objectives: To determine the feasibility of utilizing M-Mode (motion-mode) for ultrasound imaging and data collection of the diaphragm. Design(s): A review of data collected during a prospective, randomized controlled trial. Setting(s): Research hospital Participants: 12 adults (mean age = 39 years) with lab-confirmed SARS-CoV2 infection and persistent exercise intolerance affecting function. Musculoskeletal M-Mode imaging of the left and right diaphragm were acquired using a Samsung RS85 Prestige Ultrasound System and a PA1-5A transducer. Data were cataloged for 3 different breathing conditions: quiet breathing, deep breathing, and sniffing. Intervention(s): not applicable Main Outcome Measure(s): Images were scored independently by three researchers on a three-point scale. Disagreements were resolved by a senior researcher. Main outcome measures included: percentage of viable images acquired for patients with a range of BMI scores, comparison of image viability between the three breathing conditions, percentage of compromised images for the right and left diaphragm. Result(s): BMI did not impact image quality (range: 19.8-37.7). The sniff test yielded the lowest percentage of unusable images (13%) compared to quiet breathing (17%) and deep breathing (21%). Moreover, the left diaphragm yielded a higher number of unmeasurable (92% percent of imaging errors were on the left side). No statistical significance was found in image usability scores between the 3 breathing conditions on either the right or left diaphragm. Conclusion(s): M-Mode imaging of the diaphragm is feasible;however, it is accompanied by user-, machine-, and patient-dependent challenges that appear to create more obstacles when imaging the left hemidiaphragm. A sniff test performed during M-mode US imaging is more likely to provide usable measurements of diaphragmatic function than other breathing conditions.
ABSTRACT
Teaching and learning are both influenced by technology. Adoption of online learning platforms come with its own challenges and issues. Emergency remote learning was adopted by many educational institutions around the world during the COVID-19 pandemic to enable the continuation of teaching and learning. This was a shift from the traditional face-to-face to virtual classroom environment. As a result of its adoption, some institutions were exposed to security risks, necessitating proactive measures to mitigate them. In this study, a comparison of existing online security solutions is made, and a security framework is presented that can be used to guide the adoption of remote learning. The framework provides adequate security support through identity management, crypto operations, policy database, deception technology, web and email security, API security and ATP technology. This framework enhances security by ensuring that organizations are aware of current security incidents. © 2021 ACM.