Technological Affordances and Teaching in EFL Mixed-ability Classes during the COVID-19 Pandemic

With the widespread of COVID-19 in Saudi Arabia, the educational authorities issued firm directions to convert to virtual classes exploiting the available Learning Management System (LMS). However, during the academic year 2020-2021, the researchers observed that writing EFL instructors at Prince Sattam bin Abdulaziz University (PSAU), Saudi Arabia, faced diverse challenges due to having online mixed-ability classes, i.e. those classes where students have varying levels of readiness, motivation, and academic caliper. Though many previous studies explored the influence of the COVID-19 pandemic on teaching and learning practices, very few studies addressed the way technological affordances pose challenges for instructors teaching mixed-ability classes. Therefore, the present study, using mixed quantitative and qualitative research methods, sought to explore challenges that evolved due to the technological affordances of LMS to spot the persistent problems and to offer relevant solutions for upgrading, writing teaching and learning practices. The basic research design relied on an online questionnaire followed by semi-structured interviews. Findings showed that differentiated instruction proved to be the most successful strategy for teaching writing in mixed-ability online classes as it allowed the adaptation of materials, teaching and learning practices, and assessment tools to motivate low-achievers. In addition, the collaborative tools offered by the Blackboard such as the White Board, Discussion Board, Blogs, and Breakout Groups helped to meet the preferences of visual, auditory, and kinesthetic learners. Finally, further studies are recommended to explore the affordances of educational technologies regularly to identify potential benefits and limitations for offering the best teaching and learning practices.

Opinion Mining of Saudi Responses to COVID-19 Vaccines on Twitter

In recent months, many governments have announced COVID-19 vaccination programs and plans to help end the crises the world has been facing since the emergence of the coronavirus pandemic. In Saudi Arabia, the Ministry of Health called for citizens and residents to take up the vaccine as an essential step to return life to normal. However, the take-up calls were made in the face of profound disagreements on social media platforms and online networks about the value and efficacy of the vaccines. Thus, this study seeks to explore the responses of Saudi citizens to the COVID-19 vaccines and their sentiments about being vaccinated using opinion mining methods to analyze data extracted from Twitter, the most widely used social media network in Saudi Arabia. A corpus of 37,467 tweets was built. Vector space classification (VSC) methods were used to group and categorize the selected tweets based on their linguistic content, classifying the attitudes and responses of the users into three defined categories: positive, negative, and neutral. The lexical semantic properties of the posts show a prevalence of negative responses. This indicates that health departments need to ensure citizens are equipped with accurate, evidence-based information and key facts about the COVID-19 vaccines to help them make appropriate decisions when it comes to being vaccinated. Although the study is limited to the analysis of attitudes of people to the COVID-19 vaccines in Saudi Arabia, it has clear implications for the application of opinion mining using computational linguistic methods in Arabic.

Thromboembolic Events and Role of Point of Care Ultrasound in Hospitalized Covid-19 Patients Needing Intensive Care Unit Admission.

BACKGROUND: Covid-19 associated coagulopathy (CAC) is associated with prothrombotic state and thromboembolism. However, true incidence of thromboembolic events is difficult to determine in the ICU setting. The aim of our study was to investigate the cumulative incidence of thromboembolic events in Covid-19 patients needing intensive care unit (ICU) admission and assessing the utility of point of care ultrasound (POCUS) to screen for and diagnose lower extremity deep venous thrombosis (DVT). METHODS: We conducted a prospective observational study between April 22nd and May 26th, 2020 where all adult patients with the diagnosis of Covid-19 pneumonia admitted to 8 ICUs of Montefiore Medical Center were included. POCUS exam was performed on all patients at day 1 of ICU admission and at day 7 and 14 after the first exam. RESULTS: The primary outcome was to study the cumulative incidence of thromboembolic events in Covid-19 patients needing ICU admission. A total of 107 patients were included. All patients got POCUS exam on day 1 in the ICU, 62% got day 7 and 41% got day 14 exam. POCUS diagnosed 17 lower extremity DVTs on day 1, 3 new on day 7 and 1 new on day 14. Forty patients developed 52 thromboembolic events, with the rate of 37.3%. We found a high 45-day cumulative incidence of thromboembolic events of 37% and a high 45-day cumulative incidence of lower and upper extremity DVT of 21% and 10% respectively. Twelve (30%) patients had failure of therapeutic anticoagulation. Occurrence of a thromboembolic event was not associated with a higher risk of mortality (HR 1.08, p value = .81). CONCLUSIONS: Covid-19 patients in ICU have a high cumulative incidence of thromboembolic events, but not associated with higher mortality. POCUS is an excellent tool to help screen and diagnose DVT during a pandemic.