Pre-Service Science Teachers' E-Learning Styles

E-learning is becoming more popular than conventional teaching methods, particularly in science education. The use of e-learning has increased worldwide, especially after the COVID-19 pandemic. Today, students' e-learning styles have gained even more importance. The participants of this survey, which aimed to examine e-learning styles for selected variables, consisted of 401 pre-service science teachers from two public universities in Turkey. The personal information form was used to obtain data on gender, university, personal computer ownership status, type of device used to connect to the internet, grade level, number of social network memberships, internet usage purpose, and duration of social media use. Another tool used in face-to-face data collection was the E-Learning Styles Scale (ESS). As a result of the analysis, it was understood that participants' e-learning style scores were generally on the positive side. In terms of gender, grade level, and duration of social media use variables, there were statistically significant differences in the ESS and some of its sub-dimensions, while differences were found in only some sub-dimensions for the university variables, internet usage purpose, and number of social network memberships. Several suggestions were made in conjunction with the results of the descriptive and inferential analyses.

SAFETY of the PFIZER/BIONTECH and SINOVAC/CORONAVAC VACCINES among PATIENTS with BEHCET'S SYNDROME and FAMILIAL MEDITERRANEAN FEVER

Background: Since frst emerged in December 2019, the COVID-19 pandemic has resulted in a death toll surpassing 5.5 million worldwide and had severe consequences on the global economy, environment, public health and social life [1, 2]. Multiple potential vaccines against COVID-19 have been developed swiftly and as shown in several phase 3 clinical trials, they demonstrated considerable efficacy without an unusual safety signal in healthy individuals. Objectives: In this study, we aimed to evaluate vaccine reactivity and disease fare following vaccination with either Sinovac/CoronaVac or Pfzer/BioNTech among BS and FMF patients compared with patients with various diagnosis of RD and healthy controls. Methods: Only those patients and healthy controls who rece,ved at least one single shot of either CoronoVac or BioNTech against COVID-19 were included in the study. We tried to contact all of these patients and controls consecutively by telephone and attempted to make interviews with the eligible ones. Results: We studied the efficacy, side effects and disease fares after COVID-19 vaccination in 256 patients with Behcet's syndrome (BS), 247 with familial Mediterranean fever (FMF), 601 with rheumatic diseases (RD) and 612 healthy controls (HC). Study participants were vaccinated either with CoronaVac (BS:109, FMF: 90, RD: 343, and HC: 334) or BioNTech (BS: 147, FMF:157, RD: 258 and HC: 278). BioNTech ensured a signifcantly better efficacy than CoronaVac against COVID-19 in all patient groups (BS: 1.4% vs 10.1%;FMF: 3.2% vs 12.2%, RD:2.7% vs 6.4%). Those with at least one adverse event (AE) were signifcantly more frequent among those vaccinated with BioNTech than those with Coro-naVac (BS: 86.4% vs 45%;FMF: 83.4% vs 53.3%;RD: 83.3% vs 45.5% and HC: 86.3% vs 52.1%). The majority of AEs were mild to moderate and transient and this was true for either vaccine. There were also AEs that required medical attention in all study groups following CoronaVac (BS:5.5%, FMF:3.3%, RD:2.9% and HC:3.3%) or BioNTech (BS:5.4%, FMF:1.9%, RD:4.7% and HC:4.7%). The main causes for medical assistance were disease fare, and cardiovascular events. Disease fares after vaccination were signifcantly more frequent among BS (41/256;16.0%) and FMF (43/247;17.4%) patients compared to patients with RD (36/601;6.0%). This was true for both CoronaVac (BS: 11.0%, FMF: 24.4% and RD: 5.2%, p<0.001) and BioNTech (BS: 19.7%, FMF: 13.4% and RD: 7.0%, p=0.001)(Table 1). Conclusion: Our study demonstrates that BS and FMF patients vaccinated with either CoronaVac or BioNTech demonstrated almost similar AE profile and frequency compared to RD patients and HC. AEs that required physician consultation or hospitalization occurred in all study groups after either CoronaVac or BioNTech. Caution should be required when monitoring these patients after vaccination. Increased frequency of fares in BS and FMF compared to that seen in RD might refect defects in innate immunity and deserves further investigation.

Analysis of Covid 19 disease with SIR model and Taylor matrix method

Covid 19 emerged in Wuhan, China in December 2019 has continued to spread by affecting the whole world. The pandemic has affected over 328 million people with more than 5 million deaths in over 200 countries which has severely disrupted the healthcare system and halted economies of the countries. The aim of this study is to discuss the numerical solution of the SIR model on the spread of Covid 19 by the Taylor matrix and collocation method for Turkey. Predicting COVID-19 through appropriate models can help us to understand the potential spread in the population so that appropriate action can be taken to prevent further transmission and prepare health systems for medical management of the disease. We deal with Susceptible–Infected–Recovered (SIR) model. One of the proposed model’s improvements is to reflect the societal feedback on the disease and confinement features. We obtain the time dependent rate of transmission of the disease from susceptible β(t) and the rate of recovery from infectious to recovered γ using Turkey epidemic data. We apply the Taylor matrix and collocation method to the SIR model with γ, β(t) and Covid 19 data of Turkey from the date of the first case March 11, 2020 through July 3, 2021. Using this method, we focus on the evolution of the Covid 19 in Turkey. We also show the estimates with the help of graphics and Maple. © 2022 the Author(s), licensee AIMS Press.