The Effect of Electronic Flashcards on EFL Students' Vocabulary Learning: The Case of Saudi Arabia

This study aimed to investigate the effect of electronic flashcards on EFL vocabulary learning of preparatory-year female students at a  Saudi Arabia. It was conducted following the quantitative research methodology with a quasi-experimental design. Two groups were assigned: an experimental group who used electronic flashcards, and a control group who employed the traditional method of vocabulary learning. A pre-test and a post-test were administered in order to appraise their performance before and after the experiment. The results revealed that the post-test scores of students in the experimental group were significantly higher than their pre-test. Also, the results showed that electronic flashcards promoted students' vocabulary, causing a statistical significance in comparison to the control group. Based on these findings, this study was able to draw a number of implications and recommendation

The Effectiveness of Using Robots in a Computer Science Orientation Class

One goal of using robots in introductory computer science (CS) courses is to improve motivation among learners. In this study, we investigate the effectiveness of using the Cozmo and Lego Mindstorm robots to improve students’ motivation in a CS orientation course, and we describe our experience using these robots in the lab. To evaluate the effectiveness, we asked participants in pre- and post-surveys about their motivation to learn about CS and programming due to the robots, as well as follow-up questions about the different robots and their engagement in the class because of the robots. Even though our results show students significantly more motivated to use the robots to learn about CS and programming before taking the class, this might be due to the heavy use of the Lego Mindstorm, which students rated less motivating than the Cozmo. While the use of robots negatively impacted students’ motivation, their overall interests in CS and coding decrease similarly to students in a course without robots

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

Role of Serum Amyloid A as a Biomarker for Predicting the Severity and Prognosis of COVID-19

Objective. To detect biomarkers that can be used to predict COVID-19 severity to identify patients with high probability of disease progression and poor prognosis. Methods. Of the 102 patients with confirmed COVID-19 who were admitted to King Fahd General Hospital, Jeddah City, Saudi Arabia, from July 1, 2021 to August 5, 2021, 50 were included in this cross-sectional study to investigate the influence of serum amyloid A (SAA) on disease severity and survival outcomes of COVID-19 patients. Dynamic shifts in SAA, C-reactive protein (CRP), white blood cell (WBC), lymphocytes, neutrophils, biochemical markers, and disease progression were examined. At admission, and at three, five, and seven days after treatment, at least four data samples were collected from all patients, and they underwent clinical status assessments. Results. Critically ill patients showed higher SAA and CRP levels and WBC and neutrophil counts and significantly lower lymphocyte and eosinophil counts compared to the moderately/severely ill patients, especially with regard to disease progression. Similarly, nonsurvivors had higher SAA levels than survivors. The moderately/severely ill patients and the survivors had significantly higher dynamic changes in SAA compared to the critically ill patients and nonsurvivors, respectively, with differences clearly noticed on the fifth and seventh day of treatment. ROC curve analysis revealed that the combination of SAA and CRP was valuable in evaluating the disease progression and prognosis of COVID-19 patients at different time points; however, a combination of SAA and lymphocyte counts was more sensitive for disease severity prediction on admission. The most sensitive parameters for predicting survival on admission were the combination of SAA/WBC and SAA/neutrophil count. Conclusions. The study findings indicate that SAA can be used as a sensitive indicator to assess the degree of disease severity and survival outcomes of COVID-19 patients

Effectiveness of Machine Learning in Assessing the Diagnostic Quality of Bitewing Radiographs

Background: Identifying the diagnostic value of bitewing radiographs (BW) is highly dependent on the operator’s knowledge and experience. The aim of this study is to assess the effectiveness of machine learning (ML) to classify the BW according to their diagnostic quality. Methods: 864 BW radiographs from records of 100 patients presented at King Abdulaziz University Dental Hospital, Jeddah, Saudi Arabia were assessed. The radiographic errors in representing proximal contact areas (n = 1951) were categorized into diagnostic and non-diagnostic. Labeling and training of the BW were done using Roboflow. Data were divided into validation, training, and testing sets to train the pre-trained model Efficientdet-d0 using TensorFlow. The model’s performance was assessed by calculating recall, precision, F1 score, and log loss value. Results: The model excelled at detecting “overlap within enamel” and “overlap within restoration (clear margins) with F1 score of 0.89 and 0.76, respectively. The overall system errors made by the built model showed a log loss value of 0.15 indicating high accuracy of the model. Conclusions: The model is a “proof of concept” for the effectiveness of ML in diagnosing the quality of the BW radiographs based on the contact areas. More dataset specification and optimization are needed to overcome the class imbalance

Perspectives of the Saudi medical students toward the impact of lockdowns on their physical activity level and lifestyle during the COVID-19 pandemic

Background Physical activity (PA) level is affected by various factors in university students. Due to the pandemic of COVID-19, the Saudi Ministry of Education announced the closure of schools and universities as a preventive measure. This cross-sectional study aimed to evaluate the impact of the COVID-19 pandemic lockdown on PA levels and other lifestyle aspects among the Saudi medical students and to explore their perspectives toward it. Methods Three hundred ninety-six medical students have completed the survey, which consisted of three sections: (1) participant’s demographic data; (2) five statements about the PA and the lockdown; and (3) the International PA Questionnaire—Short Form (IPAQ-SF). Results About 63.9% of the participants were female, and 60.4% were of normal weight. Approximately 80% of participants were classified as inactive. Regarding the perspective of the students, 52.8% reported that they were not exercising regularly in the gym before the lockdown, and 46.9% reported that the lockdown and transition to online learning affected their compliance with exercise. During the lockdown and shift to online learning, the majority of participants experienced decreased PA levels, 42.4% experienced weight gain, and 53.6% reported a negative impact on their psychological status. Conclusion Generally, the results of this study showed that the COVID-19 had a negative influence on the PA level, as well as other lifestyle aspects (e.g., gaining weight) and psychological status of medical students. This study highlights aspects where universities and institutions delivering medical education can use resources to improve students’ well-being during pandemics

Minimal underlying data.

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List of participating sites and ethics committee approvals.

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Data measures definitions.

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