The recent coronavirus disease 2019 (COVID-19) pandemic pushed almost all institutions to adopt online and virtual education. The uncertainty of this situation produced various questions that perplexed educationists regarding what implications the pandemic would have on educational institutions, especially regarding how the switch to online education would impact the behavior and performance of students. The vast importance of this matter attracted the attention of researchers and served as the motivation for this research, which aims to resolve this confusion by studying the use of mobile learning (ML) among students for educational purposes during the COVID-19 period. This study also examines how this situation has affected student learning behavior (LB) and performance (SP) in the higher education setting. This research is based on collaborative learning theory, sociocultural learning theory, and ML theory. This quantitative research employed the convenient sampling technique to collect data through structured questionnaires distributed to 396 students of higher education institutions who carry a mobile device. This study used descriptive and inferential statistics to make the data more meaningful. Structural equation modeling (SEM) with AMOS software was used for hypothesis testing. The results showed that ML was a significant and positive predictor of SP and LB. Moreover, student LB partially mediated the relationship between ML and SP. The findings suggest that the academic performance of students can be enhanced by building a ML environment that aligns with the LB of students. Nevertheless, content suitable for ML must be developed, and future research should be conducted on this topic.
Today the world is facing one of the deadliest pandemics caused by COVID-19. This highly transmissible virus has an incubation period of 2 to 14 days. It acts by attaching to the angiotensin-converting enzyme (ACE2) with the help of glycoprotein spikes, which it uses as a receptor. Real-time polymerase chain reaction (PCR; rt-PCR) is the gold standard diagnostic test, and chest X-ray and computed tomography (CT) scan are the other main investigations. Several medications and passive immunization are in use to treat the condition. We searched using PubMed and Google Scholar using keywords such as COVID-19, coronavirus, and their combination with pathological findings, clinical features, management, and treatment to search for relevant published literature. After the removal of duplications and the selection of only published English literature from the past five years, we had a total of 31 papers to review. Most of the COVID-19 affected patients have mild pneumonia symptoms, and those with severe disease have comorbidities. Patients with COVID-19 had pathological findings, like ground-glass opacities, consolidations, pleural effusion, lymphadenopathy, and interstitial infiltration of inflammatory cells. Radiological changes show lung changes such as consolidations and opacities, and the pathological findings were infiltration of inflammatory cells and hyalinization. Patients with mild symptoms should self-quarantine, whereas those with severe acute respiratory distress syndrome (ARDS) are treated in the hospital. Medications under trial include antivirals, antibacterials, antimalarials, and passive immunization. Supportive treatment such as oxygen therapy, extracorporeal membrane oxygenation, and ventilator support can also be used. The symptoms shown by patients are very mild and selflimiting. There is no definitive treatment, although a combination of hydroxychloroquine and azithromycin have shown good results, and passive immunization also shows promising results, their safety profile is yet to be studied in detail.
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