A New Cloud Computing-Based Assessment of Issues in Online Teaching Management in the Post-Epidemic Era of COVID-19

Abstract

The COVID-19 pandemic has accelerated the development of online teaching and learning, and educational institutions are now facing new challenges and opportunities. Online teaching management has become a crucial issue in ensuring the quality of education in the post-epidemic era. Online teaching management is a complex issue that requires schools to provide technical support, develop interactive teaching methods, ensure fair assessment, provide time management support, and offer training and support to teachers. By addressing these challenges, schools can ensure the effectiveness and quality of online teaching in the post-epidemic era. This paper examined the issues and challenges associated with Online Teaching Management in the Post-Epidemic era of CoVID -19. The analysis is conducted in a study of China. The GAN_OTM (Generative Adversarial Network for Online Teaching Management) model is proposed as a solution to address the challenges faced in online teaching management during the post-epidemic era of COVID-19. This model leverages the power of deep learning and generative adversarial networks to generate realistic virtual classrooms and learning environments, personalized learning experiences, and provide real-time feedback to students and teachers. With developed GAN_OTM model discussed its potential benefits and contributions to online teaching management, including improved student engagement, personalized learning experiences, and scalability. Furthermore, highlight the performance metrics used to evaluate the GAN_OTM model and the importance of analyzing its results. In the other hand, teachers are not comfortable with online teaching management to interact with students.