Using a Learning Management System to generate, share, monitor, and maintain various kinds of education and creation content has proven a milestone in improving online learning. Since the first Learning Management System (LMS) emerged, significant technical developments made this platform a vital technology for curriculum management, rich content management, appraisal and assessment, and complex cooperation. The future expects several improvements in its development, processes, and execution, with many emerging fields of the study exploring different innovations relevant to the LMS. Online learning has been on the increase globally due to the rapid growth in technology in education. The 2019 Coronavirus disease (COVID-19) pandemic has implemented online classes for students in all colleges and universities. However, students are unknown about their ability to consider online learning. This paper presents how machine learning could support the Learning Management System's controlling to resolve student's feedback and queries associated with technical issues and problems when they have engaged in online classes. In this paper, a web-based online survey is conducted. Two hundred fifteen (215) students who have enrolled in various streams of Ph.D., Master, and Bachelor level programs in Colleges and University of Asian countries participated in this survey. Based on students' feedback, results are analyzed. A detailed analysis of possible solutions or suggestions is stated and proposed a Machine Learning-based LMS Model to handle students' problems and challenges efficiently during the online classes.

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