DEEP LEARNING-BASED MOBILE E-LEARNING MANAGEMENT IN DISTRIBUTED CLOUD COMPUTING

With the increasing number of schools of higher learning are adopting mobile technologies to improve the quality of service they provide to their student bodies. Even though mobile learning management systems (LMSs) are used all the time in higher education, not much research has been done on the factors that lead to their use and the effects of learning on students' academic performance. In this paper, we develop a cloud-based secured e-learning framework for the various educational system in schools. This framework has three models that includethe client model, networking model and storage model. The study aims at exploring the relationship between the effectiveness of education and the factors associated with mobile LMS, demographics, psychological data, and other external factors. The deep learning-basedregression shows that the employment status and age are significant in classifying the adoption of students over mobile LMSs. Thereby potential links are established between the factors and the mobile LMS. Further, the study is tested in terms of various factors associated with academic performance about mobile LMS.