An Improved Model of Virtual Classroom using Information Fusion and NS-DBSCAN
Virtual classroom is a latest concept of learning platform. It provides an environment by incorporating internet technology where teachers, students, researchers and interested people can interact, collaborate, communicate and explain their thoughts and views in well organized, technical and pedagogical procedure. Regarding present global context, the virtual classrooms is a popular technology. Very reknown e-learning platforms are Blackboard, Schoology, Moodle (Modular Object-Oriented Dynamic Learning Environment), Canvas and google classroom. In this thesis, we propose an efficient model of virtual classroom to enhance the facility of current e-learning system. To develop the model of virtual classroom, the thesis integrates the policy of cloud computing with information fusion (IF) technique for providing a ubiquitous learning capacity from an e-learning platform. In our proposed model, Density Based Spatial Clustering of Application with Noise (DBSCAN) algorithm is used for separating different layers of data to reduce time complexity and enhance data security. Here we also demonstrate the complete architecture of cloud based e-learning process through our proposed virtual classroom.
