A Non-Intricate Modeling of Transformation and Extracting Knowledge from Educational Big Data

The advent of cloud-computing has leads to evolution of collaborative state in Learning Management System leading to re-defining the process of knowledge-delivery services in its e-learning process. However, this also results in generation of voluminous number of education-related data characterized by various standard features of big data. With increasing trends in big data analytics, it has been found that there is no significant work carried out towards evolving up with similar improvement in knowledge discovery process for a given educational big data. Therefore, this paper presents a non-conventional and computationally cost effective solution where the educational big data is addressed for its challenging problem associated with its unstructured form. The proposed algorithm is smartly capable of extracting knowledge for a given set of educational data.