Survey on Big data analytics for educational sector: Abiding challenges and contributions

Abstract

Due to technology advancements, the education sector has undergone major changes, particularly with the adoption of e-learning platforms and web services for student interactions. As a result, as many people log into these programmes, a large amount of data is being generated. Most academic institutions, however, have not yet completely tapped into this data, frequently merely handling the information connected to user queries while ignoring the crucial web behavioural inputs. This research attempts to provide a paradigm for using big data technologies to improve teaching and learning in educational institutions in order to address this issue.The document has three distinct goals. To begin with, list the advantages of big data technology in education, emphasising the potential gains for educational institutions. Second, to outline several big data applications in education and show how they might be applied to enhance educational procedures and results. The paper's final goal is to present specialised big data models that are designed for the educational system and provide a useful implementation framework.The research uses both survey and modelling methodologies to accomplish these goals. The survey's component uses review papers to describe the advantages and uses of big data in education while drawing conclusions from the body of existing research. The modelling approach, on the other hand, uses the Unified Modelling Language (UML) to offer a descriptive framework for comprehending the connections between little data and big data in the educational system. Big data covers the full learning process, including both students and teachers, while small data concentrates on conventional input about student performance alone.