Big data and Analytics in Education: Leveraging Data to improve Student Performance

By transforming the analysis and optimisation of institutional procedures and student learning, big data analytics, or BDA, is completely changing the educational landscape. Analysis of Big data in education has the potential to raise student academic attainment by providing individualised learning experiences. Teachers can pinpoint problem areas and create focused interventions to help students improve their learning outcomes by gathering and evaluating data on student behaviour and performance. Big data may also be utilised to improve the grading system by eliminating errors in manual grading and providing precise and impartial assessment through analysis of information. Teachers can save time and lessen grading bias by using automated grading systems, which results in more equitable and uniform grading procedures. Additionally, this can assist teachers in pinpointing areas in which students want more assistance and in giving they focused comments to help them do better. All things considered, there are many advantages to employing big data analysis in education, such as raising student interest and engagement, improving grading procedures, boosting academic performance, and lowering dropout rates. However, when using big data in education, it's crucial to make sure that data security and student privacy comes first. Teachers and educational institutions can use Big Data to enhance instruction and set pupils up for future success by adopting a responsible and moral attitude.