Educational Data Mining tools and Techniques used for Prediction of Student's Performance: A Study

ABSTRACT

In the digital era, enormous amounts of data have been generated in education that has led to data driven approaches which in turn help effective decision making. Educational data mining has been used as a very effective tool for identifying the hidden patterns in educational data, predicting students' performance and to enhance the teaching /learning environment. Educational data mining tools and techniques help institutes in providing information about students e.g., about enrolment of students, weak students can be identified earlier so that various corrective strategies can be applied, and various resources can be allocated to enhance their performance and their success in courses they enrolled. This paper examines the research efforts that have been made in the field of educational data mining and the various educational data mining tools and techniques used in recent years for predicting student's performance. We live in a world where enormous volumes of data are collected, but if these data are not further examined, they remain nothing more than enormous amounts of data We may use this data, analyze it, and gain a significant edge by using new approaches and procedures. Data mining is the ideal approach in this situation. Extraction of hidden and valuable information and patterns from massive data sets is known as data mining. It has already been widely used in several fields, including banking, sales, marketing, telecommunications, and finance. This essay aims to introduce a unique use of data mining for education, known as educational data mining. An interdisciplinary study topic called Educational Data Mining (EDM) was established to apply data mining to the educational sector. To examine the data gathered during teaching and learning, it employs a variety of tools and methodologies from machine learning, statistics, data mining, and data analysis. The process of turning large educational databases' raw data into useful information that can be used for decision-making in educational systems as well as for a better understanding of students and their learning circumstances is known as educational data mining. © 2022 IEEE.