The Role of Machine Learning and Data Mining Techniques in Predicting Students’ Academic Performance

Abstract

The advancement in Information Technology makes it easier and cheaper to collect large amounts of data, but if this data is not further analyzed, it remains only huge amounts of data. These large amounts of data set have motivated research and development in various fields to extract meaningful information with a view of analyzing it to solve complex problem. With new methods and techniques, data can be analyze and be of great advantage. Data mining and machine learning are two computing disciplines that enable analysis of large data sets using different techniques. This paper gave an overview of several applications using these disciplines in education, with focus on student’s academic performance prediction. Early prediction of students’ performance is useful in taking early action of improving learning outcome. The perfect methods for this are machine learning and data mining. This paper also discusses special use of data mining in education, called educational data mining. Educational Data Mining (EDM) uses different methods and techniques from machine learning, statistics, data mining and data analysis, to analyze data collected during teaching and learning. The goal of this paper is to introduce the role of machine learning and data mining in predicting student’s academic performance and to present its applications and benefits