Applications of Data Mining Techniques in Student Performance Analysis: A Survey

Abstract

Educational Data Mining (EDM) is one of the useful applications of data mining. In EDM, there are two key research areas, one is related with students (both high school students and university students) and the other is with faculty (both teachers and institutional responsibility). A detailed research work has already been carried out in both domains. In the present day, the enomus challenges that educational institutions are facing the explosive growth of educational data and to use this data to enhance the quality of managerial decisions. Educational institutions are taking part in an important role in our society and playing a fundamental role for growth and development of nation. It is important to study and analyze educational data especially students’ performance. To analyze the performance of the students, every institution has their own criteria. So, it is necessary to study on existing prediction techniques and hence to find the best prediction methodology for predicting the student academics progress and performance. A detailed literature survey on predicting student’s performance using data mining techniques has already been carried out in analyzing educational data. The main objective of this survey is to provide a great knowledge and examining different data mining techniques that have been applied to analyze and predict students’ performance.