Educational Data Mining Using Analysis Student Learning Process

Higher education institutions are often very interested to know around the success frequency of the students throughout their study. It is vital to study and analysis educational data especially students? performance analysis. Educational Data Mining (EDM) is the field of study disturbed with mining educational data to find out interesting outlines and knowledge in educational administrations. This learning is equally concerned with this subject, specifically, the students? performance. It contains machine learning algorithms and statistical techniques to help the user for understanding of student?s learning habits, their academic performance and further enhancement if required. In this study explores several factors hypothetically assumed to move student performance in higher education, and finds a qualitative model which best na?ve bayes classifies and predicts the students? performance. In this paper will deliberate various techniques of data mining which are useful for predicting performance level of students.