GPA Prediction System

Abstract

Grade Point Average (‘GPA') is determined by translating letters into numerical grades. Numerical grades of all the courses are added and then divided to achieve the GPA. GPA is essential in selection and placement of the students. The main objective is to predict students’ GPA at the start of the semester when they register their courses. This early prediction will help to forecast their subsequent performance. Low performing students can change courses or get counselling from student batch advisors to improve their performance. This will decrease the drop rate of the students in university and overall quality of education will be improved. A web application will be developed to predict student’s GPA. Data mining and machine learning techniques that are two decision tree (C4.5 and ID3) algorithm, Naïve Bayes and k-nearest neighbour algorithm which are already used by the researchers [1] will be used on gathered data to predict students’ GPA. Based on this prediction, precautionary measures would be taken eventually to reduce the drop rate of students and improved students’ GPA.