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.
