Personal CGPA planning system for undergraduates: Towards achieving the first class CGPA

Abstract

Academic qualification is a necessity for an individual to compete in today's competitive environment. Employers' selection criteria of potential candidate are usually based on the grade point average (GPA). Despite a student's intellectual ability, planning is a crucial step in ensuring good GPA. However, many students do not have the necessary skills and time to plan and control their GPA. An automated education planner system will be very helpful to assist the student in aiming for the best CGPA based on their current capabilities. Despite of the existence of course plan systems, students still fail distressingly to achieve their goals. In recent times, educational data mining techniques have been adopted to discover the knowledge of the educational environment and to improve the students' performance. Several techniques which are used in educational data mining are - Artificial Neural Network, Support Vector Machine, naïve Bayesian, Decision tree, etc. This research aims to explore the use of Genetic Algorithm (GA) as an assistive tool for university students to plan and improve their academic performance. The proposed personalized web-based academic planner is developed as an online record storage that keeps all of the students' academic records. Based on the student's current achievement, the system will propose the best path to enable the undergraduates to reach their goals using GA.