Web-Based Grade Prediction System

Abstract

The need for improving the educational system has led to research in the area of educational data mining, which involves the process of applying data mining tools and techniques to analyze data at educational institutions. In some higher institutes, students are plagued with the problem of having to struggle hard to complete different courses since there is no dedicated support offered to students who may need special attention in some of the registered courses. These problems arose due to lack of system to analyse and monitor students’ progress and performance in their course at interval. This has therefore resulted in poor academic performance and sub-optimal achievement by students. To this end, this study developed a system that helps to track students’ assessments and predict their grade for different courses. The system was fed with the students’ data such as the attendance in class, and number of hours puts in for studies in each course by the student. This two are now used as a criterion to predict the performance in a particular course by getting the average of both. The system was developed using PHP for the backend, MySQL for the Database and HTML, CSS and JavaScript for the front end. Students’ data obtained were modelled to predict student grades in their related courses, and levels using a coded algorithm in PHP. Furthermore, the outcome of this research can be used by lecturers who are major module in the system, in higher institutions to track their students’ academic performance and help in advising student in subjects they need to improve. Keywords: Academic Performance, Machine learning, Web-based, Prediction System, Students’ grade