DEVELOPMENT OF A STUDENT ACADEMIC PERFORMANCE AND DEGREE CLASSIFICATION PREDICTION SYSTEM USING THE NIGERIAN GRADING SCHEME
Abstract
This project presents the design and implementation of a web-based student academic
performance and degree classification prediction system tailored to the Nigerian
university grading structure. Motivated by the limitations of manual ranking and
performance tracking methods—often plagued by inefficiency, inaccuracy, and lack
of transparency—the system provides an automated, scalable solution for calculating
Grade Point Average (GPA), Cumulative Grade Point Average (CGPA), degree classification, and student ranking using a rule-based algorithm aligned with Nigeria’s 5.0 CGPA standard. The system was developed using a three-tier architecture, incorporating HTML, CSS, JavaScript/TypeScript, and LocalStorage for client-side persistence. It supports functionalities such as CSV import/export, real-time CGPA prediction, and cohort ranking. User interface design emphasized usability and mobile responsiveness, while testing ensured cross-browser compatibility and computational accuracy. Unlike conventional student information systems, the developed tool enables students to visualize academic progress, simulate future outcomes, and identify their academic standing within a cohort. Its lightweight and offline capable structure make it particularly suited for low-resource educational settings. Evaluation confirmed the system’s effectiveness in improving result management, academic forecasting, and decision-making support. The solution contributes to a more transparent, efficient, and student-centric academic evaluation process in Nigerian tertiary institutions.
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