PREDICTING STUDENT PERFORMANCE USING DATA MINING TECHNIQUES
Abstract
This project focuses on the development of an intelligent data-driven system that integrates data preprocessing, prediction, visualization, and reporting into a single platform. The system is designed using a layered architecture comprising the user interface, application logic, and data layer. The user interface, implemented with Tkinter, provides an interactive environment for data entry, control, and visualization. The application layer, developed in Python, manages workflow processes including event handling, dataset validation, model training, and prediction. Additionally, the system incorporates visualization and export modules to enable users to generate charts, graphs, and structured reports.
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