SCHOOL MANAGEMENT SYSTEM: PREFECT OF THE DISCIPLINE MANAGEMENT SYSTEM WITH AI DECISION MAKING TOOL

Abstract

In today's rapidly evolving educational landscape, maintaining discipline and a respectful learning environment is essential for academic success. Traditional disciplinary methods often rely on manual processes and subjective judgments, resulting in delays and inconsistencies. This project introduces a School Management System integrated with a Prefect of Discipline Management System, enhanced by an AI-powered decision-making tool. The system automates the tracking, assessment, and resolution of disciplinary cases, promoting greater transparency, efficiency, and fairness through data-driven decision-making in managing student behavior. By adopting an Agile approach to project management, the project is divided into several stages to ensure flexibility and continuous improvement.

Concept Phase: In the initial stage, the product owner collaborates with the team to define the project's scope and limitations. Once the concept is clearly established, the development team is assembled. The product owner and project manager evaluate each member’s skills and availability to ensure the right individuals are selected, equipped with the necessary tools and resources to carry out their tasks effectively.

Construction Phase: This is typically the longest phase, as it involves most of the development work. During this stage, team members provide ongoing support to maintain smooth system development, address any issues, and mitigate potential risks that may arise.

Release Phase: As the project nears completion, it enters the release phase. The team performs thorough testing to evaluate the software’s quality and ensure all functionalities meet the required standards before the final deployment. The implementation of the Prefect of Discipline Management System has significantly benefited the Prefect department by minimizing manual effort in managing student information, scheduling, and data analysis. It streamlines daily operations, increases the department's capacity to handle disciplinary cases, and enhances the accuracy of data records. Overall, the system improves operational efficiency, supports scalability, and boosts user satisfaction. The system has enhanced discipline management by making processes faster, more consistent, and data-driven. The integration of AI assists in interpreting violation records; however, it still depends on accurate data input and requires human oversight to ensure responsible use. Ethical considerations—such as privacy, transparency, and fairness—must be addressed in the system's ongoing development. Overall, the tool demonstrates strong potential for enabling smarter and more efficient school discipline management.