SCHOOL MANAGEMENT SYSTEM: STUDENT AFFAIRS MANAGEMENT SYSTEM WITH AI ENGAGEMENT ANALYTICAL TOOL

Abstract

Effective management of student organizations is essential for fostering student engagement and streamlining administrative processes within academic institutions. However, many schools still rely on manual systems, resulting in inefficiencies such as delayed approvals, inaccurate tracking of participation, and excessive paperwork. To address these issues, this study developed the Student Affairs Management System—a digital platform designed to automate administrative tasks, incorporate an AI-powered Engagement Analytics Tool to monitor student participation, and enhance connectivity across institutional departments. The study adopted the Agile Scrum methodology, dividing the development process into several sprints to allow for continuous iteration and refinement. System requirements were defined through data collected from surveys and interviews with student leaders, faculty members, and administrators. Sprint planning was conducted to prioritize development tasks and ensure timely progress. The resulting Student Affairs Management System features automated notifications, comprehensive tracking of organizational activities, and integration with institutional systems to enhance efficiency and student engagement. The Student Affairs Management System implemented an AI-driven engagement tool to monitor student participation and automate activity tracking. It streamlined key processes such as registration, permit approvals, and communication, leading to greater administrative efficiency. By integrating with existing institutional platforms, the system improved data management and reporting, promoting a more organized and transparent student affairs operation. The study highlights the effectiveness of digital solutions like the Student Affairs Management System in streamlining administrative tasks and enhancing engagement tracking. The Agile methodology ensured responsiveness to user needs, while AI analytics provided valuable insights. Despite challenges in user adaptability, data privacy, and scalability, future improvements—such as mobile integration and advanced AI features—can further strengthen system performance and impact.