SCHOOL MANAGEMENT SYSTEM: ALUMNI MANAGEMENT SYSTEM W/ AI-BASED CHATBOT FOR INQUIRIES AND SOLUTIONS

Abstract

Building and maintaining strong alumni relationships is vital for educational institutions, yet many still rely on outdated manual systems that hinder effective communication, data accuracy, and engagement. Common challenges include fragmented data, outdated records, and slow response times to alumni inquiries. To address these issues, the researchers developed a capstone project titled School Management System: Alumni Management System with AI-Based Chatbot for Inquiries and Solutions. This system provides a centralized platform to manage alumni services efficiently. It also proposes the future integration of an AI-powered chatbot to streamline communication, enhance record accuracy, and strengthen alumni-institution connections. The project was developed using the Agile Scrum methodology to support iterative, collaborative development. Stakeholder requirements were gathered through interviews and observations, then translated into user stories and use cases to guide system design. A microservices architecture was employed to ensure modularity, scalability, and ease of maintenance. Module communication was facilitated through RESTful APIs, while MySQL—managed via phpMyAdmin—served as the database system. Core system features included an alumni ID application, an alumni tracer, a career opportunities portal, secure access controls, and a digital resource library. An AI-powered chatbot was also proposed to handle alumni inquiries and is scheduled for implementation in future iterations. Development sprints followed the standard Agile cycle, including sprint planning, execution, review, and retrospectives, to ensure consistent, incremental progress. The system provides alumni with a centralized dashboard to apply for IDs, track application status, explore career opportunities, and access institutional resources. Administrative users are equipped with tools to manage alumni records, enforce access controls, and monitor engagement through built-in dashboard analytics. Real-time data synchronization and structured data storage contribute to the system’s accuracy and reliability. Stakeholder feedback confirmed improvements in both usability and alumni engagement. While the AI-powered chatbot remains a planned feature, it is intended to further enhance communication and support in future system iterations. This project demonstrates how digital systems can modernize alumni engagement by centralizing services and enhancing accessibility. Its modular architecture and secure design support long-term maintainability and scalability. Although the AI-powered chatbot has not yet been implemented, its planned integration is expected to reduce administrative workload and improve support responsiveness. Overall, the system lays a solid foundation for efficient, scalable, and sustainable alumni management.