A Web-based Decision Support System for Managing Course Timetabling in Online Education

The COVID-19 pandemic precipitated an abrupt transition from traditional face-to-face instruction to online learning, posing significant challenges in managing course timetabling and ensuring efficient bandwidth utilization. This paper presents the development and implementation of a web-based Decision Support System (DSS) that employs a simulated annealing algorithm to optimize course scheduling in an online education context. Seamlessly integrated with the university's Student Information System (SIS) and Learning Management System (LMS), the DSS enables automated timetable generation and real-time data synchronization. Program coordinators can make necessary adjustments, while students and instructors access their schedules through a user-friendly interface. Experimental results demonstrate a substantial improvement in the distribution of concurrent connections compared to manually generated timetables, significantly reducing peak server loads by up to 66% and standard deviations. The proposed DSS addresses the immediate challenges of the shift to online education while offering a scalable solution for future needs, thereby enhancing the online learning experience for both students and instructors.