SchedAI: An AI-Driven Faculty Preference-Based Scheduler

The university faced significant challenges in creating a time schedule for the college departments of Western Mindanao State University (WMSU), relying on a traditional manual method that required incorporating various requirements and constraints. This process was time-consuming, prone to errors, and could take anywhere from a day to a week to complete. To address these issues, “SchedAI” was developed to automate the scheduling process using a backtracking algorithm. Designed for efficiency, “SchedAI” simplifies scheduling by integrating faculty preferences and institutional constraints, enabling the quick creation of dynamic and conflict-free schedules. Benchmark tests show that while the greedy algorithm is faster, it often generates overlapping schedules, whereas the backtracking algorithm produces schedules with zero conflicts. The system was evaluated based on functionality, usability, and reliability through quantitative data collection from faculty members. Results showed an average faculty satisfaction rating of 3.37, indicating positive performance while highlighting areas for improvement. Future enhancements may include integrating blockchain technology for security, considering student preferences, generating multiple scheduling options, and implementing a SMART scheduling system. “SchedAI” marks a significant step toward modernizing scheduling at WMSU by reducing administrative workload, minimizing errors, improving stakeholder satisfaction, and paving the way for future technological advancements in educational administration.