Optimization of AI-Based Automated Class Scheduling in Kogi State Polytechnic, Lokoja, Kogi State
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- NGN 5000
Background of the study
Class scheduling is a crucial aspect of academic administration, and in large educational institutions like Kogi State Polytechnic, Lokoja, managing the schedules of hundreds or thousands of students and faculty can be a complex and time-consuming task. Traditional class scheduling methods often involve manual calculations, leading to inefficiencies, scheduling conflicts, and suboptimal resource allocation. The integration of artificial intelligence (AI) into class scheduling systems offers a promising solution by automating the process and optimizing the allocation of resources such as classrooms, instructors, and timeslots. AI-based scheduling systems can analyze various constraints, including course requirements, instructor availability, and room capacities, to create optimized schedules that minimize conflicts and maximize the use of available resources. This study aims to design and implement an AI-based automated class scheduling system at Kogi State Polytechnic, Lokoja, with the goal of improving scheduling efficiency and reducing administrative workload.
Statement of the problem
At Kogi State Polytechnic, Lokoja, class scheduling is often hindered by scheduling conflicts, limited resources, and administrative inefficiencies. The manual scheduling process is time-consuming and prone to errors, leading to dissatisfaction among students and faculty members. The absence of an AI-based scheduling system results in suboptimal allocation of classrooms and instructors, as well as unnecessary conflicts between courses. Implementing an AI-based automated class scheduling system could significantly improve the efficiency of the scheduling process, ensuring that resources are used optimally and that students and faculty experience fewer conflicts.
Objectives of the study
1. To design and implement an AI-based automated class scheduling system at Kogi State Polytechnic, Lokoja.
2. To evaluate the effectiveness of the AI-based scheduling system in reducing scheduling conflicts and optimizing resource allocation.
3. To assess the impact of the AI-powered system on improving administrative efficiency and faculty satisfaction.
Research questions
1. How effective is the AI-based automated class scheduling system in minimizing scheduling conflicts and optimizing resource allocation?
2. What impact does the AI scheduling system have on reducing administrative workload at Kogi State Polytechnic?
3. How do students and faculty perceive the efficiency of the AI-powered scheduling system?
Research hypotheses
1. The AI-based scheduling system will significantly reduce scheduling conflicts compared to the traditional manual scheduling process.
2. The implementation of the AI scheduling system will improve administrative efficiency in managing class schedules.
3. Students and faculty will perceive the AI-powered scheduling system as more efficient and effective than the current scheduling methods.
Significance of the study
This study will contribute to the development of AI-powered solutions for class scheduling in higher education institutions. The findings will provide valuable insights into how AI can optimize administrative processes, reduce scheduling conflicts, and improve the overall efficiency of class management.
Scope and limitations of the study
The study will focus on the design and implementation of the AI-based class scheduling system at Kogi State Polytechnic, Lokoja. Limitations include potential resistance to change from faculty and administrative staff, as well as challenges in integrating the AI system with existing administrative structures.
Definitions of terms
• Class Scheduling: The process of assigning timeslots, classrooms, and instructors to academic courses.
• AI-Based Automated Scheduling: The use of artificial intelligence algorithms to automatically generate optimized class schedules based on various constraints and requirements.
• Optimization: The process of making the best use of available resources to achieve the most efficient and effective outcomes.
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