Design of an Automated Algorithm for Exam Scheduling: A Case Study of Ahmadu Bello University, Zaria (Zaria LGA, Kaduna State)
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Background of the Study
Exam scheduling in universities is a complex task that involves allocating exam slots, rooms, and resources based on various constraints, such as room capacity, student schedules, and lecturer availability (Nguyen et al., 2024). Traditional scheduling methods often lead to conflicts, underutilized resources, and administrative inefficiencies. The adoption of AI-based scheduling algorithms can streamline this process by considering multiple factors simultaneously and generating optimized schedules (Zhao & Wang, 2023). At Ahmadu Bello University, Zaria, this approach could be particularly useful given the large number of students and courses offered. Implementing an automated exam scheduling algorithm would help minimize scheduling conflicts and optimize resource usage, enhancing the overall exam administration process.
Statement of the Problem
Ahmadu Bello University, Zaria, faces significant challenges in scheduling exams for its large student population. The current manual scheduling system is inefficient, often resulting in conflicts, overcrowded exam halls, and resource mismanagement. These issues contribute to delays and inefficiencies in the academic process. An automated algorithm powered by AI could address these problems by providing a more efficient and effective approach to scheduling exams.
Objectives of the Study
- To design and implement an AI-based automated exam scheduling algorithm for Ahmadu Bello University, Zaria.
- To evaluate the effectiveness of the AI algorithm in optimizing the exam scheduling process.
- To assess the user experience of students and staff with the automated exam scheduling system.
Research Questions
- How effective is the AI-based exam scheduling algorithm in reducing scheduling conflicts and improving resource allocation?
- What are the perceptions of students and staff regarding the usability and efficiency of the AI scheduling system?
- How does the AI-based algorithm compare to traditional scheduling methods in terms of resource optimization and efficiency?
Research Hypotheses
- The AI-based exam scheduling algorithm will significantly reduce scheduling conflicts and improve resource allocation.
- Students and staff will report higher satisfaction with the AI-based exam scheduling system compared to traditional methods.
- The AI algorithm will improve the efficiency of the scheduling process and reduce administrative workload.
Significance of the Study
This study will enhance the understanding of how AI can optimize complex scheduling tasks in universities. The findings will be beneficial for improving exam scheduling at Ahmadu Bello University, Zaria, and can serve as a model for other universities facing similar challenges.
Scope and Limitations of the Study
The study will focus on the design and implementation of an AI-based automated exam scheduling algorithm for Ahmadu Bello University, Zaria, and will not extend to other universities or academic activities beyond exam scheduling.
Definitions of Terms
Automated Exam Scheduling Algorithm: A software system that uses AI to generate optimized schedules for university exams, considering various constraints and requirements.
Resource Allocation: The process of assigning available resources, such as exam halls and lecturers, to scheduled exams.
AI-Based Scheduling System: A system powered by artificial intelligence that automates the scheduling of activities such as exams, based on predefined constraints and optimization criteria.
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