Evaluation of AI-Based Smart Course Registration Assistance Systems in Federal University, Gusau, Zamfara State
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Background of the Study
The course registration process in universities often involves complex procedures that can be time-consuming for both students and administrative staff. Federal University Gusau, like many other institutions, faces challenges in efficiently managing course registrations, especially during peak periods when student demand for courses exceeds available resources. Manual registration processes often lead to errors, delays, and confusion, negatively affecting the academic experience. AI-based smart course registration assistance systems have the potential to alleviate these challenges by automating key tasks such as course selection, conflict resolution, and prerequisite verification. These systems use machine learning algorithms to recommend courses based on students' academic history, preferences, and degree requirements. This study evaluates the effectiveness of an AI-based course registration assistance system implemented at Federal University Gusau, focusing on its efficiency, accuracy, and user satisfaction.
Statement of the Problem
Course registration at Federal University Gusau remains a cumbersome process for both students and administrative staff. Manual systems and outdated registration software result in delayed registrations, errors in course allocation, and a lack of personalized guidance for students. These inefficiencies lead to student dissatisfaction and administrative bottlenecks. There is a need to implement an AI-powered system that can streamline the registration process, automate tasks, and provide personalized course recommendations.
Objectives of the Study
1. To design and implement an AI-based smart course registration assistance system for students at Federal University Gusau.
2. To assess the impact of the AI-based system on the efficiency and accuracy of course registration.
3. To evaluate student and administrative staff satisfaction with the AI-based registration system.
Research Questions
1. How efficient is the AI-based course registration system in managing student course selections?
2. To what extent does the AI-based system improve the accuracy of course registration and minimize errors?
3. How do students and administrative staff perceive the AI-based registration system in terms of usability and satisfaction?
Research Hypotheses
1. The AI-based registration system improves the efficiency of course registration compared to traditional methods.
2. The AI-based system reduces errors in course registration and enhances accuracy.
3. Students and administrative staff are more satisfied with the AI-based registration system than with traditional registration methods.
Significance of the Study
This study aims to improve the course registration process at Federal University Gusau by implementing an AI-based system that enhances efficiency, accuracy, and user satisfaction. The findings could serve as a model for other universities seeking to modernize their course registration systems.
Scope and Limitations of the Study
The scope of the study is limited to the evaluation of the AI-based course registration assistance system at Federal University Gusau. The study will focus on specific academic departments, and the limitations may include challenges in data collection and system integration with existing infrastructure.
Definitions of Terms
• AI-Based Course Registration Assistance System: A system powered by artificial intelligence that automates the process of course selection, registration, and conflict resolution.
• Course Registration: The process by which students select and enroll in courses for a particular academic term.
• Machine Learning: A subset of artificial intelligence that involves algorithms that allow computers to learn from and make predictions based on data.
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