Design of AI-Based Fraud Detection Systems for University Admissions in Kano University of Science and Technology, Wudil, Kano State
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Background of the Study
Fraudulent activities in university admissions have become a significant concern for academic institutions worldwide. These activities can include falsification of documents, impersonation during entrance exams, and manipulation of admission scores. In Nigeria, such fraudulent practices have been reported across various universities, leading to the admission of unqualified candidates and the undermining of academic integrity. Traditional methods of detecting fraud in university admissions are often slow, labor-intensive, and susceptible to human error.
Artificial Intelligence (AI) presents a powerful solution for automating and enhancing the detection of fraudulent practices in university admissions. AI-based fraud detection systems can analyze large volumes of application data, identify patterns of fraud, and flag suspicious activities for further investigation. This study seeks to design an AI-based fraud detection system for Kano University of Science and Technology, Wudil, to improve the integrity and efficiency of its admission process.
Statement of the Problem
Kano University of Science and Technology, Wudil, has experienced challenges in preventing fraudulent activities in its admission process. The traditional methods of manual document verification and entrance exam monitoring have proven to be insufficient in detecting sophisticated fraud techniques. As a result, the university faces the risk of admitting students who do not meet the required academic standards. This study seeks to develop an AI-based fraud detection system to automate the detection process and improve the reliability of the university's admission process.
Objectives of the Study
1. To design an AI-based fraud detection system for the admission process at Kano University of Science and Technology, Wudil.
2. To evaluate the effectiveness of the AI-based system in identifying fraudulent activities during university admissions.
3. To assess the potential challenges and benefits of implementing an AI-based fraud detection system in university admissions.
Research Questions
1. How effective is the AI-based fraud detection system in identifying fraudulent activities during the university admissions process?
2. What are the advantages of using AI for fraud detection compared to traditional methods?
3. What challenges do university administrators face when implementing AI-based fraud detection systems?
Research Hypotheses
1. AI-based fraud detection systems are more effective in identifying fraudulent activities in university admissions compared to traditional methods.
2. The implementation of an AI-based fraud detection system improves the integrity of the university's admission process.
3. Implementing an AI-based fraud detection system in university admissions faces challenges related to data privacy, technological infrastructure, and staff training.
Significance of the Study
This study will contribute to the improvement of the admission process at Kano University of Science and Technology, Wudil, by enhancing fraud detection capabilities through AI. The findings will provide a model for other institutions seeking to implement AI-driven fraud prevention systems in their admissions. Additionally, this research will contribute to the broader understanding of AI applications in improving the integrity of academic systems.
Scope and Limitations of the Study
The study will focus on designing and implementing an AI-based fraud detection system for Kano University of Science and Technology, Wudil. The research will assess the system's effectiveness in identifying fraudulent activities and its impact on the admission process. Limitations include challenges related to data privacy, integration with existing admission systems, and resistance from staff.
Definitions of Terms
• AI-Based Fraud Detection System: A system that uses artificial intelligence to detect fraudulent activities in data, such as falsified documents or manipulated admission scores.
• Admission Process: The procedure through which students apply, are screened, and are selected for entry into a university.
• Fraudulent Activities: Deceptive actions intended to manipulate the admission process, such as falsifying academic records or impersonating candidates.
• Data Privacy: The protection of personal data to ensure it is not misused or accessed by unauthorized individuals.
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