Enhancing University Admission Screening with AI-Based Document Verification in Minna LGA, Niger State
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Background of the Study
University admissions are a critical process for ensuring that qualified students are admitted into higher education institutions. However, the admission process is often vulnerable to fraudulent activities, including the submission of falsified documents, incorrect information, or identity theft. To combat these issues, many institutions are increasingly turning to automated systems powered by Artificial Intelligence (AI) for document verification.
AI-based document verification systems can analyze and authenticate documents, such as academic certificates, identification cards, and application forms, by comparing them with original databases and verifying their legitimacy. In Minna LGA, Niger State, the current university admission screening process involves manual document verification, which is prone to human error and inefficiencies. This research aims to explore the application of AI-based document verification systems in enhancing the university admission screening process in Minna, ensuring faster, more reliable, and secure student intake.
Statement of the Problem
At universities in Minna LGA, Niger State, the manual document verification process during admissions has led to issues such as the acceptance of fraudulent applications, administrative delays, and potential security breaches. The introduction of AI-based document verification systems could address these challenges, offering a more efficient, accurate, and secure means of verifying applicants' credentials. However, there is limited research on the feasibility and effectiveness of such systems in this region's university admission process.
Objectives of the Study
1. To design and implement an AI-based document verification system for university admission screening in Minna LGA, Niger State.
2. To evaluate the effectiveness of the AI-based system in detecting fraudulent documents and reducing errors during the admission process.
3. To assess the potential benefits and challenges of implementing AI-based document verification systems in university admissions.
Research Questions
1. How effective is the AI-based document verification system in detecting fraudulent documents during university admission screening?
2. What are the perceptions of applicants and admission officers regarding the AI-based document verification system?
3. What challenges and limitations are associated with implementing AI-based document verification in university admissions?
Research Hypotheses
1. The AI-based document verification system significantly reduces the number of fraudulent documents accepted during university admission screening.
2. Applicants and admission officers have a positive perception of the AI-based document verification system.
3. The implementation of AI-based document verification systems faces challenges related to infrastructure, data security, and system integration.
Significance of the Study
This study will offer valuable insights into the benefits and challenges of incorporating AI-based document verification in university admissions, enhancing the security, efficiency, and reliability of the admission process in Minna LGA, Niger State.
Scope and Limitations of the Study
The study will focus on the design, implementation, and evaluation of AI-based document verification systems in university admission processes in Minna LGA, Niger State. Limitations include the availability of technology infrastructure, resistance to change from administrative staff, and concerns related to privacy and data security.
Definitions of Terms
• AI-Based Document Verification: A system that uses artificial intelligence to verify the authenticity of documents submitted during university admission applications.
• Admission Screening: The process of reviewing and verifying applicants' qualifications and documents to determine their eligibility for university admission.
• Fraudulent Documents: Documents that have been altered or fabricated with the intention to deceive the admissions process.
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