Enhancing University Lecture Attendance Monitoring Using Facial Recognition Technology: A Case Study of Federal University, Kashere (Kashere LGA, Gombe State)
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- NGN 5000
Background of the Study
Lecture attendance is a critical aspect of academic engagement, but it is often challenging to monitor efficiently in large university settings. Traditional attendance systems, such as sign-in sheets and roll calls, have proven ineffective in ensuring accurate and timely attendance reporting, leading to concerns about fraud and administrative inefficiencies (Jones & Liu, 2024). Facial recognition technology (FRT) has emerged as a promising solution to address these issues, offering automated and real-time attendance tracking with minimal human intervention (Khan et al., 2023).
At the Federal University, Kashere in Gombe State, the adoption of FRT could potentially streamline attendance monitoring, reduce instances of proxy attendance, and provide more reliable data for administrative purposes. The use of facial recognition has been shown to increase accuracy in attendance management and offer a more secure and efficient alternative to traditional methods (Smith et al., 2025). However, the introduction of FRT also raises concerns related to privacy, the cost of implementation, and the technological challenges of ensuring accurate identification in various conditions (Anderson & Beck, 2024).
This study seeks to explore the feasibility and effectiveness of using facial recognition technology to enhance lecture attendance monitoring at the Federal University, Kashere. By evaluating the benefits and challenges associated with FRT, the research aims to contribute to the growing body of literature on the application of biometric technologies in educational institutions.
Statement of the Problem
The traditional methods of attendance monitoring at the Federal University, Kashere are prone to inaccuracies, time-consuming processes, and the potential for fraudulent activities such as proxy attendance (Miller & Grant, 2023). The use of facial recognition technology promises to address these problems, but the system's feasibility, privacy concerns, and accuracy in a classroom setting remain largely unexplored in the context of Kashere. This research will investigate the challenges and potential benefits of implementing FRT for attendance monitoring at the university, aiming to provide empirical data on its effectiveness and practicality.
Objectives of the Study
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To evaluate the accuracy and reliability of facial recognition technology in monitoring lecture attendance at the Federal University, Kashere.
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To assess the students' and staff's perceptions of the implementation of facial recognition technology for attendance monitoring.
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To explore the potential privacy concerns and ethical implications of using facial recognition technology in an educational setting.
Research Questions
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How accurate and reliable is facial recognition technology for monitoring lecture attendance at the Federal University, Kashere?
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What are the perceptions of students and staff regarding the implementation of facial recognition for attendance monitoring?
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What are the ethical and privacy concerns associated with the use of facial recognition technology in university attendance systems?
Research Hypotheses
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Facial recognition technology provides more accurate and reliable attendance tracking compared to traditional methods at the Federal University, Kashere.
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Students and staff at the Federal University, Kashere are generally positive about the use of facial recognition technology for attendance monitoring.
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The implementation of facial recognition technology for attendance monitoring raises significant ethical and privacy concerns among students and staff.
Significance of the Study
This research will contribute to the ongoing conversation about the use of biometric technologies in education, offering insights into the practical applications, benefits, and challenges of implementing facial recognition systems for attendance monitoring. The findings could serve as a guide for other universities considering similar technological solutions, helping them navigate potential pitfalls while enhancing administrative efficiency.
Scope and Limitations of the Study
This study will focus on the Federal University, Kashere, located in Kashere LGA, Gombe State. It will involve students and staff who participate in the lecture attendance process. Limitations include the potential biases in student and staff responses, as well as challenges related to the technology's implementation in a live university environment.
Definitions of Terms
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Facial Recognition Technology (FRT): A biometric system that identifies individuals based on their facial features, commonly used for authentication and monitoring purposes.
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Lecture Attendance Monitoring: The process of tracking students' presence in lecture halls, often for academic or administrative purposes.
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Biometric Technology: A form of technology that uses physiological or behavioral characteristics to identify individuals, including facial recognition, fingerprints, and retinal scans.
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