Implementation of an E-Attendance Monitoring System Using Facial Recognition for Secondary Schools in Dutse Local Government Area, Jigawa State
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Background of the Study
Student attendance monitoring is an essential aspect of school administration, as it directly impacts academic performance, discipline, and overall school management. Traditionally, attendance tracking has been conducted manually, requiring teachers to mark attendance registers daily. However, this process is prone to errors, inefficiencies, and manipulation, leading to inaccurate records and difficulties in monitoring student participation (Ahmed & Yusuf, 2024). With the advancement of biometric technologies, facial recognition systems have emerged as a viable alternative for improving attendance tracking in educational institutions.
Facial recognition technology utilizes artificial intelligence (AI) and deep learning to authenticate and verify individuals based on unique facial features. It offers a contactless, efficient, and automated method of attendance monitoring, reducing human intervention and improving accuracy (Okonkwo & Musa, 2023). In secondary schools within Dutse Local Government Area, the manual attendance system poses several challenges, including time consumption, data inconsistencies, and the possibility of proxy attendance, where students sign in for absent peers (Bello & Danjuma, 2024). An e-attendance system using facial recognition can eliminate these challenges by ensuring real-time authentication, preventing attendance fraud, and providing seamless integration with school databases.
Globally, institutions are increasingly adopting facial recognition for various security and administrative purposes, including automated attendance tracking (Usman & Bello, 2024). The integration of facial recognition technology in schools enhances efficiency, reduces administrative workload, and ensures accurate attendance records. Despite these advantages, many secondary schools in Dutse still rely on outdated attendance methods, limiting their ability to efficiently track student participation (Akinpelu & Yusuf, 2024). This study seeks to implement an e-attendance monitoring system that leverages facial recognition to enhance attendance tracking, improve record accuracy, and reduce administrative burdens in secondary schools in Dutse Local Government Area, Jigawa State.
Statement of the Problem
Manual attendance tracking methods in secondary schools are inefficient and prone to manipulation, leading to inaccurate records and potential academic and disciplinary issues (Ahmed & Bello, 2024). Teachers often face challenges in verifying the authenticity of attendance records, particularly in large classrooms where proxy attendance is common. Additionally, manual attendance processes consume valuable instructional time, affecting overall classroom productivity (Okoro & Musa, 2024).
While biometric technologies such as fingerprint recognition have been introduced in some educational institutions, they have limitations, including hygiene concerns, high maintenance costs, and difficulties in scanning worn or dirty fingers (Usman & Danjuma, 2024). Facial recognition technology provides a more efficient and non-intrusive alternative, enabling seamless attendance tracking without requiring physical contact. However, its implementation in secondary schools within Dutse Local Government Area has been minimal due to technological constraints, concerns about data security, and resistance to change (Okonkwo & Bello, 2024).
This study aims to address these challenges by developing and implementing an e-attendance monitoring system using facial recognition, ensuring accurate attendance tracking, reducing administrative workload, and minimizing the risk of attendance fraud.
Objectives of the Study
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To develop and implement an e-attendance monitoring system using facial recognition for secondary schools in Dutse Local Government Area.
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To evaluate the accuracy, efficiency, and reliability of the facial recognition-based attendance system compared to traditional methods.
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To assess the perceptions and acceptance of the facial recognition e-attendance system among teachers, students, and school administrators.
Research Questions
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How effective is the facial recognition-based e-attendance monitoring system in improving attendance tracking accuracy and efficiency?
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What are the comparative differences between the facial recognition system and traditional attendance tracking methods?
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How do teachers, students, and administrators perceive the usability and effectiveness of the facial recognition-based e-attendance system?
Research Hypotheses
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The facial recognition-based e-attendance monitoring system significantly improves accuracy and efficiency compared to manual attendance tracking.
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The implementation of the facial recognition system reduces cases of attendance fraud, including proxy attendance.
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Teachers, students, and administrators will have a positive perception of the usability and effectiveness of the e-attendance system.
Significance of the Study
This study is significant as it introduces an innovative approach to attendance tracking in secondary schools, leveraging facial recognition technology to enhance accuracy, efficiency, and security. The findings will provide valuable insights into the adoption of biometric technologies in education, supporting school administrators in making data-driven decisions to improve attendance monitoring. Additionally, the system will reduce administrative burdens on teachers, minimize attendance fraud, and ensure real-time student tracking for better academic and disciplinary management.
Scope and Limitations of the Study
This study focuses on the implementation of an e-attendance monitoring system using facial recognition in secondary schools within Dutse Local Government Area, Jigawa State. The research evaluates the system’s effectiveness in accuracy, efficiency, and user acceptance. It does not cover other biometric methods such as fingerprint or iris recognition. Limitations may include potential resistance to AI adoption, technical constraints, and concerns over student data privacy.
Definitions of Terms
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E-Attendance Monitoring System: A digital system that automates student attendance tracking using technology.
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Facial Recognition: A biometric technology that identifies and verifies individuals based on their unique facial features.
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Proxy Attendance: A fraudulent practice where a student signs in or is marked present on behalf of another absent student.
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