Student attendance and evaluation system : A review

In recent years, technologies have brought about significant changes in education, with digitization becoming a key feature that can enhance the quality and effectiveness of the educational process. Traditional manual attendance and performance assessment systems face several issues, including time wastage, human error, and data loss. As a result, the adoption of technology-based systems that focus on RFID, Arduino, facial recognition, and machine learning technologies has led to increased efficiency and accuracy by automating these processes. Previous studies have explored a variety of approaches and techniques to achieve these goals, such as using RFID for automatic attendance recording, Arduino systems for automated testing, and machine learning algorithms for analyzing academic performance. However, these systems also face challenges, including financial constraints, privacy concerns, and difficulties in scalability. Therefore, this paper aims to provide a comprehensive review of these studies by examining their methodologies, results, and challenges.