The Role of Facial Recognition Technology in Strengthening Academic Integrity in Higher Education E-Learning

Abstract

The rapid growth of higher academic online education has posed new challenges to academic integrity, particularly in the legitimization of student identity and assuring of authentic classes. Despite the widespread use of e-learning platforms, most of the existing systems lack reliable methods for real-time verification during online sessions. This paper presents the opportunities of facial recognition technology in solving these problems by creating Learnify which is an e-learning attendance management system. The system automates real-time attendance monitoring to validate student presence and identity during online sessions. Learnify was created using PHP, Python, Flask, MySQL, and OpenCV and evaluated under the controlled conditions to assess its performance, usability, and influence on the ethical process of learning. The experimental results showed that the Learnify achieved the highest facial recognition confidence score of 81.95, while the System Usability Scale (SUS) result revealed that more than 80% of the participants agreed that Learnify is user-friendly and time-saving. Studies have shown that implementation of facial recognition in the e-learning systems can enhance accountability, reduce impersonation, and create fairness in online learning. The study highlights the importance of moral data management and technological reliability in supporting academic honesty in online education settings.