Educational Datafication in Smart Attendance Systems: A Bibliometric and Science Mapping Analysis - Purnamawati, Purnamawati; Nuridayanti, Nuridayanti; Akil, Muhammad; Iskandar, Akbar; Pratama, Muh Riyaldi (Journal of Applied Science, Engineering, Technology, and Education, 2026)
Smart attendance systems have evolved from routine administrative tools into data-driven mechanisms for monitoring, prediction, and institutional decision-making in education. However, limited attention has been given to how this transformation is understood from educational, ethical, and socio-technical perspectives. This study aims to examine the development of smart attendance system research using a bibliometric and science mapping approach. A dataset of 108 Scopus-indexed journal articles published between 2016 and 2025 was analyzed using VOSviewer and Biblioshiny. The findings reveal a clear shift from RFID-based and manual verification systems toward artificial intelligence-driven approaches, including facial recognition, deep learning, computer vision, and predictive analytics. Despite these technological advancements, the literature remains predominantly technocentric, with major emphasis on system efficiency, authentication, and automation, while issues related to privacy, consent, fairness, and surveillance receive limited attention. This study identifies an “ethical silence” in the field and suggests that attendance is increasingly redefined as a machine-verifiable construct rather than a pedagogical expression of engagement. Future research should integrate data ethics, learning analytics, and student agency to support more balanced educational practices.