Bibliometric Analysis in AI Assistant for e-learning to Focus Students by Using Camera, Keyboard and Mouse

Abstract

In recent years, artificial intelligence has been a widely researched topic, particularly in education. This study evaluates the role of AI assistants in enhancing student motivation and focus in e-Iearning by conducting a bibliometric analysis of academic publications. In our study, we analyzed the use of AI assistants in e-Iearning to help students stay focused through the use of cameras, keyboards, and mice, addressing student distraction in e-Iearning. We propose that AI assistants can support teachers in motivating students and improving their engagement. To conduct our analysis, we examined data from the last ten years (2015-2025) using the Web of Science database and bibliometric analysis tools such as VOSviewer. We focused on publications categorized under Computer Science - Artificial Intelligence, Education - Educational Research, and Computer Science - Software Engineering. A total of 676 academic publications ten years were analyzed. The highest number of publications occurred in 2024, with 'Artificial Intelligence,' 'ChatGPT,' and 'Machine Learning' being the most frequently used keywords. The primary objective of this study was to examine previous research that applied AI in e-education, exploring its impact on students through various approaches. Based on our findings, AI assistants in e-Iearning are expected to playa crucial role not only in the present but also in the coming years. Our results indicate that AI-assisted educational technologies have rapidly evolved and are significantly improving student engagement in e-Iearning environments. © 2025 IEEE.