AI-Enhanced Attention Monitoring System for Effective Learning

Author(s)	Vasipalli Likhitha, Vootla Kavya, Vidhya Lakshmi PS, T.A. Krithika
Country	India
Abstract	There are numerous studies in which researchers have attempted to attract college students' attention. Many of these approximations lack quantitative evaluation and are primarily based on qualitative evaluation. This artistic creation thus targets to connect the distance among subjective and quantitative methodologies to developing understudy commitment. This study therefore routinely divides college students into attentive and inattentive RGB-D sensor statistics using machine learning algorithms (K-manner and SVM). The National Academy of Engineering has done a lot of research on this topic, and the findings of this study can be used to inform and support teaching methods for teachers of all levels. The ability of teachers to implement individualized learning methods is a major goal of their work. In this view, contraption learning calculations are utilized for educational purposes.
Keywords	Student Level, Behaviour, Monitoring, Online Class, Artificial Intelligence
Field	Engineering
Published In	Volume 7, Issue 2, March-April 2025
Published On	2025-04-18
DOI	https://doi.org/10.36948/ijfmr.2025.v07i02.42347
Short DOI	https://doi.org/g9f4ww

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International Journal For Multidisciplinary Research