Work

AI-Enhanced Attention Monitoring System for Effective Learning

Year: 2025
Type: article
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.
Institution: Bharath University
Language: English
Open Access status: hybrid
OpenAlex ID: W4409617142
FWCI:
Cites:
Cited by:
Related to: 10