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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM42936
Volume:
9 |
3 |
Mar 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This project introduces the Smart Attendance and Behavioural Analytic System, designed to enhance student engagement and learning outcomes in modern educational environments. Utilizing advanced voice recognition technology, the system automates attendance marking, allowing students to check in simply by stating their name or a designated phrase. This automation significantly reduces the time and effort required for manual attendance procedures. The system incorporates Natural Language Processing (NLP) and Machine Learning (ML) techniques to analyze students’ vocal expressions, tone, and speech patterns, providing real-time insights into their emotional and engagement states during classes, such as attentiveness, confusion, and interest. Equipped with a user-friendly dashboard, educators can effortlessly track attendance, visualize engagement metrics, and identify behavioural patterns over time. Equipped with a user-friendly dashboard, educators can effortlessly track attendance, visualize engagement metrics, and identify behavioral patterns over time. The system also issues alerts for drops in student engagement or persistent absenteeism, facilitating timely interventions. By integrating with Learning Management Systems (LMS), it streamlines attendance reporting and behavioural analysis, allowing institutions to monitor and support students effectively. The system also issues alerts for drops in student engagement or persistent absenteeism, facilitating timely interventions. By integrating with Learning Management Systems (LMS), it streamlines attendance reporting and behavioral analysis, allowing institutions to monitor and support students effectively.
KEYWORDS
Publication Date
3/24/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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