Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)

<Previous Article In Volume
Next Article In Volume>

Generating An Automation System for Detection Of Disengaged Students During Online Classes

Authors
K. Sri Rama Murthy1, *, Chandana Bhavya Srivilli2, Daida Geethanjali3, Kottisa Aashrita4
1Assistant Professor, Dept of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India
2Student, Dept. Of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India
3Student, Dept. Of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India
4Student, Dept. Of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India
*Corresponding author. Email: sriramamurthy_k@vnrvjiet.in
Corresponding Author
K. Sri Rama Murthy
Available Online 22 June 2025.
DOI
10.2991/978-94-6463-738-0_43How to use a DOI?
Keywords
Online Learning; Faculty feedback; Datasets; Behavioral Indicators; Distractions; Alerting System; Natural Language Processing
Abstract

With the increased popularity of massive open online courses, ensuring active engagement of the students is a prime challenge. This proposed system tries to address that need by proposing an automated mechanism for detecting a disengaged student during the online class. Advanced algorithms of machine learning and computer vision techniques are employed to analyze facial expressions, eye movements, and other behavioral indicators, thereby determining the levels of engagement in real time. The technique employs the ability of CNNs in achieving more accurate and robust feature extraction of images with accurate prediction. This will generate more informative reports in detail for analysis of time series trends regarding engagement patterns to assist educators and institutions in formulating and gathering important data that will eventually enable improvement in methodologies in teaching and modification of the teaching delivery approach for more interaction on an online platform. By quickly detecting disengaged students, the system encourages proactive action for reconnecting students with the course, which ensures improved participation and motivation overall. The new technology seeks to connect classroom monitoring practices in the real world with online learning so that the students involved stay active with their learning.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
Series
Advances in Intelligent Systems Research
Publication Date
22 June 2025
ISBN
978-94-6463-738-0
ISSN
1951-6851
DOI
10.2991/978-94-6463-738-0_43How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - K. Sri Rama Murthy
AU  - Chandana Bhavya Srivilli
AU  - Daida Geethanjali
AU  - Kottisa Aashrita
PY  - 2025
DA  - 2025/06/22
TI  - Generating An Automation System for Detection Of Disengaged Students During Online Classes
BT  - Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
PB  - Atlantis Press
SP  - 535
EP  - 551
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-738-0_43
DO  - 10.2991/978-94-6463-738-0_43
ID  - Murthy2025
ER  -