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Nature of Computation and Communication. 9th EAI International Conference, ICTCC 2023, Ho Chi Minh City, Vietnam, October 26-27, 2023, Proceedings

Research Article

Advancing Online Education: An Artificial Intelligence Applied System for Monitoring and Improving Employee Engagement in Enterprise Information Systems

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-59462-5_1,
        author={Nguyen Thanh Son and Trong Tien Hoang and Satyam Mishra and Nguyen Thi Bich Thuy and Tran Huu Tam and Cong-Doan Truong},
        title={Advancing Online Education: An Artificial Intelligence Applied System for Monitoring and Improving Employee Engagement in Enterprise Information Systems},
        proceedings={Nature of Computation and Communication. 9th EAI International Conference, ICTCC 2023, Ho Chi Minh City, Vietnam, October 26-27, 2023, Proceedings},
        proceedings_a={ICTCC},
        year={2024},
        month={5},
        keywords={Online Learning Learner Focus Real-Time Attention Quantification Convolutional Neural Network (CNN) MobileNet Emotion Detection Concentration Index (CI)},
        doi={10.1007/978-3-031-59462-5_1}
    }
    
  • Nguyen Thanh Son
    Trong Tien Hoang
    Satyam Mishra
    Nguyen Thi Bich Thuy
    Tran Huu Tam
    Cong-Doan Truong
    Year: 2024
    Advancing Online Education: An Artificial Intelligence Applied System for Monitoring and Improving Employee Engagement in Enterprise Information Systems
    ICTCC
    Springer
    DOI: 10.1007/978-3-031-59462-5_1
Nguyen Thanh Son, Trong Tien Hoang1, Satyam Mishra1, Nguyen Thi Bich Thuy2, Tran Huu Tam, Cong-Doan Truong1,*
  • 1: International School
  • 2: University of Science
*Contact email: tcdoan@vnu.edu.vn

Abstract

Online learning has gained significant popularity, but maintaining learner focus remains a challenge, especially in financial enterprise training systems. The need for training has increased with banking and finance digitalization trends, yet high learning curves and prolonged sessions often lead to distractions. This research introduces an online learning tool that monitors and quantifies learner attention in real-time. Using the MobileNet Convolutional Neural Network, we detect seven core emotions, which, combined with attention scores, form a Concentration Index (CI). Learners are then categorized as “Highly-engaged,” “Normally Engaged,” or “Disengaged.” With 70% accuracy on training and 65% on testing, our engagement metrics provide actionable insights for educators and administrators, enhancing virtual learning and aiding in analytical problem-solving strategies.

Keywords
Online Learning Learner Focus Real-Time Attention Quantification Convolutional Neural Network (CNN) MobileNet Emotion Detection Concentration Index (CI)
Published
2024-05-03
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-59462-5_1
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