AI-Based Real-Time Class Engagement Emotions Monitoring System

Title

AI-Based Real-Time Class Engagement Emotions Monitoring System

Creator

Praveen Kumar, T.; Joy, Justin

Description

This chapter introduces an AI-based system for real-time monitoring of student engagement by analyzing emotional responses and attention levels during classroom sessions. Using a camera placed in front of students, the system applies computer vision algorithms to detect focus and distraction through eye movements and facial expressions. The core of the system is the Emo-Engage Analysis framework, which classifies engagement into three levels based on eye retention, duration of attentiveness, and indicators of positive emotional response. Drawing on recent research in emotional and attentional regulation, this method offers a fine-grained analysis of student engagement. Aggregated engagement data allow instructors to assess both individual and group dynamics throughout a lesson. These insights support the evaluation of teaching strategies and provide meaningful feedback on instructional impact, helping educators adapt their methods to foster more effective and emotionally supportive learning environments. 2026, IGI Global Scientific Publishing. All rights reserved.

Source

Transforming Education With Data Science in the AI Era;pp.149-166

Date

01-01-2025

Publisher

IGI Global

Coverage

Praveen Kumar T., Manipal Academy of Higher Education, MAHE School of Business, United Arab Emirates; Joy J., Christ University, Bangalore, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISBN: 979-833732187-5; 979-833732185-1;

Format

online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.4018/979-8-3373-2185-1.ch006

https://www.scopus.com/pages/publications/105021205969?origin=resultslist