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An Experimental Platform for Real-Time Students Engagement Measurements from Video in STEM Classrooms.

Islam Alkabbany1, Asem M Ali1, Chris Foreman1

  • 1Electrical and Computer Engineering Department, University of Louisville, Louisville, KY 40292, USA.

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|February 11, 2023
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Summary

This study introduces an AI-powered system to automatically measure student engagement in real-time by analyzing behavioral and emotional cues. The innovative biometric sensor network (BSN) offers accurate, flexible engagement assessment for improved educational interventions.

Keywords:
AIbehavioral engagementemotional engagementstudent engagement

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Area of Science:

  • Educational Technology
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Measuring student engagement is crucial for timely educational interventions.
  • Existing methods may lack real-time capabilities or flexibility.
  • Understanding behavioral and emotional engagement is key to effective learning.

Purpose of the Study:

  • To propose a real-time automatic system for measuring student engagement.
  • To investigate behavioral and emotional engagement components.
  • To develop a flexible and accurate framework for diverse educational settings.

Main Methods:

  • Utilized a biometric sensor network (BSN) with cameras and high-performance computing.
  • Captured low-level features: head poses, eye gaze, body movements, facial emotions.
  • Trained an AI-based model to estimate behavioral and emotional engagement.

Main Results:

  • The proposed framework demonstrated higher accuracy in estimating engagement compared to state-of-the-art methods.
  • The system proved flexible for application in various educational environments.
  • Enabled quantitative comparison of different teaching methodologies.

Conclusions:

  • The developed AI-based system provides an accurate and flexible solution for real-time student engagement measurement.
  • This technology can significantly enhance teaching strategies and learning outcomes.
  • Facilitates data-driven insights for educational research and practice.