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Journal
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Ingenieurwesen
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Enhancing Classroom Engagement: AI-Based Analysis of Student Attention Levels
/
Identifying the Students' Attention Level by Analyzing the Sensory and Biometric Data
JoVE Journal
Ingenieurwesen
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JoVE Journal
Ingenieurwesen
Identifying the Students' Attention Level by Analyzing the Sensory and Biometric Data
Identifying the Students' Attention Level by Analyzing the Sensory and Biometric Data
Enhancing Classroom Engagement: AI-Based Analysis of Student Attention Levels
DOI:
10.3791/201553-v
•
03:08 min
•
December 15, 2023
•
Luis Marquez-Carpintero
,
Monica Pina-Navarro
,
Sergio Suescun-Ferrandiz
,
Felix Escalona
,
Francisco Gomez-Donoso
,
Rosabel Roig-Vila
,
Miguel Cazorla
1
University Institute for Computer Research
,
University of Alicante
,
2
Department of General and Specific Didactics
,
University of Alicante
Tags
Attention Level
Sensory Data
Biometric Data
Smart Watch
Gyroscope
Accelerometer
Heart Rate
Eye Tracking
Head Direction
Body Pose
Emotion Detection
Deep Learning
Attention Classifier
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Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
Hardware, Software, and Class Setup to Detect Attention Levels in Students
Identifying the Students' Attention Level by Analyzing the Sensory and Biometric Data
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