학술논문

Learners’ Efficiency Prediction Using Facial Behavior Analysis
Document Type
Conference
Source
2021 IEEE International Conference on Image Processing (ICIP) Image Processing (ICIP), 2021 IEEE International Conference on. :1084-1088 Sep, 2021
Subject
Computing and Processing
Signal Processing and Analysis
Measurement
Analytical models
Portable computers
Electronic learning
Webcams
Image processing
Sociology
E-learning
learners’ efficiency
convolutional neural network
facial behavior analysis
Language
ISSN
2381-8549
Abstract
In the e-learning context, how much the learner is concentrated and engaged, or the learners’ efficiency, is essential for providing adaptive and flexible materials, timely suggestions, etc., which can lead to efficient learning. In this work, we explore to predict learners’ efficiency with a realistic configuration, in which we use a webcam or a laptop PC’s built-in camera. Specifically, we first provide a feasible definition of the learners’ efficiency, and based on this definition, we predict one’s efficiency from facial behavior. We predict the learners’ efficiency using various convolutional neural networks. Results are discussed using different evaluation metrics.