Online Classroom Enagement Observation using Deep Learning

被引:0
|
作者
Duraisamy, Prakash [1 ]
Van Haneghan, James [2 ]
Thomas, Jude [1 ]
Gadaley, Ramya Sri [3 ]
Jackson [4 ]
机构
[1] Univ S Alabama, Dept Comp Sci, Mobile, AL 36688 USA
[2] Univ S Alabama, Dept Educ, Mobile, AL USA
[3] Univ S Alabama, Dept Informat Sci, Mobile, AL USA
[4] Univ North Texas, Dept Math, Denton, TX USA
来源
PROCEEDINGS OF 2020 IEEE LEARNING WITH MOOCS (LWMOOCS): 4TH INDUSTRIAL REVOLUTION: CHALLENGES AND OPPORTUNITIES | 2020年
关键词
engagement; class; computer vision; deep learning;
D O I
10.1109/lwmoocs50143.2020.9234339
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Classroom engagement is critical for both students and professors in order to have a successful experience at a college or university. In modern days due to a growing number of various digital distractions and other external influences, keeping student engaged is a challenging problem. This work focuses on how to measure student engagement using facial gestures along with deep learning techniques. In this work. we took seven facial gestures for our image classification to measure student engagement. We use deep learning techniques to classify the gestures and we compute cross correlation between student gestures and the instructor's teaching methodologies.
引用
收藏
页码:81 / 83
页数:3
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