Detail of Publication

Text Language	Japanese
Authors	Kazuaki Nomura,Olivier Augereau,Motoi Iwata,Koichi Kise
Title	Estimation of Student臓��s Engagement with a Pressure Mat and a Web Camera
Location	多��孫息���ﾃ�遜続��族単 ��竪多����捉続��遜測族��続��造��孫息続��存側袖脱族単(ALST)
Reviewed or not	Not reviewed
Month & Year	July 2019
Abstract	It is important for teachers to grasp students臓�� engagement in order to improve the quality of lectures. When they find that their students are not engaged in the lecture, they can give advice to the students to pay attention to the lecture. However, in the e-learning environment, there is no teacher to grasp the student臓��s engagement. So if the student loses his engagement, no one can help him to regain it. It may cause ineffective learning. The purpose of this study is to grasp the student臓��s engagement by using a pressure mat and web camera. We recorded the students臓�� postural data, that is upper body pressure distribution and upper body pose information, while they were taking e-learning lectures. In order to get the body to pose information from a web camera, we used a human pose estimation library called OpenPose. Then we extracted 38 features from upper body pressure distribution and 33 features from upper body pose information for every minute. We selected effective features by using the Forward Stepwise Selection. Lastly, we estimate whether he or she was engaged in or not with a Support Vector Machine. As a result, the average accuracy was 79.3% for student-dependent estimation. This result shows it is possible to predictthe student臓��s engagement automatically.

• Entry for BibTeX

  @InCollection{Nomura2019,
    author =	{Kazuaki Nomura and Olivier Augereau and Motoi Iwata and Koichi Kise},
    title =	{Estimation of Student臓��s Engagement with a Pressure Mat and a Web Camera},
    year =	2019,
    month =	jul,
    location =	{多��孫息���ﾃ�遜続��族単 ��竪多����捉続��遜測族��続��造��孫息続��存側袖脱族単(ALST)}
  }
  
  
  

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