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Paper Abstract and Keywords
Presentation 2019-03-15 11:05
A Study on Teacher Behavior Classification based on ST-GCN for Traial Lesson Support System
Sho Ooi, Yao Shunyu, Haruo Noma (Rits) ET2018-97
Abstract (in Japanese) (See Japanese page) 
(in English) A new teacher needs to give tuition from the first day at work. People who aim for the teacher can teach at teaching practices and a crammer. However, an classroom environment is different the actual school environment. In other words, the new teacher is difficult to train tuition in an actual environment. Therefore, we think that we need to develop a trial lesson system close to the actual environment for the new teacher. The trial lesson system has three functions, namely, to display the environment close to the actual school, to evaluate teacher behavior quantitatively, to reflect oneself an experienced video (give oneself a awareness). This study focuses to evaluate teacher behavior quantitatively. The quantitatively of teachers behavior needs to recognize the behavior and to analyze behavior transition. In this research, we defined ten kinds of teachers behavior, conducted behavior recognition using ST-GCN. As a result, we were able to recognize ten kinds of teachers behavior with 91 percent accuracy. In addition, we analyzed the behavior during the actual trial lesson and visualized the behavior transition.
Keyword (in Japanese) (See Japanese page) 
(in English) Behavior classification / ST-GCN / Teacher behavior / Deep Learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 510, ET2018-97, pp. 59-62, March 2019.
Paper # ET2018-97 
Date of Issue 2019-03-08 (ET) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee ET  
Conference Date 2019-03-15 - 2019-03-15 
Place (in Japanese) (See Japanese page) 
Place (in English) Naruto University of Education 
Topics (in Japanese) (See Japanese page) 
Topics (in English) IoT & Education/Learning Support, etc. 
Paper Information
Registration To ET 
Conference Code 2019-03-ET 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Teacher Behavior Classification based on ST-GCN for Traial Lesson Support System 
Sub Title (in English)  
Keyword(1) Behavior classification  
Keyword(2) ST-GCN  
Keyword(3) Teacher behavior  
Keyword(4) Deep Learning  
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1st Author's Name Sho Ooi  
1st Author's Affiliation Ritsumeikan University (Rits)
2nd Author's Name Yao Shunyu  
2nd Author's Affiliation Ritsumeikan University (Rits)
3rd Author's Name Haruo Noma  
3rd Author's Affiliation Ritsumeikan University (Rits)
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Speaker Author-1 
Date Time 2019-03-15 11:05:00 
Presentation Time 25 minutes 
Registration for ET 
Paper # ET2018-97 
Volume (vol) vol.118 
Number (no) no.510 
Page pp.59-62 
#Pages
Date of Issue 2019-03-08 (ET) 


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