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Paper Abstract and Keywords
Presentation 2020-11-13 15:04
[Poster Presentation] Prototype Tool to Detect Difference between State Machine Diagrams toward Automation of Providing Educational Feedback to Learners
Mitsutada Goshima, Shinpei Ogata (Shinshu Univ.), Erina Makihara (Doshisha Univ.), Kozo Okano (Shinshu Univ.) KBSE2020-15 SC2020-19
Abstract (in Japanese) (See Japanese page) 
(in English) State machine diagrams in UML are useful for system development and other purposes because they represent discrete behaviors, but they are difficult for beginners to understand. As a previous research to support beginners in learning, a tool to simulate the behavior of a state machine diagram is proposed in order to visually confirm the behavior. However, there is not enough research to detect the differences between the state machine diagrams of learner's answer and the state machine diagrams of sample answer for the purpose of identifying locations of the error. The purpose of this research is to create a tool that automatically identify locations of the error and provides feedback to support beginner to learn modeling. In this presentation, we compare between the state machine diagrams of learner's answer and the state machine diagrams of sample answers to create a learning support tool, and present the results of differential detection by focusing on "behavior", "grammar", "diagram's structure" and "correspondence between states and transitions". As a result of the differential detection, we were able to identify the location of the difference between state machine diagrams and judge whether it is an error or not, except for another solutions which are drawn in very different ways. Therefore, it was expected that the error can be identified automatically by differential detection.
Keyword (in Japanese) (See Japanese page) 
(in English) UML / State Machine Diagram / education / error identification / feedback / differential detection / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 231, KBSE2020-15, pp. 30-30, Nov. 2020.
Paper # KBSE2020-15 
Date of Issue 2020-11-06 (KBSE, SC) 
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)
Notes on Review This article is a technical report without peer review, and its polished version will be published elsewhere.
Download PDF KBSE2020-15 SC2020-19

Conference Information
Committee KBSE SC  
Conference Date 2020-11-13 - 2020-11-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Online + Kikai-Shinko-Kaikan Bldg. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To KBSE 
Conference Code 2020-11-KBSE-SC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Prototype Tool to Detect Difference between State Machine Diagrams toward Automation of Providing Educational Feedback to Learners 
Sub Title (in English)  
Keyword(1) UML  
Keyword(2) State Machine Diagram  
Keyword(3) education  
Keyword(4) error identification  
Keyword(5) feedback  
Keyword(6) differential detection  
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Keyword(8)  
1st Author's Name Mitsutada Goshima  
1st Author's Affiliation Shinshu University (Shinshu Univ.)
2nd Author's Name Shinpei Ogata  
2nd Author's Affiliation Shinshu University (Shinshu Univ.)
3rd Author's Name Erina Makihara  
3rd Author's Affiliation Doshisha University (Doshisha Univ.)
4th Author's Name Kozo Okano  
4th Author's Affiliation Shinshu University (Shinshu Univ.)
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Speaker Author-1 
Date Time 2020-11-13 15:04:00 
Presentation Time 2 minutes 
Registration for KBSE 
Paper # KBSE2020-15, SC2020-19 
Volume (vol) vol.120 
Number (no) no.231(KBSE), no.232(SC) 
Page p.30 
#Pages
Date of Issue 2020-11-06 (KBSE, SC) 


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