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Paper Abstract and Keywords
Presentation 2018-07-20 10:55
An Automated Evaluation Method for Conceptual Data Models Focusing on Appropriateness of Attributes
Takafumi Tanaka (TUAT), Hiroaki Hashiura (NIT), Atsuo Hazeyama (TGU), Kousuke Mouri, Keiichi Kaneko (TUAT) SS2018-16 KBSE2018-26
Abstract (in Japanese) (See Japanese page) 
(in English) It is important for database design education to teach skills of conceptual data modeling (CDM) to learners. In CDM exercises with many learners, it is required that teacher can evaluate learners’ models in an automated way. This study proposes an automated evaluation method for CDM considering the appropriateness of attributes when it determines existences of concepts in learners’ models. We applied our method to data collected in CDM exercises in a university. As a result, we verified the effectiveness of our method. In addition, we found that (1) learners’ average score rate of names of concepts (ASNC), (2) no correlation between ASNC and the learners’ average score rate of attributes. (3) a strong correlation between ASNC and the learners’ average score rate of whole elements in an expected answer.
Keyword (in Japanese) (See Japanese page) 
(in English) Conceptual data model / Automated evaluation / UML class diagram / / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 138, KBSE2018-26, pp. 189-194, July 2018.
Paper # KBSE2018-26 
Date of Issue 2018-07-11 (SS, KBSE) 
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)
Download PDF SS2018-16 KBSE2018-26

Conference Information
Committee KBSE SS IPSJ-SE  
Conference Date 2018-07-18 - 2018-07-20 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To KBSE 
Conference Code 2018-07-KBSE-SS-SE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Automated Evaluation Method for Conceptual Data Models Focusing on Appropriateness of Attributes 
Sub Title (in English)  
Keyword(1) Conceptual data model  
Keyword(2) Automated evaluation  
Keyword(3) UML class diagram  
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1st Author's Name Takafumi Tanaka  
1st Author's Affiliation Tokyo University of Agriculture and Technology (TUAT)
2nd Author's Name Hiroaki Hashiura  
2nd Author's Affiliation Nippon Institute of Technology (NIT)
3rd Author's Name Atsuo Hazeyama  
3rd Author's Affiliation Tokyo Gakugei University (TGU)
4th Author's Name Kousuke Mouri  
4th Author's Affiliation Tokyo University of Agriculture and Technology (TUAT)
5th Author's Name Keiichi Kaneko  
5th Author's Affiliation Tokyo University of Agriculture and Technology (TUAT)
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Speaker Author-1 
Date Time 2018-07-20 10:55:00 
Presentation Time 25 minutes 
Registration for KBSE 
Paper # SS2018-16, KBSE2018-26 
Volume (vol) vol.118 
Number (no) no.137(SS), no.138(KBSE) 
Page pp.189-194 
#Pages 6 
Date of Issue 2018-07-11 (SS, KBSE) 

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