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Paper Abstract and Keywords
Presentation 2020-03-07 11:25
A feasibility of performance assessment using a large scale data set of mutual evaluation
Minoru Nakayama (TokyoTech), Masaki Uto (UEC), Filippo Sciarrone (uniroma3), Marco Temperini (Sapienza) ET2019-79
Abstract (in Japanese) (See Japanese page) 
(in English) Learning performance is often evaluated using a peer assessment setting such as MOOC environment. Their feasibility and validity should be confirmed. Sciarrone&Temperini(2019) have developed a simulation procedure to generate a large data set of peer assessment in order to examine these issues.
Also, accurate learning performance during the setting is often measured using item response theory, it may be possible to apply the large size of data.
In this paper, a feasibility of estimating individual performance is examined for a simulated data set such as one thousand participants with three peers' assessment.
As a result, ability, consistency and strictness for each participant are evaluated using Generalised partial credit model, the validity of these calculation approach is confirmed. This is an evidence of
a possibility to predict learning performance even in large scale learning condition.
Keyword (in Japanese) (See Japanese page) 
(in English) Peer Assessment / MOOC / Item Response Theory / / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 468, ET2019-79, pp. 19-22, March 2020.
Paper # ET2019-79 
Date of Issue 2020-02-29 (ET) 
ISSN Print edition: ISSN 0913-5685  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 2020-03-07 - 2020-03-07 
Place (in Japanese) (See Japanese page) 
Place (in English) National Institute of Technology, Kagawa Collage 
Topics (in Japanese) (See Japanese page) 
Topics (in English) LMS and e-Portfolio, etc. 
Paper Information
Registration To ET 
Conference Code 2020-03-ET 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A feasibility of performance assessment using a large scale data set of mutual evaluation 
Sub Title (in English)  
Keyword(1) Peer Assessment  
Keyword(2) MOOC  
Keyword(3) Item Response Theory  
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1st Author's Name Minoru Nakayama  
1st Author's Affiliation Tokyo Institute of Technology (TokyoTech)
2nd Author's Name Masaki Uto  
2nd Author's Affiliation The University of Electro-Communications (UEC)
3rd Author's Name Filippo Sciarrone  
3rd Author's Affiliation Roma Tre University (uniroma3)
4th Author's Name Marco Temperini  
4th Author's Affiliation Sapienza University of Roma (Sapienza)
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Speaker
Date Time 2020-03-07 11:25:00 
Presentation Time 25 
Registration for ET 
Paper # IEICE-ET2019-79 
Volume (vol) IEICE-119 
Number (no) no.468 
Page pp.19-22 
#Pages IEICE-4 
Date of Issue IEICE-ET-2020-02-29 


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