Paper Abstract and Keywords |
Presentation |
2021-12-11 13:00
Development of trait-based neural automated essay scoring incorporating multidimensional item response theory Takumi Shibata, Masaki Uto (UEC) ET2021-33 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In recent years, deep neural network (DNN)-based automated essay scoring (AES) models that can simultaneously predict the overall score and multiple trait-specific scores have been proposed. However, the main problem of conventional models is the lack of explainability. To resolve this problem, this study proposes a new trait-based DNN-AES model with high explainability by integrating multidimensional item response theory. The proposed model succeeded in improving explainability without a significant loss of accuracy compared to a state-of-the-art conventional model. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
essay-type tests / automated essay scoring / deep neural networks / multidimensional item response theory / explainability / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 294, ET2021-33, pp. 23-28, Dec. 2021. |
Paper # |
ET2021-33 |
Date of Issue |
2021-12-04 (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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ET2021-33 |
Conference Information |
Committee |
ET |
Conference Date |
2021-12-11 - 2021-12-11 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Sessions for Young Researchers (Young Researcher Awards Selection), etc. |
Paper Information |
Registration To |
ET |
Conference Code |
2021-12-ET |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Development of trait-based neural automated essay scoring incorporating multidimensional item response theory |
Sub Title (in English) |
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essay-type tests |
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automated essay scoring |
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deep neural networks |
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multidimensional item response theory |
Keyword(5) |
explainability |
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1st Author's Name |
Takumi Shibata |
1st Author's Affiliation |
The University of Electro-Communications (UEC) |
2nd Author's Name |
Masaki Uto |
2nd Author's Affiliation |
The University of Electro-Communications (UEC) |
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Speaker |
Author-1 |
Date Time |
2021-12-11 13:00:00 |
Presentation Time |
20 minutes |
Registration for |
ET |
Paper # |
ET2021-33 |
Volume (vol) |
vol.121 |
Number (no) |
no.294 |
Page |
pp.23-28 |
#Pages |
6 |
Date of Issue |
2021-12-04 (ET) |
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