Paper Abstract and Keywords |
Presentation |
2017-11-24 13:55
Comment Mining to Estimate Junior High-school Student Performance toward Improvement of Student Learning Ichiro Niiya, Takayuki Nagai, Tsunenori Mine (Kyushu Univ) AI2017-12 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Estimating student performance is very useful for estimating students with poor grades early. In this research, we will estimate the performance from the retrospective sentences after the lesson described by junior high school students of the Learning Cram school and investigate the students' retrospect. In the estimation of the grades, each student made a backward sentence written after the lesson of the subject student himself / herself as a vector, followed by dimensional compression, and the student 's performance was estimated from various classifiers. In the survey of students' retrospective sentences, we examined words with high frequency of appearance by grades. As a result, the performance estimation accuracy using the binary weights and mutual information was better than the results of the previous research in the performance estimation. In the survey of retrospective sentences, it was found that the frequency of appearance and objects of respectful adverbs differed for the top grades and the students 'lower students' respect. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Machine learning, / Text mining / Junior high school student comments / performance estimation / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 326, AI2017-12, pp. 31-36, Nov. 2017. |
Paper # |
AI2017-12 |
Date of Issue |
2017-11-17 (AI) |
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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AI2017-12 |
Conference Information |
Committee |
AI |
Conference Date |
2017-11-24 - 2017-11-24 |
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(See Japanese page) |
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Paper Information |
Registration To |
AI |
Conference Code |
2017-11-AI |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Comment Mining to Estimate Junior High-school Student Performance toward Improvement of Student Learning |
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Keyword(1) |
Machine learning, |
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Text mining |
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Junior high school student comments |
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performance estimation |
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1st Author's Name |
Ichiro Niiya |
1st Author's Affiliation |
Kyushu University (Kyushu Univ) |
2nd Author's Name |
Takayuki Nagai |
2nd Author's Affiliation |
Kyushu University (Kyushu Univ) |
3rd Author's Name |
Tsunenori Mine |
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Kyushu University (Kyushu Univ) |
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Speaker |
Author-1 |
Date Time |
2017-11-24 13:55:00 |
Presentation Time |
25 minutes |
Registration for |
AI |
Paper # |
AI2017-12 |
Volume (vol) |
vol.117 |
Number (no) |
no.326 |
Page |
pp.31-36 |
#Pages |
6 |
Date of Issue |
2017-11-17 (AI) |
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