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Paper Abstract and Keywords
Presentation 2024-01-20 16:20
Comparison of AI in chatbots using agent characters in classrooms -- Comparison of effects of scenario based AI and generative AI --
Toshikazu Iitaka (Kumamoto Gakuen Univ.) ET2023-52
Abstract (in Japanese) (See Japanese page) 
(in English) This paper introduces the use and effect of the comment function which makes agent AI characters support the audiences of lectures. The function is a chatbot function that responds to audiences' comments. The command that manipulates an external AI service realizes the responses.
There are two different types of useful AI services i. e. rule-based AI and generative AI. So, both types of AI services are implemented in the chatbot function that we used in lectures. We compare the effects of both types of AI services by comparing the scores of quizzes that the audiences of lectures tried during the lectures. The result of the analysis makes us estimate that the generative AI services are more effective.
Keyword (in Japanese) (See Japanese page) 
(in English) This paper introduces the use and effect of the comment function which makes agent AI characters support the audiences of lectures. The function is a chatbot function that responds to audiences' comments. The command that manipulates an external AI service realizes the responses. There are two different types of useful AI services i. e. rule-based AI and generative AI. So, both types of AI services are implemented in the chatbot function that we used in lectures. We compare the effects of both types of AI services by comparing the scores of quizzes that the audiences of lectures tried during the lectures. The result of the analysis makes us estimate that the generative AI services are more effective. / Clicker / Generative-AI / Rule-Based-AI / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 348, ET2023-52, pp. 45-50, Jan. 2024.
Paper # ET2023-52 
Date of Issue 2024-01-13 (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)
Download PDF ET2023-52

Conference Information
Committee ET  
Conference Date 2024-01-20 - 2024-01-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyoto University Yoshida Campus / Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Bodily knowledge / Skill education, General 
Paper Information
Registration To ET 
Conference Code 2024-01-ET 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Comparison of AI in chatbots using agent characters in classrooms 
Sub Title (in English) Comparison of effects of scenario based AI and generative AI 
Keyword(1) This paper introduces the use and effect of the comment function which makes agent AI characters support the audiences of lectures. The function is a chatbot function that responds to audiences' comments. The command that manipulates an external AI service realizes the responses. There are two different types of useful AI services i. e. rule-based AI and generative AI. So, both types of AI services are implemented in the chatbot function that we used in lectures. We compare the effects of both types of AI services by comparing the scores of quizzes that the audiences of lectures tried during the lectures. The result of the analysis makes us estimate that the generative AI services are more effective.  
Keyword(2) Clicker  
Keyword(3) Generative-AI  
Keyword(4) Rule-Based-AI  
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1st Author's Name Toshikazu Iitaka  
1st Author's Affiliation Kumamoto Gakuen University (Kumamoto Gakuen Univ.)
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Speaker Author-1 
Date Time 2024-01-20 16:20:00 
Presentation Time 25 minutes 
Registration for ET 
Paper # ET2023-52 
Volume (vol) vol.123 
Number (no) no.348 
Page pp.45-50 
#Pages 6 
Date of Issue 2024-01-13 (ET) 

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