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Paper Abstract and Keywords
Presentation 2026-05-09 10:30
Task-Induced Meaning Construction from AI-Generated Text -- A Design Based on Concept Map Construction and Self-Reconstruction --
Tsukasa Hirashima, Takebe Kouta (Hiroshima Univ) ET2026-4
Abstract (in Japanese) (See Japanese page) 
(in English) Generative AI can easily provide learners with explanations and answers. Such outputs, however, may be accepted without engaging learners in meaningful interpretation. As a result, learners may receive the content without constructing their own understanding. This study proposes a design principle for learning tasks in the use of generative AI, termed “necessitating meaning construction,” which creates situations in which learners must reinterpret the meaning of AI-generated output. Specifically, we design a learning task in which learners first construct a concept map from an AI-generated explanatory text and then reconstruct the map by decomposing it into components. Through externalizing and reconstructing their understanding, learners are expected to re-examine their own knowledge structures. Through an exploratory exercise, we observe the generation and resolution of learners’ questions as well as revisions to their concept maps. The study examines whether the proposed task can function as a learning activity that promotes reconsideration of learners’ understanding structures.
Keywords Generative AI, meaning construction, necessitation, concept map, self-reconstruction
Keyword (in Japanese) (See Japanese page) 
(in English) Generative AI / meaning construction / concept map / self-reconstruction / / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 12, ET2026-4, pp. 18-25, May 2026.
Paper # ET2026-4 
Date of Issue 2026-05-02 (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 ET2026-4

Conference Information
Committee ET  
Conference Date 2026-05-09 - 2026-05-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Online Learning, etc 
Paper Information
Registration To ET 
Conference Code 2026-05-ET 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Task-Induced Meaning Construction from AI-Generated Text 
Sub Title (in English) A Design Based on Concept Map Construction and Self-Reconstruction 
Keyword(1) Generative AI  
Keyword(2) meaning construction  
Keyword(3) concept map  
Keyword(4) self-reconstruction  
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1st Author's Name Tsukasa Hirashima  
1st Author's Affiliation Hiroshima University (Hiroshima Univ)
2nd Author's Name Takebe Kouta  
2nd Author's Affiliation Hiroshima University (Hiroshima Univ)
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Speaker Author-1 
Date Time 2026-05-09 10:30:00 
Presentation Time 25 minutes 
Registration for ET 
Paper # ET2026-4 
Volume (vol) vol.126 
Number (no) no.12 
Page pp.18-25 
#Pages 8 
Date of Issue 2026-05-02 (ET) 

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