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| Presentation | 2023-01-20 15:15 Multi-task Training with Joining-in-type Robot-assisted Language Learning System Yu Zha, Tsuneo Kato, Seiichi Yamamoto, Akihiro Tamura (Doshisha Univ.)  ET2022-60 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Introducing robots into language learning systems is effective, especially in motivating learners to engage in learning and allowing the learners to talk in a more realistic conversational environment. The joining-in-type robot-assisted language learning (JIT-RALL) system uses two robots (one as a teacher and one as a co-learner) to simulate a multi-party conversation, which can increase learning effects. However, previous JIT-RALL had single training tasks and a fixed process. In order to further increase learning effects, we introduced the well-ordered system approach from second language acquisition theory and proposed a multi-task training with JIT-RALL system. In this paper, we compared the learning effects of learners who participated in the previous single-task JIT-RALL system with those who participated in our proposed multi-task training with JIT-RALL system. We found that the learning effects of the learners who participated in our multi-task RALL system increased by 0.20 points. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Joining-in-type robot-assisted language learning system / Multi-task training / Well-ordered system approach / Learning effects / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 348, ET2022-60, pp. 23-28, Jan. 2023. | |
| Paper # | ET2022-60 | |
| Date of Issue | 2023-01-13 (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 | ET2022-60 |
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| Conference Information | |
| Committee | ET |
| Conference Date | 2023-01-20 - 2023-01-20 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Hyogo College of Medicine and Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Embodies Knowledge and Skill Education, etc. |
| Paper Information | |
| Registration To | ET |
| Conference Code | 2023-01-ET |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Multi-task Training with Joining-in-type Robot-assisted Language Learning System |
| Sub Title (in English) | |
| Keyword(1) | Joining-in-type robot-assisted language learning system |
| Keyword(2) | Multi-task training |
| Keyword(3) | Well-ordered system approach |
| Keyword(4) | Learning effects |
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| 1st Author's Name | Yu Zha |
| 1st Author's Affiliation | Doshisha University (Doshisha Univ.) |
| 2nd Author's Name | Tsuneo Kato |
| 2nd Author's Affiliation | Doshisha University (Doshisha Univ.) |
| 3rd Author's Name | Seiichi Yamamoto |
| 3rd Author's Affiliation | Doshisha University (Doshisha Univ.) |
| 4th Author's Name | Akihiro Tamura |
| 4th Author's Affiliation | Doshisha University (Doshisha Univ.) |
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| Speaker | Author-1 |
| Date Time | 2023-01-20 15:15:00 |
| Presentation Time | 25 minutes |
| Registration for | ET |
| Paper # | ET2022-60 |
| Volume (vol) | vol.122 |
| Number (no) | no.348 |
| Page | pp.23-28 |
| #Pages | 6 |
| Date of Issue | 2023-01-13 (ET) |
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