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  1. 論文誌(ジャーナル)
  2. Vol.65
  3. No.2

Training AI Model that Suggests Python Code from Student Requests in Natural Language

https://ipsj.ixsq.nii.ac.jp/records/232390
https://ipsj.ixsq.nii.ac.jp/records/232390
81272271-3978-40d6-8cc3-0408d82b9df2
名前 / ファイル ライセンス アクション
IPSJ-JNL6502004.pdf IPSJ-JNL6502004.pdf (4.8 MB)
 2026年2月15日からダウンロード可能です。
Copyright (c) 2024 by the Information Processing Society of Japan
非会員:¥0, IPSJ:学会員:¥0, 論文誌:会員:¥0, DLIB:会員:¥0
Item type Journal(1)
公開日 2024-02-15
タイトル
タイトル Training AI Model that Suggests Python Code from Student Requests in Natural Language
タイトル
言語 en
タイトル Training AI Model that Suggests Python Code from Student Requests in Natural Language
言語
言語 eng
キーワード
主題Scheme Other
主題 [特集:創造的学習のための教育におけるコンピュータ] AI-based programming education, code suggestion, large language model
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_6501
資源タイプ journal article
著者所属
Department of Mathematics, Physics and Computer Science, Japan Women's University
著者所属
Division of Mathematical and Physical Sciences, Graduate School of Science, Japan Women's University
著者所属
Division of Mathematical and Physical Sciences, Graduate School of Science, Japan Women's University
著者所属
Division of Mathematical and Physical Sciences, Graduate School of Science, Japan Women's University/Presently with NTT Software Innovation Center.
著者所属(英)
en
Department of Mathematics, Physics and Computer Science, Japan Women's University
著者所属(英)
en
Division of Mathematical and Physical Sciences, Graduate School of Science, Japan Women's University
著者所属(英)
en
Division of Mathematical and Physical Sciences, Graduate School of Science, Japan Women's University
著者所属(英)
en
Division of Mathematical and Physical Sciences, Graduate School of Science, Japan Women's University / Presently with NTT Software Innovation Center
著者名 Kimio, Kuramitsu

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Kimio, Kuramitsu

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Momoka, Obara

× Momoka, Obara

Momoka, Obara

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Miyu, Sato

× Miyu, Sato

Miyu, Sato

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Yuka, Akinobu

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Yuka, Akinobu

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著者名(英) Kimio, Kuramitsu

× Kimio, Kuramitsu

en Kimio, Kuramitsu

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Momoka, Obara

× Momoka, Obara

en Momoka, Obara

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Miyu, Sato

× Miyu, Sato

en Miyu, Sato

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Yuka, Akinobu

× Yuka, Akinobu

en Yuka, Akinobu

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論文抄録
内容記述タイプ Other
内容記述 Programming is a creative activity, but it can be difficult to learn due to constant updates, poorly maintained documentation, and unexpected errors. One reason for the difficulties is the shortage of programming teachers, which often leaves students unable to get help when they need it, even for simple questions. Many unanswered questions are a barrier to improving programming skills for creative purposes. The purpose of this paper is to address this issue by exploring whether an AI-based system can help reduce the difficulties faced by students. Recent advancements in deep learning technology have made it easier for teachers to train AI models that can learn from their own experiences in the classroom, including the types of questions, requests, and difficulties that students encounter. We have developed an AI model that can translate Python code from Japanese by using machine translation techniques and large language models. We have integrated this model into a learning assistant system that suggests code to students when they express their programming intentions. In this paper, we present our experiences in developing and deploying this AI-based assistant in the classroom, as well as the feedback we have received from students. By sharing our initial experiences, we aim to envision the potential of educational AI development for the future.
------------------------------
This is a preprint of an article intended for publication Journal of
Information Processing(JIP). This preprint should not be cited. This
article should be cited as: Journal of Information Processing Vol.32(2024) (online)
DOI http://dx.doi.org/10.2197/ipsjjip.32.69
------------------------------
論文抄録(英)
内容記述タイプ Other
内容記述 Programming is a creative activity, but it can be difficult to learn due to constant updates, poorly maintained documentation, and unexpected errors. One reason for the difficulties is the shortage of programming teachers, which often leaves students unable to get help when they need it, even for simple questions. Many unanswered questions are a barrier to improving programming skills for creative purposes. The purpose of this paper is to address this issue by exploring whether an AI-based system can help reduce the difficulties faced by students. Recent advancements in deep learning technology have made it easier for teachers to train AI models that can learn from their own experiences in the classroom, including the types of questions, requests, and difficulties that students encounter. We have developed an AI model that can translate Python code from Japanese by using machine translation techniques and large language models. We have integrated this model into a learning assistant system that suggests code to students when they express their programming intentions. In this paper, we present our experiences in developing and deploying this AI-based assistant in the classroom, as well as the feedback we have received from students. By sharing our initial experiences, we aim to envision the potential of educational AI development for the future.
------------------------------
This is a preprint of an article intended for publication Journal of
Information Processing(JIP). This preprint should not be cited. This
article should be cited as: Journal of Information Processing Vol.32(2024) (online)
DOI http://dx.doi.org/10.2197/ipsjjip.32.69
------------------------------
書誌レコードID
収録物識別子タイプ NCID
収録物識別子 AN00116647
書誌情報 情報処理学会論文誌

巻 65, 号 2, 発行日 2024-02-15
ISSN
収録物識別子タイプ ISSN
収録物識別子 1882-7764
公開者
言語 ja
出版者 情報処理学会
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