WEKO3
アイテム
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/23239081272271-3978-40d6-8cc3-0408d82b9df2
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
|
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
× Kimio, Kuramitsu
× Momoka, Obara
× Miyu, Sato
× Yuka, Akinobu
|
|||||||||||||
| 著者名(英) |
Kimio, Kuramitsu
× Kimio, Kuramitsu
× Momoka, Obara
× Miyu, Sato
× Yuka, Akinobu
|
|||||||||||||
| 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 | |||||||||||||