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ファイル | 記述 | サイズ | フォーマット | |
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978-3-031-11647-6_46.pdf | 711.81 kB | Adobe PDF | 見る/開く |
タイトル: | An Automatic Self-explanation Sample Answer Generation with Knowledge Components in a Math Quiz |
著者: | Nakamoto, Ryosuke Flanagan, Brendan https://orcid.org/0000-0001-7644-997X (unconfirmed) Dai, Yiling https://orcid.org/0000-0001-9900-8763 (unconfirmed) Takami, Kyosuke Ogata, Hiroaki |
著者名の別形: | 中本, 陵介 戴, 憶菱 高見, 享佑 緒方, 広明 |
キーワード: | Self-explanation Rubric Automatic summarization NLP |
発行日: | 2022 |
出版者: | Springer Nature |
誌名: | Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium |
開始ページ: | 254 |
終了ページ: | 258 |
抄録: | Little research has addressed how systems can use the learning process of self-explanation to provide scaffolding or feedback. Here, we propose a model automatically generating sample self-explanations with knowledge components required to solve a math quiz. The proposed model contains three steps: vectorization, clustering, and extraction. In an experiment using 1434 self-explanation answers from 25 quizzes, we found 72% of the quizzes generated sample answers with all necessary knowledge components. The similarity between human-created and machine-generated sentences was 0.719, with a significant correlation of R = 0.48 for the best performing generation model by BERTScore. These results suggest that our model can generate sample answers with the necessary key knowledge components and be further improved by using the BERTScore. |
記述: | Part of the Lecture Notes in Computer Science book series (LNCS, volume 13356) |
著作権等: | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-031-11647-6_46 The full-text file will be made open to the public on 26 July 2023 in accordance with publisher's 'Terms and Conditions for Self-Archiving'. This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。 |
URI: | http://hdl.handle.net/2433/283114 |
DOI(出版社版): | 10.1007/978-3-031-11647-6_46 |
出現コレクション: | 学術雑誌掲載論文等 |
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