Personalizing Augmented Flashcards Towards Long-Term Vocabulary Learning
| 言語 | 英語 |
|---|---|
| 種類 | 国際会議等の予稿 |
| 著者 | Yuichiro Iwashita，Andrew Vargo，Motoi Iwata，Koichi Kise |
| 論文名 | Personalizing Augmented Flashcards Towards Long-Term Vocabulary Learning |
| 書名 | Proceedings of the Augmented Humans International Conference 2024 |
| Series | AHs '24 |
| ページ | pp.263-266 |
| ページ数 | 4 |
| 出版社 | Association for Computing Machinery |
| 出版社の住所 | New York, NY, USA |
| 発表場所 | Melbourne, VIC, Australia |
| 査読の有無 | 有 |
| 発表の種類 | ポスター発表 |
| 年月 | 2024年4月 |
| 分野 | 学習解析, センシング, パターン認識 |
| DOI | 10.1145/3652920.3653045 |
| URL | https://doi.org/10.1145/3652920.3653045 |
| キー | Iwashita2024 (id=1969) |
要約
Flashcards are one of the most popular tools for learning vocabulary for second-language learners. While flashcard mediated learning is efficient, it may not induce motivation for continued use. Some researchers have proposed augmented flashcards that provide multimedia contexts to motivate people to study. However, the augmented flashcards also have a problem that it takes time to learn each target word. Understanding this tradeoff, we introduce a system that users can learn vocabulary with both standard and augmented flashcards. In addition, our system recommends the best learning strategy to users adaptively, and realizes the long-term vocabulary learning. In this paper, we describe the system and present the results of the preliminary data analysis towards the long-term vocabulary learning.
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