様々なセンサを用いた読書行動解析
| 言語 | 日本語 |
|---|---|
| 種類 | 研究会等の予稿 |
| 著者 | 黄瀬 浩一，Olivier Augereau，Charles Lima Sanches，藤好 宏樹，大社 綾乃，山田 健斗，Kai Kunze，石丸 翔也，Andreas Dengel |
| 論文名 | 様々なセンサを用いた読書行動解析 |
| 論文誌名 | 教育情報システム学会研究会報告 |
| Vol. | 32 |
| No. | 2 |
| ページ | pp.53-60 |
| 発表場所 | 長野県松本市 |
| 査読の有無 | 無 |
| 年月 | 2017年7月 |
| 分野 | リーディングライフログ |
| キー | Kise2017_WS (id=1573) |
要約
Most of the current e-learning systems rely on shallow sensing of learners such as achievement tests and log of usage of the systems. This poses a limitation to know internal states of learners such as confidence and the level of knowledge. To solve this problem, we propose to employ deeper sensing by using eye trackers, EOG, EEG, motion and physiological sensors. As tasks, we consider learning of English and Japanese. The sensing technologies described in this report includes low level estimations (the number of read words, the period of reading), document type recognition and identification of read words, as well as high level estimations about confidence of answers, the English ability in terms of TOEIC scores, unknown words encountered while reading English documents, and subjective and objective level of understanding of Japanese. Such functionality helps learners and teachers to know the internal states.
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