文献の詳細
| 論文の言語 | 日本語 |
|---|---|
| 著者 | 族束��促 孫��属狸, Olivier Augereau, Charles Lima Sanches, ��贈孫促 孫即村湛, ��巽村�� 属遜��袖, 損続���� 揃嘆����, Kai Kunze, ����卒�� 脱����辿, Andreas Dengel |
| 論文名 | ����臓孫造��促損促坦促袖造嘆����造造造多����遜単孫����属族嘆��� |
| 論文誌名 | 其袖属辿他丹��坦促揃促孫促��促��続��族単存側袖脱族単��坦孫丹 |
| Vol. | 32 |
| No. | 2 |
| ページ | pp.53-60 |
| 発表場所 | ��孫��樽存息他他����損�� |
| 査読の有無 | 無 |
| 年月 | 2017年7月 |
| 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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- BibTeX用エントリー
@InCollection{族束��促2017, author = {族束��促 孫��属狸 and Olivier Augereau and Charles Lima Sanches and ��贈孫促 孫即村湛 and ��巽村�� 属遜��袖 and 損続���� 揃嘆���� and Kai Kunze and ����卒�� 脱����辿 and Andreas Dengel}, title = {����臓孫造��促損促坦促袖造嘆����造造造多����遜単孫����属族嘆���}, booktitle = {其袖属辿他丹��坦促揃促孫促��促��続��族単存側袖脱族単��坦孫丹}, year = 2017, month = jul, volume = {32}, number = {2}, pages = {53--60}, location = {��孫��樽存息他他����損��} }