Towards Guided-Breath as an Intervention Within Computer-Assisted Learning
| 言語 | 英語 |
|---|---|
| 種類 | 国際会議等の予稿 |
| 著者 | Kanta Yamaoka,Andrew W. Vargo,Motoi Iwata,Koichi Kise |
| 論文名 | Towards Guided-Breath as an Intervention Within Computer-Assisted Learning |
| 論文誌名 | Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 International Symposium on Wearable Computers (UbiComp/ISWC '22 Adjunct) |
| ページ数 | 3 |
| 出版社 | ACM |
| 発表場所 | Cambridge, UK |
| 査読の有無 | 有 |
| 発表の種類 | ポスター発表 |
| 年月 | 2022年9月 |
| 分野 | 学習解析, センシング |
| キー | Yamaoka2022 (id=1888) |
要約
Mindfulness has been actively investigated in HCI. While its positive effects on our cognitive functions are reported, carrying out mindfulness activities in general requires self-discipline to get its reported benefits. Our study aims to integrate a visual guide of breathing into computer-assisted learning to help the learner achieve better performance. We present within-subject research with 10 participants who learned sets of Croatian vocabulary with a multiple-choice interface showing either for 10 seconds : (a) guided-breath or (b) break instruction after every question. Our hypothesis was that (a) brings a better learner's score than (b). However, statistical analysis of learners' quiz scores did not support our hypothesis, which brought us two lessons for future improvements of our work-in-progress research. Such intervention (i) could lead to distraction rather than concentration without careful quantity and quality, and (ii) might need personalization depending on individual mindfulness levels.
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