Towards Guided-Breath as an Intervention Within Computer-Assisted Learning
| Language | English |
|---|---|
| Type | Proceedings of International Conferences |
| Authors | Kanta Yamaoka, Andrew W. Vargo, Motoi Iwata, Koichi Kise |
| Title | Towards Guided-Breath as an Intervention Within Computer-Assisted Learning |
| Journal | 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) |
| Number of pages | 3 |
| Publisher | ACM |
| Location | Cambridge, UK |
| Reviewed | Reviewed |
| Presentation type | Poster |
| Date | September 2022 |
| Research fields | Learning Analytics, Sensing |
| Key | Yamaoka2022 (id=1888) |
Abstract
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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