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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