书写行为作为自信的鉴别器

Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers Pub Date : 2020-09-10 DOI:10.1145/3410530.3414383

Takanori Maruichi, Taichi Uragami, Andrew W. Vargo, K. Kise

{"title":"书写行为作为自信的鉴别器","authors":"Takanori Maruichi, Taichi Uragami, Andrew W. Vargo, K. Kise","doi":"10.1145/3410530.3414383","DOIUrl":null,"url":null,"abstract":"Receiving feedback based on the combination of self-confidence and correctness of an answer can help learners to improve learning efficiency. In this study, we propose a self-confidence estimation method using a simple touch up/move/down events that can be measured in a classroom environment. We recorded handwriting behavior during the answering vocabulary questions with a tablet and a stylus pen, estimating self-reported confidence. We successfully built a method that can predict the user's self-confidence with a maximum of 73% accuracy.","PeriodicalId":7183,"journal":{"name":"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers","volume":"79 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Handwriting behavior as a self-confidence discriminator\",\"authors\":\"Takanori Maruichi, Taichi Uragami, Andrew W. Vargo, K. Kise\",\"doi\":\"10.1145/3410530.3414383\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Receiving feedback based on the combination of self-confidence and correctness of an answer can help learners to improve learning efficiency. In this study, we propose a self-confidence estimation method using a simple touch up/move/down events that can be measured in a classroom environment. We recorded handwriting behavior during the answering vocabulary questions with a tablet and a stylus pen, estimating self-reported confidence. We successfully built a method that can predict the user's self-confidence with a maximum of 73% accuracy.\",\"PeriodicalId\":7183,\"journal\":{\"name\":\"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers\",\"volume\":\"79 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3410530.3414383\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3410530.3414383","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 3

摘要

在自信和答案正确的基础上接受反馈，可以帮助学习者提高学习效率。在这项研究中，我们提出了一种自信估计方法，使用简单的触摸/移动/下降事件，可以在课堂环境中测量。我们在用平板电脑和手写笔回答词汇问题时记录了书写行为，估计了自我报告的信心。我们成功地建立了一种方法，可以预测用户的自信心，准确率最高为73%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

Handwriting behavior as a self-confidence discriminator

Receiving feedback based on the combination of self-confidence and correctness of an answer can help learners to improve learning efficiency. In this study, we propose a self-confidence estimation method using a simple touch up/move/down events that can be measured in a classroom environment. We recorded handwriting behavior during the answering vocabulary questions with a tablet and a stylus pen, estimating self-reported confidence. We successfully built a method that can predict the user's self-confidence with a maximum of 73% accuracy.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers

自引率

0.00%

发文量

期刊最新文献

Using gamification to create and label photos that are challenging for computer vision and people Pose evaluation for dance learning application using joint position and angular similarity SParking: a win-win data-driven contract parking sharing system HeadgearX Blink rate variability: a marker of sustained attention during a visual task