{"title":"Detecting Learners' Weak Points Utilizing a Digital Pen","authors":"Kazuya Kishi, Motoki Miura","doi":"10.1109/IIAI-AAI.2017.148","DOIUrl":null,"url":null,"abstract":"We consider that most learners tend to focus on and review only problems they incorrectly answered after performing exercises. To deepen their understanding, it is also necessary for learners to review problems that took time to answer even though they were answered correctly. However, it is difficult to judge which problems took time to answer with an ordinary pen and paper. Therefore, we adopt a digital pen to help learners to recognize parts of a problem that took long to complete. Using the pen-stroke interval data obtained by a digital pen, we can discover the weak points of a learner. In this study, we implemented the method and evaluated it by comparing the weak points extracted by the three methods. The results confirm that the method can detect weak points with an accuracy of about 50% to 60%.","PeriodicalId":281712,"journal":{"name":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIAI-AAI.2017.148","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We consider that most learners tend to focus on and review only problems they incorrectly answered after performing exercises. To deepen their understanding, it is also necessary for learners to review problems that took time to answer even though they were answered correctly. However, it is difficult to judge which problems took time to answer with an ordinary pen and paper. Therefore, we adopt a digital pen to help learners to recognize parts of a problem that took long to complete. Using the pen-stroke interval data obtained by a digital pen, we can discover the weak points of a learner. In this study, we implemented the method and evaluated it by comparing the weak points extracted by the three methods. The results confirm that the method can detect weak points with an accuracy of about 50% to 60%.