Estimation of confidence based on eye gaze: an application to multiple-choice questions

言語英語
種類国際会議等の予稿
著者Kento Yamada,Olivier Augereau,Koichi Kise
論文名Estimation of confidence based on eye gaze: an application to multiple-choice questions
論文誌名Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers (UbiComp'17)
ページpp.217-220
ページ数4
出版社ACM
査読の有無無
年月2017年9月
分野リーディングライフログ
DOI10.1145/3123024.3123138
キーYamada2017_UbiComp (id=1590)

要約

Multiple-choice questions are often used to assess the user's understanding. However, the system does not know if the user answered randomly, by chance, with confidence or without confidence. The user's confidence can be used as a feedback for teachers or smart interfaces that could understand that he is not sure of himself and then provide further assistance. We aim to create confidence aware interfaces such as pervasive display. As a first step, we propose an application in the context of multiple-choice question answering. By using an eye tracker, we analyze the reading and answering behavior of the user, extract some features and predict his confidence. We asked 11 participants to solve 80 multiple-choice questions about English understanding, and estimated whether they answered confidently or not. We obtained 90.1% average accuracy for this prediction.

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