文献の詳細

論文の言語	英語
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 pages
出版社	ACM
査読の有無	無
年月	2017年9月
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.
DOI	10.1145/3123024.3123138

• BibTeX用エントリー

  @InProceedings{Yamada2017,
    author =	{Kento Yamada and Olivier Augereau and Koichi Kise},
    title =	{Estimation of confidence based on eye gaze: an application to multiple-choice questions},
    booktitle =	{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)},
    year =	2017,
    month =	sep,
    pages =	{217--220},
    numpages =	{4},
    DOI =		{10.1145/3123024.3123138},
    publisher =	{ACM}
  }
  
  
  

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