Japanese / English

Detail of Publication

Text Language English
Authors Charles Lima Sanches,Olivier Augereau,and Koichi Kise
Title Japanese Reading Objective Understanding Estimation by Eye Gaze Analysis
Journal Proceedings of the 2017 ACM International Joint Conference on
Book_Title Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
Series UbiComp '17
Pages pp.121-124
Number of Pages 4 pages
Publisher ACM
Address New York, NY, USA
Location Maui, Hawaii
Reviewed or not Reviewed
Month & Year August 2017
Abstract Analyzing the eye gaze to estimate the text understanding is a good way to overcome the drawbacks of classic question based assessment tests. In particular it does not suffer from random answers, question misunderstanding and can cover every parts of the text. In this paper we propose a method to estimate the objective understanding of a learner by analyzing his eye movements while reading. We conduct our experiment on Japanese texts and try to predict, by analyzing the eye gaze, how many questions about the texts the reader will be able to answer to. We show that we obtain 5.27% of error in the number of correct answers estimation by using eye gaze features. As a comparison, we try to predict the number of correct answers by using the reader's self assessment understanding and show that it leads to 9.04% error.
DOI 10.1145/3123024.3123092
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