Japanese Reading Objective Understanding Estimation by Eye Gaze Analysis
| Language | English |
|---|---|
| Type | Proceedings of International Conferences |
| Authors | Charles Lima Sanches, Olivier Augereau, Koichi Kise |
| Title | Japanese Reading Objective Understanding Estimation by Eye Gaze Analysis |
| Journal | Proceedings of the 2017 ACM International Joint Conference on |
| Series | UbiComp '17 |
| Pages | pp.121-124 |
| Number of pages | 4 |
| Publisher | ACM |
| Address | New York, NY, USA |
| Location | Maui, Hawaii |
| Reviewed | Reviewed |
| Date | August 2017 |
| Research fields | Reading-Life Log, Learning Analytics |
| DOI | 10.1145/3123024.3123092 |
| Key | Sanches2017_ACM (id=1575) |
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.
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