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Title:
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REGION-WISE PAGE DIFFICULTY ANALYSIS USING EYE MOVEMENTS |
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Author(s):
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Tsubasa Minematsu |
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ISBN:
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978-989-8533-93-7 |
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Editors:
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Demetrios G. Sampson, Dirk Ifenthaler, Pedro Isaías and Maria Lidia Mascia |
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Year:
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2019 |
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Edition:
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Single |
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Keywords:
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Learning Analytics, Eye Movement, Machine Learning, Neural Network |
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Type:
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Full Paper |
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First Page:
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109 |
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Last Page:
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116 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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In this study, we investigated which section of a page was difficult for students to read, based on eye movement data and
subjective impressions of the pages difficulty, with the aim of helping teachers revise teaching materials. It is
problematic to manually model relationships between eye movements and subjective impressions of the pages difficulty.
Therefore, in this study, we used a neural network to model the relationships automatically. Our method generated
relevance maps representing locations where students found difficulty, in order to visualize region-wise page difficulty.
To evaluate the quality of the relevance maps, we compared them with a distribution of gaze points and highlights added
by the students. In addition, we administered a questionnaire to evaluate whether the relevance maps were useful to
teachers when revising teaching materials. Results imply that our method can provide useful information for teachers
making revisions to teaching materials. |
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