| アイテムタイプ |
共通アイテムタイプ(1) |
| 公開日 |
2025-01-22 |
| タイトル |
|
|
タイトル |
Subjective Difficulty Estimation of Educational Comics Using Gaze Features |
|
言語 |
en |
| 著者 |
Sakamoto, Kenya
Shirai, Shizuka
武村, 紀子
Orlosky, Jason
Nagataki, Hiroyuki
Ueda, Mayumi
Uranishi, Yuki
Takemura, Haruo
|
| 著作権関連情報 |
|
|
権利情報 |
Copyright (c) 2023 The Institute of Electronics, Information and Communication Engineers |
| 抄録 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
This study explores significant eye-gaze features that can be used to estimate subjective difficulty while reading educational comics. Educational comics have grown rapidly as a promising way to teach difficult topics using illustrations and texts. However, comics include a variety of information on one page, so automatically detecting learners' states such as subjective difficulty is difficult with approaches such as system log-based detection, which is common in the Learning Analytics field. In order to solve this problem, this study focused on 28 eye-gaze features, including the proposal of three new features called “Variance in Gaze Convergence,” “Movement between Panels,” and “Movement between Tiles” to estimate two degrees of subjective difficulty. We then ran an experiment in a simulated environment using Virtual Reality (VR) to accurately collect gaze information. We extracted features in two unit levels, page- and panel-units, and evaluated the accuracy with each pattern in user-dependent and user-independent settings, respectively. Our proposed features achieved an average F1 classification-score of 0.721 and 0.742 in user-dependent and user-independent models at panel unit levels, respectively, trained by a Support Vector Machine (SVM). |
|
言語 |
en |
| 書誌情報 |
en : IEICE Transactions on Information and Systems
巻 E106.D,
号 5,
p. 1038-1048,
発行日 2023-05-01
|
| 出版社 |
|
|
出版者 |
電子情報通信学会 |
|
言語 |
ja |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
cognitive state recognition |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
eye tracking |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
education |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
comic |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
learning analytics |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| DOI |
|
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.1587/transinf.2022EDP7100 |
| ISSN |
|
|
収録物識別子タイプ |
PISSN |
|
収録物識別子 |
0916-8532 |
| ISSN |
|
|
収録物識別子タイプ |
EISSN |
|
収録物識別子 |
1745-1361 |
| 査読の有無 |
|
|
値 |
yes |
| 研究者情報 |
|
|
URL |
https://hyokadb02.jimu.kyutech.ac.jp/html/100001540_ja.html |
| 論文ID（連携） |
|
|
値 |
10444563 |
| 連携ID |
|
|
値 |
12687 |
10444563.pdf (3 MB)
