Augmented Learning on Anticipating Textbooks with Eye Tracking
Augmented Learning on Anticipating Textbooks with Eye Tracking
复制标题
通过眼动追踪预测教科书的增强学习
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
A. Dengel
中科院分区：
文献类型：
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作者：
Shoya Ishimaru;S. S. Bukhari;Carina Heisel;N. Grossmann;P. Klein;J. Kuhn;A. Dengel
本文展示了眼睛跟踪技术如何理解提供商的个性化学习，尽管好奇心是学习的重要因素，但教科书一直是静态的，并且在各种学习者中都是稳定的。根据学生的兴趣，我们的兴趣是学习的积极预测指标，我们假设学生的学习和理解将在呈现与当前的认知状态一致的信息。物理学中的学习材料。和解决任务。
This paper demonstrates how eye tracking technologies can understand providers to realize a personalized learning. Although curiosity is an important factor for learning, textbooks have been static and constant among various learners. The motivation of our work is to develop a digital textbook which displays contents dynamically based on students’ interests. As interest is a positive predictor of learning, we hypothesize that students’ learning and understanding will improve when they are presented information which is in line with their current cognitive state. As the first step, we investigate students’ reading behaviors with an eye tracker, and propose attention and comprehension prediction approaches. These methods were evaluated on a dataset including eight participants’ readings on a learning material in Physics. We classified participants’ comprehension levels into three classes, novice, intermediate, and expert, indicating significant differences in reading behavior and solving tasks.