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Updated: Jan 9, 2026

Eye-tracking to Distinguish Comprehension-based and Oculomotor-based Regressive Eye Movements During Reading
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一站式: 360名参与者的英语眼睛跟踪数据集,具有不同的阅读模式.

Yevgeni Berzak1, Jonathan Malmaud2, Omer Shubi3

  • 1Technion - Israel Institute of Technology, Faculty of Data and Decision Sciences, Haifa, Israel. berzak@technion.ac.il.

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|December 2, 2025
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概括

该OneStop眼动群为360名英语母语使用者提供了广泛的阅读数据,为阅读理解和人类语言处理提供了新的见解.

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科学领域:

  • 认知科学 认知科学
  • 计算语言学 计算语言学
  • 教育技术的教育技术

背景情况:

  • 眼睛跟踪对于理解阅读过程至关重要.
  • 现有的数据集缺乏足够的规模和多样性来进行全面的分析.
  • 将眼睛跟踪数据与自然语言处理 (NLP) 和人工智能 (AI) 联系在一起仍然是一个挑战.

研究的目的:

  • 介绍一站式眼动,这是一个大规模的英语L1阅读集体.
  • 为阅读研究提供前所未有的数据量 (152小时,260万令牌).
  • 促进眼睛跟踪数据集成到NLP,人工智能,人机交互 (HCI) 和教育应用中.

主要方法:

  • 收集了来自360名英语母语人士的152小时的眼动记录.
  • 使用试点阅读理解材料,其中包含486个问题和文本注释.
  • 包括多种阅读模式:普通,信息搜索,重复和简化阅读.

主要成果:

  • 创建了最大的公共英语L1眼睛跟踪数据集用于阅读.
  • 该集体包含260万个词令牌的眼动数据.
  • 材料支持阅读理解的行为分析.

结论:

  • 一站式语料库使阅读和人类语言处理领域的新研究成为可能.
  • 它促进了眼睛跟踪数据在NLP,AI,HCI和教育中的使用.
  • 这个资源促进了阅读行为和认知过程的研究.