Comparing information graphics: a critical look at eye tracking

J. Goldberg, J. Helfman
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引用次数: 120

Abstract

Effective graphics are essential for understanding complex information and completing tasks. To assess graphic effectiveness, eye tracking methods can help provide a deeper understanding of scanning strategies that underlie more traditional, high-level accuracy and task completion time results. Eye tracking methods entail many challenges, such as defining fixations, assigning fixations to areas of interest, choosing appropriate metrics, addressing potential errors in gaze location, and handling scanning interruptions. Special considerations are also required designing, preparing, and conducting eye tracking studies. An illustrative eye tracking study was conducted to assess the differences in scanning within and between bar, line, and spider graphs, to determine which graphs best support relative comparisons along several dimensions. There was excessive scanning to locate the correct bar graph in easier tasks. Scanning across bar and line graph dimensions before comparing across graphs was evident in harder tasks. There was repeated scanning between the same dimension of two spider graphs, implying a greater cognitive demand from scanning in a circle that contains multiple linear dimensions, than from scanning the linear axes of bar and line graphs. With appropriate task design and targeted analysis metrics, eye tracking techniques can illuminate visual scanning patterns hidden by more traditional time and accuracy results.
比较信息图形:眼动追踪的关键观点
有效的图形对于理解复杂的信息和完成任务至关重要。为了评估图形效果,眼动追踪方法可以帮助我们更深入地了解扫描策略,这些策略是传统的、高精确度和任务完成时间结果的基础。眼动追踪方法带来了许多挑战,例如定义注视点,将注视点分配到感兴趣的区域,选择适当的指标,解决注视位置的潜在错误,以及处理扫描中断。在设计、准备和进行眼动追踪研究时也需要特别考虑。进行了一项说明性眼动追踪研究,以评估条形图、线形图和蜘蛛图之间的扫描差异,以确定哪种图最能支持几个维度上的相对比较。在简单的任务中,为了找到正确的条形图,需要进行过多的扫描。在比较不同图形之前先扫描条形图和线形图的尺寸,这在较困难的任务中是很明显的。在两个蜘蛛图的相同维度之间重复扫描,这意味着在包含多个线性维度的圆圈中扫描比扫描条形图和线形图的线性轴更大的认知需求。通过适当的任务设计和有针对性的分析指标,眼动追踪技术可以揭示传统的时间和精度结果所隐藏的视觉扫描模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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