Previous research has shown that various user characteristics (e.g., cognitive abilities, personality traits, and learning abilities) can influence user experience during information visualization tasks. These findings have prompted researchers to investigate user-adaptive information visualizations that can help users by providing personalized support based on their specific needs. Whereas existing work has been mostly limited to tasks involving just visualizations, the aim of our research is to broaden this work to include scenarios where users process textual documents with embedded visualizations, i.e., Magazine Style Narrative Visualizations, or MSNVs for short. In this paper, we analyze eye tracking data collected from a user study with MSNVs to uncover processing behaviors that are negatively impacting user experience (i.e., time on task) for users with low abilities in these user characteristics. Our analysis leverages Linear Mixed-Effects Models to evaluate the relationships among user characteristics, gaze processing behaviors, and task performance. Our results identify several MSNV processing behaviors within the visualization that contribute to poor task performance for users with low reading proficiency. For instance, we identify that users with low reading proficiency transition significantly more often compared to their counterparts between relevant and non-relevant bars, and transition more often from bars to the labels. We present our findings as a step toward designing user-adaptive support mechanisms to alleviate these difficulties with MSNVs, and provide suggestions on how our results can be leveraged for creating a set of meaningful interventions for future evaluation (e.g., dynamically highlighting relevant bars and labels in the visualization to help users with low reading proficiency locate them more effectively).

中文翻译：

---

杂志风格叙事可视化中用户特征的凝视分析

先前的研究表明，在信息可视化任务中，各种用户特征（例如，认知能力、个性特征和学习能力）会影响用户体验。这些发现促使研究人员研究用户自适应信息可视化，这些可视化可以通过根据用户的特定需求提供个性化支持来帮助用户。鉴于现有工作主要限于仅涉及可视化的任务，我们研究的目的是扩大这项工作以包括用户处理具有嵌入式可视化的文本文档的场景，即杂志风格叙事可视化，或简称 MSNV。在本文中，我们分析了从 MSNV 的用户研究中收集的眼动追踪数据，以揭示对用户体验产生负面影响的处理行为（即，任务时间）适用于在这些用户特征方面能力较低的用户。我们的分析利用线性混合效应模型来评估用户特征、凝视处理行为和任务性能之间的关系。我们的结果确定了可视化中的几种 MSNV 处理行为，这些行为导致阅读能力低的用户的任务性能不佳。例如，我们发现阅读能力低的用户在相关条和非相关条之间的转换频率明显高于他们的同行，并且从条到标签的转换频率更高。我们将我们的发现作为设计用户自适应支持机制以缓解 MSNV 的这些困难的一个步骤，