Visualization literacy assessments typically rely on correctness to classify performance, providing little evidence about how readers arrive at their answers. We argue that gaze can address this gap as an implicit process signal that complements standardized tests without sacrificing their scalability. Synthesizing findings from visualization and related research, we show that gaze metrics capture cognitive load invisible to accuracy and response time, and reflect strategy differences in attention allocation that track proficiency. We propose assessments that integrate literacy scores with gaze-derived process indicators - component-level attention profiles, integration frequency, and viewing path dispersion - to distinguish fluent comprehension from labored success. This would shift literacy assessment from binary classification toward nuanced characterization of how readers navigate, integrate, and coordinate information across chart components. A roadmap identifies open challenges in empirical grounding, generalizability, assessment design, and practical feasibility.

翻译：图形素养评估通常依赖正确率来分类表现，却极少揭示读者得出答案的过程。我们认为，注视信号可填补这一空白，作为一种隐式过程信号，既能补充标准化测试，又不会削弱其可扩展性。综合可视化及相关领域的研究成果，我们证明注视指标能够捕获准确率与反应时无法体现的认知负荷，并反映反映熟练度的注意力分配策略差异。我们提出一种新的评估框架，将素养分数与注视衍生的过程指标——组件级注意力分布、整合频率及浏览路径离散度——相结合，以区分流畅理解与费力成功。这将使素养评估从二元分类转向对读者如何跨图表组件导航、整合与协调信息的精细化特征刻画。最后，我们描绘了在实证基础、泛化能力、评估设计及实际可行性等方面有待突破的开放性挑战路线图。