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：可视化素养评估通常依赖正确性对表现进行分类，但关于读者如何得出答案的证据很少。我们认为注视行为作为隐含过程信号可弥补这一鸿沟，既补充标准化测试又无需牺牲其可扩展性。综合可视化及相关研究发现，我们证明注视指标能够捕捉正确率和反应时无法显现的认知负荷，并反映反映熟练程度的注意力分配策略差异。我们提出将素养分数与注视衍生过程指标——组件级注意力分布、整合频率和浏览路径离散度——相结合的评估方案，用以区分流畅理解与费力成功。这将推动素养评估从二元分类转向精细化描述读者如何跨图表组件进行导航、整合与信息协调。路线图指出了实证基础、泛化能力、评估设计及实践可行性方面的待解挑战。