  In this paper we investigate the value of gaze-driven adaptive interventions
to support processing of textual documents with embedded visualizations, i.e.,
Magazine Style Narrative Visualizations (MSNVs). These interventions are
provided dynamically by highlighting relevant data points in the visualization
when the user reads related sentences in the MNSV text, as detected by an
eye-tracker. We conducted a user study during which participants read a set of
MSNVs with our interventions, and compared their performance and experience
with participants who received no interventions. Our work extends previous
findings by showing that dynamic, gaze-driven interventions can be delivered
based on reading behaviors in MSNVs, a widespread form of documents that have
never been considered for gaze-driven adaptation so far. Next, we found that
the interventions significantly improved the performance of users with low
levels of visualization literacy, i.e., those users who need help the most due
to their lower ability to process and understand data visualizations. However,
high literacy users were not impacted by the interventions, providing initial
evidence that gaze-driven interventions can be further improved by
personalizing them to the levels of visualization literacy of their users.
