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Visualization Decision Making Laboratory
Examining Effort in 1D Uncertainty Communication Using
Individual Differences in Working Memory and NASA-TLX
VIDEO
As uncertainty visualizations for general audiences become increasingly common, designers must understand the full impact of uncertainty communication techniques on viewers’ decision processes. Prior work demonstrates mixed performance outcomes with respect to how individuals make decisions using various visual and textual depictions of uncertainty. Part of the inconsistency across findings may be due to an over-reliance on task accuracy, which cannot, on its own, provide a comprehensive
understanding of how uncertainty visualization techniques support reasoning processes. In this work, we advance the debate
surrounding the efficacy of modern 1D uncertainty visualizations by conducting converging quantitative and qualitative analyses of
both the effort and strategies used by individuals when provided with quantile dotplots, density plots, interval plots, mean plots, and
textual descriptions of uncertainty. We utilize two approaches for examining effort across uncertainty communication techniques: a
measure of individual differences in working-memory capacity known as an operation span (OSPAN) task and self-reports of perceived
workload via the NASA-TLX. The results reveal that both visualization methods and working-memory capacity impact participants’
decisions. Specifically, quantile dotplots and density plots (i.e., distributional annotations) result in more accurate judgments than
interval plots, textual descriptions of uncertainty, and mean plots (i.e., summary annotations). Additionally, participants’ open-ended
responses suggest that individuals viewing distributional annotations are more likely to employ a strategy that explicitly incorporates
uncertainty into their judgments than those viewing summary annotations. When comparing quantile dotplots to density plots, this work
finds that both methods are equally effective for low-working-memory individuals. However, for individuals with high-working-memory
capacity, quantile dotplots evoke more accurate responses with less perceived effort. Given these results, we advocate for the inclusion
of converging behavioral and subjective workload metrics in addition to accuracy performance to further disambiguate meaningful
differences among visualization techniques.
