Visual cues as perceptual load: Cues can create additional cognitive demands in interactive visualizations despite being perceived as helpful

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Authors: Patricia Engel-Hermann, Alexander Skulmowski
Cited by: 1
References: 70

Abstract

BACKGROUND: Perceptually rich visualizations are known to pose cognitive demands. Cognitive load theory suggests that design choices can mitigate negative effects on learning performance. AIMS: We aim to evaluate whether cueing is able to reduce the cognitive demands of a parallax effect induced by constrained interactivity in learning with perceptually rich visualizations. SAMPLE: 191 university students were included in the final sample. METHODS: Participants were randomly assigned to learn with a perceptually rich anatomical visualization in one of four versions resulting from the factors constrained interactivity (static vs. interactive parallax effect) and visual boundary cues (without vs. with cues). The constrained interactivity allowed participants to slightly rotate an anatomical model. Subjective cognitive load during learning was assessed using a survey. Participants completed image-based and text-based retention tests. RESULTS: Contrary to the notion that cues help learners facing perceptually rich task, we found that cues only benefit learning with the static visualization. As indicated by an interaction effect, cueing lowered retention performance in the constrained interactive condition. Germane cognitive load ratings suggest that participants recognized the cues as helpful in the interactive parallax effect condition while preferring the variant without cues in the static condition. CONCLUSION: The cognitive demands of minimally interactive perceptually rich visualizations cannot simply be reduced by inserting boundary cues. Instead, visual cues may even add to the perceptual richness of visualizations if they feature subtle forms of interactivity. The perceptual demands of a slightly adjustable visualization that was extended by cues may have been too high.

Fields of Study & Subjects

Data Visualization and Analytics Visual perception and processing mechanisms Visual and Cognitive Learning Processes

Publication details

Journal / source
Trends in Neuroscience and Education
Publisher
Elsevier BV
Volume
43
Pages
100289–100289
Publication date
15 May 2026
Language
EN