User Experience (UX) based on Data Visualization
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Date
2022
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Abstract
It is critical to build tools to study data in an environment where data is rapidly being gathered and utilized. Visualizing the data may help with this. The usefulness and efficiency of such informational visualizations are often examined, but hedonic elements such as sheer delight and aesthetic beauty are typically overlooked. These characteristics are included in the idea of user experience (UX), which is a good predictor of a user’s overall rating of an information visualization. However, since the discipline is very new and has diverse definitions, there are many different approaches to measure UX. The goal of this exploratory study was to see whether the CUE (elements of user experience) paradigm and its measurement tool, meCUB, are adequate for assessing the UX for data visualization. This study looked at the user experience of information visualizations with minor differences in terms of animation features to investigate whether UX metrics might explain user preferences. Small differences in the experiment couldn’t be seen by using the meCUE technique, hence descriptive study seems to be more appropriate in this case. Because the meCUE method failed to pick up on even the smallest differences in the trial, descriptive study seems to be the better option in this case. The findings demonstrate the subjective nature of UX and highlight the need of defining a user group. The findings also show that rather of depending just on a user’s self-report, UX assessment should include research interpretation and objectivity.
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environment, data, visualizations, objectivity