Comparative Evaluations of Visualization Onboarding Methods
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Comprehending and exploring large and complex data is becoming increasingly important for users in a wide range of application domains. Still, non-experts in visual data analysis often have problems with correctly reading and interpreting information from visualizations that are new to them. To support novices in learning how to use new digital technologies, the concept of onboarding has been successfully applied in other fields and first approaches also exist in the visualization domain. However, empirical evidence on the effectiveness of such approaches is scarce. Therefore, we conducted 3 studies: 1) Firstly, we explored the effect of vis onboarding, using an interactive step-by-step guide, on user performance for four increasingly complex visualization techniques. We performed a between-subject experiment with 596 participants in total. The results showed that there are no significant differences between the answer correctness of the questions with and without onboarding. Furthermore, participants commented that for highly familiar visualization types no onboarding is needed. 2) Second, we performed another study with MTurk workers to assess if there is a difference in user performances on different onboarding types: step-by-step, scrollytelling tutorial, and video tutorial. The study revealed that the video tutorial was ranked as the most positive on average, based on sentiment analysis, followed by the scrollytelling tutorial and the interactive step-by-step guide. 3) For our third study with students, we gathered data on users' experience in using an in-situ scrollytelling for the VA tool. The results showed that they preferred scrollytelling over the tutorial integrated into the landing page. In summary, the in-situ scrollytelling approach works well for visualization onboarding and a video tutorial can help to introduce interaction techniques.
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