Paper detail

Comparative Evaluations of Visualization Onboarding Methods

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.

preprint2022arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.