A Comparative Study of Static, Scrollytelling, and Chatbot Visualization Onboarding Techniques for UX Designers

Jul 16, 2026

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User experience (UX) designers encounter barriers when producing data visualizations, largely due to limited visualization domain expertise and unfamiliarity with specialized tools. The work evaluates three onboarding approaches—static, scrollytelling, and chatbot—through an experiment with 25 UX designers and students. Visualization comprehension and guideline adherence are assessed during a creation task, followed by surveys and interviews on preferences, engagement, and onboarding experience. Interactive onboarding improves guideline adherence and engagement, while scrollytelling and chatbot show no significant performance differences.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages14

Reading Time35 min

Introduction

Background and Related Work

Study Design and Method

Participants and Procedures

Results and Discussion

Guideline Adherence and Engagement

Comprehension and Preferences

Design Dimensions and Implications

Future Work

A Comparative Study of Static, Scrollytelling, and Chatbot Visualization Onboarding Techniques for UX Designers Ester Chen [esterchen@mail.rit.edu](esterchen@mail.rit.edu) Aboli Shete[as6151@rit.edu](as6151@rit.edu) Aditya Anavekar[aa3278@rit.edu](aa3278@rit.edu) Roshan Peiris Hidy Kong [roshan.peiris@rit.edu](roshan.peiris@rit.edu) [hidy.kong@rit.edu](hidy.kong@rit.edu)[ ](hidy.kong@rit.edu)Rochester Institute of Technology arXiv :2607 .03023v 1 [ cs .HC] 3 Jul 2026 ABSTRACT User experience (UX) designers face barriers when creating data visualizations due to limited domain expertise in visualization or unfamiliarity with specialized tools. This highlights a clear need for effective methods to build visualization literacy. To address this, we evaluated three visualization onboarding techniques—static, scrollytelling, and chatbot—in an experimental study with 25 UX designers and students. We measured visualization comprehension and guideline adherence during a visualization creation task, followed by surveys and interviews to capture preferences and experiences. Compared to static onboarding, the pooled interactive condition (scrollytelling or chatbot) was associated with significantly higher guideline-adherence scores during visualization creation; both interactive techniques also received higher engagement ratings. Instruction clarity ratings were significantly higher when the two interactive conditions were pooled. Comprehension did not differ significantly across conditions. While participants generally preferred the interactive techniques, no significant differences emerged between scrollytelling and chatbot in performance or onboarding experience ratings. Drawing on the findings, we discuss three design dimensions of visualization onboarding (narrative structure, visual content layout, and navigational flexibility), their design implications, and potential opportunities for future research in this field. Keywords: Visualization literacy, UX design, interactive learning, scrollytelling, visual onboarding, comparative study 1 INTRODUCTION As data becomes increasingly complex and multidimensional, traditional visualizations like bar and pie charts often fall short of capturing the full scope of the information [16, 33] . To address this, advanced visualization techniques such as heatmaps, treemaps, and parallel set plots are required [39, 66] . However, the effectiveness of these techniques is hindered by the prevalent lack of visualization literacy. Visualization literacy refers to “the ability to confidently create and interpret visual representations of data” [10], which is essential in today’s data-driven world for effective communication and decision-making. However, non-experts including students and the general public, often struggle with complex visualizations [9, 10, 19] . One such group of non-experts is user experience (UX) designers. A UX designer is a technical professional who focuses on creating a user-friendly experience for a product or service [31] . They often work with a variety of visualizations to create engaging dashboards that are tailored to the type of data and the dashboard’s purpose. They also use data visualizations to communicate their research findings to stakeholders [65] . UX designers responsible for dashboard design frequently face foundational challenges due to a lack of knowledge in this domain. Specifically, they face difficulties in identifying relevant data, choosing the appropriate visualization type, and effectively expressing the intended message [5, 6, 54, 75] . Other issues include balancing aesthetic appeal and functionality, and ensuring that visualizations are accessible to all users, including those with disabilities. In addition, incorporating data visualization into UX design necessitates familiarity with a variety of tools and technologies [6, 54, 75] . Beyond individual skill gaps, the collaborative nature of dashboard creation introduces its own

FAQs

What were the key findings about interactive onboarding?

When interactive techniques were pooled, guideline adherence scores were significantly higher than with static onboarding, and engagement ratings were also higher. Instruction clarity ratings were likewise higher for the interactive pooled conditions.

Jul 16, 2026

Upload by Aurora