Author ORCID Identifier

Date of Award

Spring 5-2023

Document Type

Thesis (Master's)

Department or Program

Computer Science

First Advisor

Lorie Loeb

Second Advisor

Elizabeth Murnane

Third Advisor

Tim Tregubov


Self-tracking tools have become increasingly popular, especially with the advent of wearable technology and smartphone applications. However, traditional tracking tools often display data in a quantitative format that can be overwhelming and cause users to abandon their tracking efforts. Additionally, these tools typically provide a generic user experience and are designed from a single-user perspective, lacking external support. To overcome these limitations, we develop Sprout, a mobile data-tracking application that offers a more qualitative, customizable, and collaborative experience for health monitoring and management. Sprout uses a garden metaphor to visually represent health information and allows users to tailor their data experience by customizing data capture types and corresponding visual representation for each element. Furthermore, users in Sprout can collaborate to achieve community goals, unlocking new features for their gardens. We conduct a user study with 22 participants to investigate the impact of qualitative data visualization, customizability, and social support on users' activity levels, goal attainment, engagement, and satisfaction with the self-tracking system. Our results suggest that qualitative visualization of data can help some users maintain their motivation to meet health-related goals, but a mix of quantitative and qualitative data is desired by some users. Customizability requires tailored features to help users develop a sense of ownership over time, and social features are a crucial motivator for users to achieve their health goals. However, tracking with strangers instead of friends can hinder user engagement due to the lack of connection.