People often face barriers to selecting self-tracking tools that support their goals and needs, resulting in tools not meeting their expectations and ultimately abandonment. We therefore examine how people approach selecting self-tracking apps and investigate how technology can better support the process. Drawing on past literature on how people select and perceive the features of commercial and research tracking tools, we surface seven attributes people consider during selection, and design a low-fidelity prototype of an app store that highlights these attributes. We then conduct semi-structured interviews with 18 participants to further investigate what people consider during selection, how people select self-tracking apps, and how surfacing tracking-related attributes could better support selection. We find that people often prioritize features related to self-tracking during selection, such as approaches to collecting and reflecting on data, and trial apps to determine whether they would suit their needs. Our results also show potential for technology surfacing how apps support tracking to reduce barriers to selection. We discuss future opportunities for improving self-tracking app selection, such as ways to enhance existing self-tracking app distribution platforms to enable people to filter and search apps by desirable features.
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Yarn: Adding Meaning to Shared Personal Data through Structured Storytelling
People often do not receive the reactions they desire when they use social networking sites to share data collected through personal tracking tools like Fitbit, Strava, and Swarm. Although some people have found success sharing with close connections or in finding online communities, most audiences express limited interest and rarely respond. We report on findings from a human-centered design process undertaken to examine how tracking tools can better support people in telling their story using their data. 23 formative interviews contribute design goals for telling stories of accomplishment, including a need to include relevant data. We implement these goals in Yarn, a mobile app that offers structure for telling stories of accomplishment around training for running races and completing Do-It-Yourself projects. 21 participants used Yarn for 4 weeks across two studies. Although Yarn’s structure led some participants to include more data or explanation in the moments they created, many felt like the structure prevented them from telling their stories in the way they desired. In light of participant use, we discuss additional challenges to using personal data to inform and target an interested audience
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- Award ID(s):
- 1850389
- PAR ID:
- 10158861
- Date Published:
- Journal Name:
- Graphics Interface
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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