Abstract
In self-tracking applications, data visualizations play a fundamental role in delivering efficient information and creating personalized user experiences. Literature consistently indicates that data visualization is a powerful tool to make data persuasive and improve motivation. However, how to leverage different data visualizations to boost motivation remains largely unknown. In this study, the researcher explores the effects of different data visualizations on user motivation within self-tracking mobile applications. Through design space analysis and semi-structured interviews, the researcher defines a set of design factors that impact users' exercise motivation at different levels of exercise adoption. Based on these factors, the researcher delivers a set of practical design suggestions for design practitioners and people who create visualizations for large data sets.
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CITATION STYLE
Huang, X. (2022). Data Visualization Design Strategies for Promoting Exercise Motivation in Self-Tracking Applications. In Proceedings of the 40th ACM International Conference on Design of Communication, SIGDOC 2022 (pp. 78–89). Association for Computing Machinery, Inc. https://doi.org/10.1145/3513130.3558981
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