Understanding the Mechanics of Persuasive System
Design: a Mixed-Method Theory-driven Analysis of the
Mobile Fitness Coach Freeletics
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- Abstract:
- This dataset was first used in the following article: Hanna Schneider, Kilian Moser, Andreas Butz, and Florian Alt. 2016. Understanding the Mechanics of Persuasive System Design: a Mixed-Method Theory-driven Analysis of the Mobile Fitness Coach Freeletics. In Proceedings of the 34rd Annual ACM Conference on Human Factors in Computing Systems (CHI '16). San Jose, CA, USA. DOI=http://dx.doi.org/10.1145/2858036.2858290 Please inform the author(s) if you plan to use this dataset. About the research: While we know that persuasive system design matters, we barely understand when persuasive strategies work and why they only work in some cases. We propose an approach to systematically understand and design for motivation, by studying the fundamental building blocks of motivation, according to the theory of planned behavior (TPB): attitude, subjective norm, and perceived control. We quantitatively analyzed (N=643) the attitudes, beliefs, and values of mobile fitness coach users with TPB. Capacity (i.e., perceived ability to exercise) had the biggest effect on users' motivation. Using individual differences theory, we identified three distinct user groups, namely followers, hedonists, and achievers. With insights from semi-structured interviews (N=5) we derive design implications finding that transformation videos that feature other users' success stories as well as suggesting an appropriate workout can have positive effects on perceived capacity. Practitioners and researchers can use our theory-based mixed-method research design to better understand user behavior in persuasive applications.
- Keywords:
- Behavior Change
Fitness Application
Theory of Planned Behavior
Persuasive Technology
Personal Values
- DDC:
- 000 Computers, Information and General Reference
004 Data processing computer science
Identifier
- DOI:
- https://doi.org/10.5282/ubm/data.71
- lmUB:
- a715ab30-6769-4321-923e-efb6f366c59e