Designing a personal informatics system for users without experience in self-tracking: a case study
Behaviour & Information Technology, 2018•Taylor & Francis
Thanks to the advancements in ubiquitous and wearable technologies, Personal Informatics
(PI) systems can now reach a larger audience of users. However, it is not still clear whether
this kind of tool can fit the needs of their daily lives. Our research aims at identifying specific
barriers that may prevent the widespread adoption of PI and finding solutions to overcome
them. We requested users without competence in self-tracking to use different PI instruments
during their daily practices, identifying five user requirements by which to design novel PI …
(PI) systems can now reach a larger audience of users. However, it is not still clear whether
this kind of tool can fit the needs of their daily lives. Our research aims at identifying specific
barriers that may prevent the widespread adoption of PI and finding solutions to overcome
them. We requested users without competence in self-tracking to use different PI instruments
during their daily practices, identifying five user requirements by which to design novel PI …
Abstract
Thanks to the advancements in ubiquitous and wearable technologies, Personal Informatics (PI) systems can now reach a larger audience of users. However, it is not still clear whether this kind of tool can fit the needs of their daily lives. Our research aims at identifying specific barriers that may prevent the widespread adoption of PI and finding solutions to overcome them. We requested users without competence in self-tracking to use different PI instruments during their daily practices, identifying five user requirements by which to design novel PI tools. On such requirements, we developed a new system that can stimulate the use of these technologies, by enhancing the perceived benefits of collecting personal data. Then, we explored how naïve and experienced users differently explore their personal data in our system through a user trial. Results showed that the system was successful at helping individuals manage and interpret their own data, validated the usefulness of the requirements found and inspired three further design opportunities that could orient the design of future PI systems.
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