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Mobile, wearable and other connected devices allow people to collect and explore large amounts of data about their own activities, behavior, and well-being. Yet, learning from-, and acting upon such data remain a challenge. The process of reflection has been identified as a key component of such learning. However, most tools do not explicitly design for reflection, carrying an implicit assumption that providing access to self-tracking data is sufficient. In this paper, we present Reflection Companion, a mobile conversational system that supports engaging reflection on personal sensed data, specifically physical activity data collected with fitness trackers. Reflection Companion delivers daily adaptive mini-dialogues and graphs to users' mobile phones to promote reflection. To generate our system's mini dialogues, we conducted a set of workshops with fitness trackers users, producing a diverse corpus of 275 reflection questions synthesized into a set of 25 reflection mini dialogues. In a 2-week field deployment with 33 active Fitbit users, we examined our system's ability to engage users in reflection through dialog. Results suggest that the mini-dialogues were successful in triggering reflection and that this reflection led to increased motivation, empowerment, and adoption of new behaviors. As a strong indicator of our system's value, 16 of the 33 participants elected to continue using the system for two additional weeks without compensation. We present our findings and describe implications for the design of technology-supported dialog systems for reflection on data.
Kocielnik et al. (Thu,) studied this question.