Quantified self meets perceptual learning

Despite increasing interests in learning tea mastery, current tea apps lack supports for tracking tea practices done by apprentices in the tea industry and tea aficionados who want to improve their skills. Because many of them practice their tea skills individually, a system is needed to support learners by (1) tracking tea practices in real time, and (2) estimating their improvements over time. This workshop paper analyzes recently released tea apps, suggests QS design sketches that support users' learning by displaying and comparing quantitative data collected from the trials of tea practices, and finally discusses challenges and the future work. This paper aims to provide insight into an understudied user group for future QS studies and suggests a novel design considering the users' needs.