I led qualitative research & design on a project that sought to improve calendar apps, so that users could easily acquire the necessary cognitive resources to understand their schedules. My team interviewed 30 respondents about their scheduling habits. I then used these insights and produced a prototype called BusyCal.
How do people make sense of their schedules when there are so much information available? Does a full day of work plus a group fitness class later qualify as an easy day compared to having only one monumental task on one day? Further, as the amount of events increase, the required cognitive effort to sift through the mountain of information to asses the level of busyness can be daunting for the user.
We recruited 30 undergraduate students from the Information Science department for structured interviews. The interviews collected demographic data, user self-identification of busyness, user preferences for calendar apps, and lastly, user actions in preparation for busy day ahead.
Paper planners did not fade into obscurity in the ocean of Google Calendars and Evernote because people enjoyed crossing off events and the tactile sensation associated with it. Many participants also discussed the social dimension and identity maintenance dimension of their calendar usage. Calendars allow users identity maintenance through the types of events they put down on their calendars. Further, many participants feel a sense of pride by crossing off events, because it maintains their identities as a “busy/productive person.”
To help calendar apps better assist users at understanding how busy their days are, we thought a congregate score based on prior user rating of existing events could be efficient. We conceptualized an AI supported app where initial rating would lead to automatic importance rating suggestions. The initial loading of user ratings would then guide the AI in making meaningful predictions of busyness / importance level for any upcoming events.
When users first begin using BusyCal, they will enter event information, create new category tags, and provide importance level ratings. Initially, this will be no different than other calendar usage - users still input these information. However, as the amount of events users have input cumulates, AI will grow and eventually auto-fill these information, therefore achieving our goal of making calendar usage and understanding calendars faster.
