Eliciting Gestures for Novel Note-taking Interactions

This is the authors' abstract. We don't add key points for this paper.

Handwriting recognition is improving in leaps and bounds, and this opens up new opportunities for stylus-based interactions. In particular, note-taking applications can become a more intelligent user interface, incorporating new features like autocomplete and integrated search. In this work we ran a gesture elicitation study, asking 21 participants to imagine how they would interact with an imaginary, intelligent note-taking application. Participants were prompted to produce gestures for common actions such as select and delete, as well as less common actions (for gesture interaction) such as autocomplete accept/reject, ‘hide’, and search. We report agreement on the elicited gestures, finding that while existing interactions are prevalent (like double taps and long presses) a number of more novel interactions (like dragging selected items to hotspots or using annotations) were also well-represented. We discuss the mental models participants drew on when explaining their gestures and what kind of feedback users might need to move to more stylus-centric interactions.