Eliciting Gestures for Novel Note-taking Interactions

Abstract

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, fnding 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.

From Artifacts to Outcomes: Comparison of HMD VR, Desktop, and Slides Lectures for Food Microbiology Laboratory Instruction

“…Integrating note-taking features into VR applications enables students to engage in deep information processing and achieve their full potential. In addition to facilitating memory recall, recent research has also shown the positive impacts of note-taking applications on academic success, in encouraging individual learning responsibility [114], increasing participants' social interaction quality [22,30], and assimilating large information [79,92].…”