Eliciting Gestures for Novel Note-taking Interactions

TL;DR

This paper explores user-designed gestures for advanced note-taking apps, revealing common and novel interactions, and discusses how feedback can enhance stylus-based interfaces.

Contribution

It presents a gesture elicitation study identifying user-preferred interactions for intelligent note-taking applications, including novel gestures and user mental models.

Findings

Agreement on common gestures like double taps and long presses

Identification of novel gestures such as dragging to hotspots and annotations

Insights into user mental models and feedback needs for stylus 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. We report agreement on the elicited gestures, finding that while existing common 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.