Knowledge extraction from pointer movements and its application to detect uncertainty

Abstract

Pointer-tracking methods can capture a real-time trace at high spatio-temporal resolution of users' pointer interactions with a graphical user interface. This trace is potentially valuable for research on human-computer interaction (HCI) and for investigating perceptual, cognitive and affective processes during HCI. However, little research has reported spatio-temporal pointer features for the purpose of tracking pointer movements in on-line surveys. In two studies, we identified a set of pointer features and movement patterns and showed that these can be easily distinguished. In a third study, we explored the feasibility of using patterns of interactive pointer movements, or micro-behaviours, to detect response uncertainty. Using logistic regression and k-fold cross-validation in model training and testing, the uncertainty model achieved an estimated performance accuracy of 81%. These findings suggest that micro-behaviours provide a promising approach toward developing a better understanding of the relationship between the dynamics of pointer movements and underlying perceptual, cognitive and affective psychological mechanisms.

Keywords

• Human-computer interaction
• Pointer-tracking
• Mouse movement dynamics
• Decision uncertainty
• On-line survey
• Spatio-temporal features