An Intermittent Click Planning Model

TL;DR

This paper introduces the Intermittent Click Planning model, which predicts user click actions during pointing tasks and accurately forecasts error rates for stationary and moving targets, revealing cognitive differences among gamers.

Contribution

The study presents a novel model that explains and predicts click planning and execution during pointing tasks, validated by high accuracy in experimental data.

Findings

Model accurately predicts pointing error rates (R2 > 0.98).

Successfully distinguishes cognitive traits among different user groups.

Provides insights into user click planning during target tracking.

Abstract

Pointing is the task of tracking a target with a pointer and confirming the target selection through a click action when the pointer is positioned within the target. Little is known about the mechanism by which users plan and execute the click action in the middle of the target tracking process. The Intermittent Click Planning model proposed in this study describes the process by which users plan and execute optimal click actions, from which the model predicts the pointing error rates. In two studies in which users pointed to a stationary target and a moving target, the model proved to accurately predict the pointing error rates (R2 = 0.992 and 0.985, respectively). The model has also successfully identified differences in cognitive characteristics among first-person shooter game players.