Finger-based pointing performance on mobile touchscreen devices: Fitts’ law fits

Abstract

In this paper we investigate the utility of Fitts’ law for predicting the performance of finger-based pointing on mobile touchscreens, by taking into account both different screen sizes and appropriate interaction styles. The experimental design bases on randomly generating pointing tasks in order to provide a wider range of both suitable target sizes and required finger movements, thus targeting a better representation of common pointing behavior with respect to the usual static test design with a smaller set of predetermined tasks. Data obtained from the empirical study was evaluated against Fitts’ law, specifically its revision which defines target size as the smaller dimension of a 2D shape. Results show a strong model fit with our data, making the latter a fair predictor of pointing performance on mobile touchscreen devices. Altogether ten finger-based pointing models are derived, revealing Fitts’ law pragmatic utility regarding various mobile devices, interaction styles, as well as real target sizes commonly found in mobile touchscreen interfaces.