Understanding performance in touch selections: Tap, drag and radial pointing drag with finger, stylus and mouse
Touch-based interaction with computing devices is becoming more and more common. In order to design for this setting, it is critical to understand the basic human factors of touch interactions such as tapping and dragging; however, there is relatively little empirical research in this area, particularly for touch-based dragging. To provide foundational knowledge in this area, and to help designers understand the human factors of touch-based interactions, we conducted an experiment using three input devices (the finger, a stylus, and a mouse as a performance baseline) and three different pointing activities. The pointing activities were bidirectional tapping, one-dimensional dragging, and radial dragging (pointing to items arranged in a circle around the cursor). Tapping activities represent the elemental target selection method and are analysed as a performance baseline. Dragging is also a basic interaction method and understanding its performance is important for touch-based interfaces because it involves relatively high contact friction. Radial dragging is also important for touch-based systems as this technique is claimed to be well suited to direct input yet radial selections normally involve the relatively unstudied dragging action, and there have been few studies of the interaction mechanics of radial dragging. Performance models of tap, drag, and radial dragging are analysed. For tapping tasks, we confirm prior results showing finger pointing to be faster than the stylus/mouse but inaccurate, particularly with small targets. In dragging tasks, we also confirm that finger input is slower than the mouse and stylus, probably due to the relatively high surface friction. Dragging errors were low in all conditions. As expected, performance conformed to Fitts' Law. Our results for radial dragging are new, showing that errors, task time and movement distance are all linearly correlated with number of items available. We demonstrate that this performance is modelled by the Steering Law (where the tunnel width increases with movement distance) rather than Fitts' Law. Other radial dragging results showed that the stylus is fastest, followed by the mouse and finger, but that the stylus has the highest error rate of the three devices. Finger selections in the North-West direction were particularly slow and error prone, possibly due to a tendency for the finger to stick–slip when dragging in that direction.