Choosing input devices for interactive systems that best suit user's needs remains a challenge, especially considering the increasing number of devices available. The choice often has to be made through empirical evaluations. The most frequently used evaluation task hitherto is target acquisition, a task that can be accurately modeled by Fitts' law. However, today's use of computer input devices has gone beyond target acquisition alone. In particular, we often need to perform trajectory-based tasks, such as drawing, writing, and navigation. This paper illustrates how 'a recently discovered model, the steering law, can be applied as an evaluation paradigm complementary to Fitts' law. We tested five commonly used computer input devices in two steering tasks, one linear and one circular. Results showed that subjects' performance with the five devices could be generally classified into three groups in the following order: 1. the tablet and the mouse, 2. the trackpoint, 3. the touchpad and the trackball. The steering law proved to hold for all five devices with greater than 0.98 correlation. The ability to generalize the experimental results and the limitations of the steering law are also discussed.Much research has been conducted to help designers and users choose the input device that best suits to their needs. Yet, due to the rich dimensionality of input device design and the complexity of human capability, adaptability, and limitation, human performance in using various devices can not be reliabky predicted from previous research alone. User interface designers therefore often have to conduct empirical comparisons among many candidate devices. In order to make the empirical comparison generalizable to task parameters beyond those tested in the experiment, the experimenters need performance models that provide predictable power. The best known model serving such a purpose is Fitts' law [5], commonly expressed in the following form:

Interaction tasks on a computer screen can technically be scaled to a much larger or much smaller sized input control area by adjusting the input device's control gain or the control-display (C-D) ratio. However, human performance as a function of movement scale is not a well concluded topic. This study introduces a new task paradigm to study the scale effect in the framework of the steering law. The results confirmed a U-shaped performance-scale function and rejected straight-line or no-effect hypotheses in the literature. We found a significant scale effect in path steering performance, although its impact was less than that of the steering law's index of difficulty. We analyzed the scale effects in two plausible causes: movement joints shift and motor precision limitation. The theoretical implications of the scale effects to the validity of the steering law, and the practical implications of input device size and zooming functions are discussed in the paper.

Today's graphical interactive systems largely depend upon pointing actions, i.e. entering an object and selecting it. In this paper we explore whether an alternate paradigm -crossing boundaries -may substitute or complement pointing as another fundamental interaction method. We describe an experiment in which we systematically evaluate two targetpointing tasks and four goal-crossing tasks, which differ by the direction of the movement variability constraint (collinear vs. orthogonal) and by the nature of the action (pointing vs. crossing, discrete vs. continuous). We found that participants' temporal performance in each of the six tasks was dependent on the index of difficulty formulated in the same way as in Fitts' law, but that the parameters differ by task. We also found that goal crossing completion time was shorter or no longer than pointing performance under the same index of difficulty. These regularities, as well as qualitative characterizations of crossing actions and their application in HCI, lay the foundation for designing crossing-based user interfaces.

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