Fitts' law as a research and design tool in human-computer interaction
MacKenzie places Fitts's law in its historical and theoretical context and examines problems that arise when observations keep departing from its predictions. He proposes a revised index of task difficulty, the logarithm of the distance-to-width ratio plus one, which he argues is more soundly based in information theory and which cannot return a negative value for overlapping targets. The paper reviews six studies that used the law to predict cursor-positioning and selection times with mice, trackballs, joysticks, touchpads, helmet-mounted sights and eye trackers. Their performance measures varied enormously, making cross-study comparison difficult, and the paper identifies sources of experimental variation that might account for the differences. It describes the index of performance as analogous to channel capacity and as the reciprocal of the regression slope.
MacKenzie places Fitts's law in its historical and theoretical context and examines problems that arise when observations keep departing from its predictions. He proposes a revised index of task difficulty, the logarithm of the distance-to-width ratio plus one, which he argues is more soundly based in information theory and which cannot return a negative value for overlapping targets. The paper reviews six studies that used the law to predict cursor-positioning and selection times with mice, trackballs, joysticks, touchpads, helmet-mounted sights and eye trackers. Their performance measures varied enormously, making cross-study comparison difficult, and the paper identifies sources of experimental variation that might account for the differences. It describes the index of performance as analogous to channel capacity and as the reciprocal of the regression slope.
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Human-Computer Interaction, 7(1), 91-139. doi:10.1207/s15327051hci0701_3 https://doi.org/10.1207/s15327051hci0701_3