A comparison of input devices in element pointing and dragging tasks
CHI '91 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The GOMS family of user interface analysis techniques: comparison and contrast
ACM Transactions on Computer-Human Interaction (TOCHI)
Performance differences in the fingers, wrist, and forearm in computer input control
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
The metropolis keyboard - an exploration of quantitative techniques for virtual keyboard design
UIST '00 Proceedings of the 13th annual ACM symposium on User interface software and technology
The Psychology of Human-Computer Interaction
The Psychology of Human-Computer Interaction
Card, English, and Burr (1978): 25 years later
CHI '03 Extended Abstracts on Human Factors in Computing Systems
Model for non-expert text entry speed on 12-button phone keypads
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The bubble cursor: enhancing target acquisition by dynamic resizing of the cursor's activation area
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
International Journal of Human-Computer Studies - Special issue: Fitts law 50 years later: Applications and contributions from human-computer interaction
International Journal of Human-Computer Studies - Special issue: Fitts law 50 years later: Applications and contributions from human-computer interaction
"Beating" Fitts' law: virtual enhancements for pointing facilitation
International Journal of Human-Computer Studies - Special issue: Fitts law 50 years later: Applications and contributions from human-computer interaction
A probabilistic approach to modeling two-dimensional pointing
ACM Transactions on Computer-Human Interaction (TOCHI)
Speed-Accuracy Tradeoff in Trajectory-Based Tasks with Temporal Constraint
INTERACT '09 Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I
Performance evaluation of a genetic algorithm for optimizing hierarchical menus
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Speeding pointing in tiled widgets: understanding the effects of target expansion and misprediction
Proceedings of the 15th international conference on Intelligent user interfaces
Modeling dwell-based eye pointing target acquisition
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Air pointing: Design and evaluation of spatial target acquisition with and without visual feedback
International Journal of Human-Computer Studies
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Modeling and predicting pointing errors in two dimensions
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Predictive error behavior model of on-screen keyboard users
CHI '11 Extended Abstracts on Human Factors in Computing Systems
Effects of motor scale, visual scale, and quantization on small target acquisition difficulty
ACM Transactions on Computer-Human Interaction (TOCHI)
Pointing at responsive objects outdoors
Proceedings of the 2012 ACM international conference on Intelligent User Interfaces
Two-Part Models Capture the Impact of Gain on Pointing Performance
ACM Transactions on Computer-Human Interaction (TOCHI)
FFitts law: modeling finger touch with fitts' law
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The effect of time-based cost of error in target-directed pointing tasks
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
International Journal of Human-Computer Studies
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For decades, Fitts' law (1954) has been used to model pointing time in user interfaces. As with any rapid motor act, faster pointing movements result in increased errors. But although prior work has examined accuracy as the "spread of hits," no work has formulated a predictive model for error rates (0-100%) based on Fitts' law parameters. We show that Fitts' law mathematically implies a predictive error rate model, which we derive. We then describe an experiment in which target size, target distance, and movement time are manipulated. Our results show a strong model fit: a regression analysis of observed vs. predicted error rates yields a correlation of R2=.959 for N=90 points. Furthermore, we show that the effect on error rate of target size (W) is greater than that of target distance (A), indicating a departure from Fitts' law, which maintains that W and A contribute proportionally to index of difficulty (ID). Our error model can be used with Fitts' law to estimate and predict error rates along with speeds, providing a framework for unifying this dichotomy.