An error model for pointing based on Fitts' law

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An error model for pointing based on Fitts' law

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Conference on Human Factors in Computing Systems archive
Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems table of contents

Florence, Italy

SESSION: Fitt's Law Lives table of contents

Pages 1613-1622

Year of Publication: 2008

ISBN:978-1-60558-011-1

Authors

Jacob O. Wobbrock	University of Washington, Seattle, WA, USA
Edward Cutrell	Microsoft Research, Redmond, WA, USA
Susumu Harada	University of Washington, Seattle, WA, USA
I. Scott MacKenzie	York University, Toronto, ON, Canada

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ACM: Association for Computing Machinery
SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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ACM New York, NY, USA

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ABSTRACT

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.

REFERENCES

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