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CHI
2011
ACM

The effects of task dimensionality, endpoint deviation, throughput calculation, and experiment design on pointing measures and m

12 years 7 months ago
The effects of task dimensionality, endpoint deviation, throughput calculation, and experiment design on pointing measures and m
Fitts’ law (1954) characterizes pointing speed-accuracy performance as throughput, whose invariance to target distances (A) and sizes (W) is known. However, it is unknown whether throughput and Fitts’ law models in general are invariant to task dimensionality (1-D vs. 2-D), whether univariate (SDx) or bivariate (SDx,y) endpoint deviation is used, whether throughput is calculated using the mean-of-means approach or the slope-inverse approach, or whether Guiard’s (2009) Form × Scale experiment design is used instead of fully crossed A×W factors. We empirically investigate the confluence of these issues, finding that Fitts’ law is largely invariant across 1-D and 2-D, provided that univariate endpoint deviation (SDx) is used in both, but that for 2-D pointing data, bivariate endpoint deviation (SDx,y) results in better Fitts’ law models. Also, the mean-of-means throughput calculation exhibits lower variance across subjects and dimensionalities than the slope-inverse calculati...
Jacob O. Wobbrock, Kristen Shinohara, Alex Jansen
Added 25 Aug 2011
Updated 25 Aug 2011
Type Journal
Year 2011
Where CHI
Authors Jacob O. Wobbrock, Kristen Shinohara, Alex Jansen
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