The effects of task dimensionality, endpoint deviation, throughput calculation, and experiment design on pointing measures and models
The effects of task dimensionality, endpoint deviation, throughput calculation, and experiment design on pointing measures and models
复制标题
任务维度、端点偏差、吞吐量计算和实验设计对指向测量和模型的影响
DOI：
10.1145/1978942.1979181
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
Alex Jansen
中科院分区：
文献类型：
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作者：
J. Wobbrock;Kristen Shinohara;Alex Jansen
费茨定律（1954）将指向速度-精度性能表征为吞吐量，其对目标距离（A）和大小（W）的不变性是已知的。然而，尚不清楚吞吐量和费茨定律模型通常是否对任务维度（1-D对2-D）不变，是否使用单变量（SDx）或双变量（SDx，y）端点偏差，是否使用平均值方法或斜率逆方法计算吞吐量，或者是否使用Guiard（2009）形式-规模实验设计而不是完全交叉的A-W因子。我们实证研究这些问题的汇合，发现费茨定律在1-D和2-D之间基本上是不变的，前提是在两者中使用单变量端点偏差（SDx），但对于2-D指向数据，双变量端点偏差（SDx，y）导致更好的费茨定律模型。此外，平均值的平均吞吐量计算表现出更低的差异跨学科和维度比斜率逆计算。根据这些和其他研究结果，我们提供了指向评估的建议，特别是在2-D。我们还提供了一个名为Fitts Study的评估工具，以便于进行比较。
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 calculation. In light of these and other findings, we offer recommendations for pointing evaluations, especially in 2-D. We also offer an evaluation tool called Fitts Study to facilitate comparisons.