Normalizing Speed-accuracy Biases in 2D Pointing Tasks with Better Calculation of Effective Target Widths

For evaluations of 2D target selection using Fitts’ law, ISO 9241-411 recommends using the effective target width ($W_\text{e}$) calculated using the univariate standard deviation of selection coordinates. Related research proposed using a bivariate standard deviation; however, the proposal was only tested using a single speed-accuracy bias condition, thus the assessment was limited. We compared the univariate and bivariate techniques in a 2D Fitts’ law experiment using three speed-accuracy biases and 346 crowdworkers. Calculating $W_\text{e}$ using the univariate standard deviation yielded higher model correlations across all bias conditions and produced more stable throughput among the biases. The findings were also consistent in cases using randomly sampled subsets of the participant data. We recommend that future research should calculate $W_\text{e}$ using the univariate standard deviation for fair performance evaluations. Also, we found trivial effects when using nominal or effective amplitude and using different perspectives of the task axis.