Abstract
Traditional one-dimensional error scores are still consistently used in research on motor learning to quantify two-dimensional error; however, the inherent differences in two-dimensional tasks render that application inappropriate and often misleading. Consequently, the purpose of this paper was to propose a novel method of presenting errors, which more precisely represents the accuracy, direction, and variability of error in two-dimensional settings. Although closely related to several alternatives for representing errors, the methodology used and the results obtained provide a more accurate procedure for pinpointing critical trends in what have been commonly referred to as AE (absolute error), VE (variable error), CE (constant error), and E (total variability). The proposed measurements of AVE (adjusted variable error), DE (directional error), TSE (total spread of error), and RE (radial error) provide composite error scores carrying a variety of information about performance on two-dimensional tasks. Formulas and examples are provided to facilitate computation and enhance understanding of the proposed scores.
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