Abstract
Steering a cursor through a constrained path is required for operating graphical user interfaces, such as when navigating a cascaded menu. Recently, the accuracy with which users successfully accomplish a task is emerging as an important performance indicator. In this study, we evaluated the performance of a Servo-Gaussian model to predict the success rates in linear and circular paths with 212 and 166 crowdsourced participants, respectively. The results showed that, for linear paths, the model achieved r 2 = 0.9676 , MAE = 2.036 % , and RMSE = 2.692 % , and for circular paths, it achieved r 2 = 0.9787 , MAE = 3.199 % , and RMSE = 3.927 % . Shuffle-split cross-validation with five train-test data-size ratios also demonstrated the robust prediction accuracy of the model. These findings will provide designers with a useful tool to judge if an interface can be accurately operated without running costly user studies for new task conditions.
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