Publications
JOURNAL (INTERNATIONAL) Predicting Success Rates in Steering Through Linear and Circular Paths by the Servo-Gaussian Model
Shota Yamanaka, Hiroki Usuba, Haruki Takahashi (Meiji University), Homei Miyashita (Meiji University)
International Journal of Human–Computer Interaction (IJHCI)
May 18, 2023
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 r2 = 0.9676, MAE = 2.036%, and RMSE = 2.692%, and for circular paths, it achieved r2 = 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.
Paper : Predicting Success Rates in Steering Through Linear and Circular Paths by the Servo-Gaussian Model (external link)