Developing a Predictive Model of Postcompletion Errors

Abstract

A postcompletion error is a type of procedural error that occurs after the main goal of a task has been accomplished. There is a strong theoretical foundation accounting for postcompletion errors (Altmann & Trafton, 2002; Byrne & Bovair, 1997). This theoretical foundation has been leveraged to develop a logistic regression model of postcompletion errors based on reaction time and eye movement measures (Ratwani, McCurry, & Trafton, 2008). The work presented here further develops and extends this predictive model by (1) validating the model and the general set of predictors on a new task to test the robustness of the model, and (2) determining which specific theoretical components are most important to postcompletion error prediction.


Back to Saturday Papers