ROC Curve for error model
ROC Curve for error model

Even when people know how to do a task very well, errors still occur: People forget to check their blind spot when driving or they leave their original on the glass after making a copy. Our goal is three-fold: to understand why people make errors, to build models that take that understanding and predict when someone is going to make an error, and then to prevent that error before it happens.

Our focus has been on procedural tasks -- tasks that are well known by a user and where errors are relatively rare. We use Memory for Goals (Altmann & Trafton, 2002; 2007) as our primary theory and have process models of well-learned procedural tasks that explain why people make errors on routine tasks (Trafton, Altmann, & Ratwani, 2011). We also have built statistical models that allow us to predict and prevent post completion errors with remarkable accuracy across a range of tasks (Ratwani & Trafton, 2011).

Principal Investigator:
Dr. J. Gregory Trafton
Navy Center for Applied Research in Artificial Intelligence
Information Technology Division
Naval Research Laboratory
Washington DC 20375
Email: w5515 "at"

Publication Approval: 

Selected Publications

J. G. Trafton, Altmann, E. M. , and Ratwani, R. M. , A memory for goals model of sequence errors, Cognitive Systems Research, vol. 12, pp. 134-143, 2011.
R. M. Ratwani and Trafton, J. G. , Predicting Postcompletion Errors using Eye Movements, Topics in Cognitive Science, vol. 2, pp. 154-167, 2010.
R. M. Ratwani, McCurry, M. J. , and Trafton, J. G. , Predicting postcompletion errors using eye movements, in Proceedings of the conference on human factors in computing systems (SIGCHI 2008), 2008, pp. 539-542.