The goal of this project is to design an intelligent tutor to teach visual aircraft recognition (VACR) skills to military population. Under extreme cognitive demand, soldiers must learn to rapidly recognize and identify the aircraft prior to engagement. The goal of the smart tutor is to train the trainees to look at specific features (called Wings, Engine, Fuselage and Tail- WEFT) of the aircraft that will help them proceduralize the skill of aircraft recognition.

We have conducted an empirical (fMRI, eye-tracking, behavior) study and developed a cognitive model based on ACT-R architecture that emulates trainee performance. In this paper, we present insights gained from ACT-R modeling which, in turn, will be used to develop a VACR smart tutor.