Intelligent tutoring systems (ITSs) may augment military training systems and mitigate existing limitations in training personnel and resources. A study was conducted to investigate the effectiveness of an embedded rifle marksmanship ITS for Moving Targets (MT ITS). MT ITS has two main components: (1) a Smart Sight System that provides a perceptual cue to help trainees adjust their point of aim to account for a target's speed, direction of movement, and distance, and (2) a performance based algorithm that delivers shooting performance feedback to trainees. The MT ITS was tested in an experiment where participants engaged moving targets in a virtual shooting range. Moving targets were presented at different speeds, direction of movement, and distances.

How the Army conducts rifle marksmanship training is undergo-ing a number of positive changes. Despite this, challenges to con-ducting and coordinating this critical training remain. One chal-lenge to assessing training effectiveness is a lack of persistent records of soldier performance; too often soldier data are purged shortly after training events for convenience and in order to en-sure privacy. This paper reports on our efforts to research the fea-sibility of collecting, analyzing, and storing data from multiple training systems, in order to accelerate and improve marksman-ship training. We do this through the use of cognitive, psychomo-tor, and affective constructs; and the use of predictive modeling techniques in order to forecast marksmanship qualification scores.These models successfully predicted scores on a 40-point scalewith a root mean square error (RMSE) of less than three, using models that are robust to changing input variables. Future im-provements and directions for this research are also discussed.