Abstract
The development of embedded trainers and intelligent tutoring systems (ITS) may allow modern militaries to maintain high proficiency in marksmanship skills despite limitations on training personnel and resources. A system embedding an ITS in a future rifle concept was developed to examine the potential of such technologies. This system was based on two main concepts: 1) instance-based learning and practice that uses a Smart Sight System to present a perceptual cue adjusted for the target’s properties and environmental variables and 2) rule-based learning that relies on artificial intelligence algorithm that delivers training tips and feedback to participants. The experimental task involved engaging moving targets on a virtual shooting range. Three types of training were compared: a control group that received no additional training, a standard Canadian Armed Forces (CAF) training group, and an advanced training group that received ITS training. The results showed that additional training—both CAF and ITS—improved shooting accuracy. The performance in the ITS condition was consistently better than in the Control group or in the CAF training group on selected measures of performance.
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