The U.S. Navy continues to make advances in data-rich live, virtual, and constructive (LVC) training environments that provide the ability to harness human performance data and apply machine learning (ML) and artificial intelligence (AI) to realize gains in mission performance and readiness. Additional advances in instructional methods and data science, when combined with this ability to understand and act on human performance data, provide a foundation for creating precision learning environments.

During live training, instructors offer hints and guidance in response to the students’ verbal and nonverbal cues. They also modify the sequence of training content and direct the student to additional practice time or skill remediation activities, as required. Precision learning technologies aim to emulate, not replace, this guidance in order to provide an optimal, tailored learning experience for every student. These technologies rely on real-time measures of learner performance, and use algorithms that determine precisely what the learner knows in order to recommend what learning experiences should occur next. By tailoring the sequence, difficulty, and type of learning content to the needs of each individual student, precision learning approaches can accelerate time to proficiency. Further, when critical data and performance indicators are captured and catalogued, they can be used in individual and team assessments across domains, in after action reviews, and as a means of tracking performance and proficiency over time.

This paper will detail the precision learning concepts and technologies recently adopted by the US Navy’s Center for Surface Combat Systems (CSCS). The authors will describe methods used to create the first implementation of an environment that enhances existing training content; deliver an optimized learning path, and; help instructors know exactly how each student is performing. Specific guidelines and lessons learned will be shared so that readers can implement these approaches in their own organizations.