AMPLE II: Adaptive Module for Personalized Learning Environments

As operational environments become increasingly complex, it is ever more critical that military personnel are trained to proficiency to ensure success in such environments.Developing and maintaining competence can be optimized through development of intelligent, efficient, and data-driven approaches to provide personalized training.While valuable training data exist in learning management systems (LMS), operational data reflecting mission performance can also provide valuable insight about skill proficiency.However, extracting those data from disparate databases and finding meaningful information is not a trivial task.In the absence of such information, training developers and instructors are limited to costly, time-consuming manual processes to develop training curricula, identify student needs, and deliver optimal training content.Aptima created Adaptive Module for Personalized Learning Environments (AMPLE) to perform educational data mining (EDM) using mathematical models that accurately represent training conditions and context. AMPLEs EDM algorithms identify relationships among historical performance data from training and operational environments.Relationships revealed by AMPLE are utilized by adaptive learning management systems to generate personalized training paths to accelerate skill acquisition and optimize training proficiency.AMPLE provides a powerful data mining tool that turns training and operational performance data into actionable training guidance.