Augmented Intelligence for Instructional Systems in Simulation-Based Training

Abstract

Augmented Intelligence is a design pattern for a human-centered collaboration model of people and artificial intelligence (AI), where machines assist humans in tasks such as data analysis, information retrieval, decision-making, and task execution. In this study, the concept of Augmented Intelligence is applied within the context of an instructional system for simulation-based training. Here, the collaboration between human and machine is focused on the role of the instructor, which is to guide the learning process of one or more trainees toward some learning objective. We identify different levels of machine support to assist an instructor in this role during an adaptive training cycle. Additionally, two design aspects are discussed that contribute to increased levels of intelligence, namely the challenge of domain alignment to empower automation capabilities, and the benefits of simulation-based task environments to deliver AI-enabled approaches. Examples are discussed in the context of military training.