Adaptive instructional systems (AISs) are artificially-intelligent, computer-based systems that guide learning experiences by tailoring instruction and recommendations based on the learning goals, needs (learning gaps), preferences and interests of each individual learner or team in the context of domain learning objectives (Sottilare & Brawner, 2018; Sottilare, Barr, Robson, Hu, and Graesser, 2018). Adaptive instructional systems, tools and methods enable an individual learner or team to acquire the necessary knowledge and skill to achieve a set of predefined learning objectives in a domain (subject or topical area) under study. AI-based methods are often used to reduce the cost and skills required to design and develop AISs. 

The effectiveness of artificially-intelligent adaptive instructional systems (AISs) has highlighted a need in the US military (e.g., Army Synthetic Training Environment) for intelligent, tailored, guided instruction for both individuals and teams. AISs are able to automatically adjust feedback, support, and challenge level of instruction to focus instruction to the specific needs of individual learners and teams. The marketplace for AISs (e.g., intelligent tutoring systems and intelligent mentors) has grown to a point where the IEEE standards community sees merit in developing standards and recommended practices for AIS conceptual modeling, interoperability and evaluation under Project 2247. The prevalence of AI in the IITSEC community highlights the need to understand the basics of AIS design, development, deployment, and evaluation. This tutorial provides insight into fundamental AIS principles to support military training needs, emerging standards, interoperable conceptual models that make up AISs, effective adaptive instructional policies and strategies, authoring processes, and the AIS marketplace. We are proposing this tutorial as an introduction to AISs and a companion workshop to be held on Friday morning of IITSEC week.