The training regimen for personnel entering an Aerospace Operations Center (AOC) must cover a complex organizational structure with complex information flows, both horizontally and vertically. Training and orientation includes classroom lectures on many different specialty areas within the AOC, supplemented with exercises offering limited practice in greater depth with some of these areas. Recent exercises have revealed a need for further refresher training, particularly in focus areas within the AOC that involve complex decision-making based on AOC-specific processes, as opposed to general operational knowledge or experience. This paper presents a proof-of-concept system developed to demonstrate web-based refresher training for the Master Air Attack Plan (MAAP) focus area within the AOC. The benefits of refresher training are well-documented, for the flexibility they provide trainees in reviewing concepts on their own from different locations and "just-in-time" when given a new assignment. However, distributed refresher training without an intelligent tutoring component can amount to little more than an online textbook. By implementing Intelligent Tutoring System (ITS) methods in the distributed setting, trainees can benefit from scenario-specific and student-specific feedback in response to their performance on simulated operational exercises. The system described in this paper is based on a limited principle hierarchy developed and integrated with an online simulation. This simulation models an existing software environment for the MAAP decision-making process. The student is given an introductory briefing on a targeting and resource allocation task, and the student's subsequent performance in developing an attack plan and information coordination plan is evaluated in terms of the system's principle hierarchy. The system supports an iterative training loop, where the student can revisit the exercise to modify earlier planning decisions, and receive updated feedback.