Knowledge Elicitation

Project Knowledge Elicitation for an Intelligent Tutoring System
Design an intelligent tutoring system to teach infantry basic skills of entering and clearing buildings. The tutoring will occur in a virtual reality system.

KnowledgeElicitation

Understand basic procedural aspects of the tasks at hand as well as the intricacies of visual, auditory and manual movements through the rooms. Memorizing the procedures is one thing, learning the details of working in a team, minimizing causalities and doing things like they are second nature requires deep understanding of what the expert knows.

Research Several tools and techniques were used to create an understanding of the problem space. Firstly, the Army attempts to write down all of the procedures they are training. If they are not written down for the purposes of training they are put together in after-action-review briefs. These briefs gather the learning from the field so that they may be incorporated. All of this information was gathered and used to create outlines and flowcharts of what individuals were to learn. This information was used to build the interview sheets.Multiple interviews were performed with commanders, trainers and field experts. This information was gathered and incorporated into the outlines and flows. This still remained too cursory to teach an individual how to clear a building. Deeper understanding of the thought process of the experts were pursued with forms of verbal walk-throughs, comparative analysis of different situations, and creating plans for made up situations.Manual and auditory skills still were needed for the training. Observation of training and practice missions provided hours of video footage as well as hands on practice to understand the physical parts of what was needed. Many of the assumptions of basic training and advanced weaponry were covered to set guidelines of the prerequisites for MOUT training.

Much of the manual, visual and auditory training became important when working in teams. Learning how to communicate properly, move to the appropriate positions, and cover specified regions without distraction is a challenge to the novice. In order to understand how to move the novice through stages from novice to expert, basic procedures as well as trainer expertise were required. The trainers compared individuals at different stages of learning, in addition research on teams was incorporated to round out the knowledge gathered.

Analysis The analysis was brought into the context of how you train a person using a computer. Each scenario was worked out for each person in the team. Everything was developed as using an artificial intelligence approach to scenarios by understanding events and the responses to those events. These scenarios and events gave the boundaries to the lessons and the instructions for correcting learning and behavior.

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