SBIR-STTR Award

This proposal addresses the development of an intelligent tutoring system (its) to train air force personnel. Expert-ease systems (EES) has developed and demonstrated a successful computer-based instruction technique called optimally adaptive learning (OAL). OAL combines several technologies: optimization theory, educational modeling, and human psychology. The OAL approach utilized advanced optimization theory to determine "paths" through the educational material presented to students. Based upon an individual student's needs and capabilities, the OAL program automatically tailors a specific series of course material for presentation to the student. In this proposal, EES presents a plan to combine its existing OAL approach with a knowledge-based expert system to produce a practical its for a specific air force application. Its programs will result in: (1) reduced learning times, (2) enhanced learning levels, and (3) more highly motivated students.

The phase II development of an Intelligent Tutoring System (ITS) for training is selected aspects of weather analysis is being proposed. This is the continuation of a successful feasibility and demonstration of a "weather trainer." the main objective of this system is to adaptively present the available courseware to the students in accordance with their ability to grasp the material. The system is based on the use of an expert system to contain a domainindependent instructional strategy and student model. An evidential reasoning approach will be employed to deal with conflicting evidence and to quantify the uncertainties associated with inconclusive information. A hyper-test approach will be use to effectively link text, graphical images, quizzes, etc. Two and three dimensional color graphics will be used to train and test the students in integrated concepts of weather analysis.