Student Performance Evaluation for a Simulation Based Intelligent Expert Tutoring System

Abstract

Intelligent tutoring systems offer an exciting new way to train people in areas of complex domains. A simulation-based training system provides the student with the opportunity to manipulate a system without the consequences of real life mistakes. The intelligence required in the tutoring system is focused on the tutor's ability to teach the student efficient, strategic responses. This tutoring demands that the tutor is aware of the student's current ability, specific fault areas, and preferred method of tutoring. Instructional decisions are made by assessing the student's performance. The utility of an intelligent tutoring system depends on its capacity to evaluate the student's performance. Performance assessment then has significant impact on the employment of such a system. The parameters used for performance assessment of a complex task depend on the objective of the tutoring system. We present a description of a generic intelligent tutoring system which will remove the human instructor from the training loop.