ABSTRACT
Introduction
The necessity for building a sophisticated human-machine interface for our intelligent tutoring system, called CIRCSIM-Tutor, has motivated us to explore natural language text understanding and generation. One complex task for the generator is crafting a response to student initiatives. As a basis for our research we studied human tutors' responses to student initiatives. How does a human tutor decide how to respond in real life? Initiative and response can be viewed as a cause and effect relationship where the initiative is the antecedent or cause and the response is the consequent or effect. A student initiative occurs when a student takes control of the tutoring session temporarily by saying something that forces the tutor to change the course of action and respond to the new situation. A question asked by the student in itself is considered to be one kind of initiative. A cooperative and reasonable response is considered as one that addresses the appropriate part of the question. We have analyzed tutor responses to student initiatives and developed twelve classes of tutor response to be used in CIRCSIM-Tutor.
