Indexing And Exploiting A Discourse History To Generate Context-Sensitive Explanations

A slriking difference between the interactions that students have with human tutors and those they have with computer-based instruction systems is that human tutors frequently refer to their own previous explanations. Based on a study of human-human instructional interactions, we are categorizing the uses of previous discourse and are developing a computational model of this behavior. In this paper, I describe the slrategies we have implemented for identifying relevant prior explanations, and the mechanisms that enable our text planner to exploit the information stored in its discourse history in order to omit information that has previously been communicated, to point out similarities and differences between entities and situations, and to mark re-explanations in circumstances where they are deemed appropriate.