Techreport,
Interest-Focused Tutoring: A Tractable Approach to Modeling in Intelligent Tutoring Systems
TR-96-08. University of Chicago, Chicago, IL, USA, (1996)
Abstract
Despite the progress made in the field of intelligent tutoring systems
(ITS), it is still a major challenge to build systems that can teach
about complex, ill-structured domains. A chief reason is that detailed,
dynamic modeling of students'' knowledge is intractable in such areas,
and complete, correct models of expert knowledge are inherently difficult
to build. These difficulties have led some to argue that the goal
of intelligent tutoring should be abandoned and that more benefit
could be provided by systems without tutoring. We believe that there
are many areas in which tutorial intervention is essential, particularly
for the communication of expertise. In this paper we advocate basing
tutorial intervention on an analysis of a student''s likely points
of interest within a learning environment, rather than on his or
her state of knowledge. This interest-focused approach results in
considerable simplification of the modeling task, and has other advantages
as well. We describe an interest-tracing intelligent tutoring framework
that we have been using to build learning environments for such ill-structured
tasks as selling, managing, and other interpersonal skills using
tutorial guidance. Our design is based on case-based reasoning as
a model of human problem- solving. Expertise is modeled as an organized
library of cases; student modeling is restricted to the considerations
that enter into the decision to retrieve and present relevant cases.
This paper describes the cognitive theory underlying our tutoring
approach, and the implementation of the tutor. We show how it is
possible to present useful tutorial intervention based on a student''s
state of interest, without an overwhelming burden of student modeling.
