K. de Koning, B. Bredeweg, J. Breuker and B. Wielinga. 2000
Model-Based Reasoning about Learner Behaviour.
Artificial Intelligence, Volume 117, Number 2, pages 173-229.
(PDF)
Abstract
Automated handling of tutoring and training functions in educational systems requires the
availability of articulate domain models. In this article we further develop the application of
qualitative models for this purpose. A framework is presented that defines a key role for qualitative
models as interactive simulations of the subject matter. Within this framework our research focuses
on automating the diagnosis of learner behaviour. We show how a qualitative simulation model of
the subject matter can be reformulated to fit the requirements of general diagnostic engines such as
GDE. It turns out that, due to the specific characteristics of such models, additional structuring is
required to produce useful diagnostic results. A set of procedures is presented that automatically
maps detailed simulation models into a hierarchy of aggregated models by hiding non-essential
details and chunking chains of causal dependencies. The result is a highly structured subject matter
model that enables the diagnosis of learner behaviour by means of an adapted version of the GDE
algorithm. An experiment has been conducted that shows the viability of the approach taken, i.e.,
given the output of a qualitative simulator the procedures we have developed automatically generate
a structured subject matter model and subsequently use this model to successfully diagnoses learner
behaviour.