The instructional competence of an Intelligent Tutoring System lies in
its instructional model. Such a model has been approached in the ITS
field from a theoretical and from a computational point of view. GTE a
pproaches the instructional model from an epistemological point of vie
w by making it reflect the instructional knowledge and expertise that
underlies human teaching. The underlying assumption is that such knowl
edge and expertise has a generic nature, and that it can be modelled.
The central component of the GTE architecture is therefore a large gen
eric instructional knowledge base that is capable of dynamically gener
ating a huge variety of instructional plans. It enables to flexibly ad
apt the teaching performance to the requirements of the individual tea
ching context. In this paper we describe the formalism that was develo
ped for the representation of the instructional knowledge, the interpr
etation engine that can generate instructional processes based on the
knowledge in the knowledge base, and the actual content of the knowled
ge base. It illustrates the feasibility of the assumption that was mad
e, and the impact this may have on authoring instructional strategies.