A lot of research on AI-ED has been done to date. Although we have many theories and implemented systems some of which are used in practice, we still need promising directions to which effort should be devoted in order to enable further progress of AI-ED research. The main topic here is how to engineer knowledge in IESs. On the basis of this observation, we discuss the importance of ontology engineering which is a innovative research area in artificial intelligence.
Ontology plays several roles critical to overcoming the drawbacks which the current IESs have.
It makes systems smart and reflexive. It explicates the conceptualization on which the system is based. It contributes to standardization of vocabulary. It enables them to be literate and hence to communicate with humans. In this paper, we discuss how ontology contributes to IES research in general and exemplify how it makes authoring systems smarter.