Abstract

Computer Assisted Language Learning (CALL) has been one of the first incarnations of E-Learning, which has not only become a trend nowadays but also a commercial factor. CALL has its own international conferences and a wide range of academic prototypes and commercial products are available. As with E-Learning software in general, advanced CALL systems are based on the principles of multi media design, facilitating modalities like audio and video, e.g. speech input and output, animated graphics and avatars for guiding the user. Although these design standards do improve the quality of E-Learning systems, it is widely accepted that an optimal learning environment is one where the learner is guided by an intelligent personalized tutor, that adapts to the level of expertise of the learner, for example in tailoring explanations to the user's domain knowledge and selecting appropriate exercises. This is the area of Intelligent Tutorial Systems (ITS) and User Modelling (UM), so far a mainly academic discipline. If at all, only few commercial (CALL) products incorporate such capabilities. The problem is that domain knowledge, reasoning and learning facilities and - in the case of verbal explanations - natural language understanding capabilities are to be integrated; altogether a non-trivial task for many application areas. As a consequence, intelligent tutorial systems seem to be suited well only for restricted domains, e.g. circuit design (Davis 1984).

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