Abstract
The goals of this chapter are twofold. First, we will show how the use of machine learning techniques can greatly improve the dynamic construction and updating of student models. Then, we will discuss the underlying principles of the traditional design paradigm for Intelligent Tutoring Systems (ITSs) and will argue that they are, partially, responsible for the difficulties felt by present day ITSs. We maintain the thesis that the teaching (and learning) situation is a particular instance of the general case of interaction among intelligent agents. As a consequence of this point of view, we sustain that new principles for building ITSs are needed, based on the idea of belief systems.
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© 1992 Springer-Verlag Berlin Heidelberg
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Costa, E. (1992). The Present and Future of Intelligent Tutoring Systems. In: Scanlon, E., O’Shea, T. (eds) New Directions in Educational Technology. NATO ASI Series, vol 96. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77750-9_8
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DOI: https://doi.org/10.1007/978-3-642-77750-9_8
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