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tutoring system to recognize when a new domain concept is completely unknown
to the learner, when it is fully learned or assimilated, or when it is partly known due
to the learner having previous related knowledge. This is achieved using fuzzy sets
for describing how well each individual domain concept is known or learned and
a set of fuzzy rules, which are responsible for the update of the overall learner's
knowledge level after any change of her/his knowledge of a particular domain of
the learning material.
The application of this approach is not limited to adaptive instruction, but it can
also be used in other systems with changeable user states, such as e-shops, where
consumers' preferences change over the time and affect one another. For example,
it can be used to reduce customer information overload by recommending products
that are likely to be of interest to them, considering their preferences and the depen-
dencies that exist between products' choices (in accordance to e-learning, users'
preferences correspond to users' knowledge level and products' choices correspond
to the domain concepts). Therefore, the particular novel fuzzy approach constitutes
a novel generic fuzzy tool, which offers dynamic adaptation to users' needs and
preferences of adaptive systems.
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