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Virtual learning environments systems are based on the classroom paradigm, in which the knowledge is transmitted for all the students in the same way.
To enhance e-learning, adapting the contents to the
needs of each student is essential, and a more
personalized learning support is required. The
adoption of pedagogical agents and new artificial
intelligence methodologies can response to the needs
of individual students and provide a more effective
collaboration in virtual learning environments.
The learning experience of each student can be
adapted to others students with the same
characteristics. The adaptation of past cases to solve
new problems is one of the features of case-based
reasoning methodology, which can provide an effective
knowledge transmission, based on learning activities.
In this paper, we present a case-based reasoning
approach to Adaptive Web-based Educational Systems
using fuzzy logic to adapt e-learning contents and
contexts according to the student learning style and
individual needs
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