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.