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Students are characterized by different learning styles, focusing on different types of information and processing this information in different ways. One of the goals of a Web-based education system is that all the students can learn despite their different learning styles. To achieve this goal we have to detect how students learn. We propose the use of Bayesian Networks to detect the learning style of a student in a Web-based education system. The information obtained can be then used by an intelligent agent to provide personalized assistance to students, delivering teaching material that best fits students’ learning styles.