This paper discusses techniques for adapting the content in an online lecture system for a specific user. A two-pass method is used: 1) determine the appropriate level of difficulty for the student and 2) consider the student's learning style preferences. A simple grading scheme is used to determine the student's knowledge and a Na?ve Bayes Classifier is used to reason about the student's preferences in terms of explanations, examples, and graphics. A technique for gathering and using population data is also discussed.
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