Abstract
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 Naïve 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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© 2000 Springer-Verlag Berlin Heidelberg
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Stern, M.K., Woolf, B.P. (2000). Adaptive Content in an Online Lecture System. In: Brusilovsky, P., Stock, O., Strapparava, C. (eds) Adaptive Hypermedia and Adaptive Web-Based Systems. AH 2000. Lecture Notes in Computer Science, vol 1892. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44595-1_21
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DOI: https://doi.org/10.1007/3-540-44595-1_21
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