Abstract
This paper is focused on user modeling and adaptation in distributed E-Learning systems. We describe here CUMULATE, a generic student modeling server developed for a distributed E-Learning architecture, KnowledgeTree. We also introduce a specific, topic-based knowledge modeling approach which has been implemented as an inference agent in CUMULATE and used in QuizGuide, an adaptive system that helps students select the most relevant self-assessment quizzes. We also discuss our attempts to evaluate this multi-level student modeling.
