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In this paper we describe the basis of aLF (active learning framework) an environment for web-based distance learning on the web and how it can be extended with a user modelling subsystem aimed at providing an adaptive response which can meet users' knowledge state, preferences and goals. We concentrate on user data collection and its further processing to create a user model. Furthermore, as regards the user modelling task, we claim that a combination of different machine learning algorithms should perform better than individual methods. To support our approach we will provide some preliminary experimental results.