Abstract: This paper discusses the problems of developing versatile adaptive and intelligent learning systems that can be used in the context of practical Web-based education. We argue that versatility is an important feature of successful Web-based education systems. We introduce ELM-ART, an intelligent interactive educational system to support learning programming in LISP. ELM-ART provides all learning material online in the form of an adaptive interactive textbook. Using a combination of an overlay model and an episodic student model, ELM-ART provides adaptive navigation support, course sequencing, individualized diagnosis of student solutions, and example-based problem-solving support. Results of an empirical study show different effects of these techniques on different types of users during the first lessons of the programming course. ELM-ART demonstrates how some interactive and adaptive educational components can be implemented in WWW context and how multiple components can be naturally integrated together in a single system.

The paper presents research on user modelling for an in-car spoken dialogue system, including the implementation of a generic user modelling module applied to the modelling of drivers' task objectives.

this paper, we first introduce the Experience Management Content Framework of our IESE EF to clarify the given knowledge management context. Enhancing the presented approach, we introduce new strategies to capture, process, disseminate, and exchange knowledge. Case-based reasoning (CBR) is used for both knowledge modeling/retrieval/adaptation as well as for a "learning from example" based approach to user modeling in the sense of Weibelzahl and Weber (1999)

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