User Modeling and Adaptive Navigation Support in WWW-Based Tutoring Systems
Most learning systems and electronic textbooks accessible via the WWW up to now lack the capabilities of individualized help and adapted learning support that are the emergent features of on-site intelligent tutoring systems. This paper discusses the prob
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Abstract. Most leaming systems and electronic textbooks accessible via the WWW up to now Iack the capabilities of individualized help and adapted learning support that are the emergent features of on-site intelligent tutoring systems. This paper discusses the problems of developing interactive and adaptive learning systems on the WWW. We introduce ELM-ART II, an intelligent interactive textbook to support leaming programming in LISP. ELM-ART II demonstrates how interactivity and adaptivity can be implemented in WWW-based tutoring systems. The knowledge-based component of the system uses a combination of an overlay model and an episodic user model. lt also supports adaptive navigation as individualized diagnosis and help on problern solving tasks. Adaptive navigation support is achieved by annotating links. Additionally, the system selects the next best step in the curriculum on demand. Results of an empirical study show different effects of these techniques on different types of users during the first lessons of the programming course.
1 Introduction Originally, the WWW was used to retrieve information from all over the world. Very soon, however, it became clear that the WWW will be able to allow for extended interactivity. With the increased utilization of the interactive features of the WWW a Iot of learning systerns emerged that introduce users into various domains. The number of learning courses is exploding, and one can see a Iot of interesting features that emerge with the improved capabilities of new WWW browsers. Up to now, however, most of these systems have been in an experimental stage. They provide only lirnited support to users who are not farniliar with the new domain. And there are only few systems that adapt to a particular user as on-site tutering systems do. In this paper, we first discuss why student modeling is necessary in an individualized WWWbased tutering system and what the goals of student modeling are. Then we introduce ELMART II, an adaptive, knowledge-based tutering system on the WWW that supports learning programrning in LISP. We show how the goals of individual student modeling are accomplished in this system and, finally, we report on the first results of an empirical study of different types of adaptive navigation support.
*This work is supported by a grant from the "Stiftung Rheinland-Pfalz für Innovation" to the first author.
A. Jameson et al. (eds.), User Modeling © Springer-Verlag Wien 1997
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G. Weberand M. Specht
2 Goals of Student Modeling in WWW-Based Thtoring Systems The two main features in intelligent tutoring systems (ITS) are curriculum sequencing and interactive problern solving support. These features differentiate intelligent learning systems from traditional computer-assisted instruction in that they incorporate intelligent techniques that skilled human teachers use in teaching classes or in coaching individuallearners. Most intelligent learning systems are used in the classroom and, therefore, do not necessarily need to include all these intelligent feature
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