Many Web-based educational applications are expected to be used by very different groups of users without the assistance of a human teacher. Accordingly there is a need for systems which can adapt to users with very different backgrounds, prior knowledge of the subject and learning goals. An electronic textbook is one of the most prominent varieties of Web-based educational systems. In this paper we describe an approach for developing adaptive electronic textbooks and present InterBook - an authoring tool based on this approach which simplifies the development of adaptive electronic textbooks on the Web.

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.

hypertext in early 1990, it now attracts many researchers from different communities such as hypertext, user modeling, machine learning, natural language generation, information retrieval, intelligent tutoring systems, cognitive science, and Web-based education. model, an adaptable system requires the user to specify exactly how the system should be different, for example, tailoring the sports section to provide information about a favorite team [9]. In different kinds of adaptive systems, adaptation effects could be realized in a variety of ways. Adaptive hypermedia and Web systems are essentially collections of connected information items that allow users to navigate from one item to another and search for relevant items. The adaptation effect in this reasonably rigid context is limited to three major adaptation technologies---adaptive content selection, adaptive navigation support, and adaptive presentation. When the user searches for relevant information, the system can ada

: The navigational freedom in conventional hypermedia applications leads to comprehension and orientation problems [Nielsen 1990]. Adaptive hypermedia attempts to overcome these problems by adapting the presentation of information and the overall link structure, based on a user model. This paper introduces a framework for adaptive hypermedia systems (AHS). It briefly describes some popular methods and techniques for adaptation. Examples and evaluations of existing AHS are used to illustrate the potential benefits of using adaptation in hypermedia applications. Categories and Subject Descriptors: H.1.2 Information Systems User/Machine Systems [Human information processing] H.3.5 Information Systems Online Information Services [Web-based services] H.4.3 Information Systems Communications Applications [Information browsers] H.5.1 Information Systems Multimedia Information Systems [Hypertext navigation and maps] H.5.2 Information Systems User Interfaces [Evaluation/methodology] Additional ...

Abstract. Closed corpus AH systems demonstrate what is possible to achieve with adaptive hypermedia technologies; however they are impractical for dealing with the large volume of open corpus resources. Our system, Knowledge Sea II, presented in this paper explores social adaptive navigation support, an approach for providing personalized guidance in the open corpus context. Following the ideas of social navigation, we have attempted to organize a personalized navigation support that is based on past learners’ interaction with the system. The social adaptive navigation support implemented in our system was considered quite useful by students participating in the classroom study of Knowledge Sea II. At the same time, some user comments indicated the need to provide more powerful navigation support. 1

To provide a more robust context for personalization, we desire to extract a continuum of general (long-term) to specific (short-term) interests of a user. Our proposed approach is to learn a user interest hierarchy (UIH) from a set of web pages visited by a user. We devise a divisive hierarchical clustering (DHC) algorithm to group words (topics) into a hierarchy where more general interests are represented by a larger set of words. Each web page can then be assigned to nodes in the hierarchy for further processing in learning and predicting interests. This approach is analogous to building a subject taxonomy for a library catalog system and assigning books to the taxonomy. Our approach does not need user involvement and learns the UIH "implicitly." Furthermore, it allows the original objects, web pages, to be assigned to multiple topics (nodes in the hierarchy). In this paper, we focus on learning the UIH from a set of visited pages. We propose a few similarity functions and dynamic threshold-funding methods, and evaluate the resulting hierarchies according to their meaningfulhess and shape.

In this paper we present an empirical study of the InterBook system to demonstrate the benefits of the layered evaluation framework, where the success of adaptation is addressed at two distinct layers: (i) interaction assessment, and (ii) adaptation decision making.

. Adaptive User Interfaces (AUIs) are a continuously growing area of research, with numerous experimental and commercial systems reported in the literature, in diverse application areas. Although there exist today a number of established approaches and frameworks for the design and implementation of AUIs, their evaluation is yet to be addressed in a comprehensive way. Arguably, the main drawback of existing evaluation methods and techniques is that they fail to provide adequate feedback into the AUI design process, or to generate empirical findings that can be reused across application boundaries. This paper proposes a new, modular approach to the evaluation of AUIs, which is specifically intended to cater for the aforementioned problems. The adaptive Nautilus Web browser, on which the approach will be applied is also briefly presented. 1.

Adaptive navigation support is a specific group of technologies that support user navigation in hyperspace, by adapting to the goals, preferences and knowledge of the individual user. These technologies, originally developed in the field of adaptive hypermedia, are becoming increasingly important in several adaptive Web applications, ranging from Web-based adaptive hypermedia to adaptive virtual reality. This chapter provides a brief introduction to adaptive navigation support, reviews major adaptive navigation support technologies and mechanisms, and illustrates these with a range of examples.

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