Adaptive hypermedia is a new direction of research within the area of adaptive and user model-based interfaces. Adaptive hypermedia (AH) systems build a model of the individual user and apply it for adaptation to that user, for example, to adapt the content of a hypermedia page to the user's knowledge and goals, or to suggest the most relevant links to follow. AH systems are used now in several application areas where the hyperspace is reasonably large and where a hypermedia application is expected to be used by individuals with different goals, knowledge and backgrounds. This paper is a review of existing work on adaptive hypermedia. The paper is centered around a set of identified methods and techniques of AH. It introduces several dimensions of classification of AH systems, methods and techniques and describes the most important of them.

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Methods and techniques of adaptive hypermedia

Adaptive hypermedia is a relatively new direction of research on the crossroads of hypermedia and user modeling. Adaptive hypermedia systems build a model of the goals, preferences and knowledge of each individual user, and use this model throughout the interaction with the user, in order to adapt to the needs of that user. The goal of this paper is to present the state of the art in adaptive hypermedia at the eve of the year 2000, and to highlight some prospects for the future. This paper attempts to serve both the newcomers and the experts in the area of adaptive hypermedia by building on an earlier comprehensive review (Brusilovsky, 1996; Brusilovsky, 1998).

Adaptive Hypermedia

A fundamental objective of human–computer interaction research is to make systems more usable, more useful, and to provide users with experiences fitting their specific background knowledge and objectives. The challenge in an information-rich world is not only to make information available to people at any time, at any place, and in any form, but specifically to say the “right” thing at the “right” time in the “right” way. Designers of collaborative human–computer systems face the formidable task of writing software for millions of users (at design time) while making it work as if it were designed for each individual user (only known at use time). User modeling research has attempted to address these issues. In this article, I will first review the objectives, progress, and unfulfilled hopes that have occurred over the last ten years, and illustrate them with some interesting computational environments and their underlying conceptual frameworks. A special emphasis is given to high-functionality applications and the impact of user modeling to make them more usable, useful, and learnable. Finally, an assessment of the current state of the art followed by some future challenges is given.

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User Modeling in Human–Computer Interaction

1. The Computer as a Tool for Learning Through Reflection.- 2. Toward a Theory of Impasse-Driven Learning.- 3. Psychological Evaluation of Path Hypotheses in Cognitive Diagnosis.- 4. Modeling the Knowledge Base of Mathematics Learners: Situation-Specific and Situation-Nonspecific Knowledge.- 5. The Knowledge Engineer as Student: Metacognitive Bases for Asking Good Questions.- 6. Toward a Theory of Curriculum for Use in Designing Intelligent Instructional Systems.- 7. Enhancing Incremental Learning Processes with Knowledge-Based Systems.- 8. Mental Models and Metaphors: Implications for the Design of Adaptive User-System Interfaces.- 9. Improvement of the Acquisition of Knowledge by Informing Feedback.- 10. Socializing the Intelligent Tutor: Bringing Empathy to Computer Tutors.- 11. Cognitive Economy in Physics Reasoning: Implications for Designing Instructional Materials.- 12. Experimental Data for the Design of a Microworld-Based System for Algebra.- 13. Computer-Aided Model Building.

Learning Issues for Intelligent Tutoring Systems

Preface. 1. Methods and Techniques of Adaptive Hypermedia P. Brusilovsky. 2. Adaptive Hypertext Navigation Based on User Goals and Context C. Kaplan, et al. 3. Metadoc: An Adaptive Hypertext Reading System C. Boyle, A.O. Encarnacion. 4. User Modelling in the Interactive Anatomy Tutoring System ANATOM-TUTOR I.H. Beaumont. 5. Hypadapter: An Adaptive Hypertext System for Exploratory Learning and Programming H. Hohl, et al. 6. A Glass Box Approach to Adaptive Hypermedia K. Hook, et al. 7. User-Centered Indexing for Adaptive Information Access N. Mathe, J.R. Chen. 8. A Task-Centred Approach for User Modeling a Hypermedia Office Documentation System J. Vassileva. Index.

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Adaptive HyperText and Hypermedia

Our research goals are to understand the nature of, construct and evaluate intelligent interfaces as knowledge-based systems In this paper we demonstrate the need for help systems as an essential part of human-computer communication Help strategies are based on a model of the task (to understand what the user is doing or which goals he/she1 wants to achieve) and a model of the user (to guarantee that these systems are non-intrusive and that they pay attention to the needs of individual users)We illustrate that passive and active help systems have to be constructed as knowledge-based systems Two operational systems (PASSIVIST and ACTIVIST) are described to show the usefulness of this approach

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Knowledge-based help systems

Good on-line help systems are of crucial importance for the computer systems of the future. An increased functionality (required by the many different tasks which a user wants to do) will lead to an increased complexity. Empirical investigations have shown that on the average only 40% of the functionality of complex computer systems are used. Passive help systems (which require that the user requests help explicitly from the system) are of little use if the user does not know the existence of a system feature. Active help systems should guide and advise an user similar to a knowledgeable colleague or assistant.

Active help systems

Upsilon-pi-ADAPT-epsilon-rho: Individualizing hypertext

Combining hypermedia browsing with formal queries

ΥπAdapteρ (sprich „Hypadapter“) ist ein System, das Programmierer bei der Aneignung der Programmiersprache CommonLisp [Steele Jr. 84] individuell unterstutzt. Es verhalt sich dabei wie ein intelligenter Assistent [Teitelman 79, Bocker 88], der eine adaptive und adaptierbare Lernumgebung anbietet: ΥπAdapteρ generiert individualisierte Prasentationen von tutoriellen Informationen und erlaubt den Benutzern, private Hypertext-Pfade im komplexen Netz der Informationseinheiten anzulegen und zu verwalten.

Thomas Schwab

Papers

Knowledge-based help systems

Active help systems

Upsilon-pi-ADAPT-epsilon-rho: Individualizing hypertext

Combining hypermedia browsing with formal queries

Hypadapter - Ein adaptives Hypertextsystem zur Präsentation von Lerninhalten