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

An improved human user computer interface system, wherein a user characteristic or set of characteristics, such as demographic profile or societal “role”, is employed to define a scope or domain of operation. The operation itself may be a database search, to interactively define a taxonomic context for the operation, a business negotiation, or other activity. After retrieval of results, a scoring or ranking may be applied according to user define criteria, which are, for example, commensurate with the relevance to the context, but may be, for example, by date, source, or other secondary criteria. A user profile is preferably stored in a computer accessible form, and may be used to provide a history of use, persistent customization, collaborative filtering and demographic information for the user. Advantageously, user privacy and anonymity is maintained by physical and algorithmic controls over access to the personal profiles, and releasing only aggregate data without personally identifying information or of small groups.

Database access system

One distinctive feature of any adaptive system is the user model that represents essential information about each user This chapter complements other chapters of this book in reviewing user models and user modeling approaches applied in adaptive Web systems The presentation is structured along three dimensions: what is being modeled, how it is modeled, and how the models are maintained After a broad overview of the nature of the information presented in these various user models, the chapter focuses on two groups of approaches to user model representation and maintenance: the overlay approach to user model representation and the uncertainty-based approach to user modeling

User models for adaptive hypermedia and adaptive educational systems

This article gives a comprehensive overview of techniques for personalised hypermedia presentation. It describes the data about the computer user, the computer usage and the physical environment that can be taken into account when adapting hypermedia pages to the needs of the current user. Methods for acquiring these data, for representing them as models in formal systems and for making generalisations and predictions about the user based thereon are discussed. Different types of hypermedia adaptation to the individual user's needs are distinguished and recommendations for further research and applications given. While the focus of the article is on hypermedia adaptation for improving customer relationship management utilising the World Wide Web, many of the techniques and distinctions also apply to other types of personalised hypermedia applications within and outside the World Wide Web, like adaptive educational systems.

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Personalised hypermedia presentation techniques for improving online customer relationships

Computers have transformed every facet of our culture, most dramatically communication, transportation, finance, science, and the economy. Yet their impact has not been generally felt in education due to lack of hardware, teacher training, and sophisticated software. Another reason is that current instructional software is neither truly responsive to student needs nor flexible enough to emulate teaching. The more instructional software can reason about its own teaching process, know what it is teaching, and which method to use for teaching, the greater is its impact on education. 

Building Intelligent Interactive Tutors discusses educational systems that assess a student's knowledge and are adaptive to a student's learning needs. Dr. Woolf taps into 20 years of research on intelligent tutors to bring designers and developers a broad range of issues and methods that produce the best intelligent learning environments possible, whether for classroom or life-long learning. The book describes multidisciplinary approaches to using computers for teaching, reports on research, development, and real-world experiences, and discusses intelligent tutors, web-based learning systems, adaptive learning systems, intelligent agents and intelligent multimedia.

*Combines both theory and practice to offer most in-depth and up-to-date treatment of intelligent tutoring systems available
*Presents powerful drivers of virtual teaching systems, including cognitive science, artificial intelligence, and the Internet
*Features algorithmic material that enables programmers and researchers to design building components and intelligent systems

Building Intelligent Interactive Tutors: Student-centered Strategies for Revolutionizing E-learning

Presentation of textual information is undergoing rapid transition. Millennia of experience writing linear documents is gradually being discarded in favor of non-linear hypertext writing. In this paper, we investigate how hypertext — in its current node-and-link form — can be augmented by an adaptive, user-model-driven tool. Currently the reader of a document has to adapt to that document — if the detail level is wrong the reader either skims the document or has to consult additional sources of information for clarification. The MetaDoc system not only has hypertext capabilities but also has knowledge about the documents it represents. This knowledge enables the document to modify its level of presentation to suit the user. MetaDoc builds and dynamically maintains a user model for each reader. The model tailors the presentation of the document to the reader. The three-dimensionality of MetaDoc allows the text presented to be changed either by the user model or through explicit user action. MetaDoc is more a documentation reading system rather than a hypertext navigation or reading tool. MetaDoc is a fully developed and debugged system that has been applied to technical documentation.

Craig D. B. Boyle

Papers

Metadoc: An Adaptive Hypertext Reading System