Adaptive Hypermedia is a disputed research field where hypermedia is made adaptive according to a user model.
In contrast to traditional e-learning/electronic learning, e-business, and e-government systems, whereby all users are offered or even directed a standard series of hyperlinks, adaptive hypermedia (AH) tailors what the user sees to a model of the user's goals, preferences and knowledge. Adaptive hypermedia is the answer to the "lost in hyperspace" problem, where the user normally has too many links to choose from, and little knowledge about how to proceed and select the most appropriate ones to him/her. Adaptive hypermedia thus offers a selection of links or content most appropriate to the current user.
An adaptive hypermedia system should satisfy three criteria: it should be a hypertext or hypermedia system, it should have a user model and it should be able to adapt the hypermedia using the model.
- 1 History
- 2 Architecture for adaptive systems
- 3 The basis for the classification of adaptive hypermedia methods and techniques
- 3.1 Where adaptive hypermedia systems can be helpful
- 3.2 What features of the user are used as a source of the adaptation
- 3.3 What can be adapted by a particular technique
- 3.4 Adaptation goals achieved by different methods and techniques
- 4 Methods and techniques
- 5 Adaptivity versus adaptability
- 6 Research
- 7 Related research fields
- 8 See also
- 9 References
Adaptive Hypermedia research started in the early 1990s. At that time, the two main parent areas - Hypertext and User modeling - had achieved a level of maturity that allowed for the research ideas to be explored together. Many researchers had recognized the problems of static hypertext in different application areas, and had begun to explore various ways to adapt the output and behavior of hypertext systems to suit the needs of individual users. The support from the already established user modeling research community was influential in helping the existing research teams to find each other, and in recognizing and promoting adaptive hypermedia as an independent research direction in user modeling. For example, several early papers on adaptive hypermedia were also published in the User Modeling and User-Adapted Interaction (UMUAI) journal; the first workshop on Adaptive Hypermedia was held during a User Modeling conference; and, finally, a special issue of UMUAI on adaptive hypermedia was published in 1996. By that time, several innovative adaptive hypermedia techniques had been developed, and several research-level adaptive hypermedia systems had been built and evaluated.
The year of 1996 can be considered a turning point in adaptive hypermedia research. Before this time, research in this area was performed by a few isolated teams. However, since 1996, adaptive hypermedia has gone through a period of rapid growth. In particular, several new research teams have commenced projects in adaptive hypermedia, and many students have selected adaptive hypermedia as the subject area for their PhD theses. In addition, several workshops directly or indirectly related to adaptive hypermedia were held. Finally, a book on adaptive hypermedia, and a special issue of the New Review of Hypermedia and Multimedia (1998) were published. There are two main factors that might account for this growth of research activity.
The first factor is the rapid increase in the use of the World Wide Web. The Web, with its clear demand for adaptivity due to its widely diverse audience served to boost adaptive hypermedia research, providing both a challenge and an attractive platform. Almost all the papers published before 1996 describe classic pre-Web hypertext and hypermedia. In contrast, the majority of papers published since 1996 are devoted to Web-based adaptive hypermedia systems.
The second factor is the accumulation and consolidation of research experience in the field. It is clearly visible that research in adaptive hypermedia performed and reported up to 1996 has provided a good foundation for the new generation of research. The early papers provided no (or almost no) references to similar work in adaptive hypermedia, and described original methods and techniques. Almost all the systems developed by 1996 were laboratory systems developed to demonstrate and explore innovative ideas. In contrast, many papers published since 1996 are clearly based on earlier research. These papers cite earlier work, and usually suggest an elaboration or an extension of techniques suggested earlier. In addition, a large number of systems developed since 1996 are either real world systems, or research systems developed for real world settings. This is indicative of the relative maturity of adaptive hypermedia as a research direction.
Architecture for adaptive systems
The system categories in which user modelling and adaptivity have been deployed by various researchers in the field share an underlying architecture. The conceptual structure for adaptive systems generally consists out of three models; the user model, the domain model and the interaction model.
The term in this context means a representation of the knowledge and preferences which the system ‘believes’ a user (which may be an individual, a group of people or non-human agents) possesses. It is a knowledge source which is separable by the system from the rest of its knowledge and contains explicit assumptions about the user. Knowledge for the user model can be acquired implicitly by making inferences about users from their interaction with the system, by carrying out some from of test, or from assigning users to generic user categories usually called 'stereotypes'.
The domain model defines the aspects of the application which can be adapted or which are otherwise required for the operation of the adaptive system. Other terms which have been used for this concept include application model, system model, device model and task model. A cognitively valid domain model should capture descriptions of the application at three levels, namely:
- The task level which makes the user aware of the system purpose.
- The logical level which describes how something works.
- The physical level which describes how to do something.
The interaction model contains everything which is concerned with the relationships which exist between the representation of the users (the user model) and the representation of the application (the domain model). The two main aspects to the interaction model are capturing the appropriate raw data and representing the inferences, adaptations and evaluations which may occur.
The basis for the classification of adaptive hypermedia methods and techniques
There are four dimensions of classification:
Where adaptive hypermedia systems can be helpful
Analysis of existing Adaptive Hypermedia systems allow us to name six kinds of hypermedia systems which are used at present as application areas in most of research projects on adaptive hypermedia.
The six kinds of hypermedia systems
- educational hypermedia
- on-line information systems
- on-line help systems
- information retrieval hypermedia systems
- institutional information systems
- systems for managing personalized views.
The two most popular application fields of adaptive hypermedia is adaptive educational hypermedia (AEH) and on-line information systems. Adaptive educational hypermedia tailors what the learner sees to that learner's goals, abilities, needs, interests, and knowledge of the subject, by providing hyperlinks that are most relevant to the user. Essentially, the teaching tools "adapt" to the learner. On-line information systems provide reference access to information for users with a different knowledge level of the subject.
What features of the user are used as a source of the adaptation
There are five features which are used by existing adaptive hypermedia systems: users’
- goals (a feature related with the context of a user's work in hypermedia)
- knowledge (knowledge of the subject represented in the hyperspace)
- background ( all the information related to the user's previous experience outside the subject of the hypermedia system which is relevant enough to be considered)
- hyperspace experience (how familiar is the user with the structure of the hyperspace and how easily can the user navigate it)
- preferences (the user can prefer some nodes and links over others and some parts of a page over others).
What can be adapted by a particular technique
We distinguish content-level and link-level adaptation as two different classes of hypermedia adaptation and call the first one adaptive presentation and the second one adaptive navigation support.
The idea of various adaptive presentation techniques is to adapt the content of a page accessed by a particular user to current knowledge, goals, and other characteristics of the user. For example, a qualified user can be provided with more detailed and deep information while a novice can receive additional explanations. Adaptive text presentation is the most studied technology of hypermedia adaptation. There are a number of different techniques for adaptive text presentation.
The idea of adaptive navigation support techniques is to help users to find their paths in hyperspace by adapting the way of presenting links to goals, knowledge, and other characteristics of an individual user. This area of research is newer than adaptive presentation, a number of interesting techniques have been already suggested and implemented. We distinguish four kinds of link presentation which are different from the point of what can be altered and adapted:
- Local non-contextual links - This type includes all kinds of links on regular hypermedia pages which are independent from the content of the page.
- Contextual links or "real hypertext" links - This type comprises "hotwords" in texts, "hot spots" in pictures, and other kinds of links which are embedded in the context of the page content and cannot be removed from it.
- Links from index and content pages - An index or a content page can be considered as a special kind of page which contains only links.
- Links on local maps and links on global hyperspace maps - Maps usually graphically represent a hyperspace or a local area of hyperspace as a network of nodes connected by arrows.
Adaptation goals achieved by different methods and techniques
In this section we consider methods by which adaptive hypermedia systems can help to solve some hypermedia problems and describe the most interesting techniques applied by existing AH systems to implement these methods.
Methods and techniques
Adaptation methods are defined as generalizations of existing adaptation techniques. Each method is based on a clear adaptation idea which can be presented at the conceptual level.
Content adaptation methods
- Additional explanations - hides parts of information about a particular concept which are not relevant to the user’s level of knowledge about this concept.
- Prerequisite explanations - before presenting an explanation of a concept the system inserts explanations of all its prerequisite concepts which are not sufficiently known to the user.
- Comparative explanations - if a concept similar to the concept being presented is known, the user gets a comparative explanation which stress similarities and differences between the current concept and the related one.
- Explanation variants - assumes that showing or hiding some portion of the content is not always sufficient for the adaptation because different users may need essentially different information.
- Sorting - fragments of information about the concept are sorted from information which is most relevant to user’s background and knowledge to information which is least relevant.
Link adaptation methods
- global guidance - the system suggests navigation paths on a global scale
- local guidance - the system suggests the next step to take, for instance through a "next" or "continue" button
- local orientation support - the system presents an overview of a part of the (link) structure of the hyperspace
- global orientation support - the system presents an overview of the whole (link) structure of the hyperspace
- managing personalized views in information spaces - each view may be a list of links to all pages or sub-parts of the whole hyperspace which are relevant for a particular working goal.
Adaptation techniques refer to methods of providing adaptation in existing AH systems.
Content adaptation techniques
- Conditional text - with this technique, all possible information about a concept is divided into several chunks of texts. Each chunk is associated with a condition on the level of user knowledge represented in the user model. When presenting the information about the concept, the system presents only the chunks where the condition is true.
- Stretchtext - turns off and on different parts of the content according to the user knowledge level.
- Page variants - the most simple adaptive presentation technique. With this technique, a system keeps two or more variants of the same page with different presentations of the same content.
- Fragment variants - The system stores several variants of explanations for each concept and the user gets the page which includes variants corresponding to his or her knowledge about the concepts presented in the page
- Frame-based techniques - With this technique all the information about a particular concept is represented in form of a frame. Slots of a frame can contain several explanation variants of the concept, links to other frames, examples, etc. Special presentation rules are used to decide which slots should be presented to a particular user and in which order.
Link adaptation techniques
- direct guidance - the "next best" node for the user to visit is shown, e.g. through a "next" or "continue" button
- link sorting - all the links on a particular page are sorted according to the user model and to some goal-oriented criteria: the more towards the top of the page, the more relevant the link is.
- link hiding - hiding links to "non-relevant" pages by changing the color of the anchors to that of normal text)
- link annotation - to augment the link with some form of comment which tells the user more about the current state of the pages to which the annotated links refer.
- link disabling - the "link functionality" of a link is removed.
- link removal - link anchors for undesired links (non-relevant or not yet ready to read) are removed.
- map adaptation - the content and presentation of a map of the link structure of the hyperspace is adapted.
Adaptivity versus adaptability
An interesting aspect of adaptive hypermedia is that it makes distinction between adaptation (system-driven personalisation and modifications) and adaptability (user-driven personalisation and modifications). One way of looking at it is that adaptation is automatic, whereas adaptability is not. From an epistemic point of view, adaptation can be described as analytic, a-priori, whereas adaptability is synthetic, a-posteriori. In other words, any adaptable system, as it "contains" a human, is by default "intelligent", whereas an adaptive system that presents "intelligence" is more surprising and thus more interesting. This conforms with the general preference of the adaptive hypermedia research community, which considers adaptation more interesting. However, the truth of adaptive hypermedia systems is somewhere in the middle, combining and balancing adaptation and adaptability.
Adaptive hypermedia is the object of a number of researches, in particular in conjunction with user modeling, and the results are published in several journals and conferences such as:
Related research fields
Many fields of research including human-computer interaction, educational technology, cognitive science, intelligent tutoring systems, web commerce and computer engineering are contributing to the development of adaptive hypermedia. Unlike intelligent tutoring systems, however, adaptive educational hypermedia doesn't target stand-alone systems, but hypermedia systems.
- Adaptive educational hypermedia
- authoring of adaptive hypermedia
- User modeling
- Attentive user interface
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- De Bra, Paul; Houben, Geert-Jan; Wu, Hongjing. "AHA: AHAM: A Reference Model to Support Adaptive Hypermedia Authoring". Retrieved 1 April 2013.
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