Adaptive educational hypermedia

Adaptive hypermedia (AH) uses hypermedia which is adaptive according to a user model. In contrast to linear media, where all users are offered a standard series of hyperlinks, adaptive hypermedia (AH) tailors what the user is offered based on a model of the user's goals, preferences and knowledge, thus providing links or content most appropriate to the current user. Adaptive hypermedia (AH) uses hypermedia which is adaptive according to a user model. In contrast to linear media, where all users are offered a standard series of hyperlinks, adaptive hypermedia (AH) tailors what the user is offered based on a model of the user's goals, preferences and knowledge, thus providing links or content most appropriate to the current user. Adaptive hypermedia is used in educational hypermedia, on-line information and help systems, as well as institutional 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 in an effort to shape the user's cognitive load. 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. 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. A semantic distinction is made between adaptation, referring to system-driven changes for personalisation, and adaptability, referring to user-driven changes. One way of looking at this 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. 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 of interdependent components: a user model, a domain model and an interaction model. The user model is 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 form of test, or from assigning users to generic user categories usually called 'stereotypes'. The student model consists of a personal profile (which includes static data, e.g., name and password), cognitive profile (adaptable data such as preferences), and a student knowledge profile. Systems may adapt, depending on user features such as: 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. The domain model contains several concepts that stand as the backbone for the content of the system. Other terms which have been used for this concept include content model, application model, system model, device model and task model. It describes educational content such as information pages, examples, and problems. The simplest content model relates every content item to exactly one domain concept (in this model, this concept is frequently referred to as a domain topic). More advanced content models use multi-concept indexing for each content item and sometimes use roles to express the nature of item-concept relationship.A cognitively valid domain model should capture descriptions of the application at three levels, namely: Each content concept has a set of topics. Topics represent individual pieces of knowledge for each domain and the size of each topic varies in relation to the particular domain. Additionally, topics are linked to each other forming a semantic network. This network is the structure of the knowledge domain. The interaction or adaptation 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). It displays information to the user based on his or her cognitive preferences. For instance, the module will divide a page's content into chunks with conditions set to only display to certain users or preparing two variants of a single concept page with a similar condition.The two main aspects to the interaction model are capturing the appropriate raw data and representing the inferences, adaptations and evaluations which may occur.