Automatic authoring in the LAOS AHS authoring model

In this paper, we extend the automatic authoring techniques that can be built based on the LAOS model, a five-layer AHS authoring model. As the LAOS model itself is fairly complex, although information-rich, an adaptive hypermedia author needs a lot of system support to be able to populate all its levels with the corresponding information. Therefore, such automatic authoring techniques, which are actually automatic transformation (and interpretation) rules between the different layers of the model, have been designed. These automatic rules represent, in the area of adaptive systems, designer-goal oriented adaptation techniques. They should represent the goal of the designer that is authoring the hypermedia (such as the pedagogical goal in educational adaptive hypermedia). Therefore, this paper represents yet another step towards an adaptive hypermedia (or adaptive course) that ‘writes itself’. The focus here is on automatic transformation between the domain and a newly introduced goal and constraints model, to show that the effort of introducing this new layer can be minimal

Continuous use of authoring for adaptive educational hypermedia : a long-term case study

Adaptive educational hypermedia allows lessons to be personalized according to the needs of the learner. However, to achieve this, content must be split into stand-alone fragments that can be processed by a course personalization engine. Authoring content for this process is still a difficult activity, and it is essential for the popularization of adaptive educational hypermedia that authoring is simplified, so that the various stakeholders in the educational process, students, teachers, administrators, etc. can easily work with such systems. Thus, real-world testing with these stakeholders is essential. In this paper we describe recent extensions and improvements we have implemented in the My Online Teacher MOT3.0 adaptation authoring tool set, based on an initial set of short-term evaluations, and then focus on describing a long-term usage and assessment of the system

Defining adaptation in a generic multi layer model : CAM: the GRAPPLE conceptual adaptation model

Authoring of Adaptive Hypermedia is a difficult and time consuming task. Reference models like LAOS and AHAM separate adaptation and content in different layers. Systems like AHA! offer graphical tools based on these models to allow authors to define adaptation without knowing any adaptation language. The adaptation that can be defined using such tools is still limited. Authoring systems like MOT are more flexible, but usability of adaptation specification is low. This paper proposes a more generic model which allows the adaptation to be defined in an arbitrary number of layers, where adaptation is expressed in terms of relationships between concepts. This model allows the creation of more powerful yet easier to use graphical authoring tools. This paper presents the structure of the Conceptual Adaptation Models used in adaptive applications created within the GRAPPLE adaptive learning environment, and their representation in a graphical authoring tool

Defining adaptation in a generic multi layer model : CAM: the GRAPPLE conceptual adaptation model

Authoring of Adaptive Hypermedia is a difficult and time consuming task. Reference models like LAOS and AHAM separate adaptation and content in different layers. Systems like AHA! offer graphical tools based on these models to allow authors to define adaptation without knowing any adaptation language. The adaptation that can be defined using such tools is still limited. Authoring systems like MOT are more flexible, but usability of adaptation specification is low. This paper proposes a more generic model which allows the adaptation to be defined in an arbitrary number of layers, where adaptation is expressed in terms of relationships between concepts. This model allows the creation of more powerful yet easier to use graphical authoring tools. This paper presents the structure of the Conceptual Adaptation Models used in adaptive applications created within the GRAPPLE adaptive learning environment, and their representation in a graphical authoring tool

Supporting user adaptation in adaptive hypermedia applications

A hypermedia application offers its users a lot of freedom to navigate through a large hyperspace. The rich link structure of the hypermedia application can not only cause users to get lost in the hyperspace, but can also lead to comprehension problems because different users may be interested in different pieces of information or a different level of detail or difficulty. Adaptive hypermedia systems (or AHS for short) aim at overcoming these problems by providing adaptive navigation support and adaptive content. The adaptation is based on a user model that represents relevant aspects about the user. At the Eindhoven University of Technology we developed anAHS, named AHA {DC981. To describe its functionality and that of future adaptive systems we also developed a reference model for the architecture of adaptive hypermedia applications, named AHAM (for Adaptive Hypermedia Application Model) {DHW991. In AHAM knowledge is represented through hierarchies of large composite abstract concepts as well as small atomic ones. AHAM also divides the different aspects of an AHS into a domain model (DM). a user model (UM) and an adaptation model (AM). This division provides a clear separation of concerns when developing an adaptive hypermedia application. In this paper, we concentrate on the user modeling aspects of AHAM, but also describe how they relate to the domain model and the adaptation model. Also. we provide a separation between the adaptation rules an author or system designer writes (as part of the adaptation model) and the system's task of executing these rules in the right order. This distinction leads to a simplification of the author's or system designer's task to write adaptation rules. We illustrate authoring and adaptation in by some examples in the AHS AHA

Supporting user adaptation in adaptive hypermedia applications

A hypermedia application offers its users a lot of freedom to navigate through a large hyperspace. The rich link structure of the hypermedia application can not only cause users to get lost in the hyperspace, but can also lead to comprehension problems because different users may be interested in different pieces of information or a different level of detail or difficulty. Adaptive hypermedia systems (or AHS for short) aim at overcoming these problems by providing adaptive navigation support and adaptive content. The adaptation is based on a user model that represents relevant aspects about the user. At the Eindhoven University of Technology we developed anAHS, named AHA {DC981. To describe its functionality and that of future adaptive systems we also developed a reference model for the architecture of adaptive hypermedia applications, named AHAM (for Adaptive Hypermedia Application Model) {DHW991. In AHAM knowledge is represented through hierarchies of large composite abstract concepts as well as small atomic ones. AHAM also divides the different aspects of an AHS into a domain model (DM). a user model (UM) and an adaptation model (AM). This division provides a clear separation of concerns when developing an adaptive hypermedia application. In this paper, we concentrate on the user modeling aspects of AHAM, but also describe how they relate to the domain model and the adaptation model. Also. we provide a separation between the adaptation rules an author or system designer writes (as part of the adaptation model) and the system's task of executing these rules in the right order. This distinction leads to a simplification of the author's or system designer's task to write adaptation rules. We illustrate authoring and adaptation in by some examples in the AHS AHA

Designing for change: mash-up personal learning environments

Institutions for formal education and most work places are equipped today with at least some kind of tools that bring together people and content artefacts in learning activities to support them in constructing and processing information and knowledge. For almost half a century, science and practice have been discussing models on how to bring personalisation through digital means to these environments. Learning environments and their construction as well as maintenance makes up the most crucial part of the learning process and the desired learning outcomes and theories should take this into account. Instruction itself as the predominant paradigm has to step down. The learning environment is an (if not 'the�) important outcome of a learning process, not just a stage to perform a 'learning play'. For these good reasons, we therefore consider instructional design theories to be flawed. In this article we first clarify key concepts and assumptions for personalised learning environments. Afterwards, we summarise our critique on the contemporary models for personalised adaptive learning. Subsequently, we propose our alternative, i.e. the concept of a mash-up personal learning environment that provides adaptation mechanisms for learning environment construction and maintenance. The web application mash-up solution allows learners to reuse existing (web-based) tools plus services. Our alternative, LISL is a design language model for creating, managing, maintaining, and learning about learning environment design; it is complemented by a proof of concept, the MUPPLE platform. We demonstrate this approach with a prototypical implementation and a – we think – comprehensible example. Finally, we round up the article with a discussion on possible extensions of this new model and open problems

Authoring courses with rich adaptive sequencing for IMS learning design

This paper describes the process of translating an adaptive sequencing strategy designed using Sequencing Graphs to the semantics of IMS Learning Design. The relevance of this contribution is twofold. First, it combines the expressive power and flexibility of Sequencing Graphs, and the interoperability capabilities of IMS. Second, it shows some important limitations of IMS specifications (focusing on Learning Design) for the sequencing of learning activities

Model-driven transformation and validation of adaptive educational hypermedia using CAVIAr

Authoring of Adaptive Educational Hypermedia is a complex activity requiring the combination of a range of design and validation techniques.We demonstrate how Adaptive Educational Hypermedia can be transformed into CAVIAr courseware validation models allowing for its validation. The model-based representation and analysis of different concerns and model-based mappings and transformations are key contributors to this integrated solution. We illustrate the benefits of Model Driven Engineering methodologies that allow for interoperability between CAVIAr and a well known Adaptive Educational Hypermedia framework. By allowing for the validation of Adaptive Educational Hypermedia, the course creator limits the risk of pedagogical problems in migrating to Adaptive Educational Hypermedia from static courseware