Adaptive learning resources selection and sequencing is recognized as among the most interesting research questions in adaptive educational hypermedia systems (AEHS). In order to adaptively select and sequence learning resources in AEHS, the definition of adaptation rules contained in the Adaptation Model, is required. Although, some efforts have been reported in literature aiming to support the Adaptation Model design by providing AEHS designers direct guidance or semi-automatic mechanisms for making the design process less demanding, still it requires significant effort to overcome the problems of inconsistency, confluence and insufficiency, introduced by the use of rules. Due to the problems of inconsistency and insufficiency of the defined rule sets in the Adaptation Model, conceptual “holes ” can be generated in the produced learning resource sequences (or learning paths). In this paper, we address the design problem of the Adaptation Model in AEHS proposing an alternative sequencing method that, instead of generating the learning path by populating a concept sequence with available learning resources based on pre-defined adaptation rules, it first generates all possible learning paths that match the learning goal in hand, and then, adaptively selects the desired one, based on the use of a decision model that estimates the suitability of learning resources for a targeted learner. In our simulations we compare the learning paths generated by the

Abstract. Adaptive Educational Hypermedia (AEH) is very time consuming and complex to produce. Moreover, with the rapid rate of AEH development, content generated within a given system can become outdated very rapidly. Both of these contribute to the slow uptake of AEH outside of the research community. We consider interoperability between AEH systems to be an important part of the solution to this problem. This paper describes our research into a one-to-one conversion between the AEH systems MOT and WHURLE. Here we focus on the conversion of User Model data, drawing conclusions as to the effectiveness of the conversion and identifying common aspects of the two systems ’ user models. 1

Abstract. The creation process of adaptive hypermedia is rarely evaluated. Moreover, conversion between different adaptive hypermedia systems has barely been proposed, yet alone tested in realistic settings. This paper presents the evaluation of the interoperability of two adaptive (educational) hypermedia systems,

Abstract. The penetration of Adaptive Educational Hypermedia (AEH) within the educational community has been very poor so far. In part this is due to the complexity of the authoring process. But it also influenced by the often short ‘lifetime ’ of the AEH software itself. We see AEH system interoperability as a route to address these problems. This paper builds on previous limited interoperability work, between the AEH systems MOT and WHURLE, by using open web standards. We describe a Web Service using Web Services Description Language and SOAP that is capable of converting MOT materials to WHURLE. Moreover this Web Service is flexible and easily extensible, and we hope that this will mark the first step in developing an interoperable middleware for AEH conversions. 1

Conversion between different adaptive hypermedia systems has barely been proposed, yet alone tested in realistic settings. This paper presents the evaluation of the interoperability of two adaptive (educational) hypermedia systems, MOT and WHURLE. The evaluation is performed with the help of a class of thirty-one students enrolled in the fourth year of the “Politehnica ” University of Bucharest, who were taking a oneweek intensive course on Adaptive Hypermedia. This paper describes and interprets our first experiments of the “write once, deliver many ” paradigm of adaptive hypermedia creation. Categories and Subject Descriptors

adaptive hypermedia

To my parents This research proposes a new architecture for Adaptive Educational Hypermedia Systems (AEHS). Architectures in the context of this thesis refer to the components of the system and their communications and interactions. The architecture addresses the limitations of AEHS regarding interoperability, reusability, openness, flexibility, and limited tools for collaborative and social learning. It presents an integrated adaptive and collaborative Web-based learning environment. The new e-learning environment is implemented as a set of independent Web services within a service-oriented architecture (SOA). Moreover, it uses a modern Learning Management System (LMS) as the delivery service and the user interface for this environment. This is a two-way solution, whereby adaptive learning is introduced via a widely adopted LMS, and the LMS itself is enriched with an external- yet integrated-adaptation layer. To test the relevance of the new architecture, practical experiments were undertaken.

Abstract—Today, there is a real challenge to enable personalized access to information. Several systems have been proposed to address this challenge including Adaptive Hypermedia Systems (AHSs). However, the specification of adaptation strategies remains a difficult task for creators of such systems. In this paper, we consider the problem of the definition of adaptation strategies at a high level. We present two main contributions: a typology of elementary adaptation patterns for the adaptation of navigation; and a process to generate adaptation strategies based on the use and the semi-automatic combination of patterns. We also describe how the generated adaptation strategies can be integrated into existing AHSs. A prototype has been implemented and an experiment in the e-learning domain has been conducted with a group of volunteers. This experiment shows that our pattern based approach for defining adaptation strategies is more suitable than those based on ”traditional ” AH languages. Index Terms—AHSs, Adaptation strategies, Patterns. 1