3,289 research outputs found

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

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    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

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

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    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

    Transforming a linear module into an adaptive one : tackling the challenge

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    Every learner is fundamentally different. However, few courses are delivered in a way that is tailored to the specific needs of each student. Delivery systems for adaptive educational hypermedia have been extensively researched and found promising. Still, authoring of adaptive courses remains a challenge. In prior research, we have built an adaptive hypermedia authoring system, MOT3.0. The main focus was on enhancing the type of functionality that allows the non-technical author, to efficiently and effectively use such a tool. Here we show how teachers can start from existing course material and transform it into an adaptive course, catering for various learners. We also show how this apparent simplicity still allows for building of flexible and complex adaptation, and describe an evaluation with course authors

    Automatic authoring in the LAOS AHS authoring model

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    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

    Design of the CAM model and authoring tool

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    Students benefit from personalised attention; however, often teachers are unable to provide this. An Adaptive Hypermedia (AH) system can offer a richer learning experience in an educational environment, by giving personalised attention to students. On-line courses are becoming increasingly popular by means of Learning Management Systems (LSM). The aim of the GRAPPLE project is to integrate an AH with major LMS, to provide an environment that delivers personalised courses in a LMS interface. However, designing an AH is a much more complex and time-consuming task, than creating a course in a LMS. Several models and systems were developed previously, but the (re)-usability by educational authors of the adaptation remains limited. To simplify adaptive behaviour authoring for an educational author, a visual environment was selected as being most intuitive. This paper describes a reference model for authoring in a visual way and introduces an authoring tool based upon this model

    WiBAF into a CMS: Personalization in learning environments made easy

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    Adaptivity has proven successful in reducing navigation and comprehension problems in hypermedia documents. Authoring of adaptive hypermedia documents and especially of the adaptivity in these documents has been problematic or at least labour intensive throughout AH history. This paper shows how the integration of a CMS with an adaptive framework greatly simplifies the inclusion of personalization in existing educational applications. It does this within the context of European project Autism&Uni that uses adaptive hypermedia to offer information for students transitioning from high school to university, especially to cater for students on the autism spectrum as well as for non-autistic students. The use of our Within Browser adaptation framework (WiBAF) reduces privacy concerns because the user model is stored on the end-user's machine, and eliminates performance issues that currently prevent the adoption of adaptivity in MOOC platforms by having the adaptation performed on the end-user's machine as well (within the browser). Authoring of adaptive applications within the educational domain with the system proposed was tried out with first year students from the Design-Based Learning Hypermedia course at the Eindhoven University of Technology (TU/e) to gather feedback on the problems they faced with the platform

    AHyCo: a Web-Based Adaptive Hypermedia Courseware System

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    Adaptive hypermedia courseware systems resolve the problem of users’ disorientation in hyperspace through the adaptive navigation and presentation support. We describe the AHyCo (Adaptive Hypermedia Courseware) - an adaptive Web-based educational system for creation and reuse of adaptive courseware with emphasis on adaptive navigation support and lessons sequencing. The proposed model consists of the domain model, the student model, and the adaptive model. The system is composed of two environments: the authoring environment and the learning environment

    Collaborative Authoring of Adaptive Educational Hypermedia by Enriching a Semantic Wiki’s Output

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    This research is concerned with harnessing collaborative approaches for the authoring of Adaptive Educational Hypermedia (AEH) systems. It involves the enhancement of Semantic Wikis with pedagogy aware features to this end. There are many challenges in understanding how communities of interest can efficiently collaborate for learning content authoring, in introducing pedagogy to the developed knowledge models and in specifying user models for efficient delivery of AEH systems. The contribution of this work will be the development of a model of collaborative authoring which includes domain specification, content elicitation, and definition of pedagogic approach. The proposed model will be implemented in a prototype AEH authoring system that will be tested and evaluated in a formal education context

    A spiral model for adding automatic, adaptive authoring to adaptive hypermedia

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    At present a large amount of research exists into the design and implementation of adaptive systems. However, not many target the complex task of authoring in such systems, or their evaluation. In order to tackle these problems, we have looked into the causes of the complexity. Manual annotation has proven to be a bottleneck for authoring of adaptive hypermedia. One such solution is the reuse of automatically generated metadata. In our previous work we have proposed the integration of the generic Adaptive Hypermedia authoring environment, MOT ( My Online Teacher), and a semantic desktop environment, indexed by Beagle++. A prototype, Sesame2MOT Enricher v1, was built based upon this integration approach and evaluated. After the initial evaluations, a web-based prototype was built (web-based Sesame2MOT Enricher v2 application) and integrated in MOT v2, conforming with the findings of the first set of evaluations. This new prototype underwent another evaluation. This paper thus does a synthesis of the approach in general, the initial prototype, with its first evaluations, the improved prototype and the first results from the most recent evaluation round, following the next implementation cycle of the spiral model [Boehm, 88]

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

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    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
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