Model-driven description and validation of composite learning content

Authoring of learning content for courseware systems is a complex activity requiring the combination of a range of design and validation techniques. We introduce the CAVIAr courseware models allowing for learning content description and validation. Model-based representation and analysis of different concerns such as the subject domain, learning context, resources and instructional design used are key contributors to this integrated solution. Personalised learning is particularly difficult to design as dynamic configurations cannot easily be predicted and tested. A tool-supported technique based on CAVIAr can alleviate this complexity through the validation of a set of pedagogical and non-pedagogical requirements. Courseware validation checks intra- and inter-content relationships and the compliance with requirements and educational theories

Adaptive hypermedia for education and training

Adaptive hypermedia (AH) is an alternative to the traditional, one-size-fits-all approach in the development of hypermedia systems. AH systems build a model of the goals, preferences, and knowledge of each individual user; this model is used throughout the interaction with the user to adapt to the needs of that particular user (Brusilovsky, 1996b). For example, a student in an adaptive educational hypermedia system will be given a presentation that is adapted specifically to his or her knowledge of the subject (De Bra & Calvi, 1998; Hothi, Hall, & Sly, 2000) as well as a suggested set of the most relevant links to proceed further (Brusilovsky, Eklund, & Schwarz, 1998; Kavcic, 2004). An adaptive electronic encyclopedia will personalize the content of an article to augment the user's existing knowledge and interests (Bontcheva & Wilks, 2005; Milosavljevic, 1997). A museum guide will adapt the presentation about every visited object to the user's individual path through the museum (Oberlander et al., 1998; Stock et al., 2007). Adaptive hypermedia belongs to the class of user-adaptive systems (Schneider-Hufschmidt, Kühme, & Malinowski, 1993). A distinctive feature of an adaptive system is an explicit user model that represents user knowledge, goals, and interests, as well as other features that enable the system to adapt to different users with their own specific set of goals. An adaptive system collects data for the user model from various sources that can include implicitly observing user interaction and explicitly requesting direct input from the user. The user model is applied to provide an adaptation effect, that is, tailor interaction to different users in the same context. In different kinds of adaptive systems, adaptation effects could vary greatly. In AH systems, it is limited to three major adaptation technologies: adaptive content selection, adaptive navigation support, and adaptive presentation. The first of these three technologies comes from the fields of adaptive information retrieval (IR) and intelligent tutoring systems (ITS). When the user searches for information, the system adaptively selects and prioritizes the most relevant items (Brajnik, Guida, & Tasso, 1987; Brusilovsky, 1992b)

Utilising ontology-based modelling for learning content management

Learning content management needs to support a variety of open, multi-format Web-based software applications. We propose multidimensional, model-based semantic annotation as a way to support the management of access to and change of learning content. We introduce an information architecture model as the central contribution that supports multi-layered learning content structures. We discuss interactive query access, but also change management for multi-layered learning content management. An ontology-enhanced traceability approach is the solution

From classroom tutor to hypertext adviser: An evaluation

This paper describes a three‐year experiment to investigate the possibility of making economies by replacing practical laboratory sessions with courseware while attempting to ensure that the quality of the student learning experience did not suffer. Pathology labs are a central component of the first‐year medical undergraduate curriculum at Southampton. Activities in these labs had been carefully designed and they were supervised by lab demonstrators who were subject domain experts. The labs were successful in the eyes of both staff and students but were expensive to conduct, in terms of equipment and staffing. Year by year evaluation of the introduction of courseware revealed that there was no measurable difference in student performance as a result of introducing the courseware, but that students were unhappy about the loss of interaction with the demonstrators. The final outcome of this experiment was a courseware replacement for six labs which included a software online hypertext adviser. The contribution of this work is that it adds to the body of empirical evidence in support of the importance of maintaining dialogue with students when introducing courseware, and it presents an example of how this interaction might be achieved in software

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

Using XML-based Metadata for Generating Dynamic Courseware

The objective of this paper is to explore the mechanism between the learner and learning material in generating dynamic courseware in e-learning environment, The dynamic e-learning develop flexible and dynamic course content according to the suitability level of learner, This dynamic e-learning will be using XML-based metadata in particular. XML based metadata allows any part of a course to be modularized, saves and reused as a learning object. Each learning object is described in the object repository. Learning objects are stored in central object repository and are easily locatable on an object-by-object basis. To achieve learner adaptability, learners are allowed to specify queries that will dynamically construct courses

The Conference Review Process

This presentation is for students on the 3rd year ECS Multimedia course where students run their own conference, and submit and review papers. In this presentation we explain the academic review process, look at the structure of a review, and give some examples of positive and negative reviews

Interactive online learning support: Progress on research to date

This paper reports on progress to date in relation to along term research project underway at Curtin University ofTechnology. The project aims to devise tools that interactivelysupport the cognitive learning processes of today?s knowledgeworkers as exemplified by researchers, managers and students.The empowering tools alluded to here are not simply intended tomanage, calculate, search, order and arrange search results as isoften the case with current search systems. Instead, the project isconcerned with applying semantic analysis techniques,specifically the Normalised Word Vector (NWV) technologydeveloped at Curtin to the construction of a range of ?intelligent?online cognitive support tools. The goal is to devise a system thatenhances learners? cognitive functioning by augmenting thehuman intellect to achieve greater capacity to conceptualise andultimately, construct new knowledge