Making it Rich and Personal: crafting an institutional personal learning environment

Many of the communities interested in learning and teaching technologies within higher education now accept the view that a conception of personal learning environments provides a the most realistic and workable perspective of learners’ interactions with and use of technology. This view may not be reflected in the behaviour of those parts of a university which normally purchase and deploy technology infrastructure. These departments or services are slow to change because they are typically, and understandably, risk-averse; the more so, because the consequences of expensive decisions about infrastructure will stay with the organisation for many years. Furthermore across the broader (less technically or educationally informed) academic community, the awareness of and familiarity with technologies in support of learning may be varied. In this context, work to innovate the learning environment will require considerable team effort and collective commitment. This paper presents a case study account of institutional processes harnessed to establish a universal personal learning environment fit for the 21st century. The challenges encountered were consequential of our working definition of a learning environment, which went beyond simple implementation. In our experience the requirements became summarised as “its more than a system, it’s a mindset”. As well as deploying technology ‘fit for purpose’ we were seeking to create an environment that could play an integral and catalytic part in the university’s role of enabling transformative education. Our ambitions and aspirations were derived from evidence in the literature. We also drew on evidence of recent and current performance in the university; gauged by institutional benchmarking and an extensive student survey. The paper presents and analyses this qualitative and quantitative data. We provide an account and analysis of our progress to achieve change, the methods we used, problems encountered and the decisions we made on the way

A Semantic Grid Oriented to E-Tourism

With increasing complexity of tourism business models and tasks, there is a clear need of the next generation e-Tourism infrastructure to support flexible automation, integration, computation, storage, and collaboration. Currently several enabling technologies such as semantic Web, Web service, agent and grid computing have been applied in the different e-Tourism applications, however there is no a unified framework to be able to integrate all of them. So this paper presents a promising e-Tourism framework based on emerging semantic grid, in which a number of key design issues are discussed including architecture, ontologies structure, semantic reconciliation, service and resource discovery, role based authorization and intelligent agent. The paper finally provides the implementation of the framework.Comment: 12 PAGES, 7 Figure

Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation

Content-driven design and architecture of E-learning applications

E-learning applications combine content with learning technology systems to support the creation of content and its delivery to the learner. In the future, we can expect the distinction between learning content and its supporting infrastructure to become blurred. Content objects will interact with infrastructure services as independent objects. Our solution to the development of e-learning applications – content-driven design and architecture – is based on content-centric ontological modelling and development of architectures. Knowledge and modelling will play an important role in the development of content and architectures. Our approach integrates content with interaction (in technical and educational terms) and services (the principle organization for a system architecture), based on techniques from different fields, including software engineering, learning design, and knowledge engineering