Symmetric Synchronous Collaborative Navigation

Synchronous collaborative navigation is a form of social navigation where users virtually share a web browser. In this paper, we present a symmetric, proxy-based architecture where each user can take the lead and guide others in visiting web sites, without the need for a special browser or other software. We show how we have applied this scheme to a problem-solving-oriented e-learning system

Division of labour and sharing of knowledge for synchronous collaborative information retrieval

Synchronous collaborative information retrieval (SCIR) is concerned with supporting two or more users who search together at the same time in order to satisfy a shared information need. SCIR systems represent a paradigmatic shift in the way we view information retrieval, moving from an individual to a group process and as such the development of novel IR techniques is needed to support this. In this article we present what we believe are two key concepts for the development of effective SCIR namely division of labour (DoL) and sharing of knowledge (SoK). Together these concepts enable coordinated SCIR such that redundancy across group members is reduced whilst enabling each group member to benefit from the discoveries of their collaborators. In this article we outline techniques from state-of-the-art SCIR systems which support these two concepts, primarily through the provision of awareness widgets. We then outline some of our own work into system-mediated techniques for division of labour and sharing of knowledge in SCIR. Finally we conclude with a discussion on some possible future trends for these two coordination techniques

Shared visiting in Equator city

In this paper we describe an infrastructure and prototype system for sharing of visiting experiences across multiple media. The prototype supports synchronous co-visiting by physical and digital visitors, with digital access via either the World Wide Web or 3-dimensional graphics

Adaptive Information Visualization for Personalized Access to Educational Digital Libraries

Personalization is one of the emerging ways to increase the power of modern Digital Libraries. The Knowledge Sea II system presented in this paper explores social navigation support, an approach for providing personalized guidance within the open corpus of educational resources. Following the concepts of social navigation we have attempted to organize a personalized navigation support that is based on past learners’ interaction with the system. The study indicates that Knowledge Sea II became the students' primary tool for accessing the open corpus documents used in a programming course. The social navigation support implemented in this system was considered useful by students participating in the study of Knowledge Sea II. At the same time, some user comments indicated the need to provide more powerful navigational support, such as the ability to rank the usefulness of a page

Linked education: interlinking educational resources and the web of data

Research on interoperability of technology-enhanced learning (TEL) repositories throughout the last decade has led to a fragmented landscape of competing approaches, such as metadata schemas and interface mechanisms. However, so far Web-scale integration of resources is not facilitated, mainly due to the lack of take-up of shared principles, datasets and schemas. On the other hand, the Linked Data approach has emerged as the de-facto standard for sharing data on the Web and offers a large potential to solve interoperability issues in the field of TEL. In this paper, we describe a general approach to exploit the wealth of already existing TEL data on the Web by allowing its exposure as Linked Data and by taking into account automated enrichment and interlinking techniques to provide rich and well-interlinked data for the educational domain. This approach has been implemented in the context of the mEducator project where data from a number of open TEL data repositories has been integrated, exposed and enriched by following Linked Data principles