Towards developing a collaborative video platform for learning

The work presented in this paper outlines issues relating to the development of a collaborative video platform for learning. Student adoption of collaborative and video technology is increasing dramatically, becoming part of their everyday lives. The aim of this paper is to propose a system and framework for the successful integration of these technologies into teaching and learning. At the outset we assess current trends and previous research, using these findings to inform the development of a new platform. System specifications are then presented with specific needs identified for students and educators. Finally our tentative framework for a integrating a collaborative video platform for learning is presented

Goal-based structuring in a recommender systems

Recommender systems help people to find information that is interesting to them. However, current recommendation techniques only address the user's short-term and long-term interests, not their immediate interests. This paper describes a method to structure information (with or without using recommendations) taking into account the users' immediate interests: a goal-based structuring method. Goal-based structuring is based on the fact that people experience certain gratifications from using information, which should match with their goals. An experiment using an electronic TV guide shows that structuring information using a goal-based structure makes it easier for users to find interesting information, especially if the goals are used explicitly; this is independent of whether recommendations are used or not. It also shows that goal-based structuring has more influence on how easy it is for users to find interesting information than recommendations

Improving the quality of the personalized electronic program guide

As Digital TV subscribers are offered more and more channels, it is becoming increasingly difficult for them to locate the right programme information at the right time. The personalized Electronic Programme Guide (pEPG) is one solution to this problem; it leverages artificial intelligence and user profiling techniques to learn about the viewing preferences of individual users in order to compile personalized viewing guides that fit their individual preferences. Very often the limited availability of profiling information is a key limiting factor in such personalized recommender systems. For example, it is well known that collaborative filtering approaches suffer significantly from the sparsity problem, which exists because the expected item-overlap between profiles is usually very low. In this article we address the sparsity problem in the Digital TV domain. We propose the use of data mining techniques as a way of supplementing meagre ratings-based profile knowledge with additional item-similarity knowledge that can be automatically discovered by mining user profiles. We argue that this new similarity knowledge can significantly enhance the performance of a recommender system in even the sparsest of profile spaces. Moreover, we provide an extensive evaluation of our approach using two large-scale, state-of-the-art online systems—PTVPlus, a personalized TV listings portal and Físchlár, an online digital video library system

NoTube – making TV a medium for personalized interaction

In this paper, we introduce NoTube’s vision on deploying semantics in interactive TV context in order to contextualize distributed applications and lift them to a new level of service that provides context-dependent and personalized selection of TV content. Additionally, lifting content consumption from a single-user activity to a community-based experience in a connected multi-device environment is central to the project. Main research questions relate to (1) data integration and enrichment - how to achieve unified and simple access to dynamic, growing and distributed multimedia content of diverse formats? (2) user and context modeling - what is an appropriate framework for context modeling, incorporating task-, domain and device-specific viewpoints? (3) context-aware discovery of resources - how could rather fuzzy matchmaking between potentially infinite contexts and available media resources be achieved? (4) collaborative architecture for TV content personalization - how can the combined information about data, context and user be put at disposal of both content providers and end-users in the view of creating extremely personalized services under controlled privacy and security policies? Thus, with the grand challenge in mind - to put the TV viewer back in the driver's seat – we focus on TV content as a medium for personalized interaction between people based on a service architecture that caters for a variety of content metadata, delivery channels and rendering devices

Emerging technologies for learning (volume 1)

Collection of 5 articles on emerging technologies and trend

An architecture for life-long user modelling

In this paper, we propose a united architecture for the creation of life-long user profiles. Our architecture combines different steps required for a user prole, including feature extraction and representation, reasoning, recommendation and presentation. We discuss various issues that arise in the context of life-long profiling

Personalised Universalism in the Age of Algorithms

In this chapter, I address a complex relationship in linking the principles of universalism and personalisation as a tension of considerable importance in contemporary media use. The paradoxical aspects of this relationship are especially evident when treated in the light of ideal types and praxis in legacy public service broadcasting (PSB) and digital public service media (PSM). The relationship is viewed from five angles, culminating in discussion about the materiality produced by shifting technologies in the digital environment and its bearing on the ideological concept of public service in media. The author introduces a new orientation for PSM: personalised enlightenment.Go to the full book to find a version of this chapter tagged for accessibility

Harnessing Technology: analysis of emerging trends affecting the use of technology in education (September 2008)

Research to support the delivery and development of Harnessing Technology: Next Generation Learning 2008–1