News not noise: socially aware information filtering

An understanding of how people in social networks consume news media by and about their friends shows that information overload is soon going to be a major problem for many participants. Users dislike manually prioritizing their friendships to help organize this data, and this leads us to develop a new interface to help users to find the news that most interests them by providing a visual representation of social proximity, in which friends most visited and those most likely to be met offline we prioritized

Interaction Issues in Computer Aided Semantic\ud Annotation of Multimedia

The CASAM project aims to provide a tool for more efficient and effective annotation of multimedia documents through collaboration between a user and a system performing an automated analysis of the media content. A critical part of the project is to develop a user interface which best supports both the user and the system through optimal human-computer interaction. In this paper we discuss the work undertaken, the proposed user interface and underlying interaction issues which drove its development

SenseBelt:a belt-worn sensor to support cross-device interaction

Mobile interaction is shifting from a single device to simultaneous interaction with ensembles of devices such as phones, tablets, or watches. Spatially-aware cross-device interaction between mobile devices typically requires a fixed tracking infrastructure, which lim- its mobility. In this paper, we present SenseBelt – a sensing belt that enhances existing mobile interactions and enables low-cost, ad hoc sensing of cross-device gestures and interactions. SenseBelt enables proxemic interactions between people and their personal devices. SenseBelt also supports cross-device interaction be- tween personal devices and stationary devices, such as public displays. We discuss the design and implementation of SenseBelt together with possible applications. With an initial evaluation, we provide insights into the benefits and drawbacks of a belt-worn mediating sensor to support cross-device interactions

Moving through MOOCS: pedagogy, learning design and patterns of engagement

Massive open online courses (MOOCs) are part of the lifelong learning experience of people worldwide. Many of these learners participate fully. However, the high levels of dropout on most of these courses are a cause for concern. Previous studies have suggested that there are patterns of engagement within MOOCs that vary according to the pedagogy employed. The current paper builds on this work and examines MOOCs from different providers that have been offered on the FutureLearn platform. A cluster analysis of these MOOCs shows that engagement patterns are related to pedagogy and course duration. Learners did not work through a three-week MOOC in the same ways that learners work through the first three weeks of an eight-week MOOC

Digital Behaviour Change Interventions to Break and Form Habits

Digital behaviour change interventions, particularly those using pervasive computing technology, hold great promise in supporting users to change their behaviour. However, most interventions fail to take habitual behaviour into account, limiting their potential impact. This failure is partly driven by a plethora of overlapping behaviour change theories and related strategies that do not consider the role of habits. We critically review the main theories and models used in the research to analyse their application to designing effective habitual behaviour change interventions. We highlight the potential for Dual Process Theory, modern habit theory, and Goal Setting Theory, which together model how users form and break habits, to drive effective digital interventions. We synthesise these theories into an explanatory framework, the Habit Alteration Model, and use it to outline the state of the art. We identify the opportunities and challenges of habit-focused interventions.</jats:p