10 easy steps to ease on-line communication

There are many different ways to communicate on-line now days from chat rooms, forums to e-mail, instant messaging, blogs and personal spaces. Some have clearly stated rules and some depend on unwritten codes of behaviour. Here are a few general tips provided that will hopefully make those occasions where learning and teaching are taking place more worthwhile.

Research and Communication Skills

A Collection of Material for Research and Communication Skills

A History of Communication

Speech, Writing, Print, Telephony, Web. How technology is catching up with the brain.

Tools for Communication, Collaboration �and for Mobile Learning

Introduction as part of UG TEL course

A Communication Design Handbook Vol 1 21012-13 iBooks/iPad version... PDF export

One of the things about Apple's walled garden iBooks system is the only way to share what you've created in iBooks Author is via the iPad or a PDF preview... So, for those of you who haven't got an iPad... but don't try clicking on the videos or the slideshows.

MA Communication Design Induction

Overview of the course including the structure, content and definition of post-graduate study

Research & Communication Skills (RCS) Weekly sessions (2013/14)

Slides and materials from each weeks session in one handy location

Predicting sense of community and participation by applying machine learning to open government data

Community capacity is used to monitor socio-economic development. It is composed of a number of dimensions, which can be measured to understand the possible issues in the implementation of a policy or the outcome of a project targeting a community. Measuring community capacity dimensions is usually expensive and time consuming, requiring locally organised surveys. Therefore, we investigate a technique to estimate them by applying the Random Forests algorithm on secondary open government data. This research focuses on the prediction of measures for two dimensions: sense of community and participation. The most important variables for this prediction were determined. The variables included in the datasets used to train the predictive models complied with two criteria: nationwide availability; sufficiently fine-grained geographic breakdown, i.e. neighbourhood level. The models explained 77% of the sense of community measures and 63% of participation. Due to the low geographic detail of the outcome measures available, further research is required to apply the predictive models to a neighbourhood level. The variables that were found to be more determinant for prediction were only partially in agreement with the factors that, according to the social science literature consulted, are the most influential for sense of community and participation. This finding should be further investigated from a social science perspective, in order to be understood in depth.