Teacher Training Videos

Free online training resources on using web 2.0 tools for busy lecturers. - 'Outstanding ICT initiative of the year' winner of the JISC award is commended for 'commitment to open access to online content' A wealth of openly available multimedia content won the JISC/Times Higher Award. Created by University of Westminster lecturer Russell Stannard's websites build upon pioneering work using video to mark students' work. Using screen recording software, Stannard recorded himself walking through various Web 2.0 technologies with a voice-over, which were then uploaded to a website - www.teachertrainingvideos.com. The site quickly proved popular and rapidly built into a bank of over 30 videos.

David Gauntlett's inaugural lecture, 'Participation culture, creativity, and social change', from 12 November 2008: the key themes in ten minutes

David Gauntlett's inaugural lecture from November 2008, in which he points to a shift from a 'sit down and be told' culture to a more creative 'making and doing' culture, which may offer one of the necessary keys to tackling climate change and environmental problems.

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.