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.

EdShare: collaboration in a University for learning and teaching

Poster for the School of Electronics and Computer Science, Learning Societies Lab Open Day, 27 February 2008 at the University of Southampton. Profile and presentation of the EdShare resource. The poster illustrates the philosophy of EdShare, how it relates to the Web 2.0 environment and its relationship to the education agenda in a University.

EdShare: collaboration in a University for learning and teaching

Poster for the Learning Societies Laboratory, School of Electronics and Computer Science, University of Southampton Open Day, Wednesday 27 February 2008.

EdShare: collaboration in a University for learning and teaching

Poster for the Learning Societies Laboratory, School of Electronics and Computer Science, University of Southampton Open Day, Wednesday 27 February 2008.

The value of using short-format podcasts to enhance learning and teaching

This paper presents the findings of a podcasting trial held in 2007-2008 within the Faculty of Economics and Business at the University of Sydney, Australia. The trial investigates the value of using short-format podcasts to support assessment for postgraduate and undergraduate students. A multi-method approach is taken in investigating perceptions of the benefits of podcasting, incorporating surveys, focus groups and interviews. The results show that a majority of students believe they gained learning benefits from the podcasts and appreciated the flexibility of the medium to support their learning, and the lecturers felt the innovation helped diversify their pedagogical approach and support a diverse student population. Three primary conclusions are presented: (1) most students reject the mobile potential of podcasting in favour of their traditional study space at home; (2) what students and lecturers value about this podcasting design overlap; (3) the assessment-focussed, short-format podcast design may be considered a successful podcasting model. The paper finishes by identifying areas for future research on the effective use of podcasting in learning and teaching.

Learning Resource Coursework - Team Sigma

We have created a slideshow on Open Source, and have created a reference list and poster for it.

An open mind

An article from the New York Times, 16 April 2010, by Katie Hafner. This article summarises recent significant projects for creating open educational resources in the United States and UK.