Learning Cities 2015: Using urban ‘Big Data’ to evaluate modern learning cities

28th - 30th September 2015
All day
Mexico City, Mexico

UBDC researcher Dr Catherine Lido will be presenting at Learning Cities 2015 on 'Using urban ‘Big Data’ to evaluate modern learning cities', which is research being undertaken by Dr Lido and by UBDC Co-I, Professor Mike Osborne.

Dr Lido will be representing the UBDC and the University of Glasgow School of Education as part of the PASCAL Delegation, speaking at the North America and Europe Parallel Regional Forum, as well as acting as a 'Rapportueur' at the Mayors' Forum.



Using urban 'Big Data' to evaluate modern learning cities

The new Urban Big Data Centre (UBDC) at the University of Glasgow was funded by the Economic and Social Research Council as part of the recent UK drive to ‘harness the power’ of ‘Big Data’, including administrative data, social media and novel techniques of data collection, analysis and visualisation. The UBDC is currently in the process of gathering datasets relevant to the field of education and linking these to datasets with a number of learning city and urban indicators, such as those on housing, transport, sustainability and school/ area-level metrics. These multiple intersecting data sets will enable us to assess Glasgow against operationalised ‘Key Features of Learning Cities’ (UNESCO, 2013), and to better understand the relationship between place and educational disadvantage within this city (and beyond) in order to identify the drivers of disadvantage, as well as lifelong success, and to inform policy options for narrowing the gap in educational access, attainment and lifelong participation.  The UBDC is presently running the integrated Multimedia City Data (iMCD) project to create its first ‘data product’ for open access to academics, policy practitioners and the general public, combining a representative household survey of 1500 housholds with tracking of real-time GPS data and lifelogging camera images, set within the context of a year long social media data capture.  In this way, it seeks to present a three-dimensional view of citizen-learners’ daily activity and mobility alongside engagement in various forms of learning (including in the workplace, community and family context). The approaches and methods that have been developed can be applied to other cities interested in systematically analysing their progress as learning entities.