GEEDE: Grid Enabled Educational Data Environment
The 'GEEDE' service (Grid Enabled Educational Data Environment) is one of three related provisions developed in the DAMES Node under the umbrella term 'GESDE' (Grid Enabled Specialist Data Environments; introduction to GESDE).
GEEDE is concerned with buidling up a library of data resources linked to measures of educational qualifications in social survey research. Typical resources available from GEEDE are coding frames for categories of relative educational attainment, and summary statistics covering data such as on the changing prevalence of different educational qualifications across birth cohorts
The GEEDE 'portal' has been available to registered users and guests since August 2010. To go direct to the portal follow this link. The rest of this page is used to describe the GEEDE project and the portal's contribution, and give help and instructions on using the portal itself.
Portal's down: If you tried to access the GEEDE portal but there was an error, you can also pick up many of the same resources from our back-up service 'GESDE-lite'.
BACKGROUND
Like its sister services GEODE and GEMDE (see a full description in the NTTS conference paper by Lambert et al. 2011), the Grid Enabled Educational Data Environment seeks to provide a service that social scientists can use to access specialist data about educational qualifications, as well as to disseminate their own data resources alongside adequate metadata to describe them.
Data on educational qualifications can be particularly difficult to deal with in survey research because taxonomies of educational qualifications ('educational unit groups') tend to be complex and to change rapidly over time or between societies. For instance, the figure above illustrates the difficulty of using measures of education for longitudinal comparisons in the UK, since the numbers in different qualification categories change substantially over time due to institutional transformations. Accordingly, measures of educational qualifications are frequently correlated with the age (i.e. school leaving cohort) of respondent, as well as with other socio-demographic factors such as gender and region. Such correlations mean that there is considerable pay-off to thinking hard about the way in which measures of educational qualifications are operationalised in statistical analysis.
There are many good solutions to problems of measuring education, including scaling educational categories by suitable metrics (e.g. Buis 2010) or allocating categories to a well-documented standard (e.g. Schnieder 2010). The the GEEDE service we try to facilitate good practice in working with educational qualifications such as by:
- Documenting different taxonomies of educational qualifications (what we call 'Educational Unit Groups')
- Facilitating access to statistical data about classifications (what we call 'Educational Information Resouces')
- Facilitating preparation and analysis of data on educational qualifications (by drawing upon data on EUGs and EIRs as is available for download from the GEEDE portal).
HOW TO USE GEEDE
- Talk: Introduction to GEEDE (pdf), by Paul Lambert
- Talk: Dealing with data on educational qualifications: Principles and practice (pdf), by Vernon Gayle
- Talk: Some old and new measures using educational qualifications (pdf), by Paul Lambert
- Handout: An example illustrating curating data with the GEEDE system (doc), by Paul Lambert
- Background file: A small data file used as pat of the illustrative example, featuring educational codes (xls), by Ken Prandy, Marge Unt and Paul Lambert
- Background file: A research paper used as part of the illustrative example (pdf), by Ken Prandy, Marge Unt and Paul Lambert
CONTACT
We're still developing GEEDE. Please contact us with feedback/comments on the service and its usability. Feel free to tell us...
- Did you understand what we're trying to do here..?
- What needs to be clearer?
- Did the portal work when you used it?
- What problems did you find? How could we fix them?
- Have we forgotten something?
GEEDE is work undertaken by the Data Management through e-Social Science Node, supported by the ESRC. The main work in developing the GEEDE service has been undertaken by Guy Warner and Paul Lambert (see DAMES Node personnel). Many others from the Node have also contributed to the resource, especially Larry Tan, Jesse Blum, and Vernon Gayle.
- To send us feedback on GEEDE, we suggest emailing or contacting Paul Lambert in the first instance:
Workshops/Outreach events/Publications
We have presented materails from GEEDE in several workshops and presentations, whilst the service is also desribed in some of our papers from the DAMES Node. For latest outputs see:
References
Buis, M. L. (2010). Inequality of Educational Outcome and Inequality of Educational Opportunity in the Netherlands during the 20th Century. Amsterdam: VU University Amsterdam.
Lambert, P.S., Gayle, V., Tan, K.L.L., Blum, J.M., Bowes, A., Jones, S., Turner, K.J., Warner, G., Sinnott, R.O. and Bihagen, E. (2008). Grid Enabled Specialist Data Environments: Forward Planning for the GE*DE Services for Specialist Data on Occupations, Educational Qualifications, and Ethnicity, University of Stirling: Technical Paper 2008-1 of the Data Management through e-Social Science Research Node (www.dames.org.uk).
Lambert, P.S., Warner, G., Doherty, T., McCafferty, S., Watt, J., Comerford, M., Gayle, V., Tan, K.L.L., Blum, J., Bowes, A.B. Collaborative systems for enhancing the analysis of social surveys: the Grid Enabled Specialist Data Environments, European Statistics - New Technologies and Techniques in Statistics Biennial conference, Brussels, 22-24 February 2011 (conference; full text pdf)
Schneider, S. L. (2010). Nominal comparability is not enough: (In-)Equivalence of construct validity of cross-national measures of educational attainment in the European Social Survey. Research in Social Stratification and Mobility, 28(3), 343-357.
Last updated 28/JAN/2011, by Paul Lambert