Triangulating Novel Mixed-Method Educational Data to Develop Effective, Evidence-Based Policy
- Tuesday 28 September 2021
- 12:30 - 14:00 (BST)
- Online (via Zoom) GET DIRECTIONS
UBDC’s programme involves not only large quantities of data but also the linkage and integration of diverse and often novel types of data.
The UBDC’s Educational Disadvantage & Place (ED&P) group has employed a spectrum of complementary quantitative and qualitative methods, often blurring the lines between, to address educational inequalities, with a view to informing the development of more effective policy solutions to the educational attainment gaps at all stages of life-long/life-wide education in Scotland and elsewhere.
In this session, we will use examples from the work of the UBDC’s Education work package to illustrate the impact of a range of the mixed-methods approaches, namely using:
- Novel data linkages
- Multivariate regression
- GIS mapping
- Searchable Twitter dashboards
- Lived experience interviews
Such approaches will be demonstrated by using three projects which have already generated impact in academic, media and government policy domains:
- Integrated Multimedia City Data (iMCD) as applied to adult learning and greenspace in Learning Cities
- Open data to demonstrate educational inequalities during the Scottish Qualifications Authority (SQA) exam moderation as linked to measures of deprivation
- Exploration of food insecurity of older adults in Scotland and effectiveness of food support services to tackled these inequalities
We hope these wide-ranging and diverse examples show a common thread of drawing together diverse data strands to argue for holistic and integrated solutions to Learning City issues and urban inequalities.
- Introductory overview talk on mixed-methods & triangulation
- A brief introduction to impactful policy work
- Three brief demonstrations from each of the projects above (iMCD for adult learning in greenspace, schools based open data linked to schools & food insecurity in older adults)
- Guided exercise for iMCD survey supplemented with Twitter dashboard search, and discussion of GPS maps
- Interactive discussion & conclusions
What you will learn
By the end of the webinar, attendees will be able to:
- Describe how the systematic and rigorous use of quantitative and qualitative approaches can each produce policy-relevant evidence singularly and in combination
- Outline approaches to triangulation, and the additional contribution that triangulated analyses can make to our knowledge base
- Explain the possibilities and constraints when using mixed-method-derived novel data strands to inform and develop future education policy
Who should attend
The session is aimed at educational researchers, educational stakeholders from local authorities and national level policy-makers, practitioners and stakeholders interested in impactful data for educational change.
Prior knowledge requirements
People with any level of knowledge and from any discipline are welcome. While little prior knowledge is assumed, a grounding in Scottish education policy and practice and the context of Learning Cities / Smart Cities are essential.
Experience in quantitative methods, including data management and analysis in R, and qualitative methods would be useful but are not essential for this webinar.
Data and software requirements
No data required for first-hand analysis, but datasets demonstrated include:
- iMCD project datasets (household survey, Twitter dashboard & GPS trails, etc.) and their application to linked data, such as greenspace metrics
- School-level educational attainment dataset, augmented by neighbourhood-based measures, for instance accessing open data available from scot.gov and linking to national datasets, such as Scottish Index of Multiple Deprivation (SIMD)
- Evidencing food insecurity in older adults with surveys, interviews, organisational feedback & national level metrics, the case of Eat Well Age Well & Food Train social enterprise
Please view this online tutorial for accessing and working with the iMCD datasets and code/syntax.
You can also apply to access the data.
- R studio
Registration for this online event is free and available via Eventbrite. Full details and instructions for joining will be circulated post-registration.