3-7 July 2017
This summer school strand approaches mixed methods from the viewpoint that methods can be integrated not separated at the analysis stage. It focuses on the use of case-studies and the case-study comparative method in mixed-methods research contexts. The content focuses on four topics –
- mixed methods data management;
- qualitative comparative analysis (QCA) and the comparative method;
- fuzzy set analysis of pathways of causality; and
- methods of using qualitative data to strengthen an argument and make the analysis rigorous and transparent.
The school offers unique new training, developed specifically for this outlet, in several of these areas. This one-week event involves 28 hours of contact time of which about 5-6 hours are computer practicals led by the experienced tutors, Wendy Olsen and Steph Thomson, based on previous experiences with similar kinds of materials. The computer practicals for QCA include applications of NVIVO, fsQCA, SPSS, and Excel software. We have a partial overlap with the Factor Analysis Mixed Methods Stream. The Factor Analysis students are using SPSS AMOS, STATA, and MPLUS software as well as learning about multiple methods for gaining original knowledge. There is 7/16 overlap of the two streams (7 sessions out of 16).
The organisation of the course involves lectures, active learning and a project. Each day up to two lectures and one ‘lectorial’ occur. A lectorial is active learning led from the front with guided small group work. The project is individually done and will lead to the creation of a poster display with hot links. Participants may want to bring their own laptops (but it’s optional).
The aims of the course are:
- To examine seminal papers using mixed methods and discuss rigour in comparative research. To learn more about Qualitative Comparative Analysis (QCA).
- To experience in practical settings how to use NVIVO for systematic data handling.
- To introduce Boolean algebra and Venn diagrams.
- To apply QCA ideas to personal projects, either using data offered in the course or the data you bring to the course. We show you how to use Excel software and fsQCA freeware.
- To examine fuzzy set histograms and scattergrams.
- To link NVIVO with SPSS for qualitative+demographic or survey data.
- To Practice making presentations using students’ own data and well-constructed logical arguments.
- To practice debating-format and/or panel discussion about knowledge construction.
Stephanie Thomson is a Postdoctoral Research Fellow in Oxford University (2015-). Her current work focusses on how secondary schools in England are deemed similar to one another in official discourses and the development of an alternative, typological account.
Prior to this, she was a Research Associate at the University of Manchester working on the Social Policy in a Cold Climate (SPCC) research programme (led by PI Ruth Lupton). Stephanie contributed to the assessment of the changes in educational policy (both for school-age children and those post-16) and the associated effects.
Her ESRC-funded doctoral work explored how parents helped their children with primary-school mathematics. As part of this work, she used a case-based method – Qualitative Comparative Analysis (QCA) – to assess whether particular configurations of child-level factors and parental help led to high achievement in mathematics. Her interest in methods has been sustained since then. She helped create teaching materials for ‘Core Mathematics’.
Wendy Olsen joined Manchester University in 2002 and is Professor of Socio-Economics. She worked till 2014 both for the Institute for Development Policy and Management (IDPM) and in the Discipline of Social Statistics. She is Director of the MSc in Social Research Methods & Statistics degree programme in Social Sciences (http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=24892). She has previously taught sociology, development economics, and research methodology. She teaches statistics and PhD research methodology as well as computerised qualitative data analysis, the comparative method, the case-study method, and topics in political economy (e.g. child labour in India). She has release from some of her teaching duties due to research projects (see . She is fostering the use of mixed-methods research among statistical and other researchers.
No prior knowledge is required. The course is framed at the Masters/ PhD level of achievement and aims to help researchers who wish to publish their own original findings in their later careers.
Guidance on preparatory readings will be available some days ahead of the event.
Background is held at www.compasss.org in the Bibliography and working papers areas.
QCA Seminal article: Lam and E. Ostrom (2010), “Analyzing the dynamic complexity of development interventions: lessons from an irrigation experiment in Nepal, Policy Science, 43:1, pp. 1-25. DOI 10.1007/s11077-009-9082-6 .
QCA Seminal article on national policy regimes: Hudson and Kühner, 2009, “Towards productive welfare? A comparative analysis of 23 OECD countries “, Journal of European Social Policy 2009, 19-34. DOI: 10.1177/0958928708098522 http://esp.sagepub.com/cgi/content/abstract/19/1/34.
Byrne, D., and C. Ragin, eds. (2009), Handbook of Case-Centred Research Methods, London: Sage.
Olsen, W.K. (2012) Data Collection: Key Trends and Methods in Social Research, London: Sage .
Ragin, C. C. (1987). The Comparative Method: Moving beyond qualitative and quantitative strategies. Berkeley ; Los Angeles ; London, University of California Press.
Ragin, C. C. (2000). Fuzzy-Set Social Science. Chicago; London, University of Chicago Press. Ragin, C. C. and H. S. Becker, Eds. (1992). What is a Case? Exploring the foundations of social inquiry. Cambridge [England]; New York, NY, USA, Cambridge University Press.
Ragin, C.C. (2008). Redesigning Social Inquiry: Set relations in social research. Chicago: Chicago University Press.
Rihoux, B., & Ragin, C. C., eds., (2009). Configurational Comparative Methods. Qualitative Comparative Analysis (QCA) and related techniques (Applied Social Research Methods). Thousand Oaks and London: Sage.
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