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ECPR Virtual Methods School Round-up

ECPR Methods School: follow the training tracks

What are training tracks?

The Methods School offers a broad variety of courses that can be taken on a standalone basis or in a sequence over one or more events.

Winter School courses are prefixed with a W; Summer School courses with an S.

Short courses
An introduction or refresher to tools that will be useful for further courses. Typically software training before a data analysis course.

Main and Master courses 

  • Research design/fundamentals Courses enabling you to think about your research more broadly, so you can make more informed choices about specific methods/techniques.
  • Data collection/generation Hands-on courses focused on a specific method (or family of methods) for data collection or generation.
  • Data analysis (foundation) Hands-on courses focused on a specific method (or family of methods) for data analysis, bringing you to a foundation level.
  • Data analysis (introductory) Hands-on courses focused on a specific method (or family of methods) for data analysis, bringing you to a level of well-informed use.
  • Data analysis (intermediate) and (advanced) Hands-on courses focused on a specific method (or family of methods) for data analysis, bringing you to an expert level, including more recent refinements.

Seasoned Scholar Workshops
For experienced scholars with significant research experience beyond their PhD.

With so many options, it can be difficult to know where to start, but the tips below might help.

Pick the course combination that's right for you

  • Some courses are useful to attend before or after a given course – see the categories above. It often makes senses to follow an A-B-C-D sequence: for instance; first a short course prefixed WA or SA, followed by a research design/fundamentals course prefixed WB or SB, then by a data collection/generation course prefixed WC or SC, then by a foundation or introductory data analysis course prefixed WD0/WD1 or SD0/SD1, and finally by a more advanced data analysis course prefixed WD2, SD2 or SD3. Based on your prior knowledge and/or practical constraints (funding, etc.), it’s also possible to follow only part of such a sequence (for example, A-B, B-C, C-D, D0-D1, D1-D2).
  • Not all courses are offered every year. Some more specialised courses or courses on emerging topics are offered every two years. This is useful to consider, especially if you are planning attendance over 2–3 years.
  • If you have already identified a course you want to attend but are unsure which course(s) you should choose next, you might find some hints and recommendations in the detailed course outlines, in particular the ‘prerequisite knowledge’ section and the ‘recommended courses before’ and ‘recommended courses after’ sections. You can also contact the Instructors for advice about the right training track to suit your needs. Finally, if still in doubt, you can also contact the Academic Convenors, who will be glad to provide some advice.

Notes of caution

There is an endless number of course sequences available, depending on how courses fit with each other, your prior research skills, and the specific needs for your project.

There are multiple views of what constitutes good or appropriate methods in the social sciences.

There is debate on

  • terms including ‘methodology’, ‘approach’, ‘method’, ‘technique’, ‘data’.
  • the labels used to name different approaches (quantitative vs qualitative or variable-oriented vs case-oriented; mixed or multi-method designs, etc).
  • the extent to which different phases of a research process can be considered separately. For instance: many qualitative or interpretivist researchers will contend that research design, data generation and data analysis are fully intertwined.

A number of courses do not fully ‘fit’ within one of the categories above; they may have a broader focus or cover different stages of the research process. For instance:

Quantitative text analysis is mostly a data analysis course, but it also covers some data collection/preparation aspects

Comparative research designs is mostly a research design course, but it also covers some data collection aspects as well as some (comparative) data analysis aspects

Advanced multi-method research is a research design course that also comprises some elements of data collection and data analysis.