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Course list

We provide courses across the whole range of social science methods. The course programme has been designed so that you can follow courses in a week 1 (June 20-24) + week 2 (June 27 – July 1) sequence -- see more about sequencing below.

Foundational courses
Interpretive/qualitative approaches
Case-based/comparative approaches
Statistical approaches 
Big Data approaches

Foundational courses

Interpretive/qualitative approaches

Case-based/comparative approaches

Statistical approaches

Big Data approaches 

Course Name Instructor Week 1 or 2
Collecting Web Data with R Hauke Licht 2
Applied Social Network Analysis Silvia Fierascu 1
Discourse Network Analysis Philip Leifeld 1
Inferential Network Analysis Philip Leifeld 2
Introduction to Quantitative Text Analysis Kostas Gemenis 1
Introduction to Machine Learning for Social Sciences Bruno Castanho Silva 2


Pedagogical excellence: placing the bar high -- and delivering

MethodsNET aims to set the bar very high with regards to pedagogical excellence. How is this achieved? The experienced team of MethodsNET Academic Coordinators has handpicked dedicated pedagogues, i.e.  methods experts who have a strong track record in PhD-level methods teaching and who, as importantly, are motivated by training researchers. Each of our instructors has designed an interactive course, with small-group interaction and individual tutoring. When the number of course participants allow, a sharp teaching assistant supports the instructor and provides further individual guidance. Beyond their own course, the instructors are also open to exchanging views with fellow instructors specialized  in other methods, via the Summer School’s transversal afternoon sessions. Finally, each course is subject to evaluation by its participants, and the MethodsNET Academic Coordinators closely de-brief this evaluation with each instructor in order to further improve the course for next year round.

How to choose the week 1 - week 2 sequence that meets your needs?

We have placed courses in week 1 or in week 2 in a way that maximizes the number of useful sequences. There are multiple sequences, depending on your needs and prior knowledge. We recommend that you operate in 3 steps: (1) consult your supervisor and close peers who are sharp in methods; (2) get in touch with the course instructor(s) concerned to ask for their recommendations; (3) ask the Summer School Academic Coordinators for further advice. Here is a (non-limitative!) list of typical sequences recommended by the Academic Coordinators:

Week 1 Week 2
Multi-method research - Multi-method research in practice
- Social Science measurement
Interpretive Research Methods - Qualitative expert interviews
Qualitative Data Analysis - Advanced Qualitative Data Analysis
- Qualitative expert interviews
Comparative Research Designs - Multi-method research in practice
- Social Science measurement
- Comparative Historical Analysis
Qualitative Comparative Analysis - Advanced Qualitative Comparative Analysis
- Comparative Historical Analysis
- Multi-method research in practice
Introduction to Process Tracing - Process tracing in practice
- Comparative Historical Analysis
Introduction to Inferential Statistics - Multi-method research in practice
Regression I: Linear Regression - Regression 2: Logistic Regression and General Linear Models
- More than an introduction to Structural Equation Modelling
Multilevel regression analysis of cross-sectional and panel data with R - Panel Data Analysis
- Regression 2: Logistic Regression and General Linear Models
- More than an introduction to Structural Equation Modelling
- Longitudinal Data Collection with the DearScholar Diary App
Introduction to R - Collecting Web data
Discourse Network Analysis - Inferential Network Analysis
Introduction to Quantitative Text Analysis - Collecting Web data
- Introduction to Machine Learning for social sciences

These sequences are suggestions, but there are of course many different combinations that might make sense for your research. For example, you might consider combining courses from different methodological approaches (e.g. an introductory statistical course in week 1 with an introduction to Comparative Historical Analysis in week 2). You are always welcome to contact us for more suggestions and advice.