Our 2-year study plan is focused on training our students to conduct theory-orientated and methodologically rigorous empirical research in comparative perspective. Our curriculum is split into two main parts – course in the 1. year, internship and MA thesis writing in the 2 year.
Our compulsory courses on quantitative methods will give not only deeper insight into descriptive statistics and the use of the software package R, but also convey knowledge about inferential statistics. But students also need to pass courses about qualitative methods of social inquiry. At the same time, our compulsory courses provide a deeper understanding of the concepts and models of comparison in social science. In addition, each year we organize a course on applied comparative sociology with invited guest lectures, for example on social capital in western and post-communist societies.
Our elective course are assembled each year and offer various topics in methodology and issue-related social science. Students can choose from a pool containing courses on data analysis, such as social network analysis, measurement theory, but also courses on social inequalities, ageing society, comparative public policy, and global political economy – to name just some of them.
Our compulsory research seminar runs throughout the year and provides a platform for students to develop their research questions and project designs. Here we learn and discuss the practical side of academic work from finding suitable research topics to publishing in international peer-reviewed journals.
Courses Required by the Program Educational Standard. Сompulsory Components
1. Modern Sociological theory: Comparative Sociology
This course is designed to be a broad orientation to the different methodologies featured in the program in International Master in Comparative Social Research. It therefore aims to be comprehensive about the pertinent topics, even though its time constraints render comprehensiveness an elusive aim. The goal at hand is to strengthen whatever weaknesses the course attendees may have on the topic and to improve their ability to become, down the road, intelligent about methodology as well as proficient
2. Methodology and Research methods in Sociology: Quantitative Research methods
The course aims to provide students with understanding of key concepts and methods of modern statistical data analysis. It gives an overview and practice of the skills necessary for conducting independent research with quantitative survey data, using R software. Skills include downloading data, creating a working dataset
Components of Educational Program. Сompulsory Components
1. Methodology and Research methods in Sociology: Qualitative Research methods
The course aims to introduce students to the use of qualitative methods in sociological research. The students will learn the basic fundaments of qualitative inquiry from research design to data collection and analysis. They will be introduced to practical skills in qualitative data collection, including interviews, organizing field research, writing field notes and observation. In addition to methods for gathering data.
2. Multi-level regression analysis
The course assumes the student's knowledge of linear regression modelling and consists of lectures and labs. Labs will follow lectures and will familiarize the student with practical application of the method discussed in the lecture
3. Introduction to Structural Equation Modeling
The course is intended to give an introduction to general principles and techniques of Structural Equation Modeling (SEM) and their implementations in a popular SEM software tool, R package lavaan. Students are assumed to have basic knowledge of statistics and be familiar with several conventional statistical methods, including regression analysis and principal component analysis
4.Theory and Methods of the Life-Course Approach
After this course, students will know the differences between the life span, the life cycle and the lifecourse; they will be able to work with EHA and SA in SPSS and R
5.Basic Statistics and Introduction into „R“
The course aims to provide students with understanding of basic concepts of statistical analysis and basic principles of programming in R statistical package. It gives an overview of the basic skills necessary for understanding of modern methods of data analysis and conducting independent research with quantitative survey data using R software
During the third semester our students conduct a research internship in Russia or abroad. The faculty of our programme supports students to find internship place according to their research interests and thesis projects. In doing so, we cooperate with a vast pool of partners at Russian or foreign research institutions or universities, and help our students on their search for grants and scholarships. During their internship students collect and analyze data for their MA thesis, but also take active part in their internship institution´s everyday life, learning the rhythm of research work.
Alternatively, students participate in one of our Double-Degree-Tracks during the third (and voluntary also the forth) semester and study at Freie University Berlin or EHESS Paris, where they also work on their course works and MA theses.
The fourth semester is solely dedicated to writing and defending the MA thesis.The MA thesis colloquium is accompanying this process and providing support, constructive criticism and knowledge about research presentation.