The course aims to familiarize students with the key problems, tools, and techniques of social sciences methodologies, in order to enable them to structure and conduct basic research projects. As a further objective, the course will enable students to understand and critically assess the results of empirical research in the social sciences.

Knowledge and understanding: Knowledge of: 1) the fundamental problems of social research; 2) the structuring of the different phases of the research cycle and of the problems, objectives, and specific tools of each phase (from the identification of the research question to the presentation of the results) in both qualitative and quantitative research designs. Applying knowledge and understanding: Ability to use appropriate tools for each phase of the research process, identifying problems and possible solutions. Resulting ability to structure an effective research project. Making judgements: Familiarity with the alternative choices present in each research project phase, and with the need to compromise between different objectives. Understanding of the arbitrary choices necessary in each phase of the research, the potential subjectivity of the results of individual studies, and therefore an understanding of scientific objectivity as intersubjective validation across different studies that publicly disclose their methods and choices. Communication Skills: Ability to interact with clients and to present the research results in different forms (oral presentation with slides, small research report, scientific article). Learning skills: Critical and conscious perspective towards the results of social research. Concrete understanding of the cumulative learning method of the social sciences, the crucial importance of empirical data for studying social reality, and the construction of cumulative knowledge.

The course examines the different stages of the life cycle of social research, taking into account both qualitative and quantitative approaches. It is divided into two parts, led by two different instructors. The first part of the course (weeks 1–6) will focus on qualitative research methods. After gaining an understanding of the goals, philosophical foundations, and key elements of qualitative research (week 1), students will be guided through all the fundamental stages of the qualitative research process. They will learn how to formulate meaningful qualitative research questions, select appropriate samples, and understand the differences between the researcher’s role in qualitative and quantitative inquiry (week 2). Through class discussions and practical exercises, students will explore various data collection methods, including interviews, focus groups, and observations, also in relation to emerging generative AI tools (weeks 3–4). Significant theoretical and practical attention will be devoted to data analysis techniques, with a particular focus on relational aspects (week 5), as well as to the concepts of reliability and validity in qualitative research (week 6). The second part (week 7-12) focuses on quantitative research methods, providing an overview of its foundational principles and practical applications. By the end of the first part, students should have an enhanced understanding of why social scientists rely on numbers and what implications this has for understanding real-world social, economic, and political problems. The course will focus on data analysis, introducing students to some of the basic statistical skills employed in the social sciences. They will use STATA, a user-friendly statistical software program, which will give them the opportunity to analyse real data. At the end of the course, students will be comfortable not only reading and interpreting material that relies on quantitative data but also using data in their own research.

For the qualitative part: Merriam, S., & Tisdell, E. (2015). Qualitative Research (4th ed.). Wiley. https://www.perlego.com/book/995799/qualitative-research-a-guide-to-design-and-implementation-pdf and Social Research Methods by Alan Bryman available here: (https://luiss.alma.exlibrisgroup.com) For the quantitative part, selected chapters from: Corbetta, P. (2003). Social Research: theory, methods and techniques (1st ed.). SAGE Publications. (SR) Available here: https://go.exlibris.link/kkWlB15W Kosuke Imai, Lori D. Bougher. (2024). Quantitative social science: An introduction in Stata. Princeton University Press. (QSS) Available here: https://go.exlibris.link/ZZ4T7G16 Additional materials distributed by the instructors during the course.

Lectures, in-class labs and home exercises.

Two computer-based written exams will be held during the course. The first, on qualitative methods, will take place in week 7 and will cover the course content from week 1 to week 6. The second, on quantitative methods, will take place in week 13 and will assess the topics addressed in weeks 7 to 12. Both exams will last approximately 50 minutes and will be based on multiple-choice and open questions. The quantitative part will also involve performing a data analysis exercise using Stata. Subsequent exams will consist of both the quantitative and qualitative tests combined. The final grade will correspond to the weighted average score of the two assessments and will be published on MyLuiss. Correct answers are based on: (a) reference reading chapters for all course weeks; (b) class instructor presentations and class slides and material distributed throughout the course.

Criteria for accepting requests are: 1) Exam grade ≥ 29 2) Quality of the proposed project. Thesis requests should be presented as a one-page project, with a short reference lists and a suggested index. The project should briefly detail the research question and the specific case studies considered.