METHODS OF SOCIAL RESEARCH

Francesco Visconti, Antonio Zinilli

Instructional goals

The course aims at making students familiar 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.

Prerequisites

There are no formal prerequisites for this course. Basic notions of sociology are helpful but not formally required.

Intended learning outcomes

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 competently use the appropriate tools for each phase of the research, identifying problems and possible solutions through the appropriate tools. 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 the single research, and therefore the objectivity of science only as intersubjectivity across different research that publicly disclose the methods and choices used. Communications 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.

Course Contents

The course examines the different stages of the lifecycle 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 (week 1-6) will focus on qualitative research methods. After gaining insight into the goals, philosophical underpinnings and key elements of qualitative research (week 1), students will be guided through all the fundamental stages of a qualitative research process. They will learn to formulate meaningful qualitative research questions, select samples, and understand the difference between the researcher's role in qualitative and quantitative inquiry (week 2). During class discussions and practical exercises, they will explore different data collection methods like interviews, focus groups, and observations (weeks 3-4). Substantial theoretical and practical attention will be given to data analysis techniques (week 5) and 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 second part, students should have an enhanced understanding of why social scientists rely on numbers and what implications this has for understanding real world political problems. The course will focus on data analysis, introducing students to some of the basic statistical skills employed in social sciences. They will use STATA, a user-friendly statistical software program, which will give them the opportunity to analyse real political 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.

Reference Books

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 For the quantitative part: Corbetta, P. (2003). Social Research (1st ed.). SAGE Publications. https://www.perlego.com/book/861933/social-research-theory-methods-and-techniques-pdf Daniels, L. and Minot, N (2025) An Introduction to Statistics and Data Analysis Using Stata®, Sage. https://www.perlego.com/book/4792297/an-introduction-to-statistics-and-data-analysis-using-stata-from-research-design-to-final-report-pdf Additional materials distributed by the instructor during the course.

Teaching Methods

Class teaching, interviews and data analysis exercises.

Assessment Method

Two multiple-choice exams will be held during the course. The first will take place at the end of week 6 of the course and will cover the course content from week 1 to week 6. The second will take place at the end of week 12 and cover the topics covered in weeks 7 to 11. Both multiple-choice exams will be computer-based and will last approximately 45 minutes. Correct answers are based on: (a) reference reading chapters for all course weeks; (b) class instructor presentations and class slides distributed throughout the course (excluding student slides). EXERCISES/LABS: Students will be divided into groups that will participate in two in-class exercises/laboratories. As the MSR course requires both theoretical and practical components, these activities are considered mandatory to access the final exam. These exercises/laboratories may involve, for instance, the planning, execution, and analysis of an interview for the qualitative part of the course and the analysis of social science datasets for the quantitative part. Further details on the modes and timing of the exercises/laboratories will be provided during the first lesson of the course. Other activities: Further details will be provided in class. Attendance is mandatory and will be taken for every class session. Non-attending students must register for one of the “appelli”, submit a methodological reflection paper three days before the exam (on a topic agreed upon in advance with the course lecturers), and take an in-person multiple-choice exam covering both the quantitative and qualitative parts of the program. The final grade will correspond to the weighted average score of these assessments.

Thesis assignment criteria

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

Week 1

Qualitative methods: Intro to the course. Qualitative research - features and approaches.

Week 2

Qualitative methods: Designing a qualitative study. The role of reflexivity, positionality, and ethics in qualitative research.

Week 3

Qualitative methods: Qualitative interview(s) - techniques and challenges. Focus group.

Week 4

Qualitative methods: Observational methods and document analysis. Process tracing.

Week 5

Qualitative methods: Key principles of qualitative data analysis. Thematic analysis.

Week 6

Qualitative methods: Reliability and validity in qualitative research Mid-term.

Week 7

Quantitative methods: Intro to the quantitative part of the course and the STATA software.

Week 8

Quantitative methods: The construction of a quantitative research. Operationalization: from properties to variables. Types of variables. Indicators. Indices

Week 9

Quantitative methods: Studying individuals: survey research. Sampling. The structured questionnaire. Type of response categories. Scales and scaling theory.

Week 10

Quantitative methods: Univariate analysis. Frequency distributions. Charts. Summary measures. Related exercises with STATA.

Week 11

Quantitative methods: Relationships between variables. Contingency tables. Scatterplots. Introduction to linear regression. Related exercises with STATA.

Week 12

Quantitative methods: Introduction to multiple regression. Statistical significance. Interpreting regression results. Related exercises with STATA. Multiple choice exam on the quantitative part of the course.