METHODS AND TECHNIQUES OF SOCIAL RESEARCH

Lorenzo De Sio

Instructional goals

The course aims at making students able to design and conduct a research project in the social sciences, translating even basic questions into a concretely developed research project, by developing a knowledge of the challenges and problems of each stage of the research cycle, and the competence to successfully address them.

Prerequisites

Basic concepts of sociology. Elementary knowledge of the basic techniques of quantitative data analysis (frequency distributions, cross-tabulations, elements of OLS regression).

Intended learning outcomes

Knowledge and understanding: Knowledge of the fundamental problems of social research; structuring of the different stages of the research cycle; problems, goals and specific tools of each stage (from the identification of the research question to the presentation of results), with special reference to survey-based research. Applying knowledge and understanding: Ability to competently use the appropriate tools for each research stage, by identifying problems and potential solutions that involve the appropriate tools. Resulting ability to structure a real research project (based on quantitative tools, adopting the post-positivist paradigm) starting even from simple questions. Making judgements: Familiarity with the alternative choices and decisions of each research stage, and with the necessity of making compromises between rival goals. Understanding of the arbitrary choices of each stage, leading to the relative subjectivity of a single research, thus to the objectivity of science as intersubjectivity among multiple researches that publicly disclose the methods and choices adopted. Communication: Ability to interact with external subjects, to understand the point of view of the research subject, to present research results in different formats (oral presentation with slides; small research report; research article). Lifelong learning skills: Aware, critical perspective towards the results of social research. Concrete understanding of the cumulative learning method of the social sciences, which leverages the concrete falsifiability of research hypotheses and the cruciality of empirical data to understand social reality and construct cumulative knowledge.

Course Contents

The course starts from the specific problems of building knowledge in the social sciences, then moving into detail on the specific stages of development of a quantitative, survey-based research project. The focus on survey research allows to deal with a data collection technique that is both powerful and challenging, allowing to examine the creative and problematic aspects of different research stages. All research stages are considered: identification and definition of the research question, conceptual development and operationalization, questionnaire development, questionnaire administration and data collection, data analysis, presentation of results.

Reference Books

Corbetta, P., "Metodologia e tecniche della ricerca sociale" (simgle volume, pp. 644). Other materials circulated by the instructor.

Teaching Methods

Interactive lectures; development of group project work, with the construction of an actual survey-based research: research question, conceptual map, construction of the questionnaire, data collection and analysis, presentation of results.

Assessment Method

On a weekly basis: exercises and self-assessment tests (not relevant for the final assessment). Week 4 [Individual test] TEST: Questions/exercises similar to the self-assessment ones of weeks 1-3 (about 30 in 15') 15% Weeks 6-7: [Group work] On a research question: scientific literature review; conceptual map; part of a questionnaire 20% (requires attendance) Week 8: [Individual test] TEST: Questions/exercises similar to the self-assessment ones of weeks 4-5 (about 30 in 15') 15% Weeks 10-12: [Group work] Data analysis presentations (and discussion) 20% (requires attendance) Individual final exam: TEST: Questions/exercises similar to the self-assessment ones of the last few weeks (about 40 in 20') 30%

Thesis assignment criteria

30/30 grading. Positive assessment of a small thesis project.

Week 1

Introduction At the origin of science: the research question. The research cycle and its stages. The data matrix. Units of analysis. Cases and variables. Independent and dependent variables. Correlation and causation.

Week 2

Scientific knowledge in social sciences: gnoseological and epistemological problems. Post-positivist paradigm and interpretative paradigm.

Week 3

Causality and scientific explanation. Covariation, direction and control. The fundamental problem of causal inference. Experiments. Ecological data and individual data. Ecological fallacy. Building a scientific explanation. The role of scientific literature.

Week 4

The survey. Survey design and measurement techniques. Sampling. Secondary analysis; national and international data sources. The structured questionnaire. Conceptual maps and questionnaire development.

Week 5

Measuring concepts. Survey items. Question wording and measurement bias. From indicators to indices. Validity and reliability and their measurement. Use of aggregate data.

Week 6

Data analysis. Use of crosstabs and OLS regression. Software.

Week 7

Midterm exam. Finalization of the students' questionnaire and data collection. Communicating research: audiences and tools.

Week 8

"Research in action" guest seminar. Insights: data analysis in practice.

Week 9

Student presentations. Insights: beyond survey data.

Week 10

"Research in action" guest seminar. Insights: data analysis in practice.

Week 11

Student presentations. Insights: beyond OLS regression.

Week 12

"Research in action" guest seminar. Insights: data analysis in practice.