This course considers the relationship between the dominant philosophical perspectives which inform social science research and the practice of doing social science research. It provides the foundations for learning about social science research by enabling students to justify and explain their own epistemological choices. The course highlights how these choices impact upon questions of research design and method. The course introduces philosophical/theoretical concepts alongside practical issues of research method choice and design.
The course provides a foundational understanding and skillset for conducting both quantitative and qualitative research. The course begins by explaining how research is a systematic, controlled, and empirically based, self-correcting approach for discovery. Thereafter, ontological, epistemological, and methodological foundations of both quantitative and qualitative research traditions are described. For quantitative methods, fundamental mathematical principles, such as Central Limit Theorem, are introduced in a systematic way. Students then make use of real secondary data (from a variety of discipline-specific datasets) to perform and report upon basic univariate, bivariate, and multivariate analyses (using the R programming language). Thereafter, the fundamental principles and assumptions of qualitative research traditions are described with the assumption that individual and social behavior differ from inanimate natural phenomena. Students learn about basic forms of qualitative analyses, alongside practice using open-source software (QualCoder). Strategies for leveraging AI in an ethical and transparent way are offered throughout.