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| Research Design and Research Logic in Comparative Politics | | |
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 Allocations: 2 | |
| Veranstaltungspriorität[2 reguläre Pflicht-LV]; Lehrveranstaltungsrhythmus[wöchentlich] |
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https://cccp.uni-koeln.de/sites/cccp/Lehre/2023_SS/Syllabus_23_Research_Design.pdf
Usually, whenever there is a big fire, there are also fire workers. Should we close all fire stations to prevent future outbreaks? There is also evidence that people who are infected with Covid-19 and get hospitalized have a higher probability of dying that infected people who are not hospitalized. Should we stop hospitalizing infected people? For both questions, the answer should be “no” because the suggested answers “get the causality wrong”, yet for different reasons. In this course, you will learn how to systemize your causal thinking and reasoning and learn about different research designs for answering causal research questions. In the first part, we will discuss what it means to infer causation and what it is that makes one factor causal and another one not.
In part two, you will make first steps to systemize your causal and theoretical thinking using directed acyclic graphs (DAGs) as a modern, informal tool of causal mapping. Simple DAGs can demonstrate why the closing of fire stations and non-hospitalization of infected people wouldn’t help much in preventing fires and deaths caused by Covid-19. More generally, DAGs can give one an idea about what causal research questions can be answered in principle and how. In the third part, we will discuss different research designs (a map or plan for answering a research question). We will structure and compare the designs across common dimensions – few cases vs many cases; experimental vs observational; qualitative vs quantitative – and carve out their unique strengths and weaknesses for answering research questions. At the end of the course, you will be familiar with (1) the basic elements of causality-oriented empirical research; (2) different understandings of causation; (3) how to theorize causal models, use DAGs to visualize them and understand what they imply for your analysis; (4) a variety of research designs and the research questions one can (and cannot) answer with them. Finally, we conclude on the basis of meta-studies how much we can trust the findings of different designs and how to increase the credibility of social science research. |
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| Für die Anmeldung zur Teilnahme müssen Sie sich in KLIPS 2.0 als Studierende*r identifizieren. |
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| Angaben zur Prüfung |
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| siehe Stellung im Studienplan |
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• The exam in this course is the portfolio exam. Participants have to submit multiple
assignments.
• The final grade depends on all assignments. The final grade is determined based on the
sum of the points across all assignments and is graded using a 100-point scale (see below).
• Failing a single assignment does not have consequences. Only passing in the end
matters.
• The assignments will be graded and returned to the participants with comments.
• Submissions have to be made on ILIAS |
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