Syllabus
Registration via LPIS
Day | Date | Time | Room |
---|---|---|---|
Monday | 10/02/23 | 02:00 PM - 05:00 PM | D4.0.047 |
Wednesday | 10/04/23 | 02:00 PM - 04:00 PM | LC.2.064 PC Raum |
Monday | 10/09/23 | 02:00 PM - 04:00 PM | D2.0.330 |
Wednesday | 10/11/23 | 02:00 PM - 05:00 PM | LC.2.064 PC Raum |
Monday | 10/16/23 | 02:00 PM - 04:00 PM | D2.0.330 |
Wednesday | 10/18/23 | 02:00 PM - 04:00 PM | D2.0.330 |
Monday | 10/23/23 | 02:00 PM - 04:00 PM | D2.0.330 |
Monday | 11/06/23 | 02:00 PM - 06:00 PM | D4.3.213 |
Monday | 11/13/23 | 02:00 PM - 04:00 PM | D2.0.330 |
Wednesday | 11/15/23 | 02:00 PM - 04:00 PM | D5.1.003 |
Monday | 11/20/23 | 02:00 PM - 04:00 PM | D2.-1.019 Workstation-Raum |
Wednesday | 11/22/23 | 02:00 PM - 04:00 PM | D3.0.237 |
Monday | 11/27/23 | 02:00 PM - 04:00 PM | D3.0.237 |
Wednesday | 11/29/23 | 02:00 PM - 04:00 PM | LC.2.064 PC Raum |
Wednesday | 12/06/23 | 02:00 PM - 04:00 PM | D2.0.330 |
Wednesday | 12/13/23 | 02:00 PM - 04:00 PM | LC.-1.038 |
Monday | 12/18/23 | 02:00 PM - 04:00 PM | D2.0.330 |
Monday | 01/08/24 | 02:00 PM - 04:00 PM | TC.-1.61 (P&S) |
Wednesday | 01/10/24 | 02:00 PM - 03:00 PM | D2.0.330 |
Wednesday | 01/17/24 | 02:00 PM - 06:00 PM | D2.0.330 |
There is still an ongoing debate on whether quantitative and/or qualitative methods are more appropriate to answer different research questions. Yet, both methodological approaches offer valuable contributions depending on the aim of research. While qualitative studies are suited for theory creation and require primarily exploratory designs (constructivist or phenomenological approaches), quantitative research seeks to test theories by quantifying structured data (statistical analysis). The course covers special topics in both qualitative and quantitative methods.
This semester students will work in small research groups, dealing with a specific topic. The groups learn how to do research in a team. They will draft a research design, formulate empirical questions, present them in class and they will gain relevant insights from the feedback of others. In the final research report, the quantitative and qualitative results should be connected to each other, placing a focus on the main (methodological) insights.
In the qualitative part the aim is to develop mixed methods research designs which fit to the topics and questions of the students’ projects. With a special focus on the premises and basic ideas of empirical research, we look at ways of how these are implemented adequately in the designs. Furthermore, this part will focus on the qualitative method of expert interviews. Students will generate and analyse qualitative data.
In the quantitative part of the course, students work on their research project, using large quantitative data sets and applying regression-based methods.
After successful completion of this course, students will be able to:
- develop a research question (based on the state of the art and on theories)
- specify a mixed methods research strategy in more depth (empirical design) and to formulate quantitative hypotheses
- to apply suitable methods: to analyse data using econometric techniques: regression analysis, discrete and multilevel models, and to conduct qualitative expert interviews
- to analyse, interpret and try to link the varying results from quantitative and qualitative methods
- to present research results (including a quality assessment)
- to write an academic article
Students are expected to:
- prepare the literature for discussions in class
- actively participate in discussions and assignments in class
- submit a research design
- to select data
- to apply methods
- to analyse and interpret data
- to submit a research article
80% attendance of the class is required! If you miss a class, please inform us in advance!
Design of Teaching
drafting and applying a research design, presentation, discussion, readings followed by aquestion-answer session to the obligatory texts and practical exercises.
Exigencies
Active participation in class, group assignments, presentation in class, final seminar paper on own project
- individual tasks (assignments): 20%
- contributions in class: 5%
- Group tasks: 75%
SEEP courses do not allow creation of assignments, exam answers or other assessed work using generative AI (e.g. ChatGPT). All such work is expected to be the original work by the student concerned and is assessed as such. Work copied from a generative AI source is equivalent to plagiarism and will be treated as such.
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