Theoretical and Empirical Research Methodology
Lecture and implementation lab in the fall semester 2026
📋 Seminar description
The seminar description is the syllabus of this module: it documents the goals and structure of the course, the schedule, the expected workload, the rules of examination, and the prior knowledge in mathematics and statistics that we assume. Please read it at the beginning of the semester. It is also available there as a PDF for printing.
📍 When and where
- Main lecture: Mondays, 11:30–13:00, Room MAD 024 (Madrid Building)
- Implementation lab: Fridays, 11:15–12:45, Room MAD 024 (Madrid Building). The lab does not meet on site every week — the table below marks which sessions are on-site labs and which are video labs.
- Exams: first exam on 14 December 2026, 13:15–15:15, and second exam on 24 February 2027, 09:15–11:15, both in Room MAD 024.
The lecture period runs from 14 September to 11 December 2026. There is no class in the week of 12–16 October. Since the lecture of 5 October had to be cancelled, all later lectures moved by one week; the lecture on Literature reviews is delivered as a video lecture released on 2 November, and the Monday of 7 December is kept in reserve. The dates of the implementation lab did not change. Please always check the most recent version of the seminar timetable, since dates and rooms can differ from one week to another. The authoritative timetable, rooms and times are provided on this page. For all kinds of official announcement please watch the Moodle course.
The following table gives an overview of the combined schedule and serves as the authoritative schedule:
| Week | Title Lecture | Title Lab |
|---|---|---|
| 1 | General introduction | General introduction & installation (on-site) |
| 2 | AI tools in practice | Basics of R and R Studio (video) |
| 3 | Basics of logic | Project management & recap (on-site) |
| 4 | Lecture cancelled (5 Oct) — moved to week 5 | Object types (video) |
| 5 | Logic, argumentation, models, and explanation | Quarto and R Markdown (video & on-site) |
| 6 | Quantitative and qualitative research | Importing data (video) |
| 7 | Interviews · Literature reviews (video lecture) | Data preparation (video) |
| 8 | Case studies | Data visualization (video) |
| 9 | Statistics recap | Using AI for coding (on-site) |
| 10 | Regression analysis | Linear models in R (on-site) |
| 11 | Experiments | Experimental data in R (on-site) |
| 12 | No lecture (reserve slot) | Recap session & open Q&A (on-site; material TBA) |
You find the full schedule with further information on each session on the lecture overview and the lab overview pages, and the complete syllabus in the seminar description.
💻 Exercises
There is an R package with interactive exercises for the implementation lab. I strongly recommend to do the exercises for each session since regular practice is the most important determinant in your success in learning R. You find more information on how to use the exercises in this short guide. On top of that, there are some additional exercises on selected topics here.
📂 Material
You find an overview of all lecture materials, such as slides and reading lists, on the lecture overview page, and all lab materials on the lab overview page. Complete material lists for the single sessions are distributed via the respective session pages. Scientific publications that are not available open access can be obtained via Moodle.
📚 Method and Inquiry
The tutorials complementing the lab sessions — on installing R, object types, data import and preparation, visualization, regression and much more — are hosted on Method and Inquiry, the methodology hub of the Europa-Universität Flensburg. The session pages link the relevant resource for each week; you can also browse the full resource library and the thematic tracks yourself.
💌 Contact and discussion
For asking questions and starting discussions, please use the forum in Moodle course.