240544 SE MM7 Research Design Workshop (2025W)
Continuous assessment of course work
Labels
Participation at first session is obligatory!The lecturer can invite students to a grade-relevant discussion about partial achievements. Partial achievements that are obtained by fraud or plagiarized result in the non-evaluation of the course (entry 'X' in certificate). The plagiarism software 'Turnitin' will be used.
The use of AI tools (e.g. ChatGPT) for the attainment of partial achievements is only allowed if explicitly requested by the course instructor.
The use of AI tools (e.g. ChatGPT) for the attainment of partial achievements is only allowed if explicitly requested by the course instructor.
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 01.09.2025 00:01 to Mo 22.09.2025 23:59
- Deregistration possible until Mo 20.10.2025 23:59
Details
max. 25 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 21.10. 08:00 - 11:15 Seminarraum A, NIG 4. Stock
- Friday 24.10. 11:30 - 14:45 Seminarraum D, NIG 4. Stock
- Monday 15.12. 11:30 - 14:45 Hörsaal C, NIG 4. Stock
- Thursday 18.12. 15:00 - 18:15 Hörsaal C, NIG 4. Stock
- Wednesday 14.01. 11:30 - 14:45 Seminarraum A, NIG 4. Stock
- Wednesday 28.01. 11:30 - 14:45 Hörsaal C, NIG 4. Stock
Information
Aims, contents and method of the course
Assessment and permitted materials
- Regular attendance and active participation
- Development and presentation of tasks related to one’s own project (data organization and data analysis)
- Commenting on other participants' research project
- A written report on the initial analysis of the MA data and the anticipated resultsAll materials that comply with the standards of good scientific practice are permitted, unless the teacher specifies otherwise.
- Development and presentation of tasks related to one’s own project (data organization and data analysis)
- Commenting on other participants' research project
- A written report on the initial analysis of the MA data and the anticipated resultsAll materials that comply with the standards of good scientific practice are permitted, unless the teacher specifies otherwise.
Minimum requirements and assessment criteria
The minimum requirement is regular attendance and the successful completion of all course components.
The grade will be determined by the following elements:
- Presentation of initial organization of the data (20 points max.)
- The initial analysis of the MA data (40 points max.)
- Commentary on peers’ work (20 points max.)
- Presentation of anticipated results (20 points max.)Grading scale:
91–100 points: 1 (excellent)
81–90 points: 2 (good)
71–80 points: 3 (satisfactory)
61–70 points: 4 (sufficient)
0–60 points: 5 (non sufficient)To pass the course students must reach at least 61 points.Written assignments will be evaluated according to the following criteria:
- language and style (spelling and grammar)
- use of literature (choice of relevant readings, accuracy of citations and arguments)
- organisation of the arguments
- critical thinking and originality
- reflexivity
The grade will be determined by the following elements:
- Presentation of initial organization of the data (20 points max.)
- The initial analysis of the MA data (40 points max.)
- Commentary on peers’ work (20 points max.)
- Presentation of anticipated results (20 points max.)Grading scale:
91–100 points: 1 (excellent)
81–90 points: 2 (good)
71–80 points: 3 (satisfactory)
61–70 points: 4 (sufficient)
0–60 points: 5 (non sufficient)To pass the course students must reach at least 61 points.Written assignments will be evaluated according to the following criteria:
- language and style (spelling and grammar)
- use of literature (choice of relevant readings, accuracy of citations and arguments)
- organisation of the arguments
- critical thinking and originality
- reflexivity
Examination topics
Content of the course. Students work mainly with their own data from their previous fieldwork. In addition, critical discussions of their peers’ assignments are a necessary ingredient for successful completion of the course.
Reading list
Association in the course directory
Last modified: Th 23.10.2025 12:27
The main goal of the seminar is to accompany each student who has already conducted fieldwork in organizing their fieldwork material and the initial process of its analysis for their MA thesis. If needed, the students will be assisted to reframe their initial research question and their theoretical framework in light of their data analysis. The students will submit assignments to be discussed in class and in peer-group discussions. Additionally, the students will be asked to provide constructive commentary to their peers’ assignments.
Learning Outcomes: At the end of the course, the students are expected to have learned and reflected on the process of analysis and particularly coding as well as the issues related to research ethics, especially in dealing with the collected data for their MA thesis.
Format: The class will be based on hands-on tasks related to the process of analysis and the bottlenecks of starting the analysis after fieldwork. Classes will start with a short lecture and the presentation as well as the discussion of the assigned readings. The second half of the class will be based on the discussion of the student tasks in terms of the organization and analysis of their ethnographical material.