240550 SE MM7 Research Design Workshop (2026S)
Continuous assessment of course work
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Summary
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 02.02.2026 17:00 to Mo 23.02.2026 23:59
- Deregistration possible until Mo 16.03.2026 23:59
Registration information is available for each group.
Groups
Group 1
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.
max. 25 participants
Language: English
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
- Wednesday 18.03. 09:45 - 13:00 Seminarraum A, NIG 4. Stock
- Thursday 26.03. 09:45 - 13:00 Hörsaal C, NIG 4. Stock
- Monday 20.04. 13:15 - 16:30 Übungsraum (A414) NIG 4. Stock
- Wednesday 29.04. 09:45 - 13:00 Seminarraum A, NIG 4. Stock
- N Wednesday 20.05. 11:30 - 14:45 Sitzungs-/Prüfungszimmer, NIG 4. Stock
- Wednesday 27.05. 09:45 - 13:00 Sitzungs-/Prüfungszimmer, NIG 4. Stock
Aims, contents and method of the course
Assessment and permitted materials
Your grade will be determined by the following elements:
The initial analysis of the MA data (especially coding) 40% (or 40 points max)
Presentation of initial organization of the data 20% (or 20 points max)
Commentary on peers’ work 10% (or 20 points max)
Presentation of anticipated results 30% (or 30 points max)
For the completion of the written task every means can be used with the exception of Artificial Intelligence tools such as CHatGPT.
The initial analysis of the MA data (especially coding) 40% (or 40 points max)
Presentation of initial organization of the data 20% (or 20 points max)
Commentary on peers’ work 10% (or 20 points max)
Presentation of anticipated results 30% (or 30 points max)
For the completion of the written task every means can be used with the exception of Artificial Intelligence tools such as CHatGPT.
Minimum requirements and assessment criteria
Requirements:
1) Regular attendance and active participation
2) Development and presentation of the tasks related to their own project
3) Commenting on other participants' research project
4) Draft of an initial analysis of their field materialTo pass the course students must reach at least 60 points with all components being completed in a positive way.
91-100 points: 1 (excellent)
81-90 points: 2 (good)
71-80 points: 3 (satisfactory)
60-70 points: 4 (sufficient)
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
1) Regular attendance and active participation
2) Development and presentation of the tasks related to their own project
3) Commenting on other participants' research project
4) Draft of an initial analysis of their field materialTo pass the course students must reach at least 60 points with all components being completed in a positive way.
91-100 points: 1 (excellent)
81-90 points: 2 (good)
71-80 points: 3 (satisfactory)
60-70 points: 4 (sufficient)
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
Examination topics
Students work mainly with their own data from their previous fieldwork. In addition, critical discussions of your peers’ assignments are a necessary ingredient for successful completion of the course. There are no exams for this course.
Reading list
TBA
Group 2
Anwesenheitspflicht in der ersten Einheit!Die Lehrveranstaltungsleitung kann Studierende zu einem notenrelevanten Gespräch über erbrachte Teilleistungen einladen.
Plagiierte oder erschlichene Teilleistungen führen zur Nichtbewertung der Lehrveranstaltung (Eintragung eines 'X' im Sammelzeugnis). Es kommt die Plagiatssoftware Turnitin zum Einsatz.
Die Verwendung von KI-Tools (z. B. ChatGPT) zur Erbringung von Teilleistungen ist nur dann erlaubt, wenn dies von der Lehrveranstaltungsleitung ausdrücklich gefordert wird.
Plagiierte oder erschlichene Teilleistungen führen zur Nichtbewertung der Lehrveranstaltung (Eintragung eines 'X' im Sammelzeugnis). Es kommt die Plagiatssoftware Turnitin zum Einsatz.
Die Verwendung von KI-Tools (z. B. ChatGPT) zur Erbringung von Teilleistungen ist nur dann erlaubt, wenn dies von der Lehrveranstaltungsleitung ausdrücklich gefordert wird.
max. 25 participants
Language: German
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
- Monday 02.03. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
- Monday 09.03. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
- Monday 16.03. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
- Monday 23.03. 11:30 - 13:00 Hörsaal A, NIG 4.Stock
- Monday 13.04. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
- Monday 20.04. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
- Monday 27.04. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
- Monday 04.05. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
- Monday 11.05. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
- N Monday 18.05. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
- Monday 01.06. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
- Monday 08.06. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
- Monday 15.06. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
- Monday 22.06. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
- Monday 29.06. 11:30 - 13:00 Seminarraum A, NIG 4. Stock
Aims, contents and method of the course
This course is for students after completing their fieldwork for the MA thesis.
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.
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.
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 lecturer 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 lecturer 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
Hammersley, Martyn and Paul Atkinson (1983) The Process of Analysis. In: Hammersley and Atkinson, Ethnography: Principles and Practice. London: Routledge
Emerson, R.M., R. I Fretz, and L. L. Shaw (2001 [1995]) Ethnographic Fieldnotes. Ch 1, pp: 1-21.
Flick, Uwe (2009) An Introduction to Qualitative Research, pp: 147-210 (verbal data). 4th ed. London: Sage.
Emerson, R.M., R. I Fretz, and L. L. Shaw (2001 [1995]) Ethnographic Fieldnotes. Ch 1, pp: 1-21.
Flick, Uwe (2009) An Introduction to Qualitative Research, pp: 147-210 (verbal data). 4th ed. London: Sage.
Association in the course directory
Last modified: Fr 27.03.2026 09:27
The main goal of the seminar is to accompany each student who has already conducted fieldwork in organizing their fieldwork material and the in initial process of its analysis for their MA thesis. The course will focus on the initial stages of the research design of their 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 critical commentary to their peers’ assignments. Critical discussions of your peers' assignments are a necessary ingredient for successful completion.
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 ethics, especially in dealing with the collected data.
Structure: This 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 data.