AGDK14018U Thesis Data Collection
THE COURSE CAN BE 7.5 ECTS OR 15 ECTS.
Thesis data collection is an elective course that prepares students for carrying out their master´s thesis in the fourth semester. As part of the course students draft a synopsis for their thesis, and subsequently collect data for their research project. The data can be either primary data collected through fieldwork, survey, data mining; or they can be secondary data collected from archives, databanks, existing literature, etc. Fieldwork can take place in all kinds of socio-cultural contexts on the condition that it can be realistically carried out within the given time frame and that the safety of students is not at stake. Apart from this, the choice of data to be collected is limited by research ethics only.
Data collection can be carried out individually or in smaller groups of maximum 3 students.
During the data collection process, students write a portfolio. Students are assigned a supervisor before the course starts and receive 45 minutes supervision to prepare their synopsis + 45 minutes supervision to discuss research results and prepare the final report. In case the course is 15 ects, students receive an additional mid-term supervision session to follow up on eventual problems met during the data collection exercise. For each additional student, the supervision sessions are extended with 15 minutes. When doing fieldwork abroad, supervision from teacher is organized through netbased dialogue.
The duration of data collection is max 25 days per 7.5 ects.
The course can be 7.5 ECTS or 15 ECTS.
- demonstrate familiarity with relevant metods for collecting data and the types of knowledge that the chosen method produces
- demonstrate knowledge in analysing data relevant to provide answers to research questions.
- demonstrate thematic and regional knowledge relevant to a chosen research field
- write a problem statement and a research synopsis
- collect relevant empirical material
- evaluate the problem statement and research questions in relation to collected empirical material
- organize an empirical material properly with due consideration to relevant methodological and ethical issues
- reflect critically on the methological and analytical process of data collection
This “course” offers no lecture; it consists exclusively of an exercise of fieldwork or data collection with 2 supervision sessions for 7,5 ects, or 3 supervision sessions for 15 ects. The goal of the first supervision session is to discuss and finalize a realistic research plan/synopsis. The goal of the last supervision session is to assess the quantity and the quality of the data collected, and to agree on how to present them in the final report. The goal of the intermediate supervision session (for a course of 15 ects) is to follow up on the process of data gathering and address eventual challenges met while conducting fieldwork or collecting data. The details regarding the formats of the course, of the synopsis, and of the report are negotiated and agreed upon between each student and supervisor.
7.5 ECTS = 210 hours (fieldwork: 170 hours. Exam preparation: 40 hours)
15 ECTS = 420 hours (fieldwork: 340 hours. Exam preparation: 80 hours)
- Field Work
- Exam Preparation
- 7,5 ECTS
- Type of assessment
- PortfolioPortfolio containing a synopsis (research plan) and a final report describing the data collected. The deadline for the exam is at the end of the semester.
Individual or group submissions.
Contents of the portfolio:
a) maximum 3 pages Master’s Thesis synopsis
b) maximum 3 pages final report (7.5 ECTS) or maximum 7 pages final report (15 ECTS). The length remains the same regardless of the number of students writing together.
- All aids allowed
- Marking scale
- passed/not passed
- Censorship form
- No external censorship
1st re-exam: A new assignment must be submitted. The new assignment must be submitted by the deadline for the re-exam.
2nd re-exam: A new assignment must be submitted. The new assignment is submitted during the next exam period.
Criteria for exam assesment
See learning outcome.