Advanced Qualitative Research Design and Data Collection (GEO-56806) - 6 ECTS
This course deals with qualitative social science research design and data collection. Students learn about and practice key qualitative methods while gaining exposure to how diverse theoretical lenses make use of these methods.
dr.ir. CPG (Clemens) Driessenassistant professor
R (Robert) Fletcher PhDUniversitair hoofddocent
dr. SP (Stasja) KootAssistant professor
dr. R (Rico) LieAssistant Professor
dr. ME (Meghann) OrmondAssociate Professor
dr. ED (Elisabet) RaschAssociate Professor
PA (Peter) TamasLecturer, Research Methodology
AGM (Anke) de Vrieze MScBeleidsmedewerker
dr. C (Chizu) SatoDocent
Advanced Qualitative Research Design and Data Collection (GEO 56806) offers PhD candidates and advanced master’s students enrolled in the graduate programme:
- A fuller grasp of the analytical value of arange of qualitative methods relative to yourown project's research questions and epistemological/theoretical positioning;
- The knowledge required to identify different methods’ particular logistical requirements and challenges;
- The knowledge and skills for anticipating and responding to ethical issues posed by the use of specific methods;
- The time and space to design a well-rounded strategy for data collection for your own research project aligned with your project's purpose and epistemological/theoreticalframework.
- Compulsory sessions in Weeks 1 & 4 enable students to critically investigate the values and forces underpinning their research projects, reflect on their researcher positionality and render their research project design more nuanced and robust.
- Free-choice sessions in Weeks 2 & 3 cover a range of qualitative data collection methods and techniques (see list below). Students write their assignments based on (a minimum of) 4 free-choice sessions that best fit with the research they are undertaking or wish to undertake.
Topics and methods covered
- Research as a formal system and the role of data in it (C1)
- Researcher positionality and reflexivity (C2)
- Ethnography and participant observation (FC 1)
- Data collection for discourse analysis (FC 2)
- Interviewing (FC 3)
- Participatory and co-creation methods (FC 4)
- Revisiting ontology with actor-network approaches (FC 5)
- Visual research methods (FC 6)
- Using the other senses in data collection (FC 7)
- Connecting the course content to practice x 2 (C3-4)
(C = Compulsory session; FC = Free choice session)
Assumed knowledge on:
Qualitative Data Analysis (YRM-60806) PLUS EITHER Critical Perspectives on Social Theory (PhD course) OR Advanced Social Theory (CPT-55306) OR WASS Research Methodology: From Topic to Proposal (PhD course)
Students learn about & practice key qualitative methods while gaining exposure to how diverse theoretical lenses make use of these methods. The course covers: interpretation, representation, comparison & validity; reflexivity & positionality, power relations & ethics; interviews & focus groups; (auto)ethnography & participant observation; revisiting ontology with actor-network approaches; techniques for capturing discourses; techniques for identifying proxies & using secondary sources; visual research methods.
After successful completion of this course students are expected to be able to:
- assess the analytical value of different types of methods relative to the student’s own research questions and theoretical framework;
- identify different types of methods’ particular logistical requirements and challenges;
- anticipate ethical issues posed by the use of specific research methods;
- design a data collection methods strategy aligned with the student’s own research questions and theoretical framework.
Workshops with lectures & interactive learning;
- exercises to practice specific methods & reflect on their effects;
- development of an individualised data collection methods strategy;
Each component must be marked with a 5.5 or higher:
- portfolio of peer-reviewed written post-session reflections (75%);
- individualised data collection methods strategy (25%).