HD, IJ, WP, GPH, GED
A completed 100-level in the Human Diversity Major and (Introduction to) Statistics.
This course introduces students to the features of qualitative research methods prevalent in social sciences such as anthropology, human geography, gender studies, and sociology. Qualitative methods allow researchers to use a structured process that empirically addresses conceptual questions. Students in this course will understand how methods relate to social science inquiry, and are an essential component of research design.
The course is designed as a hands-on sequence of conceptual reflection and empirical experimentation built around each student’s individual project. Students will conceptualize a social science topic in The Hague. Over the course duration, they will try out different qualitative methods in the field, assess their practical and ethical dimensions, and conducting post-fieldwork data analysis.
Learning this process enables a comprehensive and empirically grounded understanding of the social world we study. In the social sciences, qualitative methods may include: participant-observation in a specific community or organization; life-history narratives over decades with informants; and the convening of a focus group of individuals with shared social markers.
Students in this course will learn how to actually do qualitative research, to reflect on interpretive and ethical choices, and to understand how fieldwork variables condition data analysis. Qualitative methods discussed will include interviewing, mapping, and participant observation. This course will thus cover epistemological aspects of qualitative research, as well as the practicalities of design and implementation.
By the end of this course, the students will be able to:
Distinguish between qualitative and quantitative methods
Describe the ethical and epistemological dimensions of interpretive social science
Explain and assess various qualitative research methods
Operationalize research questions and determine if a qualitative approach is suitable for addressing particular topics
Reflect on the design and execution of a self-guided social science project.
Students will become acquainted with different methods of data collection, processing, and analysis within the interpretive social sciences. They will be able to make judgments regarding the reliability and pitfalls of various investigative approaches, and to assess the ethical and epistemological aspects of carrying out their own project.
Once available, timetables will be published in the e-Prospectus.
Mode of instruction
This course will consist of two-hour interactive seminars, and draw on both lectures and practical exercises. Guided by the instructor, interactive, hands-on, and reflective activities will be implemented to highlight the course material. Practical exercises will touch on participant observation, interviewing, and mapping material culture. The seminars will help students to recognize and apply qualitative research methods.
Students will, in the spirit of a practical methods course, individually engage in a fieldwork project in The Hague that will be analysed for their final essay and distilled into a podcast. This will involve using qualitative methods that enable students to think as researchers.
Group participation (on-going from week 1 to 7): 20%
Five assignments: a) brainstorming exercise; b) ethnographic reflection; c) mapping reflection; d) observation exercise; e) interview coding (from week 2 to week 7) 5 × 10% = 50%
Final essay & podcast on individual research projects (in week 8): 30 %
There will be a Blackboard site available for this course. Students will be enrolled at least one week before the start of classes.
The Blackboard site of the course will give course readings, updates, guidelines, and enable the submission of student assignments.
This course is open to LUC students and LUC exchange students. Registration is coordinated by the Education Coordinator. Interested non-LUC students should contact email@example.com.
Block 2: Dr. Ajay Gandhi (firstname.lastname@example.org)
Block 3: Marten Boekelo