MAT-50806 Qualitative Data Analysis Methods


Credits 6.00

Teaching methodContact hours
Individual Paper2
Group work4
Independent study0
Course coordinator(s)dr. PA Tamas
Lecturer(s)dr. PA Tamas
Examiner(s)dr. H Tobi
dr. PA Tamas

Language of instruction:


Assumed knowledge on:

Research design (YSS-20306 / YRM-20306 or disciplinary equivalent)

Continuation courses:

Major thesis, minor thesis.


This advanced course is for students in any program who must analyze qualitative data either to prepare more quantitative data collection methods (e.g. surveys) or to draw qualitative conclusions directly. Most MSc students, 2/3 of the class, have historically come from the MME, MID, MDR and MCH. The remaining students are PhDs from chair-groups mostly within WASS. The course covers content analysis, metaphor analysis, domain analysis, membership categorization analysis, conversation analysis, semiotics, visual data and discourse analysis.

Learning outcomes:

After successful completion of this course students are expected to be able to:
- understand the characteristics of qualitative data and analysis techniques;
- understand what sorts of data each method requires;
- understand what sorts of conclusions each method supports;
- understand the validity of the conclusions produced by each method;
- select an (or combination of) analysis methods appropriate for a research question;
- estimate the level of effort required for execution of that analysis;
- use those techniques using ATLAS.ti software;
- reflect critically upon the use and interpretation of the discussed methods.


Short lectures, tutorials, group work, papers and computer practicals.


The final grade is based on your paper (25%), group assignment (35%), and written exam (40%). To pass this course, you need to have a grade of at least 5.5 on two of the three parts above, and no part can receive less than a 5.0.


Links to resources will be provided by the lecturer.