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Qualitative data analysis (QDA) is a generic term for methods and techniques that are used for drawing conclusions from qualitative data, such as written text, (transcriptions of) open interviews, and visual material.
The course focuses on Grounded Theory as a dominant approach to QDA, but other approaches (particularly discourse analysis and semiotics) will also be discussed.
There are four sessions of workshops with mini-lectures and practical, participatory training exercises. Scroll down for a detailed breakdown of the course sessions. Participants will be informed well in advance on how to prepare for the sessions.
This course is best suited for PhD candidates that have already collected or are about to collect data for their PhD project, and that are not familiar with the methodology and method of coding and analyzing qualitative data and reporting the results of QDA.
Learning objectives After this course you will be able to: