Doing Thematic Analysis: A two-day mini-intensive introduction (2 ECTS)

Learning outcomes:
At the end of the teaching sessions, the students have a deep understanding of the potential (and limitations) of thematic analysis, and what doing thematic analysis looks like in practice. Due to the nature of qualitative analysis, not every aspect is covered in depth, but the students gain foundational skills related to coding and starting theme development, that set them on the path for doing rigorous and theoretically/methodologically coherent analysis.

Course description:
Thematic analysis (TA) is a now-widely-used qualitative data analysis method. It is one of a cluster of methods that focus on identifying, and interpreting, patterned-meaning across a dataset. The method is highly popular across the social, behavioural, health, and clinical sciences, as well as in other areas such as education, and even marketing and computing.

Various versions of thematic analysis exist, some bound to particular epistemological, ontological and methodological assumptions and practices; others freer to be applied in diverse ways. The version of TA developed by Victoria Clarke and myself exemplifies the latter: it offers a method, not a methodology. It offers a framework for the analysis of data, but does not pre-specify the interpretative or theoretical bases of the analysis.  Researchers need to interpret the meanings they identify through thematic analysis within frameworks they themselves specify. This means thematic analysis can address a very wide range of research questions, from quite essentialist or realist ones, through to more critical or constructionist ones.  

What this course offers:
This course is designed to give a theoretically-informed, hands-on introduction to the doing of thematic analysis, according to the approach developed by AP Victoria Clarke and Prof Virginia Braun. The teaching combines a range of pedagogical styles and activities, from mini-lectures through classroom discussion, small-group and individual class-time activity, and homework. Students are expected to actively engage in the classroom discussion and activities, and do the preparatory work.

Teacher: Professor Virginia Braun, School of Psychology, University of Auckland, New Zealand

Course structure & assessment

12.10.2017 at 9-16

Getting started on TA – focuses on:
•    introducing and locating thematic analysis
•    exploring and understanding key concepts
•    dataset familiarisation
•    understanding and starting coding
Day 1 also includes ‘take home’ work as preparation for Day 2

13.10.2017 at 9-16

Developing your analysis – focuses on:
•    developing coding
•    coding rigour and quality
•    theme development and exploration
•    theme/data interpretation.

Assessment
The course is assessed pass/fail, with participation in expected tasks and discussion, as well as demonstration of developing understanding, and application of concepts, key to passing.  

Place:

12.10. at 9-16, Room 3110 (at 9-13), Room 3111 (at 13-16) (Pinni B building)

13.10. at 9-16, Room 3110 (Pinni B building)

Enrolment in Nettiopsu. 25 students at the maximum. Selection method is draw. Students should check the enrolment result from Nettiopsu after the enrolment period.

Course background reading:
Braun, Virginia & Clarke, Victoria (2006) Using thematic analysis in psychology. Qualitative Research in Psychology 3:2, 77–101.