Learning outcomes

During the course, students will:
•    Develop an understanding of social constructionist epistemology and discursive research as a field of varied analytic, theoretical and practical approaches.
•    Do hands-on practical exercises in data sessions which welcome student data from everyday, interview, and institutional settings.
•    Discuss and develop their understanding of transcription, validity and transparency.
•    Learn how to use the data as evidence in their monograph, or article-size analyses.
•    Work in ways that directly feeds into their data analyses and the completion of their doctoral thesis.
•    Receive a list of relevant literature pertaining to DA.

Course description:
The term “discourse analysis” (DA) is best understood as an umbrella designation for an established and rapidly growing field of research covering a wide range of different theoretical approaches and analytic emphases. What discursive approaches in different disciplinary locations share, however, is a strong social constructionist epistemology - the idea of language as much more than a mere mirror of the world and phenomena ‘out-there’, and the conviction that discourse is of central importance in constructing the ideas, social processes, and phenomena that make up our social world.

This concise two-day course invites doctoral students working with video-or audio materials who wish to approach their data from and interactional/discourse analytic point of view. The course combines lectures with data sessions on the participants’ ongoing doctoral research projects and data. The lectures cover the key theoretical and analytical starting points of discourse analysis, questions of validity, quality and transparency of the analysis, and transcription practices.


Course Schedule:

Tuesday 7.3.2017

Place: Linna K110

09.15-10.00    Discourse analysis in the qualitative analytic tradition. Data sets, constructionist epistemology and methodological tools
10.00-12.00    The discursive PhD thesis: designing and specifying the research questions, managing and working with the data, and the logic of writing in the monograph and article thesis.
12.00-13.00    lunch
13.00-16.00    Specified mini-lectures, data sessions and comments on participants’ ongoing research projects

Wednesday 8.3.2017

Place: Linna K109

09.15-10.00    Theoretical and practical questions in transcription
10.00-12.00    Producing good quality and transparent analysis
12.00-13.00    lunch
13.00-16.00    Specified mini-lectures, data sessions and comments on participants’ ongoing research projects

Pre-assignment:
To participate in the course, please drop a short (MAX two page) pre-assignment through Moodle outlining the following:

1. Your name and discipline.
2. Your research topic, (preliminary) research questions & data.
3. A short yes/no indication as to whether you are willing to bring in your own data, or discuss your project in class.
4. A short definition of what you mean by discourse analysis (key theorists, texts, tools for analysis), and or a short description on how well acquainted you are with discourse analysis.
5. Any topics you wish to be discussed in class.


Course literature:

Before the course students are advised to read the texts below:
•    Nikander Pirjo (2008) Constructionism and Discourse Analysis. In Holstein, James, A. & Gubrium Jaber F. (Eds.) Handbook of Constructionist Research. Guilford Press, New York. Pp. 413-428.
•    Nikander Pirjo (2008) Working with Transcriptions and Translated Data. Qualitative Research in Psychology, Special issue on Teaching Qualitative Methods, 5: 3, 225-231.
•    Nikander, Pirjo (2012): Interviews as Discourse Data. Teoksessa Gubrium, Jay, Holstein, James, Mackinney-Marvasti, Karyn & Marvasti, Amir (toim.) Handbook of Interview Research. The Complexity of the Craft. 2nd Edition. London, Sage. Pp. 397-413.

Additional literature will be made available during the course.

Evaluation: pass/fail, students presenting data or presenting on their ongoing research process will receive 4 ECTS, others 3 ECTS. Students will submit a course diary through Moodle after the course.

Number of students: Max. 20. Selection method is draw.