Type of course

Admission requirements

Other applicants apply for the right to study by June 1st for courses that are taught in the fall semester and December 1st for courses that are taught in the spring semester. Application is sent through SøknadsWeb. Please use the appliction code "9301 - Singular courses at the PhD level". If granted admission to the course students must register for class and exam in Studentweb by September 1st for autumn semester and February 1st for spring semester.

PhD students and students at the Student Research Programme, or holders of a Norwegian master´s degree of five years or 3+2 years (or equivalent) may be admitted.

External PhD students and students at other Student Research programmes, must upload a document from their university stating that they are registered students.

Participants are assumed to have basic skills in qualitative methodology; theory of science, research design and research ethics. We recommend students to start with or fulfil HEL-8040 (or an equivalent course) before taking this course.

The course will be held only with a minimum of 6 participants.

Course content

The course will provide in-depth knowledge of various approaches to qualitative data analysis and their connection to theoretical perspectives and methodology. It is a specialised and advanced course relevant for students in medicine, health sciences and social sciences. The course is relevant for those who work with qualitative or mixed methods, and others who want to obtain these qualifications.

The course is about how to perform data analysis in qualitative research. Students will obtain knowledge, skills and competence that enable them to judge, select, design and perform qualitative analyses of a wide range of qualitative data based on sound and consistent methodologies. Methodologies include epistemological perspectives, theoretical framing, analytical strategies and modes of interpretation. The phase of data-analysis is the main component, but the course also entails training in critically evaluating qualitative research, how to write up results, and how to write for international journals.

We will also cover how to carry out qualitative data analysis with computer software for qualitative research involving text-based or multimedia data (ie. NVivo).

Recommended prerequisites

Objectives of the course

Knowledge:

• Differentiate and judge different analytical strategies for analysing qualitative data with qualitative methodologies
• Reflect on the role of theory in qualitative research
• Reflect on the epistemological foundation of different analytical methodologies, and what kind of knowledge qualitative data does and does not provide
• Reflect on how the context of data collection might have influenced the results

Skills: After the course, the student is expected to be able to

• select the most appropriate methodology for analysing qualitative data through qualitative interpretation
• judge the validity and reliability of different analytical strategies to different kinds of empirical data sources
• interpret qualitative data based on a sound and coherent qualitative methodology and sound arguments
• create a robust framework of concepts, theories and perspectives for qualitative research
• integrate theoretical reflections while analysing empirical data
• generate theory from empirical data through qualitative analysis
• design an effective workflow and carry out a software-assisted qualitative and quantitative analysis of qualitative data
• critically judge research based on qualitative data and methods
• carry out a theory-based qualitative analysis of qualitative data to present the research results, and integrate the findings in a theoretical framework and
• to integrate micro, meso and macro - perspectives in theoretically informed analysis
• to perform a qualitative data analysis based on sound analytical skills, scientific strength, academic maturity and critical thinking

Competence: After the course, the student is expected to be able to

• judge the appropriateness of different interpretive methodologies for different research questions
• determine the relevance of qualitative analysis methods, and judge the scientific quality of data material and research question
• deconstruct one’s biases, and reflect on how they may influence the analysis
• identify and reflect on ethical significant issues concerning analysis and dissemination of qualitative data

Language of instruction and examination

Teaching methods

The course will run through six days, divided into two workshops during one semester. Both workshops contain didactic teaching through lectures, group-working sessions, and interactive discussion and feedback. Individual reading toward knowledge assimilation is a requirement. It includes pree-course work in the form of reading the literature connected to the course.

There will be a mixture of teacher-led and student-led activities throughout each day of the course. Students will be expected to take an active and dynamic part of all coursework. We encourage students to put their knowledge into practice through group sessions that aim to improve practical skills and general competence.

Lectures and group-sessions will cover interpretations of various kinds of qualitative data sources, such as interview data collected solo or in groups; experiential autobiographical texts and images; observational data and dialogical conversation-data from naturally occurring situations. We cover theories, perspectives and methods from a wide range of research traditions.

Recommended reading/syllabus