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Qualitative data analysis (QDA) is a generic term for methods and techniques that are used to assess different forms of qualitative data, such as written text, (transcriptions of) open interviews, and visual material.
This course focuses on Grounded Theory as one of the dominant approaches to QDA, but it will also give you an impression of the broader field of QDA and the divergent ways and terminologies there are for doing QDA, particularly with regard to Discourse Analysis and Phenomenology.
The course focuses on “inductive” ways of analysing data (meaning: forming theory based on data exploration), which is the standard in QDA. The course does not deal with “deductive” approaches, which focus on testing theory-based hypotheses on data.
Note that this is not an ATLAS.ti course. However, the course introduces the program’s basic functionalities for QDA and offers a first training in using the program. To further develop your ATLAS.ti skills you can attend the course Qualitative coding and analysis of textual data with ATLAS.ti and/or consult the many online ATLAS.ti tutorials.
Before enrolling please inform yourself about the course contents, aims and planning as described below. The course is credited with 2.5 ECTS, which stands for 70 study hours. Note that 25 of these 70 hours are assigned to making a report for session 4. Please find above more information about the planning of the different sessions.
The course is designed as an introduction to QDA and Grounded Theory. This means that it is made accessible to researchers who are not familiar with the methodology and methods of coding and analyzing qualitative data and with reporting the results of QDA.
After completing the course participants will:
- understand the methodology of QDA, particularly with regard to the Grounded Theory approach;
- be able to code qualitative material with the help of the program ATLAS.ti;
- understand how to analyze coded data;
- be able to make informed decisions about how to report a QDA-based study.
Session 1: Methodology and context
In the first session we will discuss the methodology of QDA, especially with regard to Grounded Theory, and the academic context in which Grounded Theory and inductive research generally emerged.
Session 2: Coding and analyzing qualitative data
Session 2 focuses on the main techniques for qualitative data coding and analysis. We will do concrete exercises with applying those techniques in ATLAS.ti, preferably with your own data.
Session 3: Quality criteria and examples of QDA
In the third session we will explore variations in QDA (in Grounded Theory in particular) and quality criteria such as validity, reliability and accuracy of qualitative coding and analysis. We will do this on the basis of brief critical evaluations of published literature by the participants.
Session 4: Doing the write-up
For session 4 each participant will make a brief report (of approximately 1500 words) of his or her own qualitative data analysis in ATLAS.ti. This report resembles a concise version of the method and results sections of a typical research paper. By making this report and doing the underlying analyses participants will have an early opportunity to really discover what QDA (with Grounded Theory in particular) means in practice. During session 4 participants will give each other feedback on their report.
You can make the report on the basis of your own data or, if you don't have data of your own yet, data that will be given to you by the lecturer.
Participants generally require approximately 20-25 hours to make the report. This work starts right after session 2 until the deadline of handing in the report, which is about 3 days before session 4.
Dr. Fadi Hirzalla is the Graduate School senior lecturer and methodology consultant. He specialises in quantitative and qualitative methods and methodology, next to his substantive interests in citizenship and new media, with a particular focus on intercultural relations and young people. Prior to joining the Graduate School, he worked at the University of Amsterdam and Utrecht University.