Number of sessions: 4
Hours per session: 3
This course is best suited for PhD candidates who:
- Have already collected or are about to collect data for their PhD project.
- Are not familiar with the methodology and method of coding and analysing qualitative data, and reporting the results of QDA.
In the academic year 2020-2021 this course will take place online.
October 29 (Thursday) 2020
November 5 (Thursday) 2020
November 12 (Thursday) 2020
November 26 (Thursday) 2020
March 2 (Tuesday) 2021
March 9 (Tuesday) 2021
March 16 (Tuesday) 2021
March 30 (Tuesday) 2021
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 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.
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 analysing qualitative data and reporting the results of QDA.
Please note that 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.
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 with ATLAS.ti and/or consult check out the many online ATLAS.ti tutorials.
After this course you will be able to:
- understand the methodology of QDA, particularly the Grounded Theory approach;
- code your qualitative material, using ATLAS.ti
- understand how to analyze your coded material;
- make informed decisions about how to report a QDA-based study;
- and all of the above with regard to your own research and data.
Session 1: Methodologies and background of QDA
- The first session focusses on the methodology of QDA, particularly with regard to Grounded Theory.
- We will also discuss the differences and similarities between Grounded Theory and other approaches to QDA.
Session 2: Coding and analysing qualitative data
- Session 2 focuses on the methods of QDA. After discussing the main techniques for coding and analysis, you will do concrete exercises with applying those techniques in Atlas.ti, preferably on your own qualitative data. To this purpose:
- Bring your laptop
- Download and install Atlas.ti 8 (Windows version) on your own laptop. Erasmus University has a license for Atlas.ti.
- Installation instruction: https://my.eur.nl/en/eur-employee/ict/software/download-software-licences/atlasti
- Please do this well in advance and notify the course instructor if there are any problems.
Session 3: Quality criteria and examples of QDA
- You will present a short critical evaluation of a published qualitative analysis in your discipline.
- Through your evaluations we will explore the varieties of QDA and quality criteria such as validity, reliability and accuracy of coding and analysis.
Session 4: Writing about your own QDA
- In this session we will evaluate your own report based on the analysis that you have started to conduct in session 2.
- This report will be written as the 'method' and 'results' sections of a research paper. Participants will peer-review each other’s work and identify issues for further discussion.
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.