Qualitative data analysis with Grounded Theory

Introduction

Key terms: Qualitative research, Grounded Theory, inductive data analysis, ATLAS.ti, introductory course, relevant for students in any PhD phase.

ECTS: 2.5 
Number of sessions: 4
Hours per session: 3

This course offers an introduction to Grounded Theory, which is a methodology for qualitative analysis of diverse forms of data, such as interview transcripts and policy documents. 

Grounded Theory is an inductive approach, which means that it facilitates developing theory through bottom-up exploration of data. 

Grounded Theory has several advantages for qualitative research. On a practical level, it offers a procedure for data coding and analysis. From a strategic and theoretical standpoint, it serves as a comprehensive research framework.

While the course focuses on Grounded Theory, we will also take a brief look at other approaches to qualitative data analysis, such as Discourse Analysis and Phenomenology.

Please note that this is not an ATLAS.ti course. However, the course does offer a first training in using the program.

You can participate in the course even if you have not yet gathered data for your own research. In that case, the lecturer can supply sample data for you to practice with.

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. Make sure you can invest this time before you enrol in the course.

Entry level and relevance

The course is relevant for people from any research discipline who need a methodological framework for qualitative data analysis.

The course can be useful for students in any phase of their PhD project. No prior knowledge or experience is required for attending the course.

Relations with other courses

Please note that this course includes a condensed version of the ATLAS.ti practicum that is offered in the EGSH course Qualitative coding and analysis of textual data with ATLAS.ti. Both courses rely on the same video tutorial.

If you already followed the ATLAS.ti course, you can attend this course to learn more about the broader Grounded Theory methodology.

Reversely, after this course, you can attend the ATLAS.ti course for a more thorough explanation of how the program can be used for qualitative coding and analysis.

Sessions and preparations

Session 1: Methodology and context
In the first session we will discuss the methodology of Grounded Theory, and the academic context in which Grounded Theory and inductive research generally emerged.
Preparations comprise reading literature about Grounded Theory and qualitative data analysis in general.

Session 2: Coding and analysing 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.
Preparations: before the session begins participants need to install ATLAS.ti (version 22 or newer) and prepare all materials needed for exercises with the program during the class meeting, as well as read some literature about the qualitative coding and analysis process.

Session 3: Quality criteria and examples of Grounded Theory
In the third session we will explore variations in qualitative data analysis (specifically in Grounded Theory) and quality criteria. 
Preparations: course participants are expected to prepare a brief presentation in which they critically evaluate published literature that is based on Grounded Theory.

Session 4: Doing the write-up
For the last session, participants will prepare a brief report of their own qualitative data analysis using ATLAS.ti. This report resembles a concise version of the method and results sections of a typical research paper.
By making the report participants will have an early opportunity to discover what it means in practice to conduct qualitative data analysis.
During session 4 participants will give each other feedback on their reports. Afterwards the lecturer will also send his feedback.
Preparations: course participants are expected to prepare a brief report of their own qualitative data analysis using ATLAS.ti.