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Qualitative Data Analysis (week three)

Course Dates and Times

Monday 10 ꟷ Friday 14 August 2020
2 hours of live teaching per day
Courses will be either morning or afternoon to suit participants’ requirements

This seminar-type course provides a highly interactive online teaching and learning environment, using state of the art online pedagogical tools. It is designed specifically for a demanding audience (researchers, professional analysts, advanced students) and is capped at a maximum of 12 participants so that the Instructor can cater to the specific needs of each individual participant.

Purpose of the course

This course teaches you strategic understanding and applied skills in planning, conducting, and reporting the process of qualitative data analysis (QDA) in one’s research. The course combines theory, applied exercises and demos in NVivo.

ECTS Credits

3 credits Engage fully with class activities 
4 credits Complete a post-class assignment

Instructor Bio

Are you planning to conduct interviews or focus groups for your data collection, or perhaps collect policy papers or social media data from blogs, Facebook or Twitter?

If you do any of the above, you will soon or later have to confront and analyse your compiled data.

But will you know how? 

This course will give you a strategic understanding of, and applied skills in, planning, conducting and reporting qualitative data analysis. It addresses central issues often omitted in mainstream qualitative textbooks, such as: 

  • What criteria to use in choosing a method of QDA? 
  • How central is the research question in that choice? 
  • What to do after the data are coded? 
  • How to seek patterns and relationships when working inductively or deductively? 
  • How should I present my findings? Using quotes or visualisations?

In learning the foundational concepts underlying the process of QDA, you will become cognizant of:

  • the influence that epistemology and research design has on choosing a QDA method
  • what approaches to use for coding one's data and the criteria to select the right coding unit, efficiently managing a coding scheme, developing meaningful categories and memo-ing the coding process judiciously
  • the strategies to transform qualitative data into findings, and the nuts and bolts of retrieval procedures to make the analysis process efficient and transparent
  • the debates surrounding the quality of qualitative research and the techniques to confirm the trustworthiness of qualitative results
  • the best and worst practices when presenting qualitative findings and how generate visual displays that tell the story of the findings effectively 
  • appraising the quality of the reporting of qualitative analysis in published studies.

The course, which uses NVivo, explores these topics and more and puts them into practice in hands-on sessions. You are encouraged to use NVivo, or another qualitative software of your choice, provided you are adept in its use.

How the course will work online

The course combines pre-course tasks, such as readings which will be provided beforehand and pre-recorded videos, as well as live lectures, where the Instructor and participants will interact in real-time.

Apps that support online learning management systems (LMS) such as Google Docs, Slack and Asana, also feature in the course's pedagogy.

This course assumes no previous knowledge of qualitative data analysis or NVivo, but requires basic understanding of qualitative research. Only the basic features of NVivo will be taught.

Each course includes pre-course assignments, including readings and pre-recorded videos, as well as daily live lectures totalling at least three hours. The instructor will conduct live Q&A sessions and offer designated office hours for one-to-one consultations.

Please check your course format before registering.

Online courses

Live classes will be held daily for three hours on a video meeting platform, allowing you to interact with both the instructor and other participants in real-time. To avoid online fatigue, the course employs a pedagogy that includes small-group work, short and focused tasks, as well as troubleshooting exercises that utilise a variety of online applications to facilitate collaboration and engagement with the course content.

In-person courses

In-person courses will consist of daily three-hour classroom sessions, featuring a range of interactive in-class activities including short lectures, peer feedback, group exercises, and presentations.


This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc.). Registered participants will be informed at the time of change.

By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, please contact us before registering.