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Qualitative Data Analysis

Course Dates and Times

Monday 31 July – Friday 4 August 2023
Minimum 2 hours of live teaching per day
08:30 ꟷ 10:30 CEST

Marie-Hélène Paré

info@mariehelenepare.com

The Qualitative Analyst

This online course offers a dynamic and interactive learning experience, utilising advanced pedagogical tools. It is tailored to a challenging audience of researchers, analysts, and advanced students, with a maximum of 16 participants to allow for personalised attention from the instructor.

Purpose of the course

This course teaches a solid foundation and applied skills in qualitative data analysis. You will learn to:

  • develop your research design according to your epistemology
  • choose the right method of analysis for your study
  • code your data using the appropriate approach 
  • explore techniques to transform qualitative data into findings
  • apply key rules (and avoid pitfalls) to present qualitative results convincingly
  • create a solid audit trail of your analysis process.

Blending theory and practice, you will use NVivo software for the hands-on exercises. This course is a good introduction for Advanced Qualitative Data Analysis. 

ECTS Credits

4 credits - Engage fully in class activities and complete a post-class assignment


Instructor Bio

Marie-Hélène teaches qualitative research methods at the Open University of Catalonia (UOC) and is a freelance methodologist in qualitative data analysis. She was educated in Quebec, Beirut and Oxford where she read social work. A clinician by training, she worked as a mental health officer in humanitarian missions for MSF, MDM and UNWRA in psychosocial aid programs for survivors of war trauma in East Africa and the Middle East. Her clinical work led her to research the harm that INGOs can do in the name of doing good when imposing Western paradigms in culturally and politically different contexts.

Marie-Hélène is an NVivo Certified Platinum Trainer and is a member of the NVivo Core Trainer Team who teaches the NVivo online courses. She is a sought-after methodologist who has taught qualitative data analysis in more than sixty universities and research centres worldwide, in countries including Qatar and Iran. Since 2009, Marie-Hélène has taught the introductory and advanced courses in qualitative data analysis at the ECPR Methods School and teaches similar courses at the IPSA-NUS Summer School in Singapore. Her methodological interests range from advances in qualitative data analysis, qualitative evidence synthesis, decolonising epistemology and participatory methodologies. Read more about Marie-Hélène.

@TheQualAnalyst

Key topics covered

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? After you complete your data collection, you will sooner or later have to confront the mass of data you gathered and analyse your material.

But will you know how?

This course provides strategic understanding of, and applied skills in, planning, conducting and reporting qualitative data analysis in one’s research. You will learn the key concepts that underlie the process of qualitative analysis, which often go missing in qualitative research seminars, and are rarely discussed in mainstream qualitative methods textbooks, such as:

  • What influence does my ontology have on the method of analysis of my study?
  • Can induction, deduction or abduction be combined when analysing qualitative data, or are they mutually exclusive?
  • What does qualitative analysis actually involve? How is it done?
  • After I code my data and identify broad themes, what should I do?
  • Should I use quotes to illustrate my findings or visualisations like models, tables, matrices or charts?
  • What should I include in the appendix so my work is judged valid, reliable and objective?

You will explore these topics and more and get to put them into practice during hands-on sessions using NVivo.

You'll be able to work on your own data, discuss your research design and, with help from the Teaching Assistant, troubleshoot problems with your analysis. You can also present your analysis plan at the Masterclass. 


How the course will work online

The course combines asynchronous pre-class assignments, such as readings and pre-recorded videos, as well as daily two-hour live sessions with Zoom. To prevent Zoom fatigue, the course pedagogy includes small-group work, short, focused tasks and troubleshooting exercises using a range of online apps that support collective work and engagement with the content.

A basic understanding of qualitative research is required, however, previous knowledge of qualitative data analysis or NVivo is not required. 

This course teaches only NVivo's basic features. For a comprehensive NVivo course, take our Introduction to NVivo course.

You must run the latest versions of NVivo (R1 or 14) to attend the course as earlier versions (10 or 12) have different interfaces and menus. If your institution does not provide you with an NVivo license, you can download the NVivo 14-day free trial. The trial is fully operational but can't be reinstalled on the same computer once expired.

Each course includes pre-course assignments, including readings and pre-recorded videos, as well as daily live lectures totalling at least two 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 two 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.


Disclaimer

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.