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Discover ECPR's Latest Methods Course Offerings

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Qualitative Data Analysis

Member rate £492.50
Non-Member rate £985.00

Save £45 Loyalty discount applied automatically*
Save 5% on each additional course booked

*If you attended our Methods School in July/August 2023 or February 2024.

Course Dates and Times

Date: Monday 22 – Friday 26 July 2024
Time: 8:30 – 11:30 CEST

Marie-Hélène Paré

This online course offers you 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

3 ECTS credits awarded for engaging fully in class activities.
1 additional ECTS credit awarded for completing a post-course assignment.

Courses from the Instructor

Instructor Bio

Marie-Hélène is a highly regarded methodologist who has NVivo Certified Platinum Trainer status. She has shared her expertise in qualitative data analysis with over 60 universities and research centres around the world, including Qatar and Iran. Since 2009, Marie-Hélène has been teaching introductory and advanced courses in qualitative data analysis at the ECPR Methods School. Her areas of methodological interest include qualitative evidence synthesis, decolonising epistemology, and participatory methodologies. Marie-Hélène is dedicated to advancing the field of qualitative data analysis and sharing her knowledge with others.


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 present your analysis plan at the Masterclass on Friday (highly recommended!)

How the course will work online

The course includes a rich and diverse mix of online teaching techniques that includes elevator pitch, talk-to-text technique, study groups, debates and pre-recordings. The daily three-hour live session in Zoom are intertwined with hands-on exercises and group work, during which you will work on your own research and have the opportunity to troubleshoot any issue you may have with regard to the analysis of your data, or data analysis generally.

The instructor will also conduct live Q&A sessions for one-to-one consultations.

Prerequisite Knowledge

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. 

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.

Learning commitment

As a participant in this course, you will engage in a variety of learning activities designed to deepen your understanding and mastery of the subject matter. While the cornerstone of your learning experience will be the daily live teaching sessions, which total three hours each day across the five days of the course, your learning commitment extends beyond these sessions.

Upon payment and registration for the course, you will gain access to our Learning Management System (LMS) approximately two weeks before the course start date. Here, you will have access to course materials such as pre-course readings. The time commitment required to familiarise yourself with the content and complete any pre-course tasks is estimated to be approximately 20 hours per week leading up to the start date.

During the course week, you are expected to dedicate approximately two-three hours per day to prepare and work on assignments.

Each course offers the opportunity to be awarded three ECTS credits. Should you wish to earn a 4th credit, you will need to complete a post-course assignment, which will involve approximately 25 hours of work.

This comprehensive approach ensures that you not only attend the live sessions but also engage deeply with the course material, participate actively, and complete assessments to solidify your learning.


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.