Install the app

Install this application on your home screen for quick and easy access when you’re on the go.

Just tap Share then “Add to Home Screen”


Install the app

Install this application on your home screen for quick and easy access when you’re on the go.

Just tap Share then “Add to Home Screen”

Your subscription could not be saved. Please try again.
Your subscription to the ECPR Methods School offers and updates newsletter has been successful.

Discover ECPR's Latest Methods Course Offerings

We use Brevo as our email marketing platform. By clicking below to submit this form, you acknowledge that the information you provided will be transferred to Brevo for processing in accordance with their terms of use.


Introduction to NVivo

Course Dates and Times

Friday 10 – Saturday 11 February 2023
Minimum 5 hours of live teaching per day
09:30 – 12:00 and 13:00 - 15:30 CET

Marie-Hélène Paré

The Qualitative Analyst

This course provides a highly interactive blended learning environment, using state-of-the-art online and in-person pedagogical tools. Prior to the live course, you will have access to online videos and tools to help us go deeper into the material during our live sessions. The course is designed for a demanding audience (researchers, professional analysts, advanced students) and capped at a maximum of 16 participants so that the teaching team can cater to the specific needs of each individual.

Purpose of the course

This course teaches the basic and advanced features of NVivo for qualitative data analysis. You will learn to:

  • set up an NVivo project
  • organise data
  • manage your literature review
  • code data by themes 
  • seek patterns and relationships
  • present findings with visualisations.

This course does not teach how to use NVivo for specific qualitative methodologies such as thematic analysis, discourse analysis, content analysis, grounded theory, etc. For that, you need Advanced Qualitative Data Analysis.

ECTS Credits

3 credits Engage fully with class activities
4 credits 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.


Key topics covered

This course is designed for researchers who plan to use NVivo to manage, code and analyse qualitative data in the context of academic research, public policy and for not-for-profit organisations.

This is the course you need if you want to learn the added value of using qualitative software to manage large amounts of data efficiently, triangulate different data sources seamlessly, improve the auditability of your research, and conduct your analysis in a rigorous and transparent manner.

The course is structured around four modules that follow the sequence of qualitative analysis process. You will learn to:

  • import and organise data in NVivo
  • manage your literature review
  • autocode data by themes
  • code data inductively
  • work with cases and variables 
  • transform qualitative data into findings
  • present results using visualisations
  • report the process of analysis transparently. 

You can take this course on its own, or in preparation for Advanced Qualitative Data Analysis.

The course is entirely hands-on and uses sample data to learn NVivo’s functionalities. It is suitable for NVivo for Mac and Windows version R1, although all demos will be made using NVivo for Windows. If your institution does not provide you with an NVivo license, you can download the NVivo R1 14-day free trial. The trial is fully operational, but can't be reinstalled on the same computer once it expires.

NVivo for Mac does not currently have all the functionalities of NVivo for Windows. If you are a Mac user and want to learn all the functionalities taught on this course, you must attend using a PC.

Outside class hours, you will be able to work on your own data, or articles of your literature review if you have not yet collected data. With help from the Teaching Assistant, you will also be able to troubleshoot any problems with your analysis in NVivo.

Although no previous knowledge of NVivo is required, you should have some familiarity with qualitative research.

This course is suitable for NVivo for Mac or Windows version R1. If you run an earlier version of NVivo (version 12), you must install the 14-day free trial of NVivo R1 to be able to follow the course.  

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.