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Introduction to NVivo

Course Dates and Times

Monday 18 – Friday 22 July 2022
2 hours of live teaching per day
08:30 – 10:30 CEST

 

Marie-Hélène Paré

info@mariehelenepare.com

The Qualitative Analyst

This course provides a highly interactive online teaching and learning environment, using state of the art online pedagogical tools. It 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 a qualitative dataset
  • manage your literature review
  • autocode data and code data inductively
  • seek patterns and identify relationships across themes and cases
  • present qualitative findings using visualisations.

This course does not teach how to use NVivo for specific qualitative methodologies or analytical methods, such as thematic analysis, content analysis, grounded theory, etc. For that, you need Advanced Qualitative Data Analysis in week one or in week two.

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.

@TheQualAnalyst

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 not-for-profit applied research.

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 logical sequence of a qualitative journey. You will learn to

  • import and organise a qualitative dataset in NVivo
  • manage your literature review
  • autocode structured data and code data inductively
  • work with cases and variables
  • seek patterns and identify relationships across themes and cases
  • present findings using visualisations
  • coordinate teamwork
  • report the analysis process in theses or articles.

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

The course is entirely hands-on and uses sample data to learn NVivo’s functionalities. It uses the latest version of NVivo R.1 for Mac and Windows. You must run this version to successfully attend the course as previous versions (10 or 12) have different interfaces. If this is your situation, or if your university does not provide you with an NVivo license, you can download the NVivo 14-day free trial. The free trial is fully operational, but can't be reinstalled on a same computer once it expires.  

For Mac users: please note that NVivo R.1 for Mac does not currently have all the features of NVivo for Windows. If you are a Mac user and want to learn all the features 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 you might have with regard to your analysis in NVivo.

How the course will work online

The course combines asynchronous pre-class assignments, such as readings and watching pre-recorded videos, as well as daily two-hour live sessions with Zoom. To prevent Zoom fatigue and boredom, 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 course content.

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

This course is for either NVivo R.1 for Windows and Mac.

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.


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.