This course offers an interactive online learning environment using advanced pedagogical tools, and is specifically designed for advanced students, researchers, and professional analysts. The course is limited to a maximum of 16 participants, ensuring that the teaching team can address the unique needs of each individual.

Purpose of the course

This course offers a comprehensive introduction to NVivo for qualitative research from the stage of conducting literature review up to visualising qualitative findings. You will learn to:

set up an NVivo project and organise data
work with interviews, focus groups and documents
conduct your literature review effectively
autocode structured data and code for themes inductively/li>
tease out hypotheses and generate new ones from the data
seek patterns, identify relationships and explain outcomes
illustrate your results with evocative visualisations.

Important information: This course does not teach how to use NVivo for specific qualitative methodologies or analytic methods, such as thematic analysis, qualitative content analysis, cross-case analysis or grounded theory. For that, you need Advanced Qualitative Data Analysis.

ECTS Credits

3 credits - Engage fully in class activities and complete all five after-class assignments.
4 credits - Engage fully in class activities, complete all five after-class assignments and complete the course assignment.

Courses from the Instructor

Qualitative Data Analysis
26 July - 2 August 2024, Virtual

Advanced Qualitative Data Analysis
26 July - 2 August 2024, Virtual

Introduction to NVivo
3 - 7 February 2025, Virtual

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.

@TheQualAnalyst

Key topics covered

This course is for applied and academic 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.

In this comprehensive introduction, you will learn the added value of using NVivo 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 process. You will learn to:

import and organise textual and visual data in NVivo
conduct your literature review and generate summaries
autocode structured data and code for themes inductively
work with cases and sets for comparative analysis
seek patterns, identify relationships and explain outcomes
present your results with evocative visualisations
provide a transparent account of your analysis in thesis and articles

The course combines short lectures and hands-on exercises during which you use sample data to learn NVivo’s functionalities. Outside live sessions, you will have the opportunities to work on your own data or articles of your literature review, if you have not yet collected data.

This course provides a solid foundation for Advanced Qualitative Data Analysis.

How the course will work online

The course combines asynchronous pre-class assignments, such as readings, quizzes and problem-solving tasks, as well as daily three-hour live sessions with Zoom. The live sessions’ pedagogy is built around a rich and diverse mix of online teaching techniques such as elevator pitch, talk-to-text technique and debates. With the help of the teaching assistant, you will have the opportunity to troubleshoot any issue you may have regarding the analysis of your data in NVivo.

Although no previous knowledge of NVivo is required, you must be familiar with qualitative research.

The course uses NVivo 14 for Windows / Mac. You must run this version, or version R1 from 2020 which looks the same, to attend the course. Do not attend the course with version 10 or 12, as these have different interfaces and menus. To obtain NVivo, please download the NVivo 14-day free trial if your university does not provide you with a license. The trial is fully operational but can't be reinstalled on the same computer once it has expired.

Warning for Mac users: NVivo 14 for Mac currently does not have all the functionalities of NVivo 14 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. Running a virtual machine, such as Parallels, on your Mac will allow you to run Win OS, given that your Mac has the right specifications.

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.

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.

Install the app