NVivo Master Course
Key points
- This course teaches the basic and advanced features of NVivo for qualitative analysis in conjunction with the concepts that shape the process of qualitative research.
- The course brings together under one roof the content and practice of the courses Introduction to NVivo and QDA with NVivo, and teaches NVivo’s AI features with a special emphasis on what makes AI use (un)ethical in qualitative research and how to maximise its added value and avoid its flaws.
- The course can be taken on its own or in conjunction with the methodological seminars or the courses in qualitative research designs.
Description
This course teaches you to use NVivo in line with the key concepts of qualitative data analysis and qualitative research, so your use is coherent – and is an extension of – your ontological view, epistemological stance, logic of scientific reasoning, methodology, and theory. The course combines the software and methodological content of my two other NVivo courses – Introduction to NVivo and Qualitative Data Analysis with NVivo – with added insights into best practices and common mistakes to avoid when analysing qualitative data, regardless of your seniority level. From a software perspective, you will learn to maximise the added value of using NVivo to save time, manage large amounts of data efficiently, triangulate different data sources seamlessly and improve the auditability of your research. From a methodological point of view, you’ll learn to implement your research design (research question, study objectives and technique(s) of data collection) – using NVivo’s features adequately and efficiently, and link it to the philosophical foundations of your research paradigm informed by your ontological view and your epistemological stance.
The course is structured around four modules that follow the logical sequence of the qualitative analysis process. You will learn to set up an NVivo project, conduct a literature review in NVivo, autocode structured data and code data inductively, seek patterns and discover relationships across themes and cases, and present your findings using clear and evocative visualisations.
By the end of the course, participants will be able to:
- Connect ontology and epistemology with QDA decisions in NVivo
- Manage a literature review and enhance its process with AI
- Autocode structured data and code data inductively
- Generate, tease out and discard hypotheses
- Work with cases and variables for comparisons
- Seek patterns and identify relationships using different logics of scientific reasoning
- Present findings using evocative visualisations
- Spot when raw data are presented as “findings” in studies
The course is entirely hands-on and uses sample data to learn NVivo’s functionalities. Some time is also allocated to work on one’s own data. Note that this course does not teach the use of NVivo for specific qualitative research designs. For such content, see the courses Qualitative content analysis, Thematic analysis, Grounded theory and Cross-case analysis, or Overview of four designs.
Prerequisites
Although no previous knowledge of NVivo is required, participants should have some familiarity with qualitative research.
Schedule
Three days from 9:00 to 16:00.
Location
Online on Zoom or onsite. The course is capped at 20 participants.
Pedagogy
The course combines lectures, demos in NVivo and hands-on exercises with one’s data.
Cost
Fee depends on the number of participants and any prep work for a bespoke application to your research context. Please email me for more information.
Combining courses
This course can be taken on its own or in conjunction with the methodological seminars in qualitative analysis or the courses in qualitative designs.
References
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- Lumivero. NVivo 15 User Help for Windows and for Mac.
- Beekhuyzen, J., & Bazeley, P. (2024). Qualitative Data Analysis with NVivo (4th ed.). London: Sage.
Courses in qualitative research designs
This course was taught at
As a qualitative research consultant, I am on a mission to open the black box of qualitative analysis and challenge the prejudices surrounding subjectivity, bias, and anecdotalism of qualitative research. As you will learn if you work with me, qualitative analysis is systematic, transparent, and traceable, and can yield unique knowledge and insights that quantitative research can't. I train research teams and faculty staff, provide one-on-one coaching to researchers, and teach doctoral-level courses in method schools. I consult for humanitarian aid agencies worldwide in decolonising research and participatory methodologies.
