Applied Computer-assisted Qualitative Data Analysis using Nvivo

This course is for those already familiar with qualitative research approaches who are interested in using NVivo software to assist with the tasks of qualitative data management and analysis.
Level 2 - runs over 5 days

Nicola McNeil is the Head of the Department of Management, Sport and Tourism, La Trobe Business School.  Nicola is currently working on several research projects in the areas of gender and work, work-life balance and the impact of high performance work practices on employee wellbeing. She has received research grants and consultancies from the Canadian Social Sciences and Humanities Research Council, the Australian Federal Government, VicHealth, industry partners and not-for-profit organisations.

Nicola is a leading educator and teaches classes in employment relations, human resource management and research methods to undergraduate and postgraduate students. Nicola is also an instructor for the Australian Consortium of Social and Political Research Inc (ACSPRI) and offers courses on the use of computer-assisted qualitative data analysis and mixed methods research.

About this course: 

In this 5 day course, participants will learn how to analyse qualitative data using NVivo. The course takes a holistic view of the analysis of qualitative data using computer assisted techniques.  We will examine not only the mechanics of driving the NVivo software package, but also how to plan for the collection of data; preparation of data for analysis; as well as the analysis of the data. They will also be introduced to advanced analysis tools including those for theory building, validation and presentation of findings.


Participants will explore applications of the software to their own research projects. Sample data will be provided but participants should bring their own data sets, if they have them, and/or copies of articles and research reports relevant to their field of study.


The target audience for this course is researchers in the social sciences and related fields that draw on qualitative data.  The course is an introductory level course, and would suit researchers (including postgraduate students) with limited experience in qualitative methods and computer-assisted analysis techniques and processes.

Course syllabus: 

Day 1:  Getting to know the NVivo working environment.

  • Project design issues and their application in NVivo;
  • creating, saving and backing up NVivo Projects;
  • gathering and preparing data for analysis in NVivo;
  • working with data sources, including text, spreadsheet, audio and video formats and handling non-text data within the context of an NVivo project;
  • Organising and managing data sources.


Day 2:  Managing and thinking about data and recording reflections.

  • Coding qualitative data;
  • the role of journals, memos and an audit trail;
  • using memos, links and annotations to reflect on and record ideas about data;
  • documenting conversations, themes and threads;
  • exporting memos to Microsoft Word;
  • coding data in media other than text;
  • comparing coding and linking as tools for making meaning;
  • introduction to framework matrices.


Day 3:  Different approaches to coding and analysis

  • Using automated coding processes to search and code text of articles;
  • introduction to word frequency queries and cluster analysis;
  • how bibliographic packages interface with NVivo;
  • using NVivo to assist with visualising themes, conceptualising the literature and identifying gaps in the current knowledge base.


Day 4: Advanced analysis techniques

  • Classifying sources and nodes;
  • ways of representing demographic characteristics and other attributes;
  • advanced coding procedures;
  • introduction to advanced find and query functions including applications of matrix coding queries;
  • analysis of quantified qualitative data.


Day 5: Reporting your results and other software applications
On the final day, we will explore various ways of using computer-assisted qualitative data analysis software to conceptualise and build theory, including the use of Leximancer.  We will discuss the accepted conventions for representing and reporting findings.  Finally, we will introduce and review other computer-assisted qualitative data analysis software offerings, including Atlas.ti, Transana and MAXQDA.

Course format: 

Issues arising for users of NVivo for Mac will be addressed but all instruction will be in NVivo for Windows.

This course may run in a computer lab, or you may be advised to bring your own laptop with specified software.

We will let you know in advance.

Recommended Background: 

Completion of an introductory ACSPRI course in qualitative research techniques or an equivalent tertiary course is required. Alternatively a reasonable level of experience and familiarity with qualitative data analysis procedures would be acceptable. Efficiency in using Windows based software is essential. No prior knowledge of NVivo is required.


Previous participation in Qualitative Research: Design, Analysis and Representation is recommended and would be an advantage but is not a prerequisite for participating in this course.


Recommended Texts: 

Other reading:

  • Edhlund, B. and McDougall, A. (2013).  NVivo 10 Essentials.  London: Lulu.
  • Richards, L. (2009). Handling Qualitative Data: A Practical Guide (Second ed.). London: Sage.
  • Bazeley, P. and Jackson, K. (2013). Qualitative Data Analysis with NVivo (Second ed.). London: Sage.
  • Saldana, J. (2013). The Coding Manual for Qualitative Researchers 2nd Edition (Second ed.), London: Sage.
  • Silver, C., and Lewins, A. (2014). Using Software in Qualitative Research: A Step-by-Step Guide (Second ed.). London: Sage.

Q: Do I have to have used Nvivo before?

A: No prior knowledge of Nvivo is required.


Q: Do I need a background in doing qualitative research?

A: It helps significantly to have an understanding of what is involved in analysing qualitative data before taking this course.


Participant feedback: 

Went from zero knowledge of NVIVO to feeling very confident. (Summer 2020)


Working on projects is a great way to interpret the learning. The course was well structured between listening and doing. (Summer 2019)


Nicola is AMAZING she explains the applications of technical information really well. Very rich in terms of learning. (Summer 2019)


Good background knowledge given which helped structure my thinking. (Summer 2018)


I came with some basic knowledge of coding in NVIVO but had not done any analysis. I now feel I could set up a new project in a robust and useful way and undertake analysis. The instructor and students both helped to answer my queries which was just great. (Winter 2016)


It was well balanced and moving between activities kept my interest. The practical exercises and sample project were very important in consolidating learing. (Winter 2016)

The course introduced me to applied qualitative design which is extremely helpful at a current stage in my career; qualitative research at work and a PHD proposal. (Winter 2015)



The instructor's bound, book length course notes will serve as the course text.