Introduction to 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 1 - runs over 5 days

Nicola McNeil is an Associate Professor of HRM and the Head of the Department of Management and Marketing at the 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, and a variety of industry partners and not-for-profit organisations.  Her research has been published in leading journals including the Journal of International Business Studies, the International Journal of HRM and European Sport Management Quarterly.

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 NVIVO and mixed methods research designs.

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. You 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 your own research projects. Sample data will be provided but you should bring your own data sets, if you have them, and/or copies of articles and research reports relevant to your 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 no experience in computer-assisted analysis techniques and processes.

Course syllabus: 

Day 1:  Getting to know the NVivo working environment.

  • Managing your NVivo workspace;
  • Project protocols and their application in NVivo;
  • Creating, saving and backing up NVivo Projects;
  • gathering and preparing data for analysis in NVivo;
  • Working with cases, classifications and attributes;
  • Organising and managing data sources;
  • Working with data sources, including text, spreadsheet, audio and video formats and handling non-text data within the context of an NVivo project


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

  • Coding qualitative data;
  • Editing, annotating and linking your data to reflect on and record ideas about data;
  • Mind maps, project maps and concept maps;
  • Importing datasets and data imported from social media;
  • Importing bibliographic databases into NVIVO;
  • Introduction to framework matrices.


Day 3:  Different approaches to coding and analysis

  • Approaches to coding your data;
  • Achieving trustworthiness in your analysis;
  • Creating codes or themes;
  • Running queries on your data (text search, word frequency, coding, group, query, matrix and crosstab queries);
  • Using automated coding processes to search and code text .


Day 4: Advanced analysis techniques

  • Building relationships within NVivo, including creating sociograms;
  • Visualising your qualitative analysis;
  • Analysis of quantified qualitative data;
  • Inter-coder reliability;
  • Project protocols.


Day 5: Reporting your results and other software applications

  • conventions for representing and reporting findings
  • presentation of course projects
  • Q & A session


Course format: 

This course will use the Windows version of NVivo.

NVivo for Macs will not be supported.

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: 

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


Other reading:

  • 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.  Second edition, 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: 

This was the best course I have ever attended! (Winter 2021)


I definitely benefitted from attending the course and can do things with the program now that I couldn't do easily at the start of the course. (Winter 2021)


We got through 5 days of heavy content in an interactive and engaging way - the presenter did really well! (Summer 2021)


The online sessions were actually very effective. The presenter was very conscious of the limitations of online access and reduced interaction that occurs in the face to face setting. The presenter provided ample opportunity to ask questions, review activities etc. which was helpful. (Summer 2021)


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