Using NVivo QSR for qualitative data analysis and management

Dr Aleksej HeinzeSalford Business School

University of Salford508c, 5th Floor, Maxwell BuildingM5 4WT, Salford, UK0161 29 55024 a.heinze@salford.ac.uk

What specific areas are of interest to you?

Session outline• Why use NVivo or similar tools?

• Getting your computer ready

• Preparation of documents

• The process of analysis:– Coding– Developing node trees– Node diagrams

Why use NVivo or similar tools?

• Organisation of your data • Speed of qualitative data analysis• Scalability of your research • Traceability of your analysis – important for

the Viva …• Use of a ‘standard method’ making group

projects easier• Keeping files electronically available –

portability • Provides a structure/framework

How can we learn to use it?• We all have our own styles to choose

from, but…

• Training sessions see their website: www.qsrinternational.com @ £300+

• Very helpful help file!

• Read articles around the area – see references

• Just get started – learning by doing

hr.salford.ac.uk/development• Day 1 (4 February 2010, 9.30-4.30)

– covers a thorough and comprehensive demonstration of the key features of NVivo 8 with many opportunities to assess learning through tasks. Participants will recreate the Volunteering sample project that comes with Nvivo 8 software from scratch.

• Day 2 (11 February 2010, 9.30-4.30) – briefly revisits some of the key functionalities covered on

day 1. Participants are encouraged to set up their Nvivo 8 project using all the functionalities in Nvivo 8 responsive to their project needs. A clinic session is provided to assist participants through the structuring of their node system, coding and modelling as required.

Some NVivo terminology• Node: a conceptual representation of codes that the

author found significant during the analysis process using QSR NVivo software. Nodes are represented in diagrams and graphically illustrated with a ball.

• Node tree: logical composition of nodes into a tree hierarchy. Tree node diagrams are organised so that the root of the tree is at the top.

• Each node is uniquely identifiable within a tree by an automatically assigned number in QSR NVivo software. For example node number (3 7 10 14) signifies that this particular node is located within the third tree, seventh branch, tenth twig and fourteenth leaf. (Heinze, 2008:xv)

Getting the ‘right’ software• There are a number of NVivo versions

– 6 – old – 7 – currently @ University of Salford– 8 – the latest version – see QSR website

• Windows Operating System

• Telephone ILS and ask to be added to the Nvivo user group

Preparing your transcripts

• Very basic level of document analysis

• Use MS Word for document preparation

• Use styles for headings and for paragraphs

• Break down paragraphs into smaller sections

Example:• Q1 Question 1:

• Thank you very much for making it today. The reason for this interview is to follow up the focus group that we had and then see from the individual students what they think about the course. We hope to use these findings in order to improve the course. We are going away in June for a staff away day and we will focus there on the issues arising and hopefully we can improve this course. We would really like your input so that we can see what can be done better.

• First of all I just wondered if you could tell me what was your impression of the course overall?

• A1 AMH:

Heading 1Heading 1

Heading 1Heading 1

Heading 2Heading 2

Activity: break down this text:

AMH: Well it is quite different to me, because it is the first year, even though it is the second year running of the course. So, being a new person in, it is really about getting to know everyone, in the first few months, getting into the system you know the routine using the Blackboard. Because I enrolled sort of on the last day, I was just thrown in really, but I found it OK. Good learning curve you know. Lectures I thought were very good, so quite positive for me really.

The only one thing that I could criticise was the computing networking assignment, where we were all in one room, and unfortunately it was an enormous class to start with, and unless you got the tutor’s attention initially – you were really, you were at a loss in some respects. Now, for me and my partner in particular, it was a little bit hard to catch on, I found that a little bit difficult. But that was because of sheer numbers in the class to be honest. But I think that quite a few have actually left the course, I have seen the numbers go down quite a bit.

One of the bigger headaches was the one that I brought up at the other meeting, the parking. Absolutely horrendous, if you are travelling a long distance as well and you can’t park – I have actually been refused entrance on two separate occasions. I was told that I could not park across the way unless I got a permit, although I had no idea that I would have difficulties parking. I know that it is difficult for everybody to be in the car park, but if you have enrolled on the course as a part time student it is extra difficult without a doubt.

Inductive vs Deductive ?• Inductive approach: look at your data and

see what it is saying – e.g. Grounded Theory – – Nodes emerge

• Deductive approach: hypotheses which can be tested in order to support the general ideas. – – Nodes are predetermined

Import all files

Coding process

Organise your nodes into trees

Activity

• Go to this website:• http://synapticweb.pbworks.com/

• Download the content of the pages and save it in a MS Word document.

• Prepare the documents for Nvivo formatting• Import the document and code it answering the

question: What is Synaptic Web?

Build node models

Activity

• Develop a diagram to represent your findings

Summary• Why use NVivo or similar tools?

• Getting your computer ready

• Preparation of documents

• The process of analysis

References• Gregorio, S. d. (2000). Using NVivo for your literature

review. Paper presented at the Strategies in qualitative research: issues and results from analysis using QSR NVivo and Nud*Ist. London.

• Heinze, A. (2008). 4.5 Data analysis. Blended learning: an interpretive action research study. PhD thesis, University of Salford, Salford. Pages 96 - 107, Available from: http:www.aheinze.me.uk/Downloads/Heinze_A_2008_Blended_e-learning.pdf

• Miles, M., & Huberman, M. (1994). Qualitative Data Analysis: An Expanded Sourcebook. London: Sage Publications.