Team NVivo: Building Successful Research

Collaborations

www.queri.com

Kristi Jackson, MEd PhD

kjackson@queri.com

303-832-9502

Table of contents• Perspectives: Qualitative computing and NVivo

• Starting out, with a view ahead

• Designing an NVivo database

• Coding basics

• Going on with coding

• Cases, classifications, and comparisons

• Working with multimedia sources

• Adding reference material to your NVivo project

• Datasets and mixed methods

• Tools and strategies for visualizing data

• Using coding and queries to further analysis

• Teamwork with NVivo

• Moving on - further resources

1. Why do team research?2. Database options (types of

projects)3. Tools specifically designed to

facilitate teamwork4. Practical tips about other tools5. Objectives for successful teams

Presentation Overview

Multiple perspectives◦ Articulating the often unstated assumptions of the

lone researcher Large scale qualitative studies

◦ Addressing qualitative questions that cannot be answered with quantitative approaches

◦ Discovery of relevant questions in the research context

◦ Promoting social justice through research ◦ Data triangulation

1. Why do team research?

1. A single, stand-alone project (relayed or “handed off” to other researchers)

2. NVivo Server allows for synchronous use3. Multiple stand-alone projects that are

merged.

2. Database options (MS Windows)

Project AProject C Project B

Copy

Import

Prompting for user on launch◦ Items “created by KJ” and “modified by KJ”◦ Project log

Users and passwords Coding stripes by user Queries according to user Coding comparison query

3. Tools specifically designed to facilitate teamwork

File Options

Prompting for user (stand-alone projects)

Node List View

File Info Project Properties

File Info Open Project Event Log

File Info Project Properties Passwords

Project AProject C Project B

Copy

Import

Combining projects in NVivo

Combining projects in NVivoActivities

MeetingsPhone conferences

TeamworkCommunicationTrust

ActivitiesMeetingsPhone conferencesProjects

TeamworkCommunicationDiversityTrust

ActivitiesPhone conferencesProjects

TeamworkCommunicationDiversityTrust

1. Same name ◦ Nodes: trusting, work, love◦ Sources: Susan, Dorothy, William◦ (Classifications, sets, etc.)

2. Same hierarchical position in the database◦ My project:\Nodes\Themes\Trusting◦ My project:\Sources\Interviews\Susan

3. Exact same text in the sources“I love the beauty of this place”

- does not match -

“I love the beauty in this place”

DO NOT EDIT THE TEXT!

What is a duplicate? (three rules)

In general, properties of the “master” will trump the auxiliary (e.g., Node descriptions, colors, aggregate)

If two sets have different members, the new set will have all members (combined)

Help files you should review:◦ “How NVivo determines that two project items are

duplicates”◦ “How duplicate project items are handled during

import” ◦ “How project properties are handled during import”

Examples of other project items

Import one project into another

Coding stripes by User Open a node (or source)

View

Coding stripes

Selected Items

Users

Coding stripes by User

Queries (and other ways to scope)

Query (any one, except coding comparison)

Caveats◦ Hegemonic coding

Reliability at the expense of validity◦ An account of the process vs. a reliability measure

How was the coding system developed? What was it that convinced the team of their

conclusions? What were the competing explanations? How were differences resolved?

Coder reliability

Query Coding Comparison

User(s) A User(s) B

Node(s) Source(s)

Kappa Coefficient Percent agreement

Kappa vs. Agreement

I am not a Down Easter by generation by any sense. I am a dingbatter. That is what I am. But it is a beautiful area to live. I chose to live here. We’ve lived down here for about six or seven years now. A lot of people look at you strangely when you say you want to move to a remote area. But to me, there’s a lot of beauty in that, of being remote. To me it’s not that bad. I can’t imagine why anyone would want to leave to tell you the truth. I can understand why Down Easters like living here, it’s in their blood. And it might be in mine too to some extent. The main thing, besides the water and the beauty of the areas, is the people. I like the personalities and the character of these people. They are independent, they are self-starters, they are hard workers. They will make it regardless of any recession. They are that kind of people. They are good people that live Down East. And that’s probably the big attribute that this area has got. The main thing, besides the water and the beauty of the areas, is the people. I like the personalities and the character of these people.

I am not a Down Easter by generation by any sense. I am a dingbatter. That is what I am. But it is a beautiful area to live. I chose to live here. We’ve lived down here for about six or seven years now. A lot of people look at you strangely when you say you want to move to a remote area. But to me, there’s a lot of beauty in that, of being remote. To me it’s not that bad. I can’t imagine why anyone would want to leave to tell you the truth. I can understand why Down Easters like living here, it’s in their blood. And it might be in mine too to some extent. The main thing, besides the water and the beauty of the areas, is the people. I like the personalities and the character of these people. They are independent, they are self-starters, they are hard workers. They will make it regardless of any recession. They are that kind of people. They are good people that live Down East. And that’s probably the big attribute that this area has got. The main thing, besides the water and the beauty of the areas, is the people. I like the personalities and the character of these people.

double-click

Becoming reliable

Memos◦ One for each team member

Tip: Add heading levels insteadof a memo for each topicand use the “auto code”tool to sort these intonodes after combiningprojects

“Node description recommendations” “Issues for the next meeting” “Database management”

Author initials in the text of each Annotation Colors for team member work

4. Practical tips about other NVivo tools Questions about coding

Initial interpretations

Suggestions for interviewers

Ideas for conference presentation

A node (or folder) for each team member to allow for new ideas without going too far astray

Ongoing clarification of purposes and processes

Piloting Reflective writing Leveraging team strengths

5. Objectives for successful teams

What qualitative methodologies are guiding the team work? How geographically dispersed is the team? What are the ethical and human subject issues for this

project? What work will be done independently, in pairs, or in groups? What kind of access do team members have to the software? What experience do the researchers have with qualitative

methods, with the research setting, or with NVivo? What decision-making models (e.g., consensus, democratic

vote, or team leader directives) are in play to guide team progress?

Who is the project “Czar” and how will they communicate?

Objective 1: Ongoing clarification of purposes and processes

Prepare one document and import it, rather than preparing all 40 files

Ask different researchers code a page of a transcript ◦ Practice a project import◦ See the visual comparisons

Detailed project management logs (in an NVivo memo)

Run queries and visualizations early to test them

Objective 2: Piloting

Propose improvements and modifications ◦ Data collection◦ Cleaning◦ Storage, etc.

Role clarifications or job descriptions Timelines for activities or benchmarks Minutes of meetings Coding structures, definitions, examples and

counter-examples Ideas proposed by team members and decisions

made regarding these proposals Emerging models or hypotheses

Objective 3: Reflective writing

Initial assessment of skills/needs:◦ Qualitative research methods◦ Content area◦ NVivo as a database

Shifting ◦ Needs◦ Skills◦ Assessments

Short and long-term mapping of tasks and individuals

Objective 4: Leveraging strengths

Table of contents• Perspectives: Qualitative computing and NVivo

• Starting out, with a view ahead

• Designing an NVivo database

• Coding basics

• Going on with coding

• Cases, classifications, and comparisons

• Working with multimedia sources

• Adding reference material to your NVivo project

• Datasets and mixed methods

• Tools and strategies for visualizing data

• Using coding and queries to further analysis

• Teamwork with NVivo

• Moving on - further resources

Kristi Jackson, MEd PhDkjackson@queri.com

303-832-9502