Coding Qualitative Data Using NVivo
Qualitative Coding is a core strategy for qualitative data analysis in which some aspects of a data is assigned a descriptive label that allows the researcher to identify related content across the data.
SImply put, Qualitative coding involves creating and assigning codes to categorize data extracts and derive themes.
What methodologies does NVivo support?
Researchers usually adopt a qualitative methodology to suit their research question. For example, a social scientist wanting to develop new concepts or hypotheses may take a ‘grounded theory’ approach. A health researcher looking for ways to improve policy or program design might use ‘evaluation methods’. NVivo does not favor a particular methodology no matter what method you use. It is designed to facilitate common qualitative techniques for organizing, analyzing and sharing data.
BEFORE YOU BEGIN
• Prepare your interview/focus group transcriptions
• Prepare a coding table based on your first impression from your transcriptions.
FOUR IMPERATIVE STEPS TO FOLLOW IN CODING QUALITATIVE DATA USING NVIVO
• Step I. Import Data: Import the document/transcriptions you intend to use and this will become you coding source(s) as you get along with coding
• Step 2. Set up a Coding Table: You will have to have prepared a coding table based on your first impression from your transcriptions (first cycle coding) before applying it on NVivo.To view and export your code book: Go to “Share”, Go to “Export”, Click on “Export “Codebook”
• Step 3. Coding: Highlight what you intend to code, right click and select code. This will bring out a backdrop of the available categories and you care able to choose which categories you want to code into. You are able to double code or triple code and have daughter codes as relevant to each category.
• Step 4. Analyze the Data: You can simply highlight/cope and post what you have coded in a word document on your computer. You can also export and download them.
Here is what a coded document looks like for a particular node or category.
Performing an inter-rater reliability check
Coding Qualitative Data (A summary and simple four step-by-step Guide to Coding Interview and Focus Groups Data)
CMU Libraries is committed to helping members of our community become data experts. To that end, CMU is offering public facing workshops that discuss Qualitative Research, Coding, and Community Engagement best practices.
The following workshops are a part of a broader series on using data. Please follow the links to register for the events.
Upcoming Event: March 21st, 2024 (12:00pm -1:00 pm)
Community Engagement and Collaboration Event
Join us for an event to improve, build on and expand the connections between Carnegie Mellon University resources and the Pittsburgh community. CMU resources such as the Libraries and Sustainability Initiative can be leveraged by users not affiliated with the university, but barriers can prevent them from fully engaging.
The conversation features representatives from CMU departments and local organizations about the community engagement efforts currently underway at CMU and opportunities to improve upon them. Speakers will highlight current and ongoing projects and share resources to support future collaboration.
Event Moderators:
Taiwo Lasisi, CLIR Postdoctoral Fellow in Community Data Literacy, Carnegie Mellon University Libraries
Emma Slayton, Data Curation, Visualization, & GIS Specialist, Carnegie Mellon University Libraries
Speakers:
Nicky Agate, Associate Dean for Academic Engagement, Carnegie Mellon University Libraries
Chelsea Cohen, The University’s Executive fellow for community engagement, Carnegie Mellon University
Sarah Ceurvorst, Academic Pathways Manager, Program Director, LEAP (Leadership, Excellence, Access, Persistence) Carnegie Mellon University
Julia Poeppibg, Associate Director of Partnership Development, Information Systems, Carnegie Mellon University
Scott Wolovich, Director of New Sun Rising, Pittsburgh
Additional workshops will be forthcoming. Watch this space for updates.