Seeing the Forest Through the Trees: Using Nvivo to See the Bigger Picture in Your Data Through Qualitative Analysis

As a researcher in the humanities, I end up with lots of qualitative data. As much as we might try to force the full complexity of our datasets into finite rows of numbers, they simply won’t fit, and we must consider other options. This is where a qualitative analysis tool can help researchers uncover the deeper meanings, connections, and patterns present in their data. Though there are many tools of various kinds out there to categorize, tag, code, and visualize data, I would like to share one in particular with you today: Nvivo 11.

In its numerous iterations, Nvivo has been used in many projects for a variety of functions, including qualitative research, grounded theory-based research, and even literature reviews. In this tutorial, I hope to provide a better understanding about how to get started with this kind of qualitative analysis, which is integral to digital humanities research. Tools like Nvivo allow researchers to take a step back from the individual objects of analysis and see the broader connections across a corpus. Whether that corpus be made up of individual written texts, audio files, or video files, Nvivo allows the researcher to input data about the contributing entities and code points of interest. This is useful for a variety of projects, such as oral history, in which researchers collect audio recordings, transcribe interviews, and organize the data chronologically or by association with some event, or in a more pedagogically-based analysis like my own. For a more general overview about using Nvivo in qualitative research, see Dr. Helen Dixon’s SlideShare presentation on the topic.


QSR International, the company that makes Nvivo 11 — the most recent version of the program—offers numerous, well-crafted resources to help customers become familiar with the general functions of the software. These include a set of video tutorials, a getting started guide, and an online help center. For this brief tutorial, I want to focus on what a researcher in the digital humanities would need to do to get a research project off the ground using this software. As an example, I will use my own text-based data set, which I gathered from the Digital Archives of Literacy Narratives, maintained by The Ohio State University. To see the fully analyzed results of the research that I am using in this tutorial, you can visit my website.

A Brief Tutorial to Get You Started

Step 1: Downloading and Installing the software (or finding out if your university has a subscription)

These kinds of programs are expensive, with the discounted student price for a full license for the Starter Version of Nvivo 11 costing $350, so it pays to know how and when you can access them to do your work in the most efficient way possible. For many students, like myself, this means taking advantage of free trials for small-scale projects and campus resources for long-term projects. Below is the landing page for Nvivo 11. Select “Free Trial” to go to a page with several download options.

QSR’s Nvivo Website

From here, you will select the version of Nvivo 11 that is right for your operating system (Windows or MacOS) and complete the download and installation process.

Step 2: Setting up the Software

When you first run the program, you will need to enter your Nvivo 11 License Key or select a free trial option. For this tutorial, I am using Nvivo Starter. Your data may require something more robust; if so, I would recommend trying the Nvivo Pro or Nvivo Plus editions. Remember, no matter which option you choose, your trial version will only be available for 14 days.

Nvivo Setup Screen 1

Step 3: Creating a Project

Nvivo 11, the newest version of the software, has been redesigned to be a more familiar user experience for the consumer. It is reminiscent of the recent versions of Microsoft Office, utilizing a simple File menu screen and a menu ribbon in the main interface. On the File menu screen shown below, you will select Blank Project to begin a new project. (Tip: If you want to experiment with the functionality, you can use the pre-loaded Sample Project to get comfortable. This Sample Project provides data, including interviews and news articles, pre-coded nodes, entries for a set of participants, and several sample queries to practice interpreting results.)

Home Screen for Nvivo 11

Your blank project will look like this when you first open it. You will notice the ribbon and tab layout for the menu across the top. From here, you will be able to add various data components and run analysis tools to complete your research.

Basic Nvivo Interface

Step 4: Creating Nodes

Steps 4 and 5 can be interchanged, depending on your research design and approach. For this project, I am starting with a basic set of nodes and expanding/refining them as I code the data. “Nodes” are the topics, ideas, or types of words or phrases that you are going to code for in your data. For example, my nodes are divided into three categories — Personal Life, Educational, and Attitudes— and each category includes multiple nodes. The screen below shows how you would add additional nodes to the “Personal Life” category.

Sample Node System for Qualitative Coding

From this pop-up menu shown above, you will select “New Node.” This will open the dialog box shown below, and you will assign the node a name, provide a description for any other coders you are working with, make sure that it is listed correctly in the hierarchy, and assign the node a color from the drop-down menu.

New Node Dialog Box

Step 5: Processing and Uploading Your Data

This step takes place partially outside the Nvivo 11 software and will vary a little depending on your data. For qualitative analysis, you may be working with text-based files, audio files, video files, or some combination thereof. For my project, I am drawing on solely text-based artifacts; therefore, I have organized them in a folder in preparation of the upload. Nvivo 11 will accept multiple file types — including .doc, .docx, .pdf., and .txt — so I will not be converting the file types prior to upload. For more detailed information about working with audio or video files, refer to this resource from QSR.

List of Files to be Uploaded

Once you have gathered all of your sources, go to the Sources — using the tab in the lower left corner of the screen — to upload your files or “Internals.” On the Data tab in the menu ribbon, select what kind of source(s) you would like to import and where you will upload your data from.

Import Data Buttons on Menu Ribbon

When all of the files are uploaded, your Sources section will include a list of “Internals,” and you will be able to preview and interact with each file in the window on the right.

Previewing Sources in Nvivo 11

Step 6: Coding Your Data

With your nodes defined and your sources uploaded, you are ready to start coding your data! Depending on the complexity of your coding system, you may have predetermined all of your nodes or you may be adding and updating your core list of nodes as you work. The video below shows how simple it is to code a section of your data.

Step 7: Running Queries and Visualizations

Once you have all of your data coded using Nvivo's node system, you will be able to take advantage of the visualization features of Nvivo 11. The video below shows how you can go about taking your coded data and use the Query and Explore menus to better see the connections between your data.

Step 8: Reading the Results

Having all of these pretty visualizations is nice, but as with any data, the output still has to be interpreted. Please see the brief video below for some general observations and visit my website to see a more detailed account of my results as informed by Nvivo 11 and other tools as well.


A Reflection on Nvivo 11

Positives:

· Highly-Nuanced Coding

· Supports Coding Audio and Video Files

· Professional-Looking Visualizations

· Great Resources Available

Negatives:

· Expensive ($350 per student license)

· Frequently Release New Versions

· Many Complex Functions to Learn About

Overall, I would recommend Nvivo 11 for many qualitative analysis tasks; however, I would also encourage DH researchers to utilize the free trial period to make sure the Nvivo is the right tool for their data. For a short-term project, using the free trial and campus resources may be sufficient and give you the analysis power you need without the costly investment, but it is also important to remember that taking advantage of the most impressive features of Nvivo 11 will require that you seek out some additional resources. For a long-term project — such as a dissertation or book — you may find that having a license to Nvivo 11 allows you to take advantage of the best features of the program and maintain and process your data throughout the project, but you do have to be aware that QSR releases new versions regularly. They typically continue to support several of the previous versions, but a book project may go on for years, and you want to make sure that you will still be able to work with your data when it comes time to write up your results. So far, QRS has worked to make subsequent versions of Nvivo backward compatible with saved projects.


Where do you go from here?

Now that you have had some experience with this tool, the world of qualitative data analysis is your oyster, right? Well, you are certainly on the right track. This software may be the tool you need to get a deeper look at your data, but this brief tutorial may have shown you that this tool isn’t right for you. Both are okay. I encourage you to go wherever your data leads you.

If you are interested in learning more about Nvivo 11, please take advantage of the resources listed throughout this post, and you can watch QSR International’s video playlist of tutorials below to dive in a little deeper as well.

Additional Resources:

Qualitative data analysis using NVivo

Using NVivo for Qualitative Data Analysis

QSR Nvivo Tutorials

QSR Nvivo 11 Tutorials for Windows

Nvivo Online Help

Coding Audio and Video in Nvivo

Happy researching, digital humanists!