5 Reasons Why You Should Use NVivo For Your PhD Research

If you're a graduate student working on your Ph.D., then you know that research is a key part of the process. And if like most graduate students, you're always looking for ways to make your research easier and more efficient. That's where NVivo comes in. NVivo is a software program that helps researchers organize and analyze their data. Here are just a few of the reasons why you should use NVivo for your Ph.D. research:

1. Consolidated Data:

Being a Ph.D. scholar requires you to study a lot of articles, publications, papers, or books. While doing so you need to note down the important points relevant to your research. These short points could be quite handy at the time of writing your research paper, especially the literature review part.

But what if you couldn’t locate the source of particular information jotted down randomly before due to the lack of proper data management? What a waste of time that would be to go through all the resources again? This is where NVIVO comes into play. It allows you to have structured categories of all your resources where you could clearly see all the data without being worried about losing it (Anuja, 2012).

2. Pattern & Trends Recognition

There are a number of software programs that can help with qualitative data analysis, but NVivo is one of the most popular options for Ph.D. students. NVivo is designed to help researchers organize and analyze large amounts of data. It can be used to create diagrams, charts, and tables, making it easier to see patterns and trends in the data. NVivo also makes it easy to find quotes and excerpts from interviews and focus groups.

3. Develop & Test Theories

NVivo allows qualitative data analysis that can be used to develop and test theories for your Ph.D. research. It enables you to analyze data in various formats i.e., text, audio, and video data, as well as images and PDFs. This makes it an ideal tool for qualitative research.

NVivo can help you to:

  • Develop a theory

  • Test a theory

  • Refine a theory

  • Evaluate a theory

  • Understand a theory

  • Present a theory

4. Find New Sources Of Information

One of the most efficient ways to find new sources of information is to use NVIVO software. It is used in a variety of fields, including social science, education, market research, and health care. One of the great things about NVivo is that it can help you find new sources of information. By analyzing text data from sources like social media and news articles, NVivo can help you identify trends and patterns that you may not have otherwise noticed.

5. Easy Collaborations

NVivo makes collaboration easy by allowing you to easily invite others to join your project and provides a secure space for all of your data (King, 2004). You can also easily share findings and collaborate on reports. This software is especially useful for researchers and academics who need to collaborate with others in order to analyze data.

NVivo 1:1 Research Assistance

These are only a handful of NVivo's benefits. It's a massive piece of software with a high learning curve. For this reason, The Scholars Professional Editing Group offers qualitative, mixed-method, and quantitative data analysis, as well as associated services, to assist doctoral students to comprehend their data, compose their dissertations more successfully, and defend their conclusions.

Our board-certified NVivo coaches will navigate you step by step through the entire data analysis process in 1-2 weeks through our 3 simple phases described below:

Phase I:

Data Importation, store, organization, code.

Phase II:

Code, theme development, data analysis/run various queries.

Phase III:

Data visualization, sample write-up template, narrative submission review.

Book a Consultation For NVivo Now: NVivo 1:1 Research Assistance

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  1. Anuja C. (2012). Why use NVivo for your literature review? Retrieved from:

  2. King, N. (2004). Using templates in the thematic analysis of texts. In C. Cassell & G. Symon (Eds.), Essential guide to qualitative methods in organizational research (pp. 256–270). London: Sage Publications.

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