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NVivo Important Working Mechanisms
What is NVivo, and where can we use it? Good question; let us start with the first question; NVivo allows us to organise, analyse and visualise qualitative data and find patterns hidden in data which will make data manageable and easy to find, which will help make a data-driven decision.
Secondly, analysing data in NVivo can help us understand the needs of people, clients or organisations from the interview conducted or document received in a qualitative form which will give deep insight and meaningful information that will make the stakeholders happy.
However, Data Analysts and researchers can use qualitative data and apply different methods to analyse, describe, and understand social phenomena in data.
NVivo can be used to analyse data in industries ranging from social science and education to healthcare business, and they evaluate data from interviews, surveys, field notes, websites, or journal articles.
From the below figure 1, Nvivo is divided into 7 (seven) main parts, [1] List View, [2] Quick Coding bar, [3] Detail View, [4] Status bar, [5] Find bar, [6] Navigation View, [7] Menu bar the interface is user friendly.
Figure 1: NVivo workspace sectioned view
Figure 1 shows the navigation view, where the import section contains files, file classification, and Externals as subcategories; we might wonder why we need all this in NVivo but the uses are explained as follows.
In NVivo, the data we want to evaluate and our thoughts about the data which we have stored in files, Can be imported as PDF, Microsoft word, Picture, Memo, framework matrices, Audio and Video as the file under study.
Figure 2: Positions of an Import Files
To manage some aspects of your files, we will utilise file classifications. However, this will help us organise the files and reduce the number of files, making it easy for us to locate them quickly, as shown in figure 3.
Figure 3: how files are classified base on a given criteria
Books and home videos are examples of where externals are used because of their large size and cannot be imported into NVivo.
We use external only when we need to outline, describe or summarise a book's chapters or explain a particular moment from the movie. Additionally, other material can then be coded or annotated.
After creating the content on the external, we can now perform our coding to collect information using a subject or theme as listed below.
This part of NVivo is where content-coding is done, like creating a table of content
NVivo offers several options for file coding. We have two options: Establish our node structure first, then program at the already-existing nodes, or construct new nodes as we go through our files.
To work in NVivo, coding are central to understanding and working; they enable us to compile relevant information in one location where we can search for developing trends and ideas; coding lets us collect relevant data in one location and search for developing trends and ideas as shown in figure 4.
Figure 4: The selected text is Coded with the player's biography
Sentiment coding identifies feelings of tenderness, sadness, or nostalgia in data and then scores them, using what we know as sentiment score.
The link between two project objects is defined by a particular form of code called a relationship.
Relationships document assumptions we have made about the connections between the elements in our project. We could establish associations to demonstrate the connections between concepts and research participants.
Relationship type provide information about the relationships and characteristics in data. We can create our own relationship type or use the system-generated "Associated" relationship type.
We have three basics of creating a relationship type in NVivo, which are as follows:
Cases store information for a given person, location, or other units of analysis. We can view all this information coded in a case by opening it.
Depending on the research topic case might not be used. However, NVivo cases must be involved because it is from the unit of analysis, as shown in figure 5, which can be a single participant or an organisation.
Furthermore, we create cases in other to assign them, classifications, and attributes.
Figure 5: Case created and about to be classified
Creating a sub-folder to store cases makes them easy to assess when necessary and will help organise our cases as shown in figure 6.
Figure 6: After a case has been classified as a person with an Attribute
Memos are particular documents that let us keep track of our thoughts, revelations, and interpretations and develop an understanding of our project's subject matter. They give us a technique to keep our analysis distinct from (but connected to) the source material.
Framework matrices can assist us in acquiring an understanding of our data and can help us handle massive numbers of interview data by breaking it down into more manageable portions.
A framework is set up with the cases in rows and code in columns, and we can write a summary for each case and code.
we might wish to annotate an extract to investigate and develop a theme or subject. Annotations can be used to make notes about a specific phrase or flag content for further investigation, even if memos may be a better option for collecting our introspective views about a subject.
Annotations might be utilised to take notice of the tone of voice or body language used at a specific moment in a conversation.
Choosing how several materials interact to one another can be a crucial step in the analytical process. For instance, an issue brought up in an interview may serve as an illustration of something we have read about in the literature.
Use "see-also" links to keep track of these relationships. Consider adding a "see also" link to Point out inconsistencies across different files or inside a specific file.
Static sets are data collection that was manually selected, which is not repeated or created again.
Project extracts are grouped into sets. Data files, codes, cases, memoranda, framework matrices, search results, and coding matrices are a few examples of what can be mapped as a set.
Sets are used to organise work, gather objects connected to a specific subject, create photo galleries, or describe the parameters of a query or visualisation. Once a set is formed, we can quickly run various studies.
If Project items currently fit the search parameters we have established for each set that are included in dynamic sets. For instance we can, all of the project's codes, cases, connections, and coding matrices can be searched.
Queries help us investigate our data and test theories. we can look for and investigate any code extract or phrases and ask questions, even look for trends in our coding, and assess the team's coding consistency, e.g., Word frequency query and so on.
The Query Results folder is the default location where we can save query results as a code or coding matrix; this is a valuable place to save result codes until we wish to add them to our code hierarchy.
To observe the coding intersections between two lists of data objects in our project, use coding matrices.
For instance, a coding matrix may be used to compare what big and small companies have to say about various types of the transaction costs.
Visualisations in Nvivo can assist us at every level of the research process and complement the iterative nature of qualitative research, and we have different types of visuals that will describe our analysis at a glance e.g. Chart, Hierarchy Chart, and comparison diagram.
In qualitative research, visualisation tools like maps are crucial. We can map our code extract to demonstrate relationships in the data or explore our ideas concerning the data.
The Formatted Report Wizard will walk we through creating and executing a formatted report. We may want to generate and execute a text report with the help of the Text Report Wizard.
We may want to create our formatted reports using the report designer manually. Either the Formatted Report Wizard or the Report Designer may be used to produce reports with the same material.
As we can see NVivo can be used to extract hidden information and pattern from data and can be used to organise, analyse, visualise and report on qualitative data.
However, researchers or data analysts can use NVivo to create incredible insight while reflecing on their thoughts on a given data.
Finally, depending on the type and size of the data we want to analyse, different approaches can be applied.
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