However, in the case of Nvivo, validity and reliability of the results or data representation are not sufficiently explained. Therefore, reliability and validity can be achieved by maintaining quality, rigor and trustworthiness through processes such as triangulation. One can analyze data on the basis of individual understanding and interpretation of the responses, attitudes and behavior of the participants. In majority of the cases, qualitative data is manually handled. Qualitative analysis lacks details about methods used to generate results. Scholars have studied and acknowledged the significance of meeting the condition of reliability and validity in data for generating reliable results. It is important to establish the reliability and validity of the data before going further into the procedure of using NVivo for qualitative data processing, manipulation, analysis and representation. Result summarisation using Nvivo,framework matricesĭivya Dhuria and Priya Chetty on July 20, 2017.Results summarisation using reports and extracts in Nvivo.

Data visualisation using mind maps in Nvivo.Data visualisation through concept maps in Nvivo.Data visualisation using cluster analysis.Qualitative data representation in Nvivo.Demographic data representation in Nvivo.Data analysis by generating Nvivo coding query.Importing sources and creating new documents and memos in Nvivo.Understanding issues and limitations of Auto-Coding in Nvivo.Procedure to create different types of nodes in Nvivo.Quality assessment of higher secondary education at schools using Nvivo.Explaining validity and reliability of qualitative data in Nvivo.Bibliographical data analysis using Nvivo.Managing imported data in Nvivo workspace.Importing quantitative and qualitative data in Nvivo for analysis.Outline of Nvivo workspace with three different views.Nvivo's interface and its utility in analyzing qualitative data.Approaches to qualitative data analysis using Nvivo software.

Using nvivo