Purpose
NVivo is a qualitative data analysis software that is commonly used in various fields such as social sciences, education, and market research. It is specifically designed for researchers to assist them in the process of collecting, organizing, and analyzing unstructured data. The software provides several tools for data collection, mapping, and analysis that allow researchers to efficiently manage and analyze large amounts of data. NVivo can be used to analyze various types of data, including text, audio, and video, and it supports the use of mobile devices for data collection.
Overall, NVivo is a powerful tool that enables researchers to efficiently collect, organize, and analyze unstructured data from various sources. It allows them to identify patterns and themes in their data, making it an essential tool for research design, mobile data collection, mapping, and data analysis.
Course Objectives
- Data collection: Collecting data from various sources such as surveys, interviews, social media, and web scraping. NVivo supports the use of mobile devices for data collection, which allows researchers to collect data in the field.
- Data organization: Organizing and structuring collected data using coding and annotation tools, allowing researchers to identify patterns and themes in their data.
- Data analysis: Analyzing data using various tools such as text mining, sentiment analysis, and network analysis to identify patterns, themes, and relationships within the data.
- Data visualization: Creating visual representations of data, such as maps, charts, and network diagrams, to help communicate the results of the analysis.
- Collaboration: Sharing data and annotations with other researchers and stakeholders, which allows for a more efficient and collaborative research process.
- Mobile data collection: With the integration of mobile devices data collection, NVivo allows researchers to collect data in real-time and in the field, providing more flexibility and opportunities for research.
- Data Governance: Enforcing data governance rules, such as data lineage and data quality, to ensure data integrity and compliance.
Overall, the main objective of using NVivo for research design, mobile data collection, mapping, and data analysis is to efficiently collect, organize, and analyze large amounts of unstructured data, and gain insights to support research and decision-making.
Target Audience
- Social scientists: Researchers in fields such as sociology, anthropology, psychology, and political science who use NVivo to analyze qualitative data from sources such as interviews and surveys.
- Market researchers: Professionals who use NVivo to analyze customer feedback and social media data to gain insights into consumer behavior and preferences.
- Education researchers: Professionals who use NVivo to analyze data from classroom observations and student interviews to gain insights into teaching and learning.
- Healthcare researchers: Professionals who use NVivo to analyze data from patient interviews and focus groups to gain insights into healthcare issues and patient experiences.
- Humanities scholars: Researchers in fields such as literature, history, and philosophy who use NVivo to analyze qualitative data from sources such as primary texts and historical documents.
- IT professionals: Professionals in IT departments who use NVivo to automate data management tasks, enforce data governance rules, and provide data access to different stakeholders.
Overall, the target audience for NVivo for research design, mobile data collection, mapping, and data analysis includes anyone who needs to work with qualitative data to gain insights and make data-driven decisions.
Program Outline
Topic 1. Introduction to NVivo
Overview of the software, its features, and its capabilities.
Topic 2. Data collection
Techniques for collecting data from various sources such as surveys, interviews, social media, and web scraping. How to use mobile devices for data collection.
Topic 3. Data organization
Techniques for organizing and structuring collected data using coding and annotation tools.
Topic 4. Data analysis
Techniques for analyzing data using various tools such as text mining, sentiment analysis, and network analysis.
Topic 5. Data visualization
Techniques for creating visual representations of data, such as maps, charts, and network diagrams.
Topic 6. Collaboration
Techniques for sharing data and annotations with other researchers and stakeholders.
Topic 7. Mobile data collection
Techniques for collecting data in real-time and in the field, providing more flexibility and opportunities for research.
Topic 8. Data Governance
Techniques for enforcing data governance rules, such as data lineage and data quality, to ensure data integrity and compliance.
Topic 9. Advanced topics
Depending on the course, this section may cover additional features of NVivo such as working with multimedia data, advanced data analysis, and integrating data from other sources.