Learn how to use text searches in NVivo for MAC:
Summary
This video tutorial on NVivo 15 for Mac explains how to use text search queries to efficiently locate specific data within large datasets. The presenter highlights two main reasons for performing text searches: to quickly find relevant field notes or transcripts and to conduct preliminary searches for coding purposes. The tutorial covers the steps for creating a text search query, using Boolean operators, and saving results as codes in the coding hierarchy for better organization and context.
Highlights
- 🔍 Text Search Queries: Text search queries help users quickly locate specific information in large datasets by typing in keywords, such as “pumpkin,” to find all related files.
- 📊 Preliminary Search and Coding: Users can conduct preliminary searches to identify important words, which aids in generating codes before manually coding all files.
- ⚙️ Creating and Saving Queries: The tutorial demonstrates how to create a query, use Boolean operators for stemmed words, and save results as codes in the coding hierarchy for easy access and organization.
Key Moments
- Introduction to Text Search Queries00:00
- Overview of NVivo 15 for Mac and its text search queries feature.
- Text search queries are useful for navigating large datasets and locating specific field notes or transcripts.
- Example provided: searching for the word “pumpkin” to find relevant data.
- Generating a Text Search Query00:35
- Steps to create a text search query using the Explore tab.
- Explanation of including stemmed words and using Boolean operators for more comprehensive searches.
- Demonstration of searching for “draw” and its variations (drawing, draws, Drew).
- Analyzing Search Results01:58
- Overview of how to view and summarize files that meet search criteria.
- Discussion on accessing references and examples from the search results.
- Importance of reviewing context to determine relevance of results.
- Saving and Coding Results02:43
- Instructions on saving search results as a new code in the coding hierarchy.
- Tips for naming codes to maintain clarity and track the origin of queries.
- Example of creating a code titled “draw search” for better organization.
- Cleaning Up and Contextualizing Codes03:27
- Process of reviewing and refining coded items for accuracy.
- Methods to access original files for context and make decisions on coding relevance.
- Explanation of spreading coding to narrow or broad contexts for better understanding.
- Best Practices for Query Results05:33
- Reminder about saving query results to the coding hierarchy for better management.
- Limitations of saving to the default query results folder regarding coding and uncoding.
- Final tips on maintaining organized and meaningful codes for analysis.
