How to use AI Tools in NVivo for Literature Review, Screening and Synthesis

How to use the new AI tools in NVivo for literature Review, Screening or Synthesis - tips and tricks:
Summary

The video discusses the new AI tools integrated into NVivo 15 for conducting literature reviews. It highlights how these tools can summarize articles, suggest codes, and facilitate data management without ethical concerns associated with primary data. The session focuses on practical applications of AI assist in literature reviews, including summarizing documents, annotating passages, conducting tech searches, and merging primary and secondary data for comprehensive analysis.

Highlights
📚 AI Integration: NVivo 15 features built-in AI tools like ChatGPT and Gemini for ethical handling of primary data in literature reviews.
📝 Summarization: The AI can generate accurate summaries of articles and passages, saving time and enhancing efficiency in qualitative analysis.
🔍 Tech Searches: Users can conduct tech searches for specific themes (e.g., pollution) across multiple documents, allowing for organized coding and deeper analysis.
🔄 Data Merging: The ability to merge primary and secondary data enhances comparative analysis, providing insights into lived experiences versus theoretical frameworks.
📊 Visualizations: NVivo allows for visual representation of data, helping users understand the relationships and prevalence of themes within their literature review.
Key Moments
Introduction to NVivo AI Tools00:08
Overview of the new AI Assist feature in NVivo 15, incorporating language models like Chat GPT and Gemini.
Discussion on ethical concerns with using primary data and how NVivo resolves these issues.
The focus of the session is on literature review and the advantages of AI tools for managing larger datasets.
Setting Up Literature Review in NVivo02:14
Introduction of the tutorial dataset related to environmental changes.
Explanation of the need for NVivo 15 for compatibility and functionality.
Reference to a previous video on setting up literature reviews, emphasizing the importance of understanding cases and classifications.
Summarizing Articles with AI Assist04:03
Demonstration of using AI to summarize articles and attach memos, enhancing efficiency in qualitative analysis.
The AI's ability to generate accurate summaries and suggest descriptive codes is highlighted.
Importance of annotations for clarity and data reduction is discussed.
Conducting Text Searches and Coding05:24
Explanation of the process to conduct text searches related to specific themes, such as pollution.
Merging literature data with primary data for comparative analysis.
The significance of coding frameworks in organizing literature for analysis.
Visualizing Data and Reporting06:41
Discussion on how to visualize data and report findings hierarchically.
Emphasis on cross-referencing data with metadata for comprehensive analysis.
Mention of a separate video focused on visualizing data within NVivo.
Using AI for Efficient Data Management10:34
Demonstration of summarizing documents and extracting key information using AI tools.
Discussion on the integration of literature and primary data for a holistic view of research findings.
Highlighting the reduction of administrative tasks, allowing more focus on intellectual work.
Merging Primary and Secondary Data22:25
Explanation of merging codes from primary and secondary data to enhance analysis on pollution.
The benefit of having a consolidated view of lived experiences versus literature findings.
Discussion on the implications of outdated literature in the context of current research.
Conclusion and Future Resources26:15
Summary of the advantages of using AI tools for literature reviews in NVivo.
Encouragement to reach out for further questions or resources related to NVivo functionalities.
Call to action for viewers to like and subscribe for more content.