Summarizing Codes with AI Chat
Alex Limpaecher avatar
Written by Alex Limpaecher
Updated over a week ago

This article walks through the benefits of writing a code description, and how you can use Delve's AI Chat to create them.

Why Create Code Descriptions?

Writing code descriptions is crucial in qualitative research, ensuring thorough, insightful analysis by defining each code clearly. This step aids in:

  • Clarification and Improved Analysis - Ensures each code is distinct and has a defined meaning, preventing overlap and confusion.

  • Enhanced Communication - Facilitates clearer communication with fellow researchers, peer debriefers, stakeholders, and advisors by providing a common language and understanding. This helps in effectively sharing and discussing findings, facilitating collaborative analysis and review.

  • Continuous Analysis and Insight Capture - Encourages analyzing data as it is collected, rather than postponing analysis until the end of the project. This real-time insight capture, ensures that important observations are documented and utilized throughout the research process, preventing a backlog of unanalyzed data.

This structured approach to writing code descriptions not only streamlines the research process but also enriches the quality of insights derived from qualitative data, making it an indispensable practice for researchers.

How to Summarize Your Codes with AI Chat

It can be tempting to bypass the detailed work of writing code descriptions—be it due to time constraints, perceived redundancy, cognitive load, or undervaluing its significance—Delve's AI Chat emerges as a powerful ally. It not only simplifies but also enhances the process, ensuring your codes are richly defined and beneficial for your analysis.

Steps to Summarizing Your Codes

Step 1: Select the Code You Wish to Discuss

  • Navigate to the AI Chat interface, and choose a specific code that you want to explore or for which you need a summarized description. This could be a theme, a pattern, or any qualitative element you’ve identified in your data that requires clearer definition or further elaboration. The AI will automatically read these snippets to answer any chats you send it.

Step 2: Input Your Prompt into AI Chat

  • Navigate to the AI Chat interface and type in the prompt: “Summarize these snippets related to [Your Code]”. Make sure to replace “[Your Code]” with the actual name or concept of your code. You are not limited to this prompt, and can adjust it to fit your needs. Here are some other example prompts for creating a code description:

    • Providing Illustrative Examples

      • Provide a summary based on the snippets available. Additionally, include illustrative examples snippets from the data that exemplify the summary you wrote.

    • Creating a instructional summary:

      • Write an instruction on what sort of snippet belongs in this group. Focus on the snippets similarities.

    • Anchoring your code in a theoretical framework

      • Write a summary based on the snippets available. Situate the summary within the theoretical framework of [theoretical framework].

Step 3: Iterate with the AI

  • Once you receive the initial summary from AI Chat, review it for accuracy, depth, and relevance. If necessary, engage in a dialogue with the AI to refine the summary. This could involve asking for clarifications, requesting further detail, or providing a different tone of voice. Iteration is key to honing in on the most accurate and useful code description. Here are some some common follow ups:

    • Let's add some more examples to the summary to make it clearer and deeper.

    • Can we make the instructions a bit more friendly and concise?

    • Let's strengthen the summary's connection to the theory. Can you focus on ...

Step 4: Add the Code Description to Your Code

  • With a satisfactory summary in hand, add this description to your code.

By following these steps, you can leverage Delve's AI Chat to efficiently create detailed, insightful code descriptions, overcoming the common challenges that researchers face in qualitative analysis. This process not only saves time but also enriches the quality of your analysis, helping to capture the full complexity and nuance of your data.

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