If you’ve heard the buzz about the research-assistant from Google, you may be wondering how to use Notebook LM for instructional design. The strength of this AI tool is that it quickly synthesizes facts and concepts from various sources to find connections and accompanying insights. As users upload their media files, Notebook LM summarizes each one.
As with other AI tools, this one comes with a familiar warning: “NotebookLM may sometimes give inaccurate responses, so you may want to confirm any facts independently.” In addition, NotebookLM will omit some information from your sources when it generates content.
How It Works
Users can upload various document types, pasted text, and audio files, and link to websites and YouTube. It will then generate a summary of the information. It also creates AI-generated questions, which may or may not focus on critical points you want to emphasize.
Selecting a question creates a response, which you can save as a research note. You can also enter questions in the Chat feature, generating additional responses, which you can save as a note. The default screen is a set of summary research notes for each notebook, presented in a card interface. In the example below, I uploaded one chapter, “Make the Abstract Concrete,” from my book Visual Language for Designers. Although NotebookLM’s strength is synthesizing and connecting multiple sources, I experimented with both multiple and single-source notebooks.
To generate documents from your sources, select Notebook Guide. There, you can create an FAQ, Study Guide, Table of Contents (like an outline), Timeline (often not relevant), and Briefing Doc.
Audio Overviews
The feature that fascinates everyone is the Audio Overview option. NotebookLM creates a more or less realistic podcast conversation between two AI voices that discuss and explain the key points of your research notes. These are called “deep dive” discussions. You can try to customize the discussion to control the focus of the conversation.
Use in Learning Design
What are the uses of Notebook LM for instructional design? Although the tool appears to be designed with students and faculty in mind, the functionality can help learn designers too. I’m too cautious to recommend it for final course creation. It won’t provide the variety of instructional strategies and creative thinking required to meet varied learner needs. Also, you may find it is not accurate and will undoubtedly omit some information. In addition, Google advises to “Avoid uploading documents you don’t have the applicable rights to.” With all of these caveats, I still see a few possible ways to use NotebookLM to speed up or enhance your workflow.
1. Team Collaboration
Share a Notebook with team members. Everyone can then upload relevant documents for a project, such as SME slides (as Google Slides), related research, and a recorded SME lecture. As noted, every source file triggers a summary and suggested questions, which you can save as Notes. Create a Briefing Doc or a Table of Contents for the team to use as input to your project. As always, check for inaccuracies.
2. Content Curation of Learning Resources
You can use NotebookLM to provide learning resources to participants before a course to ensure everyone has the necessary background knowledge. Using it for content curation can also work as a continuous source of learning after a program ends or instead of a course. Learn more about Content Curation (listen or download the transcript).
3. Audio Overviews Before a SME Meeting
If you’ve ever attended a meeting with expert SMEs and felt utterly lost, the Audio Overview feature would be helpful, especially when you’re short on time. Audio overviews get the most attention because they have an uncanny ability to sound like a realistic conversation between two AI voices. They’ll briefly explain the topic in language that is easy to understand, making the experience painless.
4. Overviews for Participants
Can learners benefit from audio overviews? Although I’m hesitant to use these for final products, you could check all the citations and the information, then use them to bring all participants up to the same level. An audio overview might be sufficient for busy participants to orient them to a subject if they don’t have the proper background. A workaround I’m experimenting with is using only one master source to create the overview or podcast. A sole source combined with the customization feature will increase the likelihood of including the essential information.
5. Discussion and Assessment Questions
You are probably familiar with prompting ChatGPT to write discussion or assessment questions. You can make the same request in NotebookLM. The quality of the responses seems similar, meaning you’ll want to omit some questions, tweak others, and accept some. The significant advantages of NotebookLM is that it suggests questions from the start and provides a numeric citation for each question and response. Clicking on the citation number brings you directly to the source text, making it easy to check for accuracy. The other advantage may be that the questions come from a synthesis of multiple sources.
Conclusion
You may not think of your work as research-oriented, but when you are unfamiliar with a topic, using multiple sources, or working on a team, NotebookLM may help to organize and accelerate your process. Also, there are some uses for learners, particularly as a content repository for enhanced learning and for generating discussion or assessment questions.
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