Using NotebookLM to Synthesize Higher Education AI Research

On a daily basis, I devote 15 to 20 minutes to reviewing a wide range of higher education articles, research, and opinion pieces. Generally, this information is delivered to my inbox from various higher education organizations, including OLC, The Chronicle of Higher Education, Inside Higher Ed, and CCDaily.

When I wanted to take a deeper dive into AI literature and research, however, the scope of available materials became overwhelming. I needed a broad understanding of several emerging AI concepts, but I could not devote hours to reviewing the material. Upon the recommendation of a colleague, I explored NotebookLM and am currently using the free version of the tool.

NotebookLM fits my needs because it limits its responses to only the sources that I add to a notebook. These sources can include files, websites, videos, copied text, or items stored in Google Drive. I appreciate that this creates what I think of as a “picket fence” around the materials I choose to use and, in turn, the responses I receive. I also like that the tool does not share my prompts.

I think of NotebookLM as an AI assistant that organizes the information I collect. The latest version also includes an embedded search feature that makes locating additional resources more efficient. Based on the sources I provide, the tool can generate summaries in several formats, including audio overviews, videos, and infographics.

While I appreciate having all of these options, my primary use is aggregating research findings and opinions about the overall impact of AI on education, particularly higher education. I still read the original articles, but having NotebookLM organize the information and suggest overarching themes and summary ideas has been very helpful.

I also experimented with a separate NotebookLM project to generate a video. However, I was not satisfied with the results because the narration sounded too stilted, and the visuals were not engaging.