Here are three ways AI can help educators in regards to course content:
Grouping = often, I create a lot of content because I know the field I’m teaching well and there’s a lot I can say about it. This can result in a situation where the information I want to share (e.g., slides) is fragmented, containing many topics, ideas, and concepts. AI can take a look at the overall content and say, “here are logical groups that your material falls under”. This can help me better understand and structure the information I want to convey to students.
Compression = AI can help me trim out parts that are less relevant, too challenging for the study level, or not connected/aligned with the other parts (e.g., isolated content without a group). This can simplify the presentation and help me clarify what is essential that students have to know, what they benefit from knowing, and what is nice to know. Even when I would be the better judget of this categorization than AI, the fact that AI provides an initial opinion already has value, because, again, it provides a structure or scaffold for me to operate.
Gap detection = AI can help identify missing points, as it knows state-of-the-art and trends in many fields (this wasn’t a case with the earlier models, but the current models are very up-to-date, e.g., Gemini). This makes them useful “idea generators” for fast-moving fields. Again, I as the educator exercise my judgment on whether some trending topic is relevant enough to include, but AI provides a clear service by identifying possibly interesting candidate topics.
In all these techniques, the educator of course needs to “stay with it” and exercise their own judgment. This is hybrid work, collaboration between AI and educator.
ps. Notice also that none of these were, “generate my course content for me.” Which, of course, could be a use case, too!