Generative Textbooks – A Brief Example
There was some interest in my post yesterday about what I called “generative textbooks,” but based on people’s comments I don’t know that I explained the idea very clearly.| improving learning
There was some interest in my post yesterday about what I called “generative textbooks,” but based on people’s comments I don’t know that I explained the idea very clearly.| improving learning
I’ve limited myself to one hour of writing for this post, so it’s more a collection of thoughts than a coherent narrative. I expect I’ll have lots more to say on this topic in the future. For now, I just want to get the beginnings of this idea out into the world, together with some initial implications.| improving learning
tl;dr – Go play around with generativetextbooks.org and let me know what you think.| improving learning
“Generative AI models don’t understand, they just predict the next token.” You’ve probably heard a dozen variations of this theme. I certainly have. But I recently heard a talk by Shuchao Bi that changed the way I think about the relationship between prediction and understanding. The entire talk is terrific, but the section that inspired this post is between 19:10 and 21:50.| improving learning
Last week I had the amazing opportunity to speak at the 3rd Annual AI Summit at UNC Charlotte. The entire event was wonderful and the organizing team were terrific. My keynote wasn’t recorded, so I thought I would serialize it across a series of blog posts. This post is the first in that series, and this section of the talk was titled Writing Is Thinking.| improving learning
Back in the mid-1990s I read an absolutely amazing article that had a lasting impact on my thinking. Despite looking for it several times over the years, I’ve never been able to find it again. This was the era of 14.4k, 28.8k, and 56k modems, when we used our home landlines to dial up and connect to the internet. The article’s main argument was that, just as architects have to understand and account for gravity in their designs of bridges and buildings, web architects have to understand a...| improving learning
Human Teachers and AI Teachers| improving learning
The OELMs source code has been updated on GitHub to include better documentation to help you get started as well more examples of content and activities. As you may remember from last week’s post about the OELMs architecture, the design goal of Open Educational Language Models is to combine the technical power of generative AI with the participatory power of open education. To help you see how that works, the initial implementation in GitHub is sub-optimized in order to make it easier to u...| improving learning
Or, in which Generative AI meets OER meets Reusable Learning Objects.| improving learning
Since the advent of ChatGPT it seems like everyone is talking about Bloom’s 2 sigma problem. The quick version is this: the average student who is taught using a combination of (1) one-on-one (or small group) tutoring and (2) mastery learning performs about two standard deviations better then the average student taught in a typical classroom setting. The “problem” in Bloom’s 2 sigma problem is that, while we know that this dramatic improvement in student learning is possible, we don...| improving learning
Prelude| improving learning
This is the video recording of my recent talk, “Why Open Education Will Become Generative AI Education.” I previously published some of the content in written form as How Generative AI Affects Open Educational Resources and Why Generative AI Is More Effective at Increasing Access to Educational Opportunity than OER.| improving learning
