Information Age vs Generation Age Technologies for Learning

It is absolutely critical that everyone who cares about technology-mediated learning understand this point. There is a seismic shift in perspective necessary from pre-generative AI technologies to generative AI technologies. It requires changes in the way we think about everything - from pedagogy to supporting infrastructure. I’ve been writing and speaking about this for months now, and I’m not alone. Here’s how the CEO of Groq put it: “Think about it this way: we were in an information age where you would make copies of data with high fidelity and you’d distribute it. That’s what the internet was. That’s what mobile was. But that’s also what the printing press was. They’re effectively the same type of technology, just at a different scale. And even though it was the same type of technology at a different scale, even that was hard for our intuitions to adapt to. But generative AI is not an information age technology - because you’re not making copies of something. You’re making something new in the moment. And the difference is when you’re making something new and in the moment you need *compute* to do that. It’s not about retrieving something from a hard drive, and doing a little bit of compute and sending it out. You’re creating it in response to a particular question.” ...

April 29, 2024 · David Wiley

An "AI Student Agent" Takes an Asynchronous Online Course

The earlier we all start thinking about this problem, the sooner we can start generating ideas and potential solutions. Given the magnitude of impact generative AI is having and will have in education (and many other aspects of life), I’m working with some diligence to keep up to date with developments in the field. Recently, I noticed how a couple of the emerging capabilities of generative AI will come together in the future in a way that will impact education much more dramatically than I am hearing anyone talking about currently (if I’m missing this conversation somewhere, please help me connect to it!). But before I give away the punch line, let me share the individual pieces. Maybe you’ll see what I saw. ...

April 18, 2024 · David Wiley

Reflections on a Conversation about a US National Open Education Strategy

I recently attended one of the community meetings discussing whether or not a national open education strategy is needed in the US. There were two other meetings I did not attend, so I can’t speak to them. But here are my quick takeaways from the meeting I did attend: There was enthusiasm about the idea of a national open education strategy. There were very few expressions of doubt about the need for a strategy (beyond those I expressed). It felt like everyone who came to the meeting was already on board with creating a strategy before we began discussing its merits. No one knows what the purpose of such a strategy would be. There was no discussion of what the goal would be of creating a national open education strategy. There were several times during the meeting when attendees were asked to contribute their thoughts on a range of topics. Each time I asked some version of “what goal would this strategy be trying to achieve?” No one seemed interested in discussing the question, neither the session moderators nor the participants. I asked the question repeatedly because it’s impossible to create effective strategy without a clear goal that you’re trying to achieve with the strategy. I predict a national “open education” strategy would actually end up being something like a national zero textbook cost strategy. The sense I got is that reducing textbook costs isn’t enough anymore, the advocacy has moved on to eliminating them. For many years now what people call OER advocacy has actually been “zero textbook cost” advocacy. This is partly because policymakers don’t understand openness, but they do understand costs. Consequently, in order to get a grant program created in your department / institution / system / state / country you have to focus on the amount of money the program will save constituents. So for the last decade or so there has been a lot of energy devoted to either “OER programs with a laser focus on cost savings” or “zero textbook cost” programs. The US Department of Education’s Open Textbooks Pilot program is a great example. It “supports projects at eligible institutions of higher education that create new open textbooks and expand the use of open textbooks in courses that are part of a degree-granting program, particularly those with high enrollments. This pilot program emphasizes the development of projects that demonstrate the greatest potential to achieve the highest level of savings for students through sustainable, expanded use of open textbooks in high-enrollment courses or in programs that prepare individuals for in-demand fields” (emphasis added). Expect to see more of this language - probably switching from “highest level of savings” to “eliminating costs” - in any future strategy. The strategy may have little to nothing to do with openness. Because there are many ways to eliminate textbook costs or “achieve the highest level of savings for students_”_ without using OER (e.g., library resources, traditionally copyrighted resources online, etc.), a national “open education strategy” may not actually end up being about open education at all. The one place openness might make an appearance is in language like, “one way to eliminate textbook costs is to adopt OER.” But it seems likely that OER and openness would play a supporting role to the real star of the strategy, eliminating textbook costs. A national zero textbook cost strategy would be the beginning of the end for the OER movement as we know it. I’ve written before about how the adoption of “zero textbook cost” policies undercuts the sustainability models used by OpenStax and other large OER publishers, who sustain their efforts through sales of related products like homework systems and printed editions of their books. If some version of the zero textbook cost policies that exist at select institutions were to be implemented nationally, it would be a death knell for major OER producers and maintainers. OER advocates may see their national strategy work backfire much sooner. Many OER advocates are vocal critics of inclusive access and equitable access models, and the US Department of Education is poised to prohibit schools from automatically billing students for their course materials. However, inclusive access and equitable access aren’t the only models that automatically charge students a fee for their course materials. Many institutions charge students a fee associated with their OER courses as a way of funding the institutions’ OER efforts. For example, Kansas State University’s Open/Alternative Textbook Initiative course fee is a $10 fee that is payed by students in courses that use OER and other free, traditionally copyrighted resources. But this fee, and others like it that have helped sustain institutional OER efforts for many years, will likely be prohibited under the new rule. These are very plainly fees for course materials that are automatically billed to students. The main difference between these fees and inclusive access models being that with inclusive access its possible to opt out. (It’s almost like every time the OER community finds a sustainable model, the OER community turns around and undercuts it!) There was not a single mention of generative AI. I wrote at length a few weeks ago about how generative AI completely changes the future of OER, and specifically spelled out what that meant for a potential national strategy on open education. I purposefully didn’t raise the topic of generative AI in the meeting because I wanted to see if anyone else would raise it. Generative AI wasn’t mentioned a single time. Creating a national open education strategy in 2024 that didn’t account for generative AI would be like creating a national transportation strategy centered around horses and buggies. If zero textbook cost policies and prohibitions on models like inclusive access don’t kill the OER movement, a determination to ignore generative AI for the same cost-related reasons definitely will.

February 21, 2024 · David Wiley

Do We Need a National Open Education Strategy?

tl;dr - In order to be relevant today and in the future, a national open education strategy must (1) know exactly what it is trying to accomplish and (2) deeply integrate generative AI. WICHE is convening a series of conversations this week and next titled, “Do We Need a National Open Education Strategy?” This essay is my (very) personal contribution to that conversation. How We Got Here In 1998, when I launched the OpenContent project and the first open license for educational materials and other creative works (that weren’t software), I encouraged anyone and everyone to openly license anything they were willing to openly license. I was inspired by the transformational potential of the internet - only available to the broader public for a few years at that point - and the open source software movement. Combining open licenses with the internet’s capacity to share instantaneously around the world seemed to have the potential to revolutionize education. I had no strategy in terms of making open content easy for educators and learners to understand, adopt, or use - I was just trying to convince people the world wouldn’t end if they shared their work under open licenses (because most were convinced it would). The materials shared during those first years were totally random - essays, photos, technical documentation, etc. Similarly, when Connexions launched at Rice University in 1999, it promoted sharing individual bits of content as well. ...

February 5, 2024 · David Wiley

Thinking about AI Equity from the Perspective of Broadband Equity

There’s broad recognition that access to high-speed internet is necessary for success in school, work, etc. This recognition has led to a number of state and federal programs to improve access to broadband, like the FCC’s Affordable Connectivity Program (ACP) which provides internet subsidies to low-income households. If you believe that access to large language models (LLMs) and other generative AI will also be necessary for success in school, work, etc. in the future - as I do - it’s probably not too early to start learning lessons from programs like ACP and thinking about how we can apply them to improve access to LLMs and other generative AI. ...

January 17, 2024 · David Wiley

The Near-term Impact of Generative AI on Education, in One Sentence

Preparing to participate in a panel on generative AI and education at this week’s AECT convention gave me the excuse to carve out some dedicated time to think about the question, “how would you summarize the impact generative AI is going to have on education?” This question is impossible to answer over the medium to long-term, but maybe I could give an answer addressing the near-term? My approach to this question was to look for a different, comparable example and try to work my way into the question from that more familiar territory. The internet seems like the obvious choice here, as no other recent advance can even begin to compare to the potential impact generative AI will have. ...

October 17, 2023 · David Wiley

All work is group work now: Collaborative learning as a pedagogical and assessment framework for learning with generative AI

One of the main concerns about generative AI is “cheating,” or students getting credit for work they didn’t do. This is actually a problem that collaborative learning has been grappling with for decades. In fact, if you think of generative AI as a collaborator in a group project, there’s actually quite a lot of existing practice and literature we can tap into for guidance about using generative AI effectively in the service of learning - both in how students learn and how instructors assess. ...

September 25, 2023 · David Wiley

An Analogy for Understanding What it Means for Generative AI to be "Open"

I’ve found this to be a useful analogy for understanding what it means for generative AI to be “open”: Operating systems can be proprietary or open source. Device drivers and other kernel modules that change the behavior of the operating system can be proprietary or open source. Software programs that run on an operating system can be proprietary or open source. Foundation models are like operating systems. Fine-tuning a foundation model is like writing a device driver or other kernel module. ...

August 30, 2023 · David Wiley

Humans, Generative AI, and Learning from Copyrighted Materials

If you’re not listening to the Latent Space podcast, you’re missing some of the best thinking on generative AI happening right now. The show notes for a recent episode begin, Stop me if you’ve heard this before: “GPT3 was trained on the entire Internet”. Blatantly, demonstrably untrue: the GPT3 dataset is a little over 600GB, primarily Wikipedia, Books corpuses, WebText and 2016-2019 CommonCrawl. The Macbook Air I am typing this on has more free disk space than that. In contrast, the “entire internet” is estimated to be 64 zetabytes, or 64 trillion GB. So it’s more accurate to say that GPT3 is trained on 0.0000000001% of the Internet. ...

August 2, 2023 · David Wiley

Teaching Assistants that Actually Assist Instructors with Teaching

Last week I asked a “What if?” question about the way generative AI might change the ways that learners interact with instructional materials like textbooks. This week I’d like to ask another. I’m at the GRAILE workshop on AI and higher education in Denver today, and sitting here in this space I’m hearing things through a slightly different filter. For example, when someone mentioned teaching assistants earlier this morning, it made me think - what if generative AI could provide every instructor with a genuine teaching assistant - a teaching assistant that actually assisted instructors with their teaching? ...

July 13, 2023 · David Wiley