Improving-Learning

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. ...

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. ...

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. ...

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? ...

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. The idea of a “generative textbook” is that, instead of containing instructional content, it provides the learner with a series of prompts they can use to elicit information from a large language model like ChatGPT. Here’s a brief example to clarify what I mean. ...

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. Since ChatGPT’s meteoric rise to popularity, I’ve constantly been amazed by the creative ways people have imagined to make use of generative AI. For months now it feels like each week I read about some new way generative AI is being used that just completely blows my mind. For example, my son who is studying cybersecurity recently told me prompted ChatGPT along these lines: ‘You are the hiring manager for a cybersecurity position at a large company. Conduct a mock interview with me, asking me ten conceptual questions. After I have answered all the questions, give me feedback on my answers. Then ask me ten technical questions. After I have answered all the questions, give me feedback on my answers again.’ My son tells me this exercise was incredibly helpful and he plans to do it several more times before having a “real” interview. ...

If you can remember the web of 30 years ago(!), you can remember a time when all it took to make a website was a little knowledge of HTML and a tilde account on the university VAXcluster (e.g., /~wiley6/). While it’s still possible to make a simple website today with just HTML, making modern websites requires a dizzying array of technical skills, including HTML, CSS, JavaScript frameworks, databases and SQL, cloud devops, and others. While these websites require far more technical expertise to build, they are also far more feature-rich and functional then their ancestors of 30 years ago. (Imagine trying to code each of the millions of pages on Wikipedia.org or Amazon.com completely by hand with notepad!) ...

Treadmills are iconic pieces of exercise equipment for the wrong reason. They’re famous primarily for sitting unused in basements and spare bedrooms all across the country. These treadmills go unused despite having some pretty sophisticated features, including embedded video trainers who talk to you during your workout, realistic imagery of running routes, automated speed and incline adjustment to match the imagery you’re seeing, and even a “cruise control for your heart” that monitors your heart’s beats per minute and adjusts the difficulty of your run in real-time to keep you in your target heart-rate zone throughout your workout. However, all the amazing features in the world can’t improve your fitness level if you never get on the treadmill and use them, which apparently many owners don’t. ...

[caption id=“attachment_7070” align=“alignright” width=“167”] https://cheezburger.com/8016802816.[/caption] Do you know the #nailedit meme? In its most common form: Someone sees a recipe or craft online. They try to recreate it. Things go terribly, comically wrong. They graciously post the results online, allowing us all to take joy in the degree to which they absolutely #nailedit. Part of what makes these memes great is that they’re so relatable. Everyone has been there - faithfully (we believe) following a recipe or other set of instructions (looking at you, Ikea), only to have things go horribly wrong. It really can be difficult to get the desired results even when you’re following a step-by-step recipe with illustrations. ...

I’ve been writing this article 30 minutes here and 60 minutes there for several months (Wordpress tells me I saved the first bits in March). I’ve probably deleted more than is left over. It’s time to click Publish and move on. This article started out with my being bothered by the fact that ‘OER adoption reliably saves students money but does not reliably improve their outcomes.’ For many years OER advocates have told faculty, “When you adopt OER your students save money and get the same or better outcomes!” That claim is fine enough if your primary purpose is saving students money (which feels like the direction that OER and ZTC degree advocates have been moving for some time now, and explains why I don’t feel like I’m part of that community any more). But if your primary purpose is improving student outcomes, the shrugging “sometimes it works, sometimes it doesn’t” uncertainty is utterly unacceptable. So I’ve been thinking more than I’d care to admit about the relationship between OER and improving student outcomes. This thinking, with all the benefit that hindsight affords, doesn’t always reflect well on some of my earlier research. But that’s no reason not to share it. ...