Open Educational Resources

Ai: The Trend That Was Promised To Be Different Keeps Following The Path of All Other Fads

Pulling through the drive through at Panda Express the other day, I was greeted by an “Ai Ordering Assistant” where the speaker to talk to a real person used to exist. Of course, this system is not Ai. Phone-based customers service lines have had this technology for decades. The one at Panda even came complete with the admonition to “speak loudly and clearly,” just like the early phone menus did as well (I also remember a long time ago when some chain restaurant tried phone menus for taking orders over the phone).

We are well into the stage of Ai that every trend goes through: things that aren’t part of the trend – but are close enough – get labeled with the trend name to cash in on said trend. Of course, with other places like McDonalds backing away from Ai as a failure, I’m wondering how long the Panda Express option will last. For those that actually use Ai, you experience and see frustration and abandonment. At least, that is what I am seeing all over social media as well as from friends, co-workers, and family that are trying it. A few stick with it, but most give it up saying “it’s quicker to do it myself in the first place than fix what Ai spits out.”

Of course, there are those that occasionally claim that Ai saves them time. For example, Miguel Guhlin in My Ai Breakthrough. But what did Guhlin actually do to reduce something from “weeks” of work to “10 minutes?” These people rarely say. Mainly because the few that do say run into people in their field replying “THAT took you weeks? Really?” But then Guhlin goes on to explain a very time consuming process that will take more than weeks to integrate this new process into all of his tasks at work.

From what I have seen, Guhlin is an outlier. His breakthrough was asking a set of questions that most people I know started with before jumping into Ai… so since they are not having the same results, I doubt Guhlin has stumbled upon a very generalizable approach.

But this “breakthrough” is important to discuss, because we have reached the point in the Ai fad hype cycle where leaders are pulling out the “only the cool kids will do this” statements:

This is what we call “Tool Worship” in instructional design circles: trying to make the tool the center of education. Of course, Generative Ai is not a whole classification of education like “open education” is – it is more of a suite of tools with a main company like Microsoft Office and some competitors. Saying “Generative Ai Education” makes about as much sense as saying “Office Software Education.” This is really the first of three important problems with Wiley’s assertation above.

The second problem is that I personally can’t really align Generative Ai with most principles of Open Education. Heather M. Ross does a better job of expressing this in her post The Soul of Open Is in Danger: “GenAi may be fun to play with and make some tasks easier, but the cost to the values of open, the planet, marginalized groups, and humanity as a whole are far too great.” Many people have agreed with this sentiment. A few have not, and their points against her basically come down to the following (in bold):

  1. Ai generally make education more effective for cheaper, so it’s a net good. This is only really true if you cherry-pick the successes uncritically, while ignoring the massive evidence of it’s failures and ineffectiveness. The “My Ai Breakthrough” article above does have some statistics in it about how little Ai is being used and found effective, which generally match what I see in real life and online. A few like it, most don’t. And the truly effective services or tiers are rarely cheap – not to mention that those that are will unlikely stay free or low cost as time goes on. Of course, you also only see the high cost options as cheaper if you also cherry-pick the results that say they save time and ignore the masses that point out they do not.
  2. Does Ai Really Cause Harm? I would say those killed or injured by self-driving cars, job applicants skipped over by application sorting Ai, those being bullied into suicide by Ai bots, and many, many, many other people harmed by Ai would like a word. Questioning whether Ai harm actually exists in this day and age is…. something.
  3. Ai environmental damage isn’t that serious when compared to overall global climate issues. This might sound like a line straight from a Big Business shill. It actually is (it was said to Chris Gilliard on Bluesky this year). But it is surprisingly coming from multiple people that are not fans of Big Business. It is an argument used to gloss over local environmental damage in favor of the “Whataboutism” of global issues. I’m so sure the cities that saw their lakes suddenly sucked dry when the new data center went on line really care about Big Business arguments about personal habits being more dangerous. And the idea that renewable sources will take up the energy challenges? Highly unlikely to happen in anyone’s lifetime (including Gen Z). We need to deal with environmental problems TODAY, not some magical future that may or may not happen.
  4. Damage to marginalized communities would be lessened if they would speak up. Except, they already are speaking up – a lot of them for a long time. It boggles the mind that people want to act like there is a need for the marginalized to speak when they already are. Most of them are not wanting to be used for training Ai data. A few don’t mind, but they are generally outliers in their community. The fear of abuse runs centuries deep, and just saying we need to listen and amplify won’t calm those fears. Listening and amplifying have led to abuse as well – just look at U.S. Politics for examples of that.
  5. Ai doesn’t “copy” work, it “learns” from it, so Ai copyright violation is not a thing. This is a popular argument, but still misses the point that Ai is a computer program that does not copy or learn. It processes information and stores resulting variables in a database that doesn’t operate like an organic brain (because it doesn’t forget things). You can’t use copyrighted content to process computer data (which is what Ai is) without compensating the copyright owner fairly in most cases. Even if you go with the problematic concept of Ai as “learning,” all learning is subject to copyright still. You have buy books and videos. Libraries pay a fee to offer their materials to multiple people. So do video services like Netflix. When you borrow a book from a friend, that friend still paid for that one copy. Popular teachers, musicians, artists, etc that try to get too close to copying what they they were trained on run the risk of getting sued for copyright infringement. And many content creators have found their copyrighted ideas coming out of Ai, because yes Ai does sometimes copy and reproduce content.
  6. Humans are all influenced by ideas, so Ai should be able to as well. The problem is, Ai is a computer and does not suffer from memory loss or forgetfulness like humans do. Computers have the ability to process and store information perfectly – humans do not. In reality, human brains don’t store or process information like computers do, so any comparison between human brains and the computers that make Ai are just outdated science.

Some of the Ai enthusiasm would be better served by avoiding so much “whataboutism” in response to legitimate concerns.

Ross goes on to compare trying to change OpenEd to GenAiEd with colonialism. Her critics accused her of doing the real colonialism for… reasons that are unclear. She said “get off our field” and that was inexplicably changed to “your field” in the response. There are huge important differences between “our” and “your” (assuming it was meant as singular in the criticism).

Anyways, the third problem with Wiley’s statement is the claim that “people who care deeply about affordability, access, and improving outcomes will shift their focus away from OER and toward generative Ai.” You can’t really blame Wiley for this, as this myopic, siloed view of education is often found throughout academia. For my students, any of them that have ever used Ai for an assignment have failed that assignment massively. These assignments existed before ChatGPT came on the scene – there is just no way to use Ai on them and score very high. Ai just can’t handle the assignment, and probably never will be able to. I try to encourage my students to avoid using Ai for those assignments, but some still do and find out why. I also use OER for my classes. Does this mean that I don’t “care deeply about affordability, access, and improving outcomes” because I have to tell my students to avoid Ai? Give me a break. I have a different type of class than Wiley does. I know many, many educators like me. Generative Ai is NOT a solution for every class that uses OER currently.

This is what “worshipping the tool” means. You place it as a central starting point for your view of education and build everything around it. This happened with blogs, social media, virtual worlds, MOOCs, learning analytics, etc near the downfall of each of those fads. All of those concepts are still around – just none of them are the future of education, open or otherwise. Like all other tools, they are just one of many, many different ways to accomplish learning.

Building a Self-Mapped Learning Pathways Micro-Lesson: H5P vs Twine

One of the issues that I often bemoan in relation to creating Self-Mapped Learning Pathways lessons is how there really isn’t simple technology that will let you quickly build non-linear, interactive, open-ended content. I have been keeping my eye on H5P, and building a few things with Twine or SAP Chatbots, so I decided to take them all out for a spin in trying to build something that allows for learners to build their own learning pathway.

So how did it turn out? In general, there were some interesting affordances of the tools, but they still don’t get me to where I would like to be with the lesson design. And none of them really did much for the open-ended part. But I did create some OERs that you can use if you like (details at the end). First, some of the process.

SAP Chatbots have some pretty robust tools for creating interactive chats. In theory, I think I could have built everything within a bot, but didn’t get around to it this time because it would have taken some deep dives. I’m also not convinced that a chatbot interface is the way to go, but more about that later. I decided to use a chatbot at a specific point in the learning pathways lesson to help learners think through modality options.

With H5P, I used the Branching Scenario and Course Presentation tools mainly. With H5P, you get a more intuitive interface that looks nice (and we are told is completely accessible), but very little options for customizing anything. I couldn’t change the look, program variables, or embed things like the SAP Chatbot anywhere into the lesson. So I came up with a way to get around that. It seems to be a good basic option for those that don’t want to get into the weeds of programming variables, but it still is mainly a way to create a Choose Your Own Adventure book. Which is what some call “personalized” these days, even though its really not.

With Twine, there were many options to customize, add variables, manipulate code, and embed what you want. I am not sure how accessible everything in Twine is, but it does give you a lot more flexibility for customization. Also, the option to set variables means you can let learners choose some options that would reformat what they see based on their selections. I did a little bit of that, but I need to dig into this some more. Since I could embed more things in Twine, I was able to build the entire lesson from beginning to end in Twine (with a chatbot embedded near the beginning, and an H5P assessment embedded at the end of one modality).

So I ended up with two different versions of the same lesson that will allow you to compare the two options. Before I share those, a few thoughts on building the lesson.

It took a long time to think through the options and build the simple choices that I did below. A lot of this could be attributed to the fact that I was building an entire lesson from scratch. I decided to dig some into Goals, Objectives, and Competencies because so many of my students struggle with these concepts. Someone that already has a complete lesson built would probably save a lot of time on that front.

Also, I will say that I ran out of time to re-record the videos. There are some mistakes and poorly chosen words here and there (like me saying “behaviorist” when I mean “behavioral”). Maybe I will fix that in the future.

Ultimately, it a took a lot of time to build the options and think through how to navigate the options, while also trying to find ways to get people who choose to take their own path to the tools they need. This is the open ended part I still struggle with. It really comes down to this: learners will step out on their own into the garden, or not. I can’t do much to pre-program those options into a system. I could be there in person to discuss their pathways if they needed it, but that is hard to pre-design for. You would spend hours creating the ability for each option, and then maybe have one or two people choose it.

I should point point out that this lesson uses a modification of the course metaphor idea that asks learners to choose between the “sidewalk” or the “garden” (or to mix both if they like). The metaphor is based on the botanical garden concept, where sidewalks guide those on pre-determined paths to show the highlights of the garden, while the gardens themselves can be explored as you like by leaving the sidewalk. The sidewalk represents the instructor-centered pathway, while the garden represents the student-centered, heutagogical option.

What I don’t like is the modular way all of these parts feel. I wish there was a way to combine all of the elements so that learners only see one page that re-loads new content based on their input. In other words, instead of a chatbot that tries to mimic human conversation (which some like, but others don’t), why not have a conversational interface that would ask questions and then supply new content, videos, activities, etc based on the learner input?

Plus, chatbots tend to be cloud-based, meaning everything you put in them is stored on someone else’s computer. Why can’t that be a local tool that protects your privacy better?

Anyways, these lesson are some basic ideas of what a self-mapped learning pathways micro-lesson could look like. I still feel there is more that could be done with the garden pathway in using the coding/variables option in Twine. I also utilized some tools like Hypothes.is and Wakelet in the garden modality (just because I like them), but I need to ponder more about how those tools can be utilized as a mapping space themselves.

So here is what I have:

Goals, Lesson, and Competencies Self-Mapped Learning Pathways micro-lesson in Twine

or

Goals, Lesson, and Competencies Self-Mapped Learning Pathways micro-lesson in H5P

The H5P tool does use plain html pages for the first three pages – you will see when the switch happens. Also, the Twine tool still uses some H5P activities for the sidewalk modality assessments at the end of that modality. Since this is a stand-alone lesson, I needed some kind of assessment option and decided to re-use what I had created already.

A few design notes: The Sidewalk modality is designed so that there is always a main option to choose from for those that need the most guidance, but also links to other options for those that want to skip around. My goal is to always encourage non-linear thinking and learner choice in small or large ways whenever possible. In the Twine version of the lesson, if you choose the Sidewalk option, that is what you see. If you go to the Sidewalk + Garden option, then there is code that inserts links back to the Garden section into the Sidewalk. This is some of the customization I would like to explore more in the future.  Also, the Garden and Sidewalk + Garden option have some examples and ideas for learners to choose from (basically, custom links to Twitter, Wikipedia, etc to show specific evolving searches there). This obviously isn’t much, but it is a self-determined option and therefore I didn’t want to offer too much. But maybe its not enough?

But, this is a full micro-lesson, and I am designating it as an OER with a CC Attribution-NonCommercial-ShareAlike 4.0 International license for those that want to use it:

  • The videos are on YouTube if you just want to use those.
  • I have created a zip file with all of the html files that you can download and edit. The Twine file in that zip archive (“goals-objectives-competencies.html”) can be loaded into Twine itself and edited as you need.
  • You can also download and update the two H5P files by going either to the full lesson or the assessment portion and clicking on the “Reuse” link in the bottom left corner.
  • The chatbot itself can even be forked and customized by creating an account with SAP and using the fork function on the main page for the bot.

I may even create a badge for those that complete the lesson – who knows? If you want to send a few people through the lesson, feel free to do so with the links above. If you want to send a lot of people through it, maybe consider hosting it on your server. :)