Eli Davis: Welcome to artificial Intelligence, real Talk AI with Eli, the space where human consciousness meets machine possibility.
And it is not about the algorithm alone, it is about identity, ethics, and evolving shape.
The evolving shape of learning today's guest is going to bring us clarity, depth, and something more a sense of becoming, which I think is super dope because, you know, I think that's what learning and education is about.
So our guest today is Dr. John and Philip.
Donaldson, a learning scientist who's reshaping how we think about education, design, and intelligence in the age of ai.
Jonin is an assistant professor of learning design and learning Sciences at the University of Alabama at Birmingham, where he leads the master's program and learning design and learning sciences.
his work draws from the foundational ideas from learning sciences like constructionist learning and design based research.
You gonna have to explain that for my mama.
Joan.
Joan, you real smart, but I know that she's gonna want to she's gonna be like, what is that?
Because I'm like, what is that?
All right.
And he pushes them into new territories.
Blending in complexity theory, creativity studies, and design sciences.
At the heart of his work is a powerful idea that learning isn't about acquiring knowledge.
It's about becoming someone new, constructing not only knowledge, but also perspectives, ways of thinking, and ways of being and reshaping the world around us.
He's brought that vision to his life through research on everything from AI literacy for children, to helping faculty rethink their own assumptions about teaching and learning.
And he talks, and when he talks about ai, he's not just talking about artificial intelligence, he's talking about augmented intelligence, how we can design technologies that help human beings become more deeply, beautifully human.
Jonah has taught in places like Texas a and m, Drexel, Oregon State and Noun, UAB, and his work spans from formal classrooms, faculty development, informal learning environments.
More.
He's passionate about helping people not just learn, but live more fully as designers of their own paths.
a colleague of Tiara, and Tiara is my wife.
Everybody's just been listening to these podcasts.
You know, Tiara has been on the podcast and right now that podcast probably is the one that is the most talked about because we were on there and we were just having a good time.
Through ra I was able to meet Jonah.
And as you're getting ready to find out, jonin is someone who well, I would say, has an expansive way of articulating his ideas and it was when we sat down to kind of go over how this podcast was getting ready to go, we met at a coffee shop, Joan, in.
Just blew my mind.
I, all of a sudden I came there, you know, just meeting somebody to, to interview for a podcast to get some knowledge and share some knowledge, but I feel as if when I left I had a friend, right?
So,
Dr Jonan Donaldson: Same.
Eli Davis: yep everybody.
Welcome.
Please welcome Jonah.
Go ahead, Jonah.
Is there anything else that you would like to add to that?
Dr Jonan Donaldson: No, but I think I'll weave in.
You ask about the design based research.
I'll weave that in a.
Eli Davis: Okay.
Okay.
So here we go.
So what I want to do is I want to start with a question.
I think that this is a really good way to get Joan engine starters so we can start to hear some of that, that that, that needed knowledge for so that he can share it.
So, question.
are you becoming right now and how is AI a part of that process?
Dr Jonan Donaldson: Nice.
Okay.
I like this.
Who am I becoming.
I should probably think about that more often, shouldn't I?
But I don't know exactly how to answer that except for who I'm hoping to become and who I'm, the direction I wanna go in, in terms of who I am.
And that is, I wanna I wanna change, I wanna be the kind of person who changes the world, but make it a better place.
But nobody knows.
Nobody can trace it back to me.
Nobody can say Jonah did that.
I want it to be just out there in the world like ideas and ways of doing.
And ways of being, and ways of knowing that I can be the person who puts this into the world in such a way that I don't need to claim ownership over it.
Now, there are things.
I do have some ego.
There are things I wanna claim ownership on, you know, like I ur article, I wanna claim ownership on that, right?
And being a founder of a learning sciences program, master's degree in learning science learning Design and learning sciences, I built this program.
That's my baby.
I love it and I feel a bit of ownership over
But my most important work, my most important research, and just the work I do, I wanna be the person that I can say, oh, see how my work and who I am is changing the world.
But nobody else can see it.
It's kind of like a little bit of a subversive or like under the radar situation.
And how does AI play into it though?
You know, that's a hard one because I use AI every day, all the time.
A bunch of different AI tools, generative AI tools, and it's just become a part of who I am and how I be because.
I can't really say this was the AI and this was the jonin because like it is part of me now,
So that's a hard one to answer.
Yeah, and like you said in the intro, augmented intelligence, I don't think the word artificial is right.
I think it is augmented intelligence.
Eli Davis: Have quite a few people that I engage with and them don't have.
Or have not spent the time to understand artificial intelligence like you.
What's the difference between your idea of artificial intelligence and augmented intelligence?
E Ex Explain the difference.
Dr Jonan Donaldson: I think.
The easiest way to understand it would be the idea of complex systems.
And
Eli Davis: Hold up, Jonah, you go.
You gonna start off with, so, so Jon is brilliant.
Y'all.
So when Jonah says, the easiest way to understand this is to think of it through complex systems.
That's hilarious.
Okay.
I'm sorry, Jonah.
Jonah.
I I just thought, I was like, how you going?
How you gonna say something?
That's easy, but yet you say it's getting ready to be complex.
Go ahead.
Go ahead, Jonah.
Dr Jonan Donaldson: just think about like, let's think about an ant hill.
So in an ant hill there are.
Thousands sometimes hundreds of thousands of ants doing their thing, right?
They're all interrelated, interdependent, interacting.
But in that ant hill, there are things that are kind of amazing.
Like they have ventilation, they have waste disposal, they have farming, they have nurseries.
They got really cool stuff going on, and.
If you were to study the individual ads all your life, you'd never get it.
No way to understand how that stuff happened.
And that's what I mean by complex systems.
Complex systems have this thing called emergence.
Something happens that's greater than the sum of the parts,
And if you try to understand it using any like cause and effect, thinking this caused that.
It won't get it.
It's impossible to understand how that happened if you're relying on cause and effect thinking.
So you have to think of other ways of understanding the whole and the parts all at the same
So you, the old way of science was you take a system and you break it down into smaller and smaller parts and understand each part and.
Hopefully by understanding each part and how it works, then you'll understand the whole thing.
And that does work for a photocopy machine
And probably under, yeah, it works for your car.
It works for your cell phone, but it doesn't work for complex systems like Ant
Because those ones require different way of thinking.
You have to look at the whole, but not just the whole, you have to look at all of the parts.
And the whole all at the same time.
And then you can start to get it, you can start to understand the emergence.
But once you start to see emergence and start to see complex systems in the world, then you start to see many things from a very new perspective.
So for example, this generative ai.
I've heard like high level, top level experts say it's a stochastic parrot or it's just predicting the next word.
No, it's not.
It's emergence.
There's amazing things happen that are much greater than the, some of the parts and those things, were never intended by the people who built the
I mean, just take it back to the very simple example, just language.
So generative AI started with the large language models, and of course there's other models too, like visual and multimodal models, but just, let's just say language only if a model is built just on language and how are you going to explain why it can do math?
That's emergence.
Nobody taught that thing how to do math.
And some people are thinking, well, maybe it just saw examples in the training data.
No, that's not it.
It's much greater than that.
It's doing things that are greater than the sum of the parts.
And the good news is that human beings are exactly the same.
We have all of this emergence, so in our brains we got neurons.
Synapsis, we got all that kind of good stuff, right?
But it's just like ants.
If you try to understand the neurons, you could study them your entire life and you'll never understand how an idea happens.
Eli Davis: So, so.
While you were doing that it made me think of something that I have recently started to, to have an understanding, to gain understanding.
And I think it is it through engage with artificial intelligence in which this idea, emerged.
It was, I had a best friend, I was 27.
He was 26 years old.
He, went to North Carolina a and t became a, civil engineer.
He was living in Atlanta, driving back and forth through parts of Florida.
And while he was driving back home from Florida, he got into his car hydroplaned and it hit a tree and he passed away.
Right.
Pretty much instantly.
Because of that, I remember feeling this sense of something pressure the night that he had passed away after his sister told me about it.
And what I have gotten.
Because I always felt that he had given me something.
But what has emerged due to my interaction with artificial intelligence and me engaging these kind of ideas with it is that what I always wondered was what was he giving me and what I found out that he was giving me music because it was.
Because of that incident, I went spent my last $300 on a credit card or something and bought a guitar.
And ever since then I've been playing guitar.
Not only do I play guitar, I also bring incorporate into the classroom.
I do, kind of sessions for other teachers in classroom, bringing that rhythm.
So for me, if I ask myself the question of who am I becoming right now?
And, how does AI play a part of it?
I think it, it is.
I have always had these thoughts, but I never knew where to put 'em.
Or what to do with them.
these thoughts in which you know that they're so individual that, it might not benefit asking somebody else.
Know what I mean?
engaging with somebody else, you probably could do therapy or something, but at the same time, you on time, you on you, you got a time.
You wanna be able to say this, you want to investigate this, But what, what happens here is that there is a lot of access to establishing and getting feedback from inquiry.
Dr Jonan Donaldson: I would say my reaction to that is.
You and your I, all of your ideas with the AI are generating something that neither of you could have done alone,
Eli Davis: Right.
Dr Jonan Donaldson: which is another sign that, that emergence is happening and that this is a complex system with the emergence happening where.
Things, humans plus technologies can sometimes make humans less like, it's like cold and hard and distant.
You know, there's technologies that can do that.
Well, not for everybody, but just in general.
In fact, there's many books written about like, Sherry Turkel wrote a book.
That I love.
It's a very good book.
She's from MIT called Alone.
Together, how these technologies are separating us and making us all alone and lonely, like social medias and stuff like that.
There's some truth in that, but I guess I'm, optimist or something, but I feel something different with my interactions with ai.
I feel something different there than any other technology I've engaged with in my life, except for I'd say writing and reading.
Those technologies I think have this similar ability to.
To make people to help us well together.
The technology plus US merges into this something that enables us to be, as you said in, in the intro, more deeply and beautifully human and like the book, the novel.
It is often been said, but I don't remember who said it, that all of the great philosophers, at least in the last thousand years or so, all the great philosophers have written novels.
Why?
Because in novels you can get to deeper truth than what we would experience as reality.
So that's power of a technology, a book that is more, that is really helping us become more deeply and beautifully human.
And I think AI is exponentially more potential to make us more awesome, more beautiful, more human.
But we gotta be careful.
We gotta do it right and we gotta make sure that everybody has access and we have to make sure that everybody, especially as educators, that everybody is learning how to use it.
And I guess I, I could be a little bit, a little bit radical here and say that if any educators are banning AI in their classroom, I believe they're behaving more unethically than if their students were using AI to cheat.
Eli Davis: I believe I,
Dr Jonan Donaldson: Get, gotta lean into it.
Eli Davis: yep.
I believe that to be true too.
I remember you saying that during our meeting at Starbucks, I. Not to put Starbucks out there or nothing like that, but just saying it was a meat place.
'cause you know, some of their ethical issues are starting to show their selves too.
Alright.
But here we go.
So this is a good segue into the next question.
I. On ethics and education and educational responsibilities.
So what ethical responsibilities do educators carry when bringing AI into their classrooms, especially when knowing the systems mirror and sometimes magnifies society biases.
Dr Jonan Donaldson: Actually, I'm not as concerned about that last part about Theis mirroring and magnifying because the way that I interact with the ais so for example, you could say to an AI take on the role of.
Dot.
Right.
And it does really good at that.
And and then the perspectives would be from the perspective of that role.
And so I don't really think there's a lot of biases baked into ai.
I think that there's, this is a oversimplification, but I think there's many thousands of different roles, and if you elicit the roles that align with your purposes, then you don't have to worry about those issues of baked in biases.
So I'm not too worried about that.
What I am
Eli Davis: But let's put that, let's put that out there.
That is a skill of artificial intelligence literacy that many people may not know.
Dr Jonan Donaldson: Yeah.
Eli Davis: Many people may not know that simple prompt, right?
It, it can be huge.
It can go in and it can, and it could cover or, you know, operate without those biases or with an understanding of that they are biases within this.
So, but go ahead, Jonah.
Dr Jonan Donaldson: So what I am worried about is exactly as you were saying, is educators not helping the students develop the literacies to be able to interact.
With AI appropriately, and I am worried that students without the guidance of educators are going to interact with these generative AI tools as if they are information sources rather than thinking partners.
And that is really dangerous because, I'm not worried about like hallucinations or the AI is giving you facts that are not true or something like that.
I'm worried about students thinking that the source of knowledge or truth is in the AI just as much as, I would be worried if the students are thinking the source of knowledge is a textbook or a teacher.
I want the students to think of themselves as critical thinkers where the source of knowledge is within and they're constructing knowledge.
They're not discovering it.
I'm a constructivist obviously.
Eli Davis: So what I see with teaching in schools in Birmingham City even teaching in St. Clair Clowny Moody you know, teaching at Miles College what I see is.
The, I, they have very difficult time thinking, you know, what they wanna do is they, you know, if they think on a multiple choice, they want to be able to see.
To be able to guess and see the answer so it can have that support within that thinking.
But when you ask them to think especially, you know, the upper grades in college, when you ask them to think, they, it almost as if.
The they can have a conversational tone and like
The wheels are turning.
But when you asking them to think complexly complexly with using artificial intelligence, it is, it's like you're pouring tar on the gear mechanism and it's just.
Sluggish, you know, super sluggish.
So, you know, that's what I'm running into with using artificial intelligence in side of my school.
But this also is with the adults that are teaching as well.
Dr Jonan Donaldson: I've seen something similar, but only when people are interacting with the ais, with the goal of getting to.
An answer or you know, they have this
Eli Davis: Okay.
Dr Jonan Donaldson: predetermined idea of what it's supposed to, the outcome is supposed to be, rather than, okay, we're starting on a journey together, let's do stuff.
So, so for example now this is in a school, but.
Just the power of this generativity, the human generativity and the AI's generativity.
Last year my nieces, they're like, I think they're 10 and 11 and 13 years old.
Last year they went on a camping trip with their group, and it's you know, boy Scouts, girl Scouts, this is a similar kind of vibe to their group.
So there were thousands of people there.
And so it was really important and they went there with my, with their mom and dad in an RV and drove cross halfway across the United States to get there.
And they had this awesome adventure for over a week.
Then they got back and I was talking to the oldest one on the phone and she was so excited about it, and I'm like, I have an idea.
So I pulled up a, a Google doc and I started taking notes and I, shared the Google Doc with her so she could see me as I was taking notes and I'll just telling her, just randomly tell me everything you can possibly remember about that trip.
And you don't have to be sequential, just all over the place.
That's fine.
And then I just took notes for about three hours
And then I fed that that Google doc to an ai and I said, let's write a book.
First of all, help me make, outline chapters and it did a wonderful job.
And I'm like, okay, help me write draft of chapter one.
It did a wonderful job.
Chapter two, chapter three, chapter 13.
It did all the way through.
We actually had a really robust kind of draft of a book that she would've never even imagined she could start writing, and now she's taking that draft and She's rewriting it herself and she's gonna get published.
Eli Davis: Wow.
Dr Jonan Donaldson: And I think we could just be doing that in, with young people and Polish students and just all of us.
We could be a lot more generative if we just like have these, the imagination to try to do that.
Eli Davis: Wow.
Okay.
so as I think about that, I think of my, college students at Miles and I'm like, okay, yeah, that would be great to be able to do.
How do we incorporate, those standard tests, the ideas within the standard testing that pre-service teachers have to take to become teachers, you know, the praxis and, all that stuff.
How do, can you think of anything, of way in which we can do that?
I'm asking because I was asked by the chair at Miles.
As I'm part of the, black male teacher initiative to incorporate more black men into, education.
And I was asked by the chair to, spoke to 'em and we had a session and she was like, okay, so.
What else can we give these, to them.
So we're gonna come up with a book and all that.
And what I also suggested was to give them something dealing with artificial intelligence.
Understand the artificial intelligence.
She was thinking that we need to give them a book on how to take the praxis.
I was thinking, well, if you have artificial intelligence, you gonna have the book on how to take the practice and you're gonna be able to have.
The ability to interrogate and question and develop some of the things that you need to according to the practice, you know?
So, what do you think about a idea like that, you know, incorporating it for people who have to take that test?
Dr Jonan Donaldson: So this is this is something really important in the learning sciences.
And this goes back to the very beginning of learning sciences, which started in like not too long ago, 1991.
And it all started with the idea of generativity.
Not AI generativity, but human generativity
Making, constructing this generativity is essential for learning.
So learning scientists would say nobody should ever be doing like lectures unless it's the students doing the lectures.
Nobody should ever be using a textbook unless the students are writing the textbook.
Nobody should ever be using like exams unless the students are coming up with.
Their own perhaps alternative and more powerful and more complex evaluations, because we all know that anything multiple choice is, it's not going to measure what you think it's measuring.
It's, it is really ineffective, but.
Like with ais and all this, maybe we can move past all of that.
But it all comes down to the core that generativity is where it all starts.
And so what you gotta do with the students and things like the Praxis is first of all, help the students understand that any sort of standardized test is very problematic.
And it's not a measure of you or your abilities or your knowledge or skills, it is more a measure of your ability to align yourself with basically, okay, I'm gonna be a little radical, the white male, straight way of seeing the world.
our students need to understand that these exams exist for a reason.
Now, the reason is probably valid.
We want teachers to have.
We want a certain kind of person to be a teacher and we want peop them to be able to like, have ways of thinking and being and doing and knowing and all that kinda stuff that are a very high quality, you know, situation.
Yeah.
That's probably the purpose for the these exams.
But the exams are.
Not doing that, but they're probably the best that people could come up with for now.
But we gotta move beyond 'em because they're really bad.
However, we're stuck with them now until we can come up with better alternatives.
But just because we're stuck with them doesn't mean that we have to accept like.
Everything about them as light ground truth.
No.
We need to feed all of these ideas that are in practice and stuff into our conversations with the ais, have theis help us interrogate it and work with it.
And hopefully we can do a lot of generative things together.
Your your students, can they go write a book?
And in doing so, they will be preparing for the Praxis without being subjugated by the Praxis.
Eli Davis: Okay.
Subjugated, that's a that's a huge word.
Jonah how could one be subjugated by a a system of trying to make sure that we have what we call highly qualified educators?
Dr Jonan Donaldson: If our students aren't questioning who made those decisions, who's what ideas are accepted as that is good, that is not good.
Right?
All of those things are within things like any of our exams, not just practice any of our exams.
They're built into it.
Somebody made a bunch of decisions and our students need to be questioning and problematizing all of that, and in doing so, they will come to really understand deeply better than.
As if they were just studying for the exam and just blindly accepting everything as truth.
Eli Davis: Yeah, I I I think that's something that we, that has to be worked on, especially in the areas that I've where I've been teaching because you know That social media is powerful.
So, in the the honor of your time, I do have one more question to, to ask you.
And it is can frame it in artificial intelligence or we can frame it in just existing.
But the question goes what are, what is something.
Or are some things that you're unlearning right now with the help of artificial intelligence or just, you know, through your own becoming.
Dr Jonan Donaldson: Unlearning.
Well, personally as an academic, I have a lot of training in like research methods, right?
And there's a whole lot of tradition about here's the correct way to do it.
And they have different ways of, doing different things, the statistics and case studies and grounded theories and just whatever, different methodologies.
But I have been learning to, and AI's been helping me with this to, to have my own authority to invent my own and.
I think that it's good to understand the traditions because there's good reasons for some of the traditions, but To unlearn those traditions, you have to, I think you have to be aware of them enough to push back on 'em.
Right.
And so for me, I think that's one little area, and I think the learning sciences as a field is, if I were to characterize learning sciences, it would be that wanna study what is learning, of course, not just classroom learning, but every day, all the time, everywhere.
This learning that's becoming, what is it and how?
And then second, how can you make that happen?
And my field invented this thing called design-based research, bringing it back to the intro there.
And before design-based research, there was the traditions in academia were that to do an experiment, you have to have a control group.
And then you have to have pre and post tests, pre and post majors.
But design based research then what we do is we design something, for example, a learning experience.
And as we're designing it with, then we have to justify every decision we make using principles from learning theories.
And we don't get into learning theories today, but if you wanna read about learning theories, there's quite a few wonderful handbooks about all the different learning theories.
And then we ground our design.
Very deeply in learning theories.
And then we run it.
We have students, learners engaging with that learning experience and we collect data, but it's not the kind of data like, did you learn this or not?
It's not that sort of thing because number one, learning science.
Scientists believe that learning is too complex to ever measure.
I. And you can't ob objectively measure learning, so you gotta be measuring other things.
And so usually what we do is we measure changes like identity changes and confidence changes and self-perception change, all kinds of different changes.
We'll measure these changes.
But what I did is I invented a new methodology where we're measuring the learners' experiences themselves.
So I ask the students every, like, for example, if the course or if the learning experiences is.
Like a one week thing, then maybe every day at the end of the experience, and I'll be asking them, what did you struggle with today and what worked really well?
And just what does it all mean to you?
That sort of thing.
And reflection papers like that.
And then analyze that carefully and then do like network analysis based on.
How likely is it that one ex, one particular experience?
For example, if a student says, I was struggling with procrastination, that would be like I would call that a code.
So I've coded that in the data.
How likely is it that one code appears near another code in the data?
And from that, then I could say, for this particular kind of student, I can see.
kind of student is struggling with this and this, but what works really well for them is that and that.
So let's leverage the pieces of experience that really work well for them to try to address that issue, that struggle, redesign that learning experience with that in mind, and we'll do a lot of these changes.
And then run it again and collect data again,
Analyze the data again, change the design, run it again, and keep doing this iteration after iteration.
And you see, there's no pre-post, there's no control group, but the trajectory of the learners experiences over time, you get.
Or 5, 6, 7 iterations, you can start to see a pattern of their experiences and how they're improving.
And that's the kind of evidence we use rather than did it work?
Did the students learn how to can they tell me what photosynthesis is?
I don't care about that.
I care that they're engaging with photosynthesis or whatever it is, but their experiences are.
Learning experiences, they're becoming the kind of people who think about photosynthesis.
Eli Davis: We Jonah, that was powerful, my man.
That was.
And thank you for sharing that.
Okay, so here we go.
Oh, you got something else?
Dr Jonan Donaldson: No, I think that's good.
Yeah.
Eli Davis: Okay, cool.
I think it was excellent.
Joan I would most definitely love for you to come back 'cause I have a whole bunch of questions to keep on asking you.
And.
I have a little kid, little student who is dealing with autism and maybe some kind of other things going on with her.
She's hitting her chin really bad.
She's doing some self-injurious behavior.
And, you know, sometimes it's unprompted, she'll just kick into it, you know.
So, her parents wanted me to talk to the the doctor and her behavioral specialist doctor and and I mentioned that I was doing a podcast on artificial intelligence and she said that she knows somebody who's doing something or artificial intelligence and she's going to listen to the podcast and, you know, so.
Those are the kind of people are listening, Joan and I think that those are the kind of people that really is going to enjoy listening to your perspective and going to gain a lot of insight into how to use artificial intelligence, how to think about using art.
Artificial intelligence and also how to become who they desire to become with intentionality while using artificial intelligence.
So, I'm getting ready to go ahead and close it on.
I'll thank you Jonin for being a guest on the podcast.
And thank everybody else for listening to Artificial Intelligence, real Talk, AI with Eli.
Peace out.