WEBVTT NOTE This file was generated by Descript 00:00:26.573 --> 00:00:35.093 Eli Davis: Welcome to artificial Intelligence, real Talk AI with Eli, the space where human consciousness meets machine possibility. 00:00:35.393 --> 00:00:43.223 And it is not about the algorithm alone, it is about identity, ethics, and evolving shape. 00:00:44.558 --> 00:00:58.208 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. 00:00:58.208 --> 00:01:01.418 So our guest today is Dr. John and Philip. 00:01:01.913 --> 00:01:09.323 Donaldson, a learning scientist who's reshaping how we think about education, design, and intelligence in the age of ai. 00:01:09.803 --> 00:01:20.583 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. 00:01:21.128 --> 00:01:30.128 his work draws from the foundational ideas from learning sciences like constructionist learning and design based research. 00:01:30.758 --> 00:01:32.738 You gonna have to explain that for my mama. 00:01:32.988 --> 00:01:33.318 Joan. 00:01:33.498 --> 00:01:36.948 Joan, you real smart, but I know that she's gonna want to she's gonna be like, what is that? 00:01:37.428 --> 00:01:38.838 Because I'm like, what is that? 00:01:39.168 --> 00:01:39.618 All right. 00:01:39.618 --> 00:01:42.498 And he pushes them into new territories. 00:01:42.588 --> 00:01:48.108 Blending in complexity theory, creativity studies, and design sciences. 00:01:48.473 --> 00:01:53.633 At the heart of his work is a powerful idea that learning isn't about acquiring knowledge. 00:01:53.633 --> 00:02:03.743 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. 00:02:03.983 --> 00:02:13.703 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. 00:02:14.298 --> 00:02:29.688 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. 00:02:30.408 --> 00:02:41.958 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. 00:02:42.783 --> 00:02:43.413 More. 00:02:43.983 --> 00:02:51.453 He's passionate about helping people not just learn, but live more fully as designers of their own paths. 00:02:53.278 --> 00:02:56.168 a colleague of Tiara, and Tiara is my wife. 00:02:56.168 --> 00:02:59.228 Everybody's just been listening to these podcasts. 00:02:59.288 --> 00:03:10.568 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. 00:03:10.808 --> 00:03:14.288 Through ra I was able to meet Jonah. 00:03:16.178 --> 00:03:35.230 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. 00:03:35.765 --> 00:03:37.325 Just blew my mind. 00:03:37.610 --> 00:03:52.230 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? 00:03:52.230 --> 00:03:52.650 So, 00:03:52.650 --> 00:03:52.940 Dr Jonan Donaldson: Same. 00:03:53.300 --> 00:03:54.240 Eli Davis: yep everybody. 00:03:54.240 --> 00:03:54.750 Welcome. 00:03:54.800 --> 00:03:55.670 Please welcome Jonah. 00:03:56.195 --> 00:03:57.065 Go ahead, Jonah. 00:03:57.415 --> 00:03:59.335 Is there anything else that you would like to add to that? 00:03:59.835 --> 00:04:01.785 Dr Jonan Donaldson: No, but I think I'll weave in. 00:04:01.785 --> 00:04:04.005 You ask about the design based research. 00:04:04.005 --> 00:04:04.915 I'll weave that in a. 00:04:05.545 --> 00:04:05.845 Eli Davis: Okay. 00:04:05.875 --> 00:04:06.145 Okay. 00:04:06.145 --> 00:04:06.865 So here we go. 00:04:07.105 --> 00:04:10.525 So what I want to do is I want to start with a question. 00:04:10.525 --> 00:04:19.440 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. 00:04:19.440 --> 00:04:20.590 So, question. 00:04:22.120 --> 00:04:27.340 are you becoming right now and how is AI a part of that process? 00:04:27.890 --> 00:04:28.610 Dr Jonan Donaldson: Nice. 00:04:28.700 --> 00:04:29.180 Okay. 00:04:29.180 --> 00:04:29.990 I like this. 00:04:29.990 --> 00:04:30.710 I like this. 00:04:31.760 --> 00:04:33.170 Who am I becoming. 00:04:33.890 --> 00:04:36.410 I should probably think about that more often, shouldn't I? 00:04:36.540 --> 00:04:48.835 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. 00:04:49.335 --> 00:04:55.585 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. 00:04:55.585 --> 00:04:56.695 But nobody knows. 00:04:57.535 --> 00:04:59.215 Nobody can trace it back to me. 00:04:59.680 --> 00:05:01.650 Nobody can say Jonah did that. 00:05:02.140 --> 00:05:07.715 I want it to be just out there in the world like ideas and ways of doing. 00:05:07.715 --> 00:05:17.825 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. 00:05:17.885 --> 00:05:19.565 Now, there are things. 00:05:20.060 --> 00:05:21.290 I do have some ego. 00:05:21.290 --> 00:05:28.970 There are things I wanna claim ownership on, you know, like I ur article, I wanna claim ownership on that, right? 00:05:29.520 --> 00:05:39.650 And being a founder of a learning sciences program, master's degree in learning science learning Design and learning sciences, I built this program. 00:05:39.740 --> 00:05:40.400 That's my baby. 00:05:40.400 --> 00:05:43.550 I love it and I feel a bit of ownership over 00:05:43.655 --> 00:05:59.095 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. 00:05:59.845 --> 00:06:01.945 But nobody else can see it. 00:06:01.945 --> 00:06:06.775 It's kind of like a little bit of a subversive or like under the radar situation. 00:06:07.915 --> 00:06:10.735 And how does AI play into it though? 00:06:11.905 --> 00:06:16.225 You know, that's a hard one because I use AI every day, all the time. 00:06:16.435 --> 00:06:25.769 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. 00:06:26.444 --> 00:06:35.190 I can't really say this was the AI and this was the jonin because like it is part of me now, 00:06:35.370 --> 00:06:36.690 So that's a hard one to answer. 00:06:36.690 --> 00:06:42.870 Yeah, and like you said in the intro, augmented intelligence, I don't think the word artificial is right. 00:06:42.870 --> 00:06:45.690 I think it is augmented intelligence. 00:06:45.740 --> 00:06:53.090 Eli Davis: Have quite a few people that I engage with and them don't have. 00:06:53.687 --> 00:06:58.487 Or have not spent the time to understand artificial intelligence like you. 00:06:58.977 --> 00:07:03.927 What's the difference between your idea of artificial intelligence and augmented intelligence? 00:07:04.207 --> 00:07:05.707 E Ex Explain the difference. 00:07:06.357 --> 00:07:06.987 Dr Jonan Donaldson: I think. 00:07:07.077 --> 00:07:13.207 The easiest way to understand it would be the idea of complex systems. 00:07:13.297 --> 00:07:14.167 And 00:07:14.677 --> 00:07:15.677 Eli Davis: Hold up, Jonah, you go. 00:07:15.707 --> 00:07:19.047 You gonna start off with, so, so Jon is brilliant. 00:07:19.332 --> 00:07:19.512 Y'all. 00:07:20.052 --> 00:07:26.122 So when Jonah says, the easiest way to understand this is to think of it through complex systems. 00:07:27.737 --> 00:07:28.877 That's hilarious. 00:07:30.377 --> 00:07:31.077 That's hilarious. 00:07:31.522 --> 00:07:31.882 Okay. 00:07:31.882 --> 00:07:32.752 I'm sorry, Jonah. 00:07:32.802 --> 00:07:33.192 Jonah. 00:07:33.197 --> 00:07:34.887 I I just thought, I was like, how you going? 00:07:34.887 --> 00:07:35.847 How you gonna say something? 00:07:35.847 --> 00:07:38.697 That's easy, but yet you say it's getting ready to be complex. 00:07:39.147 --> 00:07:39.627 Go ahead. 00:07:40.167 --> 00:07:40.797 Go ahead, Jonah. 00:07:41.167 --> 00:07:43.927 Dr Jonan Donaldson: just think about like, let's think about an ant hill. 00:07:44.347 --> 00:07:46.837 So in an ant hill there are. 00:07:47.887 --> 00:07:52.647 Thousands sometimes hundreds of thousands of ants doing their thing, right? 00:07:52.647 --> 00:07:55.737 They're all interrelated, interdependent, interacting. 00:07:56.567 --> 00:08:01.937 But in that ant hill, there are things that are kind of amazing. 00:08:01.937 --> 00:08:07.247 Like they have ventilation, they have waste disposal, they have farming, they have nurseries. 00:08:07.247 --> 00:08:10.067 They got really cool stuff going on, and. 00:08:10.742 --> 00:08:14.772 If you were to study the individual ads all your life, you'd never get it. 00:08:14.982 --> 00:08:17.802 No way to understand how that stuff happened. 00:08:18.132 --> 00:08:20.232 And that's what I mean by complex systems. 00:08:20.502 --> 00:08:24.462 Complex systems have this thing called emergence. 00:08:25.552 --> 00:08:28.882 Something happens that's greater than the sum of the parts, 00:08:29.487 --> 00:08:35.577 And if you try to understand it using any like cause and effect, thinking this caused that. 00:08:35.722 --> 00:08:36.502 It won't get it. 00:08:36.532 --> 00:08:43.132 It's impossible to understand how that happened if you're relying on cause and effect thinking. 00:08:43.257 --> 00:08:48.807 So you have to think of other ways of understanding the whole and the parts all at the same 00:08:49.102 --> 00:08:59.362 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. 00:08:59.782 --> 00:09:04.222 Hopefully by understanding each part and how it works, then you'll understand the whole thing. 00:09:04.972 --> 00:09:08.062 And that does work for a photocopy machine 00:09:08.162 --> 00:09:10.982 And probably under, yeah, it works for your car. 00:09:11.342 --> 00:09:16.592 It works for your cell phone, but it doesn't work for complex systems like Ant 00:09:16.852 --> 00:09:19.702 Because those ones require different way of thinking. 00:09:19.702 --> 00:09:24.227 You have to look at the whole, but not just the whole, you have to look at all of the parts. 00:09:24.832 --> 00:09:27.202 And the whole all at the same time. 00:09:27.727 --> 00:09:31.897 And then you can start to get it, you can start to understand the emergence. 00:09:32.347 --> 00:09:44.377 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. 00:09:44.497 --> 00:09:47.287 So for example, this generative ai. 00:09:47.887 --> 00:09:55.117 I've heard like high level, top level experts say it's a stochastic parrot or it's just predicting the next word. 00:09:55.417 --> 00:09:56.557 No, it's not. 00:09:56.857 --> 00:09:57.907 It's emergence. 00:09:57.937 --> 00:10:09.887 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 00:10:10.222 --> 00:10:13.422 I mean, just take it back to the very simple example, just language. 00:10:13.512 --> 00:10:34.582 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? 00:10:34.682 --> 00:10:35.822 That's emergence. 00:10:36.602 --> 00:10:38.852 Nobody taught that thing how to do math. 00:10:39.422 --> 00:10:45.272 And some people are thinking, well, maybe it just saw examples in the training data. 00:10:45.302 --> 00:10:46.382 No, that's not it. 00:10:46.442 --> 00:10:47.792 It's much greater than that. 00:10:48.362 --> 00:10:52.502 It's doing things that are greater than the sum of the parts. 00:10:53.102 --> 00:10:58.412 And the good news is that human beings are exactly the same. 00:10:59.162 --> 00:11:03.992 We have all of this emergence, so in our brains we got neurons. 00:11:04.892 --> 00:11:07.532 Synapsis, we got all that kind of good stuff, right? 00:11:07.592 --> 00:11:11.012 But it's just like ants. 00:11:11.012 --> 00:11:18.812 If you try to understand the neurons, you could study them your entire life and you'll never understand how an idea happens. 00:11:20.372 --> 00:11:21.362 Eli Davis: So, so. 00:11:21.862 --> 00:11:31.212 While you were doing that it made me think of something that I have recently started to, to have an understanding, to gain understanding. 00:11:31.212 --> 00:11:40.922 And I think it is it through engage with artificial intelligence in which this idea, emerged. 00:11:41.597 --> 00:11:44.917 It was, I had a best friend, I was 27. 00:11:44.917 --> 00:11:46.237 He was 26 years old. 00:11:47.137 --> 00:11:52.447 He, went to North Carolina a and t became a, civil engineer. 00:11:52.817 --> 00:11:57.017 He was living in Atlanta, driving back and forth through parts of Florida. 00:11:57.407 --> 00:12:06.057 And while he was driving back home from Florida, he got into his car hydroplaned and it hit a tree and he passed away. 00:12:06.612 --> 00:12:06.882 Right. 00:12:06.882 --> 00:12:07.902 Pretty much instantly. 00:12:08.332 --> 00:12:18.912 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. 00:12:19.362 --> 00:12:21.682 And what I have gotten. 00:12:22.552 --> 00:12:24.922 Because I always felt that he had given me something. 00:12:25.472 --> 00:12:43.022 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. 00:12:43.572 --> 00:12:50.142 Because of that incident, I went spent my last $300 on a credit card or something and bought a guitar. 00:12:50.532 --> 00:12:53.112 And ever since then I've been playing guitar. 00:12:53.312 --> 00:12:57.812 Not only do I play guitar, I also bring incorporate into the classroom. 00:12:58.082 --> 00:13:01.992 I do, kind of sessions for other teachers in classroom, bringing that rhythm. 00:13:02.312 --> 00:13:07.882 So for me, if I ask myself the question of who am I becoming right now? 00:13:07.942 --> 00:13:10.282 And, how does AI play a part of it? 00:13:10.282 --> 00:13:11.512 I think it, it is. 00:13:11.782 --> 00:13:17.482 I have always had these thoughts, but I never knew where to put 'em. 00:13:18.082 --> 00:13:19.252 Or what to do with them. 00:13:19.252 --> 00:13:27.132 these thoughts in which you know that they're so individual that, it might not benefit asking somebody else. 00:13:28.062 --> 00:13:28.812 Know what I mean? 00:13:28.812 --> 00:13:36.442 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. 00:13:36.472 --> 00:13:46.502 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. 00:13:47.552 --> 00:13:50.717 Dr Jonan Donaldson: I would say my reaction to that is. 00:13:51.462 --> 00:14:04.842 You and your I, all of your ideas with the AI are generating something that neither of you could have done alone, 00:14:05.027 --> 00:14:05.377 Eli Davis: Right. 00:14:06.612 --> 00:14:17.792 Dr Jonan Donaldson: which is another sign that, that emergence is happening and that this is a complex system with the emergence happening where. 00:14:18.587 --> 00:14:30.797 Things, humans plus technologies can sometimes make humans less like, it's like cold and hard and distant. 00:14:31.217 --> 00:14:33.617 You know, there's technologies that can do that. 00:14:34.617 --> 00:14:37.227 Well, not for everybody, but just in general. 00:14:37.227 --> 00:14:41.957 In fact, there's many books written about like, Sherry Turkel wrote a book. 00:14:42.347 --> 00:14:43.277 That I love. 00:14:43.277 --> 00:14:44.357 It's a very good book. 00:14:44.977 --> 00:14:47.917 She's from MIT called Alone. 00:14:47.917 --> 00:14:57.492 Together, how these technologies are separating us and making us all alone and lonely, like social medias and stuff like that. 00:14:57.882 --> 00:15:06.502 There's some truth in that, but I guess I'm, optimist or something, but I feel something different with my interactions with ai. 00:15:07.372 --> 00:15:18.232 I feel something different there than any other technology I've engaged with in my life, except for I'd say writing and reading. 00:15:19.522 --> 00:15:25.842 Those technologies I think have this similar ability to. 00:15:26.757 --> 00:15:30.267 To make people to help us well together. 00:15:30.297 --> 00:15:46.648 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. 00:15:47.158 --> 00:16:00.971 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. 00:16:01.901 --> 00:16:02.561 Why? 00:16:03.251 --> 00:16:10.876 Because in novels you can get to deeper truth than what we would experience as reality. 00:16:11.876 --> 00:16:21.358 So that's power of a technology, a book that is more, that is really helping us become more deeply and beautifully human. 00:16:21.448 --> 00:16:30.568 And I think AI is exponentially more potential to make us more awesome, more beautiful, more human. 00:16:31.873 --> 00:16:33.163 But we gotta be careful. 00:16:33.163 --> 00:16:44.473 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. 00:16:45.693 --> 00:16:59.633 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. 00:17:00.688 --> 00:17:01.258 Eli Davis: I believe I, 00:17:01.313 --> 00:17:02.693 Dr Jonan Donaldson: Get, gotta lean into it. 00:17:02.848 --> 00:17:03.148 Eli Davis: yep. 00:17:03.178 --> 00:17:04.588 I believe that to be true too. 00:17:05.298 --> 00:17:14.248 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. 00:17:14.818 --> 00:17:18.538 'cause you know, some of their ethical issues are starting to show their selves too. 00:17:18.838 --> 00:17:19.168 Alright. 00:17:19.168 --> 00:17:19.888 But here we go. 00:17:19.888 --> 00:17:23.648 So this is a good segue into the next question. 00:17:24.163 --> 00:17:28.488 I. On ethics and education and educational responsibilities. 00:17:28.488 --> 00:17:40.163 So what ethical responsibilities do educators carry when bringing AI into their classrooms, especially when knowing the systems mirror and sometimes magnifies society biases. 00:17:41.163 --> 00:17:58.533 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. 00:17:59.033 --> 00:17:59.303 Dot. 00:17:59.333 --> 00:17:59.783 Right. 00:18:01.163 --> 00:18:03.863 And it does really good at that. 00:18:04.853 --> 00:18:10.873 And and then the perspectives would be from the perspective of that role. 00:18:11.413 --> 00:18:15.693 And so I don't really think there's a lot of biases baked into ai. 00:18:15.843 --> 00:18:35.481 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. 00:18:35.981 --> 00:18:37.541 So I'm not too worried about that. 00:18:38.201 --> 00:18:38.721 What I am 00:18:38.721 --> 00:18:40.851 Eli Davis: But let's put that, let's put that out there. 00:18:41.151 --> 00:18:46.666 That is a skill of artificial intelligence literacy that many people may not know. 00:18:47.166 --> 00:18:47.596 Dr Jonan Donaldson: Yeah. 00:18:47.671 --> 00:18:51.301 Eli Davis: Many people may not know that simple prompt, right? 00:18:51.866 --> 00:18:53.151 It, it can be huge. 00:18:53.186 --> 00:19:04.016 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. 00:19:04.016 --> 00:19:05.216 So, but go ahead, Jonah. 00:19:06.054 --> 00:19:16.134 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. 00:19:17.124 --> 00:19:34.812 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. 00:19:35.812 --> 00:19:48.482 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. 00:19:48.902 --> 00:20:03.257 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. 00:20:03.737 --> 00:20:14.083 I want the students to think of themselves as critical thinkers where the source of knowledge is within and they're constructing knowledge. 00:20:14.083 --> 00:20:15.463 They're not discovering it. 00:20:15.823 --> 00:20:17.683 I'm a constructivist obviously. 00:20:18.118 --> 00:20:31.744 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. 00:20:32.744 --> 00:20:45.894 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. 00:20:46.394 --> 00:20:52.154 To be able to guess and see the answer so it can have that support within that thinking. 00:20:52.694 --> 00:21:03.245 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. 00:21:03.695 --> 00:21:06.605 The they can have a conversational tone and like 00:21:06.605 --> 00:21:07.445 The wheels are turning. 00:21:07.445 --> 00:21:19.335 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. 00:21:19.685 --> 00:21:24.035 Sluggish, you know, super sluggish. 00:21:24.065 --> 00:21:29.625 So, you know, that's what I'm running into with using artificial intelligence in side of my school. 00:21:29.655 --> 00:21:34.145 But this also is with the adults that are teaching as well. 00:21:35.079 --> 00:21:43.539 Dr Jonan Donaldson: I've seen something similar, but only when people are interacting with the ais, with the goal of getting to. 00:21:44.214 --> 00:21:46.884 An answer or you know, they have this 00:21:47.544 --> 00:21:47.834 Eli Davis: Okay. 00:21:48.324 --> 00:21:59.034 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. 00:21:59.514 --> 00:22:03.064 So, so for example now this is in a school, but. 00:22:03.827 --> 00:22:10.517 Just the power of this generativity, the human generativity and the AI's generativity. 00:22:11.017 --> 00:22:22.318 Last year my nieces, they're like, I think they're 10 and 11 and 13 years old. 00:22:22.693 --> 00:22:31.163 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. 00:22:31.163 --> 00:22:32.903 So there were thousands of people there. 00:22:32.963 --> 00:22:43.633 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. 00:22:44.473 --> 00:22:48.703 And they had this awesome adventure for over a week. 00:22:49.348 --> 00:22:57.158 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. 00:22:57.608 --> 00:23:13.258 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. 00:23:13.628 --> 00:23:17.588 And you don't have to be sequential, just all over the place. 00:23:17.588 --> 00:23:18.368 That's fine. 00:23:18.858 --> 00:23:22.258 And then I just took notes for about three hours 00:23:22.598 --> 00:23:29.388 And then I fed that that Google doc to an ai and I said, let's write a book. 00:23:30.093 --> 00:23:34.323 First of all, help me make, outline chapters and it did a wonderful job. 00:23:34.323 --> 00:23:37.383 And I'm like, okay, help me write draft of chapter one. 00:23:37.713 --> 00:23:39.093 It did a wonderful job. 00:23:39.183 --> 00:23:41.183 Chapter two, chapter three, chapter 13. 00:23:41.183 --> 00:23:42.443 It did all the way through. 00:23:42.973 --> 00:24:00.063 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. 00:24:00.363 --> 00:24:01.143 Eli Davis: Wow. 00:24:02.823 --> 00:24:09.423 Dr Jonan Donaldson: And I think we could just be doing that in, with young people and Polish students and just all of us. 00:24:09.423 --> 00:24:14.823 We could be a lot more generative if we just like have these, the imagination to try to do that. 00:24:15.023 --> 00:24:15.473 Eli Davis: Wow. 00:24:15.863 --> 00:24:16.163 Okay. 00:24:16.163 --> 00:24:24.464 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. 00:24:25.014 --> 00:24:36.139 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. 00:24:36.739 --> 00:24:40.019 How do, can you think of anything, of way in which we can do that? 00:24:40.499 --> 00:24:44.929 I'm asking because I was asked by the chair at Miles. 00:24:45.769 --> 00:24:50.889 As I'm part of the, black male teacher initiative to incorporate more black men into, education. 00:24:51.399 --> 00:24:58.991 And I was asked by the chair to, spoke to 'em and we had a session and she was like, okay, so. 00:25:00.266 --> 00:25:02.896 What else can we give these, to them. 00:25:02.896 --> 00:25:05.326 So we're gonna come up with a book and all that. 00:25:05.656 --> 00:25:13.606 And what I also suggested was to give them something dealing with artificial intelligence. 00:25:13.606 --> 00:25:15.166 Understand the artificial intelligence. 00:25:15.166 --> 00:25:18.766 She was thinking that we need to give them a book on how to take the praxis. 00:25:19.156 --> 00:25:25.996 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. 00:25:26.386 --> 00:25:33.296 The ability to interrogate and question and develop some of the things that you need to according to the practice, you know? 00:25:33.296 --> 00:25:38.546 So, what do you think about a idea like that, you know, incorporating it for people who have to take that test? 00:25:39.846 --> 00:25:43.901 Dr Jonan Donaldson: So this is this is something really important in the learning sciences. 00:25:44.451 --> 00:25:51.321 And this goes back to the very beginning of learning sciences, which started in like not too long ago, 1991. 00:25:52.371 --> 00:25:56.451 And it all started with the idea of generativity. 00:25:57.081 --> 00:25:59.841 Not AI generativity, but human generativity 00:26:00.251 --> 00:26:06.195 Making, constructing this generativity is essential for learning. 00:26:06.674 --> 00:26:18.014 So learning scientists would say nobody should ever be doing like lectures unless it's the students doing the lectures. 00:26:18.314 --> 00:26:23.244 Nobody should ever be using a textbook unless the students are writing the textbook. 00:26:24.256 --> 00:26:29.356 Nobody should ever be using like exams unless the students are coming up with. 00:26:30.436 --> 00:26:46.346 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. 00:26:47.505 --> 00:26:50.445 It's, it is really ineffective, but. 00:26:50.970 --> 00:26:54.480 Like with ais and all this, maybe we can move past all of that. 00:26:54.990 --> 00:27:02.580 But it all comes down to the core that generativity is where it all starts. 00:27:03.690 --> 00:27:15.400 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. 00:27:15.805 --> 00:27:37.195 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. 00:27:38.845 --> 00:27:43.435 our students need to understand that these exams exist for a reason. 00:27:43.850 --> 00:27:47.566 Now, the reason is probably valid. 00:27:47.626 --> 00:27:50.446 We want teachers to have. 00:27:50.996 --> 00:28:06.636 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. 00:28:06.636 --> 00:28:06.786 Yeah. 00:28:07.434 --> 00:28:10.984 That's probably the purpose for the these exams. 00:28:11.444 --> 00:28:13.744 But the exams are. 00:28:14.679 --> 00:28:21.129 Not doing that, but they're probably the best that people could come up with for now. 00:28:21.129 --> 00:28:24.009 But we gotta move beyond 'em because they're really bad. 00:28:24.399 --> 00:28:30.279 However, we're stuck with them now until we can come up with better alternatives. 00:28:30.939 --> 00:28:38.319 But just because we're stuck with them doesn't mean that we have to accept like. 00:28:39.084 --> 00:28:41.574 Everything about them as light ground truth. 00:28:41.964 --> 00:28:42.354 No. 00:28:42.354 --> 00:28:54.594 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. 00:28:55.404 --> 00:28:59.454 And hopefully we can do a lot of generative things together. 00:28:59.874 --> 00:29:02.049 Your your students, can they go write a book? 00:29:02.599 --> 00:29:13.241 And in doing so, they will be preparing for the Praxis without being subjugated by the Praxis. 00:29:14.596 --> 00:29:15.106 Eli Davis: Okay. 00:29:15.476 --> 00:29:19.006 Subjugated, that's a that's a huge word. 00:29:19.506 --> 00:29:33.446 Jonah how could one be subjugated by a a system of trying to make sure that we have what we call highly qualified educators? 00:29:33.996 --> 00:29:43.776 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. 00:29:44.466 --> 00:29:44.856 Right? 00:29:44.886 --> 00:29:51.926 All of those things are within things like any of our exams, not just practice any of our exams. 00:29:52.476 --> 00:29:53.946 They're built into it. 00:29:54.546 --> 00:30:10.487 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. 00:30:11.037 --> 00:30:20.367 As if they were just studying for the exam and just blindly accepting everything as truth. 00:30:21.116 --> 00:30:30.421 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. 00:30:30.421 --> 00:30:35.161 So, in the the honor of your time, I do have one more question to, to ask you. 00:30:35.541 --> 00:30:41.501 And it is can frame it in artificial intelligence or we can frame it in just existing. 00:30:42.141 --> 00:30:45.361 But the question goes what are, what is something. 00:30:45.856 --> 00:30:54.656 Or are some things that you're unlearning right now with the help of artificial intelligence or just, you know, through your own becoming. 00:30:55.656 --> 00:30:56.326 Dr Jonan Donaldson: Unlearning. 00:30:57.326 --> 00:31:04.046 Well, personally as an academic, I have a lot of training in like research methods, right? 00:31:04.736 --> 00:31:10.226 And there's a whole lot of tradition about here's the correct way to do it. 00:31:10.766 --> 00:31:20.976 And they have different ways of, doing different things, the statistics and case studies and grounded theories and just whatever, different methodologies. 00:31:21.096 --> 00:31:32.851 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. 00:31:33.130 --> 00:31:48.900 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. 00:31:48.990 --> 00:31:49.320 Right. 00:31:49.860 --> 00:32:09.747 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. 00:32:10.632 --> 00:32:14.926 This learning that's becoming, what is it and how? 00:32:14.986 --> 00:32:17.056 And then second, how can you make that happen? 00:32:17.116 --> 00:32:24.046 And my field invented this thing called design-based research, bringing it back to the intro there. 00:32:24.536 --> 00:32:35.546 And before design-based research, there was the traditions in academia were that to do an experiment, you have to have a control group. 00:32:36.266 --> 00:32:40.596 And then you have to have pre and post tests, pre and post majors. 00:32:41.206 --> 00:32:48.006 But design based research then what we do is we design something, for example, a learning experience. 00:32:48.546 --> 00:32:56.706 And as we're designing it with, then we have to justify every decision we make using principles from learning theories. 00:32:57.996 --> 00:33:07.626 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. 00:33:08.376 --> 00:33:10.866 And then we ground our design. 00:33:11.586 --> 00:33:13.206 Very deeply in learning theories. 00:33:13.716 --> 00:33:15.096 And then we run it. 00:33:15.126 --> 00:33:27.426 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? 00:33:28.446 --> 00:33:33.906 It's not that sort of thing because number one, learning science. 00:33:34.156 --> 00:33:38.416 Scientists believe that learning is too complex to ever measure. 00:33:38.416 --> 00:33:45.901 I. And you can't ob objectively measure learning, so you gotta be measuring other things. 00:33:45.901 --> 00:34:00.211 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. 00:34:01.096 --> 00:34:02.716 We'll measure these changes. 00:34:02.836 --> 00:34:11.046 But what I did is I invented a new methodology where we're measuring the learners' experiences themselves. 00:34:11.046 --> 00:34:18.966 So I ask the students every, like, for example, if the course or if the learning experiences is. 00:34:20.196 --> 00:34:30.666 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? 00:34:31.266 --> 00:34:33.366 And just what does it all mean to you? 00:34:33.726 --> 00:34:34.566 That sort of thing. 00:34:35.106 --> 00:34:37.116 And reflection papers like that. 00:34:37.116 --> 00:34:45.756 And then analyze that carefully and then do like network analysis based on. 00:34:47.526 --> 00:34:52.416 How likely is it that one ex, one particular experience? 00:34:52.416 --> 00:34:59.236 For example, if a student says, I was struggling with procrastination, that would be like I would call that a code. 00:34:59.506 --> 00:35:00.916 So I've coded that in the data. 00:35:01.306 --> 00:35:08.536 How likely is it that one code appears near another code in the data? 00:35:08.536 --> 00:35:14.116 And from that, then I could say, for this particular kind of student, I can see. 00:35:15.556 --> 00:35:21.976 kind of student is struggling with this and this, but what works really well for them is that and that. 00:35:22.936 --> 00:35:39.496 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. 00:35:40.486 --> 00:35:43.456 And then run it again and collect data again, 00:35:43.681 --> 00:35:51.871 Analyze the data again, change the design, run it again, and keep doing this iteration after iteration. 00:35:52.231 --> 00:36:01.291 And you see, there's no pre-post, there's no control group, but the trajectory of the learners experiences over time, you get. 00:36:01.816 --> 00:36:10.126 Or 5, 6, 7 iterations, you can start to see a pattern of their experiences and how they're improving. 00:36:10.486 --> 00:36:16.096 And that's the kind of evidence we use rather than did it work? 00:36:16.096 --> 00:36:21.866 Did the students learn how to can they tell me what photosynthesis is? 00:36:21.866 --> 00:36:22.826 I don't care about that. 00:36:22.826 --> 00:36:30.326 I care that they're engaging with photosynthesis or whatever it is, but their experiences are. 00:36:31.901 --> 00:36:36.131 Learning experiences, they're becoming the kind of people who think about photosynthesis. 00:36:36.701 --> 00:36:38.871 Eli Davis: We Jonah, that was powerful, my man. 00:36:38.901 --> 00:36:39.171 That was. 00:36:39.201 --> 00:36:40.601 And thank you for sharing that. 00:36:40.941 --> 00:36:42.051 Okay, so here we go. 00:36:42.111 --> 00:36:42.786 Oh, you got something else? 00:36:44.091 --> 00:36:44.986 Dr Jonan Donaldson: No, I think that's good. 00:36:44.986 --> 00:36:45.316 Yeah. 00:36:45.586 --> 00:36:46.306 Eli Davis: Okay, cool. 00:36:46.306 --> 00:36:47.356 I think it was excellent. 00:36:47.636 --> 00:36:54.846 Joan I would most definitely love for you to come back 'cause I have a whole bunch of questions to keep on asking you. 00:36:55.336 --> 00:36:56.026 And. 00:36:56.526 --> 00:37:02.606 I have a little kid, little student who is dealing with autism and maybe some kind of other things going on with her. 00:37:02.606 --> 00:37:04.406 She's hitting her chin really bad. 00:37:04.676 --> 00:37:06.566 She's doing some self-injurious behavior. 00:37:06.966 --> 00:37:10.746 And, you know, sometimes it's unprompted, she'll just kick into it, you know. 00:37:11.126 --> 00:37:29.931 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. 00:37:30.191 --> 00:37:44.026 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. 00:37:44.046 --> 00:37:52.826 Artificial intelligence and also how to become who they desire to become with intentionality while using artificial intelligence. 00:37:52.826 --> 00:37:55.336 So, I'm getting ready to go ahead and close it on. 00:37:55.366 --> 00:37:59.176 I'll thank you Jonin for being a guest on the podcast. 00:37:59.176 --> 00:38:06.256 And thank everybody else for listening to Artificial Intelligence, real Talk, AI with Eli. 00:38:06.766 --> 00:38:07.606 Peace out.