S2:E1 "Teaching at the edge: Think more, not less" w. Michele Lackovic

"I don't need an AI detector to tell me this isn't your work." After twenty-five years of reading student writing, Michele Lackovic knows when a voice goes missing from the page — and what she does next is the heart of this episode. Not policing. A conversation. And these learning dialogues with students have reduced her own take home workload, freeing her up to get creative to remove barriers to learning in the classroom.

Yes, this is a discussion about AI in education. But it's not only about that. We discuss strategies that are grounded in making the learning visible not just so teachers can be sure students did the work themselves, but to help each learner understand how they are learning, and why it matters.

Michele Lackovic is an IB Literature and Theory of Knowledge teacher, workshop leader, examiner, and author, and the voice behind Teaching at the Edge. We explore what it means to teach at the edge — not the edge of technology, but the edge where students and teachers have agency. Along the way: foam swords and Shakespeare, visible drafting, her voice authentication protocol, and why the most powerful response to AI in the classroom is convincing students their own voice is enough. This is why Michele designed the V.O.I.C.E framework as authentication process.

This one is full of things you can carry straight into a classroom — and a reminder that tech tools have never been the answer on their own. It's always been the pedagogy behind them.

If something here sparks for you, please pass it on — share it with a colleague, leave a comment or rating wherever you're listening, and tell me what it sparked by writing me a note or finding me on social media. 

Tribute and dedication: This episode is dedicated to Michele's late mother Nancy Bianco, who passed away suddenly in June 2026. Nancy was a longtime Information Security Systems Association leader and cybersecurity pioneer, helping create a space where security leaders could collaborate, learn, and support one another. Michele would often discuss her work in education with her mother, who was so supportive of providing high-quality education, for all students. Read more about Nancy's work.

Connect with Michele on LinkedIn

Read Michele's Substack

Explore the AI in education pioneers, Michele mentioned in the episode: Michelle Kassorla from Georgia State University Perimeter College &  Ethan Mollick from The Wharton School.

Follow the EduByDesign Blog to explore the podcast topics, further.

And please let Phil know what resonates with you, in the comments.

Transcript

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Phil Evans 0:01

There are a lot of conversations about AI in the classroom that start around policing. Our guest Michele Lackovic starts somewhere else with convincing students that their own voice is enough. And this is education by design. We are educators, leaders, and innovators, bringing out pieces of what education could become and creating it together through collective innovation. And I am your host, Phil Evans. Like many experienced educators, my guest in this episode has been reading student writing for more than 25 years. She'll tell you that she doesn't need an AI detector to know when a piece of writing no longer sounds like the student who handed it in. And more importantly, she's not interested in catching anyone. What does interest Michele Lackovic is what happens next. The conversations that bring students back to their own thinking, and the classroom conditions that convince them that their voice is enough. Michele is an educator through and through. She's also a workshop leader, an examiner, an author, a coordinator of programs. But as she puts it, it's always important to keep one foot in the classroom. She writes at Teaching at the Edge and she also presents at global conferences. This week, in Denver, she'll be talking about thinking more and not less. Michele doesn't just talk about these things. She designs them. She uses them in the classroom. She encourages others to experiment and to take the resources she's willing to share freely and to adapt them for your own context. So this episode is about that edge. Not the edge of technology, but the edge of where students have agency, where teachers have agency, and where honest conversations do so much more than just detect. They empower students to see themselves as capable.

Michele Lackovic 2:06

What

Policing use of AI

Michele Lackovic 2:07

teachers want to talk about most when I go into any professional development is the uh policing part. You know, it it becomes very adversarial because they're seeing text in front of them that they know their students didn't produce. And it the cognitive offloading, there's such a temptation there. But if you give students space to create things in the classroom, they're going to be less likely to take those shortcuts. Number one. And number two, it's, I feel part of our job as teachers to convince students that their voice is enough. They don't need to turn to these tools to polish their own voice just because they're out there. In fact, a lot of times their own voice, that authenticity of their own voice is a lot more refreshing. But there are things the tools can do to help them. So I think it's just a matter of tweaking. And I think teachers are completely overwhelmed because they think they have to redo everything when really it's just a matter of revising things we already do well, adding AI as just one tool amongst many. Um, when you talk about principle play, I'm still putting foam swords in students' hands when we do Shakespeare because that movement links with the difficult speech. And there's something about that that that helps students understand and engage with something that's 400 years old in a way that just reading the dry dead text on a page does not. Um, but then you have to do the work of annotating and writing things in the margins, and but then but then AI can get us to further places as well. Um, but only after you do the sort of the heavy lifting of of you know thinking about the text first. So you can't, if you start with AI, then you know, you're not gonna do the thinking. But if you if you add it in as one of these things that you do as a practice, you know, it's it's enormously helpful. I've I've seen kids stress test arguments. I've seen them, you know, um help them uh create study guides for their um their, you know, their exams, you know. Um I've seen them, you know, back in the day we would create little note cards for ourselves. Now there's technology out that creates those note cards for them and it it it organizes that in a way. Um there's podcasts that are created from their notes, and they can listen to those while they work out or they are, you know, traveling to school. So there are things that AI can do. Um, and a lot of these things my students will come and talk to me about. Look what I found. Let's talk about it. So I think that we are at a really interesting and exciting part of education where where we can do a lot with this technology. But I think that the reality of it is that it's very difficult in the classroom to, you know, send kids into their own thinking if you think you have to change everything at once. It's it's really, it's it's you know, little steps, um, you know, teaching students to trust themselves, um, you know, and and that's that's the the the the whole thing to me is that it's um we are in exciting times, but but tech tools alone have never been the answer.

Speaker 5:38

No, they certainly haven't. And I'm

Teaching at the edge

Speaker 5:40

I'm really interested in the teaching at the edge. You know, tell me a little bit more about um where this uh concept sits for you um and how it's evolved over time. Um for me, it sort of sounds to me very uh as though you're already talking about how this applies to you know all kinds of different ways we're experimenting around uh meeting the needs of the students where they are removing barriers to their learning.

Speaker 1 6:06

Well, it's interesting because when I was naming the Substack, I really wanted to name it teaching and learning at the edge, but it was one character short, and I really couldn't fit it. So I ended up with teaching at the edge because I said, you know, that works too. Teaching and learning are sort of, you know, the the the opposite sides of the same coin, right? Um teaching at the edge doesn't mean the edge of technology or what's new, but just finding that edge where where students have agency, where teachers have agency, where you know, we we learn that collaboration is sometimes better than isolation. And sometimes we learn that we learn things better in isolation. And I think that that um I have a very RD mindset, you know, I've always been that way. Let's experiment, let's see what works, let's see what doesn't work. Um, and I've always believed in getting kids to to, you know, rather than just read the text in front of them, you know, let's explore with it, let's illustrate it with art. So then my art students will own it. I did this for a um uh one of the global conferences in IB, you know, about 10 years ago, where I worked with a math teacher and we worked with uh poetry and math, and we had students write mathematical equations for poetry. So the students who um loved poetry could all of a sudden appreciate math in a different way, and the students who loved math could appreciate poetry. So teaching at the edge is is finding connections and and um it's finding ways to learn things um in uh you know in in a in a different arena. And when AI came onto the field, you know, I was a little skeptical at first, to be honest with you. My my husband has a background in physics and mathematics, and um, and he used to be a teacher. He's um he he he is uh he's in industry now, but he was telling me daily what he was doing with with um with AI when it first came out. And it wasn't until I actually took a a workshop with Marilyn Sinclair, who is an IB kind of guru in theory of knowledge, and she just, you know, she had us go ahead and open up a chat GPT account right there in the workshop. And I thought, I want to do this with students. And I looked at my IB coordinator who was sitting right next to me. I said, I want to do this with students. She said, let's go ahead and do it. And this was early on, you know, um, you know, uh 2023, you know, early in 2023. And from there, I realized the potential when you use it in the room with students. You don't send them off to yonder to, you know, figure it all out on their own, but you say, all right, we're we're talking about some sort of you know analysis here. Um, let's go ahead and analyze it, color mark it. I'm a literature teacher by nature. I also teach um Ivy's theory of knowledge course, which is about thinking about thinking, right? Which is so perfect for AI, right? Because it's a thinking tool. Um, but I had the kids, we were just annotating a literary passage, and then I had the students turn to AI, and I had them give the AI a guardrail. And the guardrail was don't answer the questions for me, ask me more questions about what I've done, or tell me what I'm doing well. What connections can you see? What other questions should I be exploring? And those sort of guardrails were really interesting because it the students were fascinated with what the AI came back with. Um, but then it wasn't like I was having them do that at home. They were in groups and they would turn to each other and they would say, Well, what did your AI say? And what did your AI say? So the iteration was not just with the large language model, like Chat GPT or whatnot. At the time we had adopted Khan Academy's Con Migo, so we were using that tool, but it wasn't what that came back with, it was what the students came back with. And then I was roving around as well. So, so the collaboration piece, the iteration piece was human, and the AI tool was part of that mix. So it really wasn't all that different than a class discussion. It's just now we had a large language model that had access to so much. But they could find the hallucinations, which they love to do, the you know, the mistakes that AI makes. Um, but they would also find things that I hadn't considered that connection. Well, let's talk about that more. And then they would talk about that with each other, and then they're all in. Then they're not cognitive outloading, they're actually learning more.

Speaker 10:54

Yeah, and they're and they're thinking more. I'm you know fascinated in this idea of uh the way that students are discovering AI, not so much as an answer factory and you know, to make things for them, but to be able to understand how to reflect and how to think alongside the AI.

AI as a thinking partner

Speaker 11:11

Can you talk to me a little bit more about the AI as a thinking partner?

Speaker 1 11:14

Well, it was interesting. We were studying um this past year uh Frederic Duranmont's play, The Visit, which takes place um post-World War II. And it's it's a play about a woman who comes back to a town um where she's been run out of the town, and she had, you know, had a child who had died, and it was she was destitute, and she comes back. She's a millionaire, and uh actually like a billionaire, and the town is destitute, and they are desperate for her money. And she says, I can fix all your problems. You simply have to kill the man who wronged me. And so it's this ethical play. And the um the text itself isn't really difficult to read, but it's epic theater. It's there's things called the alienation effect and the grotesque and very difficult layered theater techniques that that students can kind of understand and define, but rarely feel. So we I decided let's experiment with AI and see if we can take some of the illusions. There's many illusions to Greek things, to paintings, to um enlightenment figures, things like that. Let's go ahead and have them find an um, you know, an open source example of one of these illusions and have them animate it through AI and see what happens. And the results were just fascinating because my students who were typically you know very comfortable with literature were not as comfortable with the technology. But my students who were not comfortable with literature were comfortable with tech became sort of the experts in the room. We were using the uh technology that was um adopted by the district, which was a little bit clunky and it wasn't working as well as we'd hoped. But the students started layering the tools. One of them opened up another account under their own name to get more tokens. I mean, they were doing things that I hadn't thought of, and the results were fantastic. We put it on a Google slide deck and they were giving each other props. And one student was adamant, she was an art student, she was adamant about not using AI. And I said, Oh, absolutely, you don't have to use AI. You can she was using another program. Um, she knew a lot about um different programs, and it was painstakingly, you know, it took her a lot of time, but then she taught the class a different way to animate um that wasn't AI related. So it just the the the whole classroom became very inclusive. Um it took a couple of days, we showcased it. But the the real, I guess, um, I don't know, the real win, I guess, is that months later, not only did the students do much better on the exam that I gave, which was, you know, sort of you know, understanding how these techniques work and and the um the play itself, but months later they could um explain how some of these techniques worked in other um uh literary Wow, that kind of retention of knowledge and transfer is something that a lot of teachers don't see um come up over and over again um be in as a result of the learning.

Speaker 14:30

You know, it's kind of like what we're hoping for and what we're you know, it's kind of a dream.

Speaker 1 14:34

And it didn't feel like a dream at the time. It was messy. It was, you know, and RD is messy, but and and I and I would say, oh, this is not gonna work. Canva doesn't allow X, Y, and Z. And the students were, they were um, they they they were consoling me. They're like, don't worry, we got this, we figured this out. And I just loved that. But if I had sent them home to do it, it wouldn't have had the same effect. It was because I put them in small groups and they work together. And, you know, I set it up where here's the illusions, here's this, and they got to pick which one. And then once we had it on a slide deck, then they understood all the illusions and then they could see how that all fit together. It was, it was really a great um experiment. Some experiments don't go as well. Um uh, and

Approaches that no longer work

Speaker 1 15:23

then some of the old things that I've been doing um for many, many years are no longer applicable. So for example, um, you know, when students are in a proposal form for, you know, um a uh an assessment that that needs to be scored externally by a you know a board like AP or IB or or whatnot, um, you know, let's say the International Baccalaureate, they have a proposal that they put forward. And I would always write comments in the margin, you know, to get them to think. And at one point I was going to be out of class. So I wrote more carbon comments than I normally do, didn't have time for as many um conferences. And they uploaded those comments to an AI because I could tell by what happened when they turned in the drops, the their voice seemed to disappear. And all of a sudden, my advice was just seamlessly in their paper. So I brought them up one at a time and I said, okay, what happened here? And they're like, we're really sorry. We just ran out of time and we thought we would see what happened when, you know. So I learned from that and I said, okay, what worked for many years is now become a recipe for how to get AI to write a really great draft for you. So now those comments live in discussions rather than in the margins, and it actually saves me more time because I'm not writing them at home, and um, I am building more time for discussions in the classroom and then sending students back into their thinking. So, but but the important thing I think in all of this is when I did figure out what they were doing, um it wasn't a policing situation and it wasn't a punitive situation. It was, I really want to know what happened. Can you explain to me how my comments are in your paper, but they're not in your voice anymore? And I really want to hear your voice. So, can we talk about this?

V.O.I.C.E authentication framework

Speaker 17:30

Wow, what just a beautiful opportunity to tune into identity. You know, like discovering who you are and your voice as a teenager is real it's it's hard, you know, like that's the whole thing. And and I mean, even as an adult, you know, or in college, like you're learning to write, you know, what's this professor looking for? What like, you know, how do I write for this particular purpose? So, like this kind of opportunity in high school to really think about voice, is this sort of where the voice authentication framework that you've designed comes from?

Speaker 1 18:04

Yeah, you know, it's funny. I I created this voice authentication protocol, and it um it's about visible drafting, right? It's it's not something the teachers are doing brand new. It's things that we've been doing for decades and decades, but um, it moves more of the drafting process into the room. So maybe years ago we would start some of that in the classroom and say, okay, finish this up at home. I have um retooled my class, so we do more of that. And actually, I started doing that pre-COVID with what's called the um the HL essay in um in IB, which is a 1200 to 1500-word literary analysis. It it tracks to many other literature papers, no matter what program you're in. Um, but it's uh it's something that works better for us because when do students cut corners? When they're at home and they have no one to ask questions to, when um they have three things due the next morning and they have limited time. So we decided to move that into the classroom. And so we start with um sort of that visible drafting, but the conversation is not just like, okay, I'm gonna talk to you at your um your initial conference, and then you're just gonna go, and then that's gonna be it. We have what's called the O of voice, the ongoing conversation. And that's you know, conversation not just between me and the student, but the students and each other. Um so it's all very collaborative. And then um I do something called interim reflection. So when students move to the draft form, they usually upload that to some sort of platform, you know, in a in a typed form. And then I have them come in and I have them take out a piece of paper and then they just jot down some things off grid about their paper. It's not a test, it's a tell me about what you just wrote this. So tell me about what your main assertions are. Um, what is your support? What what are some analysis points? Um, you know, a couple of full sentences here, and then you're gonna bring that with you up to our conference when we talk about your draft. And then what we do is I um, and that's where the the C comes in for voice the clarifying um conversation. So we look at what's on the screen, we look at their um, you know, their what they've written. And if there's a mismatch, then you have a very different discussion than if it's oh, like we just need to tweak a few things. If there's a mismatch, we talk about what happened here. Can you explain, you know, this this research paper a little bit more? Can you explain this terminology? What does it mean? And if they can't answer those questions, I just look at them plainly. I say, you don't own this. This isn't this isn't yours. So how you know, this is somebody else's.

Speaker 20:56

And I guess it's the moment where you sort of think, like, what what where's your thinking at? And like, how do we come back to like what you understand?

Speaker 1 21:03

Well, exactly, Phil. I say, so what do you know? And it's interesting because they know a lot, but they don't trust themselves to put that in the paper. So we'll have the discussion. And I even tell them, take out your recorder, let's record this discussion. What do you know? And I'll say, and sometimes I I'll say, Where is the draft that's in your voice right now? They're like, oh, I kind of threw that one out because this one sounds so much better. I'm like, no, no, bring that one back. And then let's go back and work through that one. And and I have had students say that their voice isn't enough.

Speaker 21:35

And this is the critical role, you know, of teacher, like to be, you know, we've talked about this uh, you know, before that it's the students that really have low self-efficacy for learning that are really quite threatened by the AI revolution because it's you know, like now there is this whole like level of polish on work that, you know, is clearly not what I'm capable of. Um talk to us a little bit about. your experience you know supporting students to build their self-efficacy for learning in this in the context of AI.

Speaker 1 22:07

Well I think it's I think it's what like some of the AI tutors, the the the um I think it's what some of the tech companies were hoping their AI tutors would do, right? It's like, oh the students who are um struggling the most will get so much help with these AI tutors on the side who are are there to answer questions when the teacher isn't there. But I think what they're missing is that that students will rarely trust an AI tutor when they'll trust their teacher right so and I think that I think that teachers rightfully get upset when they see that students have offloaded. But it wasn't until I actually sat down with students and just said the tone was was everything right what happened here. And I'm like you can't hide this from me. And they're like, well how do you know and I said look I have been reading student writing for decades. Students don't write like this. I don't need an AI detector to tell me this isn't your work. And they'll just kind of I'm like look just come clean let's talk about this and then then 98% of the students I mean really almost all of them will come clean at that point if they know they have another opportunity. I said I'm interested in what you have to say. I'm interested in your learning my whole goal is that you learn can can we get back to that and usually if you just frame it like that, you get the students who are in the gap and they're like I honestly don't know what to do because I feel like I'm not good enough. And I'm like well talk to me about what you know. All right let's let's let's do this and we we start to to have a process and that's where that clarifying conversation becomes really important. And then the last part E, evidence of ownership for voice is in the very after they go from draft form to the final we have a a final discussion and the students know that they're gonna have that final discussion. And think about if you know you're gonna have a final discussion, what do you do? You prepare for it. It's kind of like the old days where you would get one note card that you could use on an exam and you would write on it and you would do all these other things but by the time you did all of that you didn't need it. If students know that part of the grade and we do this at our school as part of the grade part of that grade is that verbal um evidence of ownership discussion that goes along with the paper. It's not just the product it's their discussion of the product that's part of the grade and a lot of students will, you know, and and are there going to be students who memorize things for the occasion sure you know there's always going to be students who are cutting corners that's that's the oldest story of all times. But but I find that if they think that you care and and and they are actually interested in the topic even a little bit and you can kind of push them they will work for you especially when they know you're gonna have a one-on-one with them. Now I've had teachers say there is no way I have time for all of this. You know what I do I'm I'm teaching fewer works I'm teaching shorter works and I never thought I would be this kind of teacher because I'm like oh we're not teaching anacrinina we're not doing this right but you know what you know doing something with more um depth rather than breadth is I I think the key to a lot of this uh because um we need time for that discussion and the discussion I mean you know the

The human in the loop

Speaker 1 25:31

the little cliche out there is human in the loop but um but it to keep to keep it more human and I think that's been the problem with the ed tech companies all along is that so much of ed tech is created to take the human out of the loop because I think that's just sort of the nature of ed tech right is that is that they can't really control how humans are going to react with their, you know, and and so you know let's deploy and then the students can work with the ed tech. But really it's like any any other good pedagogy the when the teacher is there and I like to kind of use the metaphor as director right um then you know if you don't have a good director in a play you have nothing. So um but it it doesn't mean that teachers have to do extra work. It just means they have to do things a little things a little differently.

Speaker 26:17

You know well you know we're talking about where the productive struggle shifts you know you're you're not leaving it up to the students to do things at home and you're sort of working with them through this process. And that process seems to me much more metacognitive. Like you're getting the students to reflect really deeply on what it is that they're learning and what it is that they think you know what are their ideas and how are they how are they presenting those ideas, whether it's you know in the oral conversations with you as a teacher in the conference or if it's the way that they're positioning their ideas in their written papers as well. And this voice framework gets them to think about ownership early on but it's also coming back at the end to look at the evidence of ownership. And I really think that is really key to sort of how is this learning experience going to serve you in the future? Did we get something done to be compliant and get it kind of turned in or are we really thinking about what this is all for in the long run? And I think it's interesting to sort of look at where edtech is going. You know in the past perhaps they were more sort of designing for education but now they seem to be like really designing you know alongside and with educators what do you see?

Speaker 1 27:29

I um I I I love the fact for example cognity is um is using a very ethical approach to AI um and you know and in you know in terms of some of their their grading practices their it's it's a second set of eyes um you know helping students you know look at you know look at student work um and not to offload everything but to you know to help to help give students more feedback in addition to their own you know that we started using conmigo a con academy's tool and even even salcon and their um you know the their whole team has admitted it didn't go exactly as planned and you know but I give a lot of credit to SalCon I mean he he he built he's built an amazing company and his intentions were 100% right. And when I used his product especially their essay feedback tool some of my struggling um writers did um did really love having an extra set of feedback but I used it as a second set like okay look at my feedback now look at the Khan Academy feedback what do you see in that liminal space between is there any overlap is there something different you know what and so it's that whole evaluative piece that isn't included as part of the package and you know why it's not really the ed tech company's fault right it's it's because it isn't always built into the professional development of and I and some of your other podcasts talk about the system right but but the way I see this working is evaluation is a community practice right it's it's not a solo skill. So if you look at any evaluation of anything with you know what you're doing in the classroom and especially with large language models and ed tech tools um that students learn better when they discern together right rather than individually because they they have each other and they're a teacher to lean on and that's where the learning can can grow. That's at least that's what I've been seeing in my experience.

Speaker 29:35

I

Support for teaching strategies

Speaker 29:36

know that you've been in the space of educating teachers and working closely with them for a long time. We've been talking a lot about the students and you know I just want to return to like the beginning of our conversation what are you seeing in terms of the what are you learning about what we need to be doing to you know improve the way we support teachers?

Speaker 1 29:55

Well you know it ranges you know you'll go into a professional development uh you know situation and you'll have people who are using this every day. I mean they couldn't live without some of these tools that's in their workflows they're having students experiment you know then you have the um other end where it's like these tools are making my life very very difficult I you know I have to police everything and then you have the people in the middle who are just kind of sitting on the fence waiting to see what's next you know so um bridging that one of the things that that I see is just um ongoing conversations and sharing time to share space and um and you and I have talked about that which is why you know you've developed a networking site and you know a networking time for um a you know an upcoming conference to give educators time to actually talk with each other because it's not just like people like you or me or whomever who do this and and all of a sudden disseminate what we know but but teachers need to share ideas and they need time and space for that. In this last February I reached out to um a former student of mine at Florida State University who um was working with um an AI association in Florida state and what they do is they go into you know um elder care facilities and talk about deep fakes and they do a lot of PD. They go to K to 12 they do you know so I said would you like to work with 130 ish uh IB teachers and talk to them about like how how you use AI in the university space and in your workflows. And she said sure and their dean who uh kind of runs their their partnership came down with them and they worked with the IB educators, sitting with them, showing them what's next. Because I think a lot of times you know especially in the K to 12 space you're not sure where this is all going. So um you know the students opened with a panel of of what this looks like in higher ed and um I don't like to think of it as K to 12 and then university I like to think of it as K to 20, you know, that we're all part of you know this same space. But these students were doing amazing things with AI. They were um you know and they were talking about how some professors forbid it and some one professor actually required the students to use AI. And then their final exam was an oral examination just like my I'm like that's what I do with voice. So it's like if we're kind of all arriving at the same thing. So my advice getting back to your question for educators is to you know and and I guess this is more not to educators but to people who are you know superintendents and in part of leadership roles is to build space in for people to um come up with ideas for how to tweak what they already do, not throw everything out and make it new, but but tweak and it will take some time. And I think the the difficulty right now is because there's such exponential growth with large language models. It feels like what what worked two months ago is no longer working. And it and if you change this and if you keep this as a police state you're never going to be able to keep up because there's always going to be some tool that's a workaround where it humanizes the voice or it does something else. But if you keep it where your whole purpose is I want students to learn. So we're gonna just work with this in the classroom as one tool amongst many, that becomes something that I think is doable for any educator.

Speaker 33:43

Well Michele one of the things that inspires me so much about our conversation is that you actually you know you you gave away so many resources. Let's talk a little bit about this conference session that's coming up at the IB Global conference in Denver this coming week. You know think more not less tell us a little bit about like kind of what's going through your mind as you're thinking about building a session like this and for those that aren't able to attend um what are the principles around this topic?

Think more, not less

Speaker 1 34:13

So think more not less is not just about students. It's it's about it's for everyone right so um so how do we do that in the age of AI? So you know anybody can use a large language model to think less right you can just offload anything and then turn it in as as your own work. I know people who use large language models and it takes them more time because they iterate back and forth so much that it it took more time than if they would have started it on their own and just finished it. So why use a large language model at all? Well because sometimes another set of eyes on something gives you a way to think about it as it gives you a problem solving skill. But with um with students especially I think sequencing really matters you know um you have your foundations first and then you use the tool to sort of deepen that but you you don't do that in isolation you do that within your community in your classroom and you um have students you you know analyze something in history in literature in biology and then you turn to the tool and you give the tool very specific parameters not to fix something for you not to answer all your questions but to ask more questions. And and um you know don't make me think less make me think more about this and and it's really interesting what the results are but the key to thinking more is the in the iterations and the iterations aren't simply part of the large language model they're with each other. And then having the kids have the discussion it's like that didn't even come from our book. That's a hallucination and somebody might not have realized that and then the students are talking to each other about something the large language model came up with and then that becomes a lot more interesting than students sitting at home generating an essay or a response and turning that in. But when I say it's for everyone I mean I'm thinking about an administrator who's trying to fit X amount of people in an auditorium in a space that might not work you know maybe upload a picture of your auditorium how might this work and then getting information from a large language model about that and then coming in the hallway and saying to another administrator hey I ran this by ChatGPT what do you think about this? They said actually you know last year we did X, Y, and Z, and that might be and then going back to the large language model and putting that information in. And it becomes sort of a habit of mind where you use the tool as just one other voice in the conversation. And I think that's the thinking more.

Speaker 37:01

Yeah my experience with AI has been very much around um iterative you know development of thinking thinking about the thinking you know slowing down you know ask me 20 questions one at a time let's really kind of go through a reflective process. There's you know a lot of this I've learned you know in innately and sort of by experimenting. Who are you uh paying attention to in education?

Speaker 1 37:34

Who's who's someone that you follow or like where are some of the where's the thought leadership coming

Inspiring innovators in this space

Speaker 1 37:39

from in higher uh the or at a Georgia University this is a um a professor uh named Michele Castlera what she does is she has her comp composition students do that piece by piece with their compositions and she will ask them you know have the AI she requires AI in her courses she is just an absolute pioneer and an absolute delight to follow because she literally has students ask questions along the way and it's all scaffolded which is which I think is fascinating. And um and then she has her students at the end of the course evaluate and they take a survey and then she shares some of those survey results online about what some of the students say like before this course I had no idea how to talk to a large language model. I had no idea how it could help me think through things in this way. And she's she's doing the a lot of the same kind of work that you are but she's training you know young university students to do that. And and another person that I follow um is Ethan Moloch. He's a a Wharton professor and he um you know an MBA professor and he also runs their AI lab and he um is just he plays talking about principled play he plays and plays and plays with AI but his whole mantra is that it's not that students know a lot about AI. They have to know first of all how to scope problems. They need the thinking skills but they also need the content knowledge. So I think that's really important just going back to what we were talking about with pedagogy it's very important that students understand the knowledge of the course that they understand also how to think those are two really important future ready skills.

Speaker 39:34

Absolutely it's the thinking is much more important than you know any of the content that we're using to do the thinking. You know as we as we finish up today like what are some of the what's the most important thing uh that we should think about in all of this I think the that the teacher is is probably one of the most important defining factors in all of this and the pedagogy.

Speaker 1 40:01

But I don't think it needs to be really daunting where the teacher needs to feel like everything hangs on you know what they do or say or whether or not they know everything about AI. But but um what I was saying earlier about um having those honest conversations with students about you know um I want you to think more not less let's talk together about how we can get there. And I think that that honesty and transparency at least in my experience um you know I have 25 plus years experience um in education when you're transparent with students about that when they know that you're all in um I find that they they want to rise up to that occasion you're always going to have students who want to cognitively offload or you know cut corners. And certainly AI has made that easier in some respects. And you know some days we just take all the technology away and we're all about the books and paper. Some days we add the tools in some days we take swords that are made out of foam and we act out scenes from Shakespeare and some days we put it all together you know sort of as a little you know cobble it all together um and it it becomes a type of play but I think it all equals engagement. And I think that that AI has a way AI can be incredibly engaging. Students take our their cues from us. And so I have found that I have been frustrated at moments but my my best days with AI are when I have those honest conversations with students and when I see the work that they've turned in that has been somewhat offloaded now turns into something that's authentic and and I I I have a lot of hope for for what we have in the future for um this new way of teaching and learning I'm Phil Evans and thanks for listening to the Education by Design podcast.

Speaker 42:09

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