Amplifying Your Impact with Everyday AI, with Tyler Moberg

In this episode, we’re joined by Tyler Moberg, an AI learning and training specialist and founder of Amplified Impact. Drawing on his rich experience as a classroom teacher, instructional coach, and professional learning designer, Tyler shares how educators can embrace AI as a powerful tool to streamline planning, boost creativity, and achieve meaningful results without losing the human touch. Tyler includes both mindset shifts and practical strategies in his guidance on how to invite AI to the table, not as a replacement, but as a collaborator. This conversation will help you rethink what’s possible when educators use everyday AI to amplify their impact. Visit AVID Open Access to learn more.

Transcript

Unpacking Education Podcast Transcript

Episode: Amplifying Your Impact with Everyday AI, with Tyler Moberg

Tyler Moberg 0:00
If you're not leveraging AI in your everyday work, you're missing an opportunity to be more effective and efficient as an educator and maybe even have more work-life balance, right? Which I think is a big struggle. It's okay to be where you are. It's not okay to stay there. There's always room to grow. Get in there and try it and play around and share it with others and celebrate the wins.

Paul Beckermann 0:23
The topic for today's podcast is amplifying your impact with everyday AI with Tyler Moberg. Unpacking Education is brought to you by avid.org. AVID believes in seeing the potential of every student. To learn more about AVID, visit their website at avid.org.

Rena Clark 0:41
Welcome to Unpacking Education, the podcast where we explore current issues and best practices in education. I'm Rena Clark.

Paul Beckermann 0:53
I'm Paul Beckermann.

Winston Benjamin 0:54
And I'm Winston Benjamin. We are educators, and

Paul Beckermann 0:58
we're here to share insights and actionable strategies.

Transition Music with Rena's Children 1:02
Education is our passport to the future.

Paul Beckermann 1:07
Our quote for today is from our guest, Tyler Moberg, on his website, Amplified Impact. He writes, "AI isn't just about working faster. It's about producing better outcomes, unlocking creativity, and achieving meaningful results, all while keeping humans at the center."

Paul Beckermann 1:23
All right, Winston, what are you thinking about that quote today?

Winston Benjamin 1:27
So for me, sometimes when I hear AI, I have to actually push myself from being a young child who grew up watching a lot of sci-fi movies where, you know, The Matrix, where AI was bad, right? Like, I recognize that I have to push myself. But for this one, I really love the idea that it's not about doing the menial things. It's about the opportunities to think about: What do I really want to say? How do I really want to say this? Now that I've gathered all the information, what's the best way for me to use my voice, knowing that I don't have to spend two or three hours doing the grind of getting the information? Now I can spend two or three hours thinking about what I want to do and how I like to show my creativity. So I like that aspect of it about unlocking the creativity because, again, it's giving you time. So I'm really feeling that idea.

Paul Beckermann 2:27
Yeah, I kind of settled in on that "unlock" word too, because I think right now there's a lot of people that are nervous about AI. They think AI is going to either take their job, or it's going to pull the creativity out of our students, or it's going to make them lazy because they're just going to cheat on every assignment. But I like the positive, forward thinking of "unlocking" because that means that AI is like a missing key that we can use to get to someplace where we haven't been before. And we don't know where that is exactly, but I think that's the positive, exciting way that we can look at it. So I'm kind of stuck on the same word: unlock.

Winston Benjamin 3:04
See? Teamwork.

Paul Beckermann 3:07
All right. Well, we are really excited today to have Tyler Moberg with us. Tyler is an AI learning and training specialist and the founder of Amplified Impact. His background includes experience as a middle school science teacher and as an instructional coach and leader. We want to welcome you to the show, Tyler. Welcome.

Tyler Moberg 3:26
Thank you, Paul. Thank you, Winston. Super pumped to be here. Honored to be invited. Thanks for coming.

Paul Beckermann 3:31
Yeah, we're happy to have you here. And, you know, I shared just a real brief introduction of you. If you want to take just a minute and tell us a little bit more about yourself, your background, let our audience get to know who you are a little bit.

Tyler Moberg 3:42
Yeah, absolutely. So, yeah, like you said, my background—I was a middle school science teacher for a huge chunk of my career, and never thought I would be doing anything different. I loved it. Got an invitation to be an instructional coach and instructional leader at a school called Crestview Middle School, and it's a school that I'm very proud to be a part of. Just the things we had going on between flex time and advisory, multi-age advisory, giving voice and choice, building agency and belonging for kids—just so many amazing things happening at that school where that really helped me grow a ton as an educator and then kind of see myself even as, "Hey, I could lead some of this work," and I didn't see that in myself until I had that opportunity. So, by the way, fun fact: we actually did start a podcast. I was part of starting a podcast at that school. The tagline was "Highlight the learning and efforts of our staff," where we would interview other teammates and just kind of rise to the surface and share, increase sharing. And it was so fun.

So then from there, I had an opportunity to join the Bob Pike Group. It's a relatively small company but a nationally recognized one, where I had the opportunity to travel around the country for the last couple of years and consult organizations on what does good training look like. And for really, for me, that passion of designing meaningful learning experiences where people walk away learning, retaining, and remembering what you hope. Getting to work in corporate America with companies, I learned that a lot of what is out there is like a lot of reading of PowerPoints and sit-and-get. And then being able to bring, you know, I guess you could call it almost reminded me of Zaretta Hammond for adult training, right? Of like neuroscience-based, research-based—whoever's working hardest is learning the most. That was a really amazing opportunity where I discovered AI in that work, started using it, started using it in that work and as a part of that corporate training world, and just fell in love with it and developed a passion. And so much so that I was spending all my free time learning it and taking courses and using the tools. And I ended up saying, "You know what? I love this so much that I think I'll start my own company called Amplified Impact, where I help people amplify their impact using everyday AI." And so that's kind of what I've been doing. And I can talk more about that, but it's—I launched October 1st last year, and it's been a really fun journey, unexpected where it's gone, but just super fulfilling work.

Paul Beckermann 6:15
Right now. Well, congratulations. About a one-year anniversary then, yeah?

Winston Benjamin 6:19
Congratulations.

Winston Benjamin 6:21
Coming up. I'm so glad that you're our guest. Speaking of your history in the classroom, your transition into corporate America, understanding the still need for the pedagogy of teaching, right, in terms of applying that and then in terms of engaging that in AI—so I'm really appreciative of your past and present as a way of helping our listeners and teachers potentially support their AI engagement. So with that said, as teachers start engaging and digging into this generative artificial intelligence—AI, right—what are some practical ways that they can integrate this tool into their everyday workflow? Right? Because that's really the thing. Teachers don't want another new thing they've got to think about. So what could they actually—how could they use this tool in their everyday workflow?

Tyler Moberg 7:17
Yeah, I love that question. And that's like, that's literally what I zone in on. And I didn't say—right now I mentioned I was doing a lot with corporate, but I'm working a ton with school districts and schools and leaders. And that question of "What can I use it for?" And I think that's the big question, right? It's like, "I hear it can do all these really cool things, but what does that actually look like in my day-to-day work?" And I think for me, number one is: don't think of it like one more thing, right? And you kind of alluded to this, but when I was a teacher, I remember the more I learned about what good teaching looked like, the more I realized what I needed to do, right, to actually have a well-designed lesson and an assessment and give feedback and be, you know, coming up with an instructional response and giving kids choice and differentiating. And gosh, that was like, you know, the more that I learned, ignorance wasn't bliss because I knew kind of like, "Okay, this is what a good lesson is." And so, you know, and then you see AI. AI for a lot of teachers, and they're probably like, "Oh great, we got one more thing to add to my plate of all the—you know, where's that going to come from? Where are we going to do that?"

So that quote that we talked about is it's not just to help you become more efficient in all those things, but to see it as a tool that can help you do those things better, to a higher level. Hopefully, if you're using it right, right? Yeah, you can cut shortcuts and you can just do, you know—sure, you can make more worksheets, but that's not the point, right? It's to invite it to—when I work with teachers, I'll say, "You know, what's on your to-do list today?" And whatever that is, that's the thing you should invite AI to the table on. And it's not just lesson plans. It's going to be all the other things that are on teachers' plates, right? And so I think that is huge. Don't think of it as another thing. Invite it to your day, your work you're already doing. That's how you're going to learn the limits, and that's how you're going to learn what it's currently good at. And also, my experience has been I've been pleasantly surprised by a lot of it. I'm like, "Oh, well, that's something to work with. I can work with that." It helps me hit the ground at like 30 miles an hour versus from scratch, you know. It's not done. There's still a lot of me guiding and steering, but yeah.

Paul Beckermann 9:36
Kind of goes back to that quote at the beginning. There's a little bit of unlocking that's going on there—unlocking your ideas, new ways to go. I like that idea of inviting AI to the table. It's like AI is now a collaborator with you. It's like a co-planner. That's cool.

Tyler Moberg 9:54
Oh yeah. I mean, I mean, thinking of it like if you think about the PLC process, like the four PLC questions, right? What do we want our learners to know and be able to do? How will we know if they learned it? What if they do, and what if they don't? If we invite AI to those four questions alone, right, helping unpack standards, helping write learning objectives, scope and sequence, you know, that's question one. Let's come up with some high-quality assessments, you know, and going through, you know, determining instructional responses. Like if we invite AI to those four PLC questions alone and we think of it like another PLC teammate, really, I think that has a ton of power, right?

Paul Beckermann 10:35
I like that idea of bringing it to the table as a teammate because that does not mean you're giving up any power. You're just collaborating with another really smart teammate, right?

Tyler Moberg 10:46
Yeah, who makes mistakes, for sure, you know? Who can do more than you think, but yet, as long as we have that mindset—we're the thought leaders in that work. AI can be our partner along the way to help us do some of that stuff.

Paul Beckermann 11:01
We still got to check their work sometimes. Absolutely. I hope people check my work sometimes. So, you know, we're going to check. So kind of along that same line, you know, when people are getting started—kind of a follow-up to Winston's question—sometimes there are misconceptions because we don't really know what we don't know yet. What are some of the major misconceptions about AI, or maybe even mistakes that people have made that you're seeing as you're kind of going out and around working with people?

Tyler Moberg 11:30
Yeah, I'll tell you one that's like one of my passion areas because it's just really changed the way that I interact with AI, and that is not leveraging or using the voice prompt button. There's a little dictate button on most of the tools—not all of them, but most of them have that right now. Are you guys using that button when you prompt?

Paul Beckermann 11:49
Sometimes. I feel weird talking to myself sometimes when I do that. But no, it's really handy because it's like having a conversation.

Winston Benjamin 11:58
It's like Siri, yeah.

Tyler Moberg 12:01
But like, that idea of being able to spit out a messy idea and unformed thought and just talk to AI like you talk to a person can really up that prompting game to get results that are more aligned with your goals. Because most people's prompts are very short. They're like a Google search, right? Seven to nine words is what they say. And what if we just kind of said, you know, and we press that button and we just go, "Here's the context. Here's what's going on. Here's what I'm trying to do. Here are my goals." Now, because AI is a pattern predictor, those outputs are going to be way more closely aligned to my actual goals. And then it won't have to adapt it as much, and it'll help me just get higher-quality output.

Paul Beckermann 12:43
Have you seen people have success with that?

Tyler Moberg 12:47
Oh yeah, yeah, definitely. I mean, that's one of the big things in a lot of the different workshops that I lead—just having people kind of get into doing that. And it is a little awkward when you're around people. And it also is a little awkward when your wife says, you know, "Tyler, you're talking to me like you talk to ChatGPT. Don't you know? Your tone of, like, you've got to have a cadence to it, right?" I think we don't give enough context, and I think that it doesn't need to be clean, and there's not a magic formula to it. It's just a matter of kind of getting that into the prompt. So that would be one. I definitely have some others, but any other thoughts on that from your end? I'm curious.

Paul Beckermann 13:24
No, I think it's underutilized too, and I think maybe it's the feeling self-conscious about doing that around other people. I do think that plays into it. You know, if you're all by yourself, you know, maybe you're more apt to give it a shot. Yep.

Winston Benjamin 13:39
Yeah, yeah. Sometimes I think it's like the art of writing also is valuable when you have to think about what you want to really try to get to, to really get condensed that thought. But I could hear the brainstorming part of the value of that, absolutely. But for me, sometimes it is being able to craft something that I valuably want to get back because then that allows—for me, to then interrogate because my question is: Did it clearly understand what I was looking for in this jumble of thought, right? So unless, you know what I mean, unless there is that two-way—"Am I understanding this? Am I getting this right?"—then that becomes a better brainstorm. So I think that in that way, I can see. But I recognize the value of trying to be, to create a concise idea, right, in just the way that we're trying to ask our students to create those ideas, to then ask AI to help support that, right?

Paul Beckermann 14:43
Yeah, yeah, that resonates. I've seen somebody take it even one more level up. I've seen people turn the camera on and show AI what—so that's that conversation again, right? "So here's what I'm working on. I'm trying to do this. What are your thoughts about that? How should I approach this?" And then, you know, having that visual on there as well. That's like a whole other level playing field.

Tyler Moberg 15:06
Yeah, yeah, that is—I don't see a lot of people using that. I played with it when it first came out, and then you kind of forget about it, right? Yeah. But, you know, that process of writing, either typing your prompt or saying it—that is part of the learning process. As we're using it as teachers, and if kids are using it, they're having to put thoughts to words. That is—they're carrying the cognitive load. They're trying to shape and form it. That, for me, has led to deeper learning and understanding.

Winston Benjamin 15:38
Without a doubt. I love the iterative process, absolutely, right? The actual doing it instead of just being like CliffsNotes or going back to where you just get a shorthand version of things. But you said something in your answer that I'm still kind of like, "Ooh, I want to pull that out a little bit more." The next question: You said AI is a predictor, right? How it predicts your ideas. If you use it enough, it starts to recognize your pattern because, as it is, it's just using algorithms to understand ideas, if that's—if I'm even getting that understanding, quote, right. So here's my question to you: How do we maintain the human in that loop, right, where instead of it just predicting our thought bubble, right, how do we continue to make sure it doesn't totally automate, right? We know you need to do this, but also make sure that it's not done for us but to make sure it's done with us, right? Not to us. So how do we make sure that we keep and maintain that human interaction as we move forward?

Tyler Moberg 16:50
Yeah, so I think it's way too easy with AI to generate a ton of white noise, a ton of text, a ton of whatever it is, you know—code, images, sound, video. You can make so much stuff that's just not good or not helpful. And that's where I think creativity comes into play—realizing with AI, you can idea-brainstorm, and it's infinitely patient, and you can come up with so many different, like, I call it menus of ideas. Where, as the human in the loop, I have taste. I have judgment, and I know what good looks like, and I know what I'm trying to use it for. And by the way, I love this quote—there's some quote to the extent of: The better you are at your craft, AI will make you just a little bit more. Because if you're really good at your craft, you can shape it because you have a high standard of what good looks like.

But with this concept of, "Okay, I use AI, I make a bunch of stuff. Now I pull out the things that I think are good," and I picture it kind of like a giant funnel, almost like we're a human funnel where our job is to input, filter, refine, and really extract and work with some of those gems, some of those best elements, and then do something with it. So that's where I really see the human in the loop with this.

Paul Beckermann 18:14
I love that idea of the human as kind of sitting at the funnel. They're like the gatekeeper a little bit, right? You know, when I was in Scotland, the sheep come running in a herd, and the dogs all corral it into this tiny little funnel. But you need to be at the funnel to make sure the right ones get through.

Tyler Moberg 18:34
Yeah, yeah. And then when you look at creativity—you know, we were talking about the beginning of the conversation—Yo-Yo Ma said, "Creativity is infinite. Energy is not." And if we have all this creativity and we can, you know, that's the cool part about AI—if you can envision it, if you can dream it up and you can describe it using natural language, you can make it, you know. And that is unlocking opportunities that have never really been possible before. Two years ago, they weren't possible, right? I can make a music video that teaches a concept, or I can code an interactive learning game just by saying, "Here's my standards and here's my goals. Make an interactive learning game," right? Like, stuff like that. So I just think that when you look at creativity and you look at the human in the loop, you know, there needs to be the human guiding and steering and iterating, like you said earlier, Winston, and just coming up with the stuff that's actually going to be useful, not white noise.

Paul Beckermann 19:32
That kind of makes me think of mindset a little bit. What kind of mindsets do you think people need to have now as they engage with AI? Because it's a different experience than what we're used to.

Tyler Moberg 19:44
Yeah, so I've thought a lot about that because, you know, these are new mindsets. They're new paradigms. You know, AI has totally caught us off guard, right, in terms of how we see work. And I've narrowed it to four. So we've actually—they've been coming up a lot actually already—but I have four mindsets.

Mindset number one is: We need to craft communication to get results that match our goals. So we think of it like there's a communication that needs to go on between us and whatever AI that we're using so we can paint a clear picture of what we're aiming for and get what we want, right? So it's all about communication as the first mindset—crafting communication.

Mindset number two is: Interact collaboratively with AI as a capable and fallible colleague or thought partner—that's the word I like better. But collaborate. We've talked about that word as well. But capable and fallible thought partner—makes mistakes. We are the overseer. We are ultimately responsible for what we put in and then what we do with it. And, you know, I think a lot of people's—and tell me, I'd be curious your take on this—a lot of prompts, you know, AI interactions, where a lot of people are kind of short, they might do it and they might be like, "You know, this wasn't very good," or "I didn't like it," or "I took it and I changed a bunch of stuff." And that's good too. You should change stuff. But what if we kept it as a collaboration and we just kept going and we were like, "Oh," you know, we continue down the thread of what we were working on to continue to come up with better stuff? So think of it like a collaboration.

Paul Beckermann 21:21
The one thing that comes to mind with the collaboration piece is when we're collaborating with humans, we ask them for their opinion. And I don't know if we always do that with AI because I think we should be asking AI, "What do you need to know from me so that we can together come up with a better idea? What questions should I be asking you? And what do you need from me?" That makes it really collaborative.

Tyler Moberg 21:46
Yeah, and it's actually a prompt engineering strategy. Two parts to it. One, if you say, you know, "Explain why" or "What are you thinking behind it?" to AI. But then one of my go-to prompts—this is if you know nothing about prompting or even if you do—if you throw into the end of your prompt, "Interview me one question at a time to learn more so you can give me the best possible answer." That's it. "Here's what I want to do. Interview me one question at a time so you can learn more to give me the best possible answer." And that will change the way that you interact with and collaborate with AI because it's going to actually ask you some pretty high—I've been shocked and pleasantly surprised by some of the things that it's asked me. And as a result, because it has all that context, now the output's more aligned to what I want.

Paul Beckermann 22:35
Yeah, I love that.

Tyler Moberg 22:39
So then the third mindset is—and we've actually been, so funny how these have really been coming up the whole conversation because they're really embedded in the way that I think about AI—is narrow creatively with human expertise. This is where that third mindset—we're the funnel. Our job is to input, to get a lot, to guide and steer, and to come out with something that's useful. And so that's really—it's the end of the framework that I'll share with you shortly.

And then the last mindset is: Ground critically and responsibly the inputs and outputs. And what that means is, you know, we're critically evaluating two things—what we put in. So what we put in: Are we putting in data that we shouldn't put in, like student last names or anything, you know, that is a personal identifier that maybe we should just delete or extract or anonymize? And then the other awareness that I don't know if this has come up on any of your podcasts, but just an awareness that when we prompt, when we input into AI, there is an environmental cost to that, right? It does use energy. It does use electricity. And if you're conscientious of that, at least so that you're not wasting prompts, but you're really thinking through, like, "I'm voice prompting, crafting prompts, being clear." You're going to get better outputs than if you just do little tiny phrases at a time, and that actually taxes it more. So that's the input part.

And then the output part is: With what we make, you know, are we—if credit is due, right—are we giving credit? And that's a really great question right now. Like when do we credit AI? That's very, you know, to what degree and how did it help? And then with the outputs, are we checking it for accuracy? You know, did it hallucinate? Are we putting out something that's not true? If so, we need to be the filter on that. And then, is it biased, right? Because AI is a pattern predictor, and it learned a lot of patterns on the internet and what it was trained on, and so that can come out in the responses. And so are we filtering for that? Are we saying, "Does this represent what I want to represent?" And if not, we're giving the AI feedback, and we're changing it, or we're changing it ourselves, or, you know, making adjustments.

So really, all four of those mindsets, they're not in an order. They all kind of overlap. But what I love about them is one of the key words in every single one—have you talked about the Four Cs on this show? The future-ready skills: creativity, probably communication...

Paul Beckermann 25:24
Communication and critical thinking. Yep.

Tyler Moberg 25:26
And critical thinking. They're all embedded in those four mindsets because I just think those are the way that we need to be teaching kids too—how do you interact with AI?

Winston Benjamin 25:36
I know that you developed this framework called the CRAFTING framework. What is that CRAFTING framework, and how could someone use that?

Tyler Moberg 25:47
Yeah, so I love to learn new things, and when I was getting into this, I was taking just tons of courses and reading a bunch of books and following a bunch of thought leaders. And what I was finding was I was finding useful things in a lot of different places that I didn't know where to put, right? I had seen prompting frameworks out there. There are tons, you know, plenty of ones that are just for prompting. And what I was like, "What's missing here is the mindsets." And what's missing here is not just how do you put input into AI to get something that you want? And so that's kind of where the CRAFTING framework—the idea of it came from because I was like, "I feel like there's a need here to kind of put it all together in one place." And so there's—what I would describe it as is mindsets, which we've talked about, and skillsets to responsibly leverage everyday AI. That's kind of what I would describe it as. And I was just trying to figure out, "How do I make this sticky?" You know, kind of thinking about my background in learning. "How do I package this in a way that I can share it with others so they can learn it too?"

And I will note, if you Google this, there is a pretty awesome one called "Crafting AI Prompts," and it's a great framework. It has really good—a few prompting elements in there—but different enough in a way where this one is really geared to those mindsets and to some different bigger-picture ideas of how to approach AI.

Paul Beckermann 27:21
I know it's a long framework, and we don't want to dive too deep into each, but can you give us a quick overview? What do each of the acronyms stand for?

Tyler Moberg 27:30
Yeah, so the CRAFT part—we talked about crafting communication to get results that match your goals. This is just kind of crafting basics. The C is context. So you say to AI, "Here's who you are, and here's what you're good at." You kind of establish this persona. And I'll give you an example after this. But then R is request—what do you want it to do? Here's your task. The A is audience. This will assist with goal alignment. So who's it for, and what's the goal? The F is format. So how do you want it to look? Show in a rubric. Show in learning objectives. Show, you know, just listing the style of the output.

Now, something with that format: An even better way to provide format is to upload examples or exemplars to say, "Here's what good looks like. Study and learn from these and make me more like that." That's one of the best prompt tips out there. You know, "Here's a great assessment I have. Upload it and say, 'Study and learn this. Here's what I want. Make a new one for these objectives or these standards.'" And that one is so powerful.

And then the T is tone. And I used to describe tone as optional, but the more that I do it, you know, because think about an output for AI—it's going to be whatever is the most mainstream possible answer because it's a pattern predictor, right? So if you don't say in there something like—at least right now, I'm sure it'll get better—if you don't say, "Be learner-centered," it's probably going to be a little more traditional lecture-style type of lesson, right? If you don't say, "Be research-based," if you don't, you know, those are a couple of examples, but when you name that, it's going to change the way that it outputs.

Paul Beckermann 29:12
What's the ING?

Tyler Moberg 29:15
Yeah, so that's CRAFT. You craft the prompt. And then on the back of the—so the ING, we've actually talked about these, so it'll be really fast. The I is interact collaboratively with AI as a capable and fallible colleague. The N is narrow creatively with human expertise. And the G is ground critically and responsibly the inputs and outputs. So we kind of already unpacked those. There's a lot more to all of this, but that's just a big-picture overview.

Paul Beckermann 29:41
That's perfect. So as you were building this, I'm curious: What were two or three of the big aha moments or takeaways that you had kind of developing this process? Anything kind of rise to the top for you?

Tyler Moberg 29:55
Yeah, I mean, I think, okay, so I don't know what you've learned or heard about this, but probably prompt engineering is kind of getting a bad—have you heard, "Oh, we don't need to prompt engineer anymore"? And I actually don't like the word "prompt engineering." But have you heard any of that?

Paul Beckermann 30:07
I mean, at the beginning, it was like this was going to be everybody's future career—you've got to become a prompt engineer. Yeah. And then, yeah, in the next breath, it seemed like people were saying, "No, you don't need to know anything at all. Just talk to it." So yeah, that's what I've heard. I mean, it's kind of like the pendulum has swung completely.

Tyler Moberg 30:29
Yeah, and I think that's such a bad term. "Prompt engineering" sounds so technical. But you talk to it like you talk to a person, and you communicate what you want, right? That's really essentially what prompt engineering is. The CRAFT part here is, "Oh, these aren't just kind of good elements of good communication," of saying, "Here's who you are, and here's what I want, and here's what I want it to look like." I do think that certain systems are getting better, right? Or even, let's just say Magic School or SchoolAI, right? They have the prompt engineering in the background where they've turned the prompts into buttons that you can just fill in what you want, right? But just realize you can do any of those things that you can do in those tools in any of the big tools, right? ChatGPT, Google Gemini, Claude, Copilot, Grok—all of them.

Winston Benjamin 31:13
So here's something that I actually enjoy doing. It's just the "Hey, what have you been thinking about?" So what have you been thinking about lately regarding AI—just anything? Where's your brain at? Where's your mind at? Just your thoughts as you are engaging with your own thinking. What are you thinking about lately?

Tyler Moberg 31:37
Yeah, well, the name of my company is Amplified Impact, and what I mean by that is I want to help people use AI to amplify their ability to make an impact. And in what I do—so I do a lot of traveling and training schools and organizations about how do you use everyday AI, right? And a lot of times it'll be a short one. It'll be, you know, maybe it'll be a two-hour crash course, a half-day crash course, a full day, you know, deeper dive. And I really am like, "Okay, what is going to make the biggest impact?" And I've just been thinking about change management, you know, because one-and-dones—the research shows one-and-dones don't work, right? You need leadership. There's so much more to it. It needs to be job-embedded, ongoing, relevant to the goals of your organization. And so I'm like, "Okay, so what are some ways that you can actually implement this stuff in a way that's practical and actually moves the needle?"

So I guess I was thinking about, like, what are three things that I think are helpful for that? One is increase sharing and de-privatize your practice. And I've got to credit my school that I was at. I mean, that was our big phrase: "We're going to open doors. We're going to increase sharing. We're going to de-privatize practice." The more that you can share your experiences with AI—within your PLC, within your staff, maybe you structure time and space for it in a staff meeting, right—but like, "Hey, let's all round, small group, share: How did you use AI, and how did it go? Did it help you? Did it not? What questions did you have?" It's not perfect, right? Where were the problems? But if we can have better structures to share more, I think that's going to really spur growth in our teams.

Number two is celebrate the wins and be like, "Oh, that felt good." Whatever you tried, whatever you did, don't just keep moving and don't pretend like it wasn't awesome. You know, celebrate the win and recognize that. And you get a little dopamine hit from that. And I think that'll reinforce some of that behavior change.

And then the last one is treat it like play. One of my favorite things to do with AI—it's becoming less and less common just because of where things are at—but I'll have a whole afternoon where I'll be like, "Oh, I get to go and try out a bunch of new tools today," or "I get to go experiment. I have this task, and I wonder if AI could help me with that." And I go and I invite it to the table, and that thing—and it feels like play. And sometimes it's amazing, and sometimes it's like, "Oh yeah, it's not there yet." But that discovery and that mindset has been, I think, really, really big around change management. And yeah, so those are the three things: celebrate the wins, increase sharing, and treat it like play. I think that's going to help move the needle.

Winston Benjamin 34:27
I love that. I really do love that. Again, play is learning, right? When you're playing, you're actively engaging with more parts, and you'll remember that. So I mean, that's such a—

Paul Beckermann 34:38
We don't play enough at all.

Winston Benjamin 34:40
At all, as adults, right? Like, enjoy engaging with it. It's like, "Yo, I'm going to learn this inside and out by breaking it and doing it all," you know what I'm saying? So I really appreciate the concept of that because, you know, sometimes it feels like you're going to break AI, and it's not going to be a good thing if I ask this, you know what I'm saying? Like, "What am I doing?"

Now it's time for the next segment: What's in the Toolkit?

Speaker 1 35:06
Check it out. Check it out. Check it out. What's in the toolkit? Check it out.

Winston Benjamin 35:17
So today we've talked a lot about AI. We've learned about the CRAFTING framework. We've been given a lot of different tools to think through. Paul, as you think, what's the tool that you want to throw into our toolkit?

Paul Beckermann 35:32
I think I'm going to kind of reinforce the idea of using AI as a collaboration partner. Think of it as another—I mean, it's not a human being, but interact with it like it's a human being. Have those kinds of back-and-forth, and like Tyler said, maybe you turn on that microphone mode and have it—if it's easier as a conversation, then have a conversation. But go back and forth and have that communication with it as if it is a fallible—again, you've got to check things—but a partner in your planning. I think that's a great place to start, and it's not super intimidating. So even if you haven't engaged a lot with AI, I think that's a good way to start.

Winston Benjamin 36:13
I think it's a great way to start. Here's some—take Paul's idea of how to do it, and then try SchoolAI. That's a really good tool to definitely try out. But I believe, going back to the original quote of "unlocking your creativity," let's use the tool to unlock our ideas of thinking about how do we reach our students? Because we know our students better. So we can allow AI to answer some questions on how we can make it better and more creative to engage with our students. So I really love—I've been really thinking about that "unlocking" part from the beginning because we've all rounded back into that at some point in this conversation. So I really want us to continue to think about how do we unlock learning for our students. Tyler, it's your turn. What would you like to throw into the toolkit?

Tyler Moberg 37:06
Oh, can I just build on your two and then share mine? Because I've got to—both. So as teachers, I think there's a lot of misconceptions around how kids are using AI, and I think the more we learn how to use it for our own good, that will trickle out to our learners, and we'll see differently how they can use it, right? Because yes, it can be used to shortcut learning, and yes, it can be used to deepen learning. And so the better we do at just getting in there and playing and doing those things, I think that's going to make a big difference.

And then, Paul, I've got to say the anthropomorphism piece—as adults, we're good with that. We get the difference that AI is not human. And there is a risk as we talk about this with kids just wanting to—and I know you're not intending this, but I just think it's good to call out because I know there are going to be people listening that have been in this conversation of we have to be really careful that kids know AI is not a person and, you know, just that clear line.

Paul Beckermann 38:08
I think it's really good that you mentioned that too, Tyler, because, you know, there are a lot of stories in the news right now about kids befriending AI, getting dependent on AI. It becomes—I don't want to say a crutch, but it becomes a replacement for that human interaction. So I do think that that's an important thing to note.

Tyler Moberg 38:28
Yeah, yeah. And here's my tip, my tool: If you don't have the app for whatever your major tool of choice is—if it's Google Gemini, if it's Claude, if it's ChatGPT, if it's Copilot, Grok, whatever—if you're only working in the browser, get it on your phone, and you can work between the two easily. And there are some cool extra maybe buttons potentially that in some of the apps show up. And it just allows you to expand your flexibility when you get an idea to do that collaboration with that partnership. So get the app of your tool of choice would be my tip.

Paul Beckermann 39:05
Cool. All right, it's time for us to jump into our one thing.

Paul Beckermann 39:12
It's time for that one thing.

Paul Beckermann 39:20
It's that one thing. All right, one thing time—time for a final thought today. What do you got, Winston?

Winston Benjamin 39:26
I'm really rounding back into this idea of when do we provide AI with credit for how it's supported us? Because, like, I—many of the listeners know I love hip-hop, and sometimes giving credit for a person who says a word and then you add that into the sentence of the line—how much credit do you give that person, right? That's hard to define, but that line would be different if it wasn't for that word, right? So sometimes we do have to credit even if it's a small, minuscule—and going back to that earlier point of if we don't allow our students to learn how to model engagement, right, how do we support them from not just going and using it to cheat?

So if we don't demonstrate and show, "Hey, this is where and how I use this tool. This is how this tool created and provided and supported me through this piece," I don't think we'll be able to help students recognize how to give credit or validate their own thinking by demonstrating where AI was in that process. So I'm going back—I'm going back to this idea of how do we give credit while also allowing our students to claim credit?

Paul Beckermann 40:54
Yeah, love it. I'm thinking about a pretty short phrase that I think Tyler said a couple of times: "Invite AI to the table." You know, it's part of the play experience, right? When you've got a problem that you're trying to solve or if you've got a task that you have to complete, invite AI to the table and see how that goes—interacting and collaborating with the AI assistant—because that is how you will learn what it's capable of, the strengths, the weaknesses, the things that you need to figure out a little bit more. You've got to invite them over first.

Tyler Moberg 41:27
Yep. People forget because it's a new mindset, right? I know some people that have a little Post-it note that says—they'll put it up here on their computer: "How might AI assist with this? How might AI help?"

Paul Beckermann 41:38
For sure.

Tyler Moberg 41:40
I'm going to channel my inner mentor, Tim Anderson. I quote him often on this thing, and he started every single staff meeting with this, and it didn't get old for me. He would—every single day he'd say, "It's okay to be where you are. It's not okay to stay there. There's always room to grow." And I would add: If you're not leveraging AI in your everyday work, you're missing an opportunity to be more effective and efficient as an educator and maybe even have more work-life balance, right, which I think is a big struggle. So it's okay to be where you are. It's not okay to stay there. There's always room to grow. Get in there and try it and play around and share it with others and celebrate the wins.

Paul Beckermann 42:20
I love that. And before we log off here, Tyler, you want to share with our listeners where they can go to find your website? What's that web address?

Tyler Moberg 42:29
Yeah, amplifiedimpact.solutions. And I love working with educators. I have worked with lots of other fields as well, but things like, you know, whether you're—I've done a lot of district kickoff keynotes of, you know, "What is AI? How do we use it? What are the mistakes to avoid? And here, what's this framework, and how can we use it?" And there's been—that's gone really well, and I think that's really helped schools with that adoption of getting some common language and an experience dedicated to that. And then I do all kinds of different things, like coaching or extended modules. And I would love to be a part of that. If you have any interest, please reach out.

Paul Beckermann 43:07
Well, thank you for being a part of this episode with us. We really appreciate you being here, Tyler.

Tyler Moberg 43:12
Yeah, thanks. I'm honored, absolutely honored that you invited me to be a part of this. This was a fun conversation. Definitely was. All right, take care. Thank you.

Rena Clark 43:22
Thanks for listening to Unpacking Education.

Winston Benjamin 43:26
We invite you to visit us at avidopenaccess.org, where you can discover resources to support student agency and academic tenacity to create a classroom for future-ready learners.

Paul Beckermann 43:39
We'll be back here next Wednesday for a fresh episode of Unpacking Education.

Rena Clark 43:43
And remember: Go forth and be awesome.

Winston Benjamin 43:47
Thank you for all you do.

Paul Beckermann 43:49
You make a difference.