Episode 2 | Fostering Experimental Research in Teaching & Learning

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Welcome to EduCast 3000. It's the most transformative time in the history of education. So join us as we break down the fourth wall and reflect on what's happening. The good, the bad, and even the chaotic. Here's your hosts, Melissa Lobel and Ryan Lufkin. Hey there, everyone. Welcome to InstructureCast. I am your co -host, Melissa Lobel. And I'm your co -host, Ryan Lufkin. We are super excited for this episode. We have two really special guests with us.

And they're here to talk not only about experimental research, which we're going to dig into the work that the Terracotta Project has done, but also I think get a little nerdy around education and learning in general if we can go there. So with no more further ado, I'm so pleased to introduce our two guests. First, we have Dr. Benjamin Mautz. He is the director of e -learning research and practice lab at Indiana University, a faculty member there as well in the psychological and brain science area.

And then also joining us is Dr. Mary Murphy, the Herman B. Wells Endowed Professor of Psychological and Brain Sciences at Indiana University as well. Welcome Ben and Mary. Thank you so much. So happy to be here. Thank you. We're excited to have you. So Ben, let's start with you. Tell us a little bit about yourself, maybe your professional journey, areas of research, something fun. We'd love to hear more about you. Sure. Yeah. So let's see. I had a nonlinear journey. I started in grad school being interested in

cognitive science and actually wound up dropping out of grad school. I got recruited to go work in marketing in a marketing firm in Los Angeles. They offered a ton of money. I was going to make more money than my assistant professors were making. And that seemed really alluring when I was poor as a grad student. Got really excited about like big data analytics. That was what was hot at the time in marketing and climbed up the corporate ladder a little bit and then decided this was not for me. I got to a certain rung and was like, no, I need to go back to academia.

But even while I was doing all of that, I was really excited about teaching. was like giving classes to my marketing firm. was like teaching them lunch and learns. I was very strange. So yeah, the return to academia was also very natural because I love to teach. I spent, I don't know, a long time, like over a decade as a teaching faculty member and started doing research on teaching, started doing the big data analytics that I'd done in marketing now on my teaching. And yeah, found myself in this position. So I'm now an assistant professor and also leading some of the technologies that I think are going to be really useful to being able to do research on students.

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Awesome. love it. Mary, your turn. Yeah. Well, I am a Texan at heart, born in San Antonio. I went to UT Austin for undergrad, and that's where I first got exposed to social psychology research. It was very much by accident, where at that point they had bulletin boards on the walls outside the advising offices. And you could pick from index cards on the bulletin boards which lab you might want to work in. And I just happened to choose off the board a social psychology lab.

And suddenly three years later, I was applying to graduate school to go and get my PhD in social psychology. I went to Stanford, I got my PhD there. I've been studying issues of identity and context and how our different contexts and the people around us shape who we are and who we become and how that influences the things we pay attention to, the things we learn, the things we develop over time. I love both those stories. I love the paths that people take to find their journey.

Yeah, it makes me feel a little bit better too, especially Ben, because I was working through my EDD and got lured by a corporate job and I actually did not get back to it, which I'm still now admitting to the world that I didn't do that. But I get that lure when you're a poor grad student trying to figure out how to do this and that, you you'll find your journey. Maybe it's still in my journey yet. I think about it all the time. Yeah, it's not going anywhere. I love it. That's right. That's right. It's not going anywhere.

Well, I have one more question for the both of you and I will start with you, Mary, on this one. So we'd to ask our guests also a favorite learning moment. And it could be one where you were teaching. It could be one where you were a learner yourself, anything, you name it. What's a favorite learning moment for you, Mary? Well, last summer I decided to take up the cello. Music is in my family and my background. so I am...

I play violin and also piano and I just was really interested. got obsessed and I just, know, so Bloomington, Indiana has one of the best music schools in the country. And so we have incredible instructors. And so I just started to take cello lessons for the first time. And I wrote this book and for a book, I had to go on this big podcast. And at the very end of the podcast, the host asked me if I'd play some cello. I was three weeks in to learning.

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cello and I texted my cello teacher and I said, you know, I need to do this. We need to record at your studio. She said, you're not ready. and so that was part of the thing is that we're always learners, you know, where we are is where we are and we're going to get better. We're going to learn.

And so I played Twinkle Twinkle Little Star. Mary had a little lamb for the first time. that was my most recent learning experience and making myself vulnerable in the process of learning. that's incredible. what a fun story. And did they play it on the podcast? They will be playing it on the podcast. The podcast hasn't hit yet, but I think they are going to end.

and take us out at the end with a little bit of one And then we'll drop a couple weeks later, right? I love it. That's right, that's right, that's right. That's right. So good. OK, Ben, how about you? Favorite learning moment? I'm going to give a much more standard middle of the ground on my professional journey sort of learning moment. Historically, in all of the different ways I've done science and done cognitive science, the question kind of always becomes like,

How can we get at mental states? And this is something that I've explored from a variety of different angles. done brainwave research and response times and eye tracking and all of them have their own special flavors and special unique capabilities. Eye tracking is especially wild. Like if you ever watched like a path of somebody when they're doing a task and you can see where their eye movements are, it's like you feel like you're inside their head.

When I've been starting to play around with this in education, I've always looked for that same feeling of like, I've got data now, it gives me strong insight into what a student's doing. This doesn't necessarily come out of the box. I've built my own little assessment tools that give me log data. The first time that I deployed a learning tool on a class of students, like a large class of students, and could dig into the log data, like the actual transactions of where they clicked and when they clicked and what the order of the clicks were, and how that led up to different grades.

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It was just like the eye tracking experience where all of a sudden I felt like I was getting this very covert but very illuminating sort of view of what a student's experience was and when they experienced challenges or when they had no challenges at all and just kind of like magically got through to the end. So yeah, this like wake up moment at this moment with like a totally homebrewed assessment tool that made me feel like there's something there and like if we built the right sorts of tools.

we could get better knowledge and better theory about what might be going on in education and practice. Yeah. I love that story. mean, for so long, learning has been a bit of a black box, right? Like we can't, how do you peer into that student's brain to see how are they processing not only the interactions with the content or the instructor, but also the environment, a lot of about the research you do too, Mary. And so that's so interesting to think about how technology can get us so much more inside that black box if possible.

Which I think leads us to my first question I wanted to ask you, Ben. And part of this conversation is this idea of experimental research behind terracotta and like why you even founded the work around terracotta? How is it, where is it today? Give us a primer on this.

and how that connects to this idea that we want to get underneath the learning in the classroom to understand how it is happening and to improve that practice. Yeah, I'd be excited to share that path. Yeah, I mean, as you might guess from the story I just told about like the log data, the obvious next question becomes, well, how can you use that to help students? Like what types of interventions might you use? And we've explored all sorts of stuff, like if we discovered that a student was, I don't know, spinning their wheels, what types of like feedback could you give them? Or if a student is trying to game the system, like they're just guessing all over the place.

Maybe there's a way of intervening and giving them a delay and saying, wait, you should think about this. And anytime you're thinking about what's the intervention or what's the change, what you really want is you want data that suggests that this change had this effect outside the scope of what would have normally happened. So what would have normally happened is a control. And then when I did this, I want to know what the effect is.

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There's a method for that. Like to do that research, you do an experiment. And yeah, I've been trying to do experiments in education settings for a long time. It's been, I've done it like low tech. I've done like different like experimental interventions stuffed into manila envelopes with different colors for the different treatment groups. And that's fine. I mean, like you can do some amazing stuff with low tech, but as you start to scale and as you start to like imagine, well, how would this effect change if I go to three different classes or to five different types of disciplines, then you can't do things manually anymore.

So yeah, technology becomes a really important tool to be able to like say, okay, I want to test my intervention and I want to do it at scale and I want to get rigorous data on what will work. So terracotta was like a need that we just kind of like engineered into reality. It's something that we were talking about. The more that we were doing experiments, it was just kind of like, we need a tool to make this possible. And after we talked about it with enough people, we found somebody who was willing to support like an early prototype and we made it come to life.

And so what it is is it's a LMS plugin. So it's an LTI 1 .3 app that fits into the Canvas learning management system. And right now it provides support specifically for somebody to manipulate different versions of an assignment. So the assignments tool is by far like the most used tool in an LMS. And yeah, what you can do with Terracotta is you can make it so that some students get one version of assignment, and other students get another version. And you can actually measure in those detailed logs what somebody's behaviors are after they get the assignment, and also how that affects their out.

their downstream outcomes, like how they do on the midterm or something in a way that's also very transparent and responsible. So students in terracotta submit their informed consent, like teachers can't see their informed consent response, so there's no coercion. All the data is rigorously de -identified. So it also is an effort to do things that we want to do, but to do it responsibly with protections for students so that we're doing the right kind of research and doing it in a way that everybody feel good about. That's amazing. So as a learning researcher,

How did you get involved with Terracotta? What was compelling about the mission? Well, I learned about it from Ben, who is my colleague at Indiana. And really, what I saw is it's transformational to teachers on the ground. So I run a K through 6 summer institute every summer out in Seattle. And what I see over and over is that these are people who are really dedicated to the learning and growth and development of their students.

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but they don't often know what works or why it works. there's no real way. exactly. And what I saw in Ben's technology around terracotta was really this opportunity to put this kind of power in teachers' hands and to let them sort of identify ways that they could test. If I describe the instructions this way, does it motivate students differently than if I described the instructions that way? If I figure out a different way to give feedback to students in this way or that way, right?

how do I communicate my own desire for them to learn, grow, and develop through these different experiments? And then how can I actually see that in real time influencing student outcomes? And I think that it makes learning come alive for students. I think it makes learning come alive for teachers. And in this moment where we really have a lot of teacher shortages and motivation and morale in many educational settings are kind of at an all time low. I think technology like this can really help

bring back that spark, right? To really understand what's working and learning and how we can actually improve it. Yeah, it's amazing. So that is inspiring. And it's incredible work that Terracotta continues to do. It is open source. Institutions can leverage it for free. How do you make that happen, Ben? how do you... I'm really rich. How does that work? Because this is such a gift back to education. Yeah, so thankfully, it's not just Mary and me who want to improve the evidence base in education. Like, other people are actually...

keenly interested in this as well, including funders. So yeah, we make it possible by seeking federal grants and also like awards from philanthropic organizations, because this is not just something that they see as being an important part of a nation's research infrastructure, but for exactly the reasons that Mary said, if a teacher has an idea of how to improve something in their class, it shouldn't be a struggle for them to like go off and like spend years working on an experiment or for them to not have data on whether it works.

So this is like, I don't know, it seems so obvious now that we've put it all together that like, yeah, teachers and researchers both need tools to be able to produce evidence of what works. So yeah, thankfully there's philanthropic organizations and federal funders who also see the same vision. Yeah, I would also just add to that, that I think that it's important to remember how we used to or how many of us still do educational research and what that usually looks like.

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is that we get a grant somehow, some way, there's a miracle, and then you have to kind of build your research infrastructure in order to conduct that research on the ground. And so you find the schools who you'll work with, you find the teachers, you get your technology in order for your own study to be able to take place. You put the data agreements in place, right, to be able to share and get the student data with the institutions.

and then find ways to collaborate and support that relationship that you've created. And when the grant ends in three to five years, let's say, the infrastructure goes away and the next person gets a grant and they have to rebuild it all over again. So this is the cost, right? This is the cost of educational infrastructure. And if we could build technology and infrastructure that can be reused.

for many different purposes. And scientists don't have to do that every single time, every single grant, brand new, brand new. And we can actually grow and develop it in the way that Ben is doing with Terracotta. I think that that's really the future. And that allows so much more equity in who can actually do these experiments, who can actually conduct this research, and how we can understand how to improve it over time, because we're actually using that same technology across contexts, across studies.

everybody has access to it. So I think it's an equity enhancing impact. And I also think just for research infrastructure, it saves so much tax dollars and other kinds of funds for us to be able to have this kind of technology and infrastructure. Yeah. I had not thought about it that way that you'd have to kind of rebuild that infrastructure every single time. the plight of the education researcher. I think about that in other disciplines.

Like, yeah, so I don't know, like if you're an astronomer, could you imagine if every astronomer had to build their own telescope or if every biologist had to like engineer their own test tubes or something? So it's totally normal in other research domains that there's shared infrastructure. Just education hasn't really caught up. Yeah. And it's a leveler. That's right. That's right.

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How broadly is Terracotta adopted right now? How many schools are using it? And what are some examples of outcomes we've seen? It's really new. So I'm not going to like wave the flag and say like dozens and dozens and dozens. It's actually about one dozen institutions, so districts and schools that are using it. And it's under consideration in a variety of others with varying states of adoption. So what are some of the things that we're seeing? We're seeing like things that are beyond the scope of what I imagined when I first put it together. That's one of the

joys of this idea of a shared infrastructure is that what I've initially thought it could be used for turns out to be a small component of what the potential use is. So I'm a cognitive psychologist. I've been interested in basic cognitive processes of learning and memory, but it turns out that there's a great need in social psychology as well. So people who are more interested perhaps in interventions that change behavior and change the way that students feel in an educational environment, interventions that modify like the situational cues that somebody experiences as a student in a classroom environment.

So there's a variety of different domains that are being explored ranging from like, let's change this one little thing about feedback to like, let's change the way that we talk about all the assignments in a class. And there's also a variety of different ways that I'm seeing it adopted in terms of its scale of impact. So there's some places where it's being adopted because there's one teacher wants to this one thing in the one physics class. And there's other places where it's being adopted because there's a cohort of faculty all across the district who are sharing this.

I don't know, professional development experience, and they're all doing something in the same way, and they want to combine their efforts and collaborate on what the outcome is. I wish that I could say like, there's this one use case that we're just like churning out stuff on, but it turns out, no, there's an amazing diversity of need for this type of thing. I love when you've got like that use cases you've never even thought of, you know, that's when you're on the right track, when it's that broadly referenced. Yeah, but in the process putting this together, I'm discovering. Yeah.

Right and that it's used across k -12 and higher education at the out right small, know You're in your first dozen but still that unlocks so much potential not just even in those individual domains But as those two domains start working together more closely I mean think about what that can unlock because it's bringing ease of research to the table in so many ways whether it's

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very formal research that's funded or whether it's trying to understand how you can deliver a better learning experience. think that that's really powerful because it also democratizes learning about education. So when we think about how many studies are conducted, usually there's a researcher, our team of researchers who go into a district or go into a set of campuses and conduct their research. Then they get all the student data, they analyze it, and then the researchers know the answer. Sometimes that research

answer is shared back with the instructors. Sometimes it's not. And so in this way, teachers on the ground can actually not only be collecting the data themselves, they get the answers sometimes first.

right? In this, they get to see sort of how this is impacting. And so it really does democratize that learning about student learning kind of on a meta level. Can I just like plus one that? That's something that we're experiencing as we interact more with teachers and with districts is this idea that the past research that's been done in schools and in universities for that matter

sometimes feels a little bit exploitative. Like there's a researcher that goes in and it's this one extra thing that a teacher has to do. Sometimes if there's lucky, the teacher brings funds and makes it possible that the teacher has more funds available for the next class. But really it's a one way street where like the teacher provides the data to the researcher who then goes off and does something with the data. And that's really not how it should be. In fact, that's totally not sustainable if we actually want to do like scalable education research. So there really needs to be research infrastructure that also supports the teachers and the districts to run their own studies.

where researchers are not necessarily the gatekeepers and instead were the enablers of the types of questions that they might want to address. And actually, I think that's powerful because they have good ideas. Like, it's not the case that their ideas are outlandish. Instead, they're very practical and geared toward what experiences they're seeing in their own classes. So yeah, the infrastructure needs to go that way too, for sure. Yeah, it really what it's doing, it's doing two things. One, it's sharing back those results in real time and in meaningful ways. But it's also developing the practice of research more broadly.

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in the teaching base, right? Which I think is so powerful. That's right. It makes evidence -based teaching possible in a lot of ways. Yes. Yeah. And I think we're all hungry for that, especially as we're seeing so many disruptors or opportunities, if you want to call them that, come into the teaching practice. We're hungry for experimenting with that. I think of all of the conversations around AI. Of course, we have to have AI mentioned on this podcast, but I think about all of those, what the questions it's asking. And what we're seeing is that

People just want to understand how are we thinking about this? How are we unpacking the opportunity? They're not everybody's looking for the destination of where we get, but how do I even wrap my brain around understanding what I could be doing with this and testing it meaningful ways? That's right. Yeah. I think one of the things that's been interesting too is we still see lot of headlines around online learning is less than in -person classroom.

learning, right? And obviously we're talking about technology enhanced learning, you have to be using this technology, but there's a lot of different versions, hybrid, fully online, right? And I think the research you're doing really helps understand that done correctly and best practices that you're kind of teasing out of this is what makes the difference in all of those various settings, right? They can all be incredibly effective if done correctly. That's right. That's right. And gathering the data is the number one thing, right? To be able to say, does this work better? Does this not? And so

Being able to compare apples to apples with that data collection seems really important across these different learning contexts, right? Yeah, to build on that, there's also this additional element where education in America is amazingly diverse. So it might not be the case that there's like a main effect, like whatever we're talking about, whatever the experimental manipulation is, it might not be the case that that is the same effect across all students. And what we really need are not just like one person doing the study in one setting, but we need people who are

Collaborating and finding out what the possible moderators are and collecting individual differences on their students. So this is another thing that might otherwise be challenging in education settings. yeah, getting access to student level covariates, like whether they're on fair reduced meal plans or what their home environment is or how they feel in the classroom. These are difficult data points to collect, especially if you're already busy with the difficulties of doing experimental research. So kind of another need is that not only do we need infrastructure for doing the experiment, we also need infrastructure for collecting.

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really kind of like, I don't know, granular data on what's going on so that we can make these sorts of inferences. Yeah, there was a headline last week that I saw that was literally like absenteeism is through the roof post COVID because students don't care about going to class anymore. And it's like, that is such a one dimensional data set because how many of those students were able to complete their coursework online? How many of those students is -

that outdated metric of butts in seats the right metric, right? And I think we're still seeing those headlines, those kind of fear -mongering headlines, and the data, the work that you were enabling really helps us counter that. Totally. Yeah. So yeah, there is an amazing diversity of different types of education experience. Yes. Yeah. One of the places that is currently thinking about using Terracotta is an online K -12 Academy. And yeah, when I asked what kinds of students are in your classes, it's students who don't feel the same sort of comfort level that maybe we would feel.

in a face -to -face education setting. And it makes sense for them to choose to be in an education setting where they do feel comfortable. And in this unique case, there's many different ways where students might be made to feel more comfortable, whether they experience a disability or whether they've had issues with a social group that was at their residential school or something like this. So yeah, in these unique cases, there's a lot of benefit for the students to be at the school of their choice. And yeah, this is one way in which we could actually start to make more precise estimates of what it is about that experience that's working.

Yeah. Well, that's a really great segue. It's, it's, we bring lots of guests on our podcast, but it's a treat to get to bring researchers doing some really innovative research, I think in learning in general. So if we can pivot a little bit and nerd out with you, this is maybe my inner nerd. And maybe start with you, Mary, you alluded to this at the beginning, some of the research that you're doing around identity.

Would you share a little bit about that, what you've uncovered? And I do know you have a book coming out or it just launched. And would love to just, what does that dig into? Cause I think our listeners will be really interested. Yeah, I'm really interested in this question. You know, in American society, we like to think that we are just individuals, right? That nothing, we make our own choices. We're not shaped by anything. No one's going to tell us what to do. But what we really know about the way humans operate is that we're really influenced by other people around us in our context.

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And so my research has really looked at how the cues in our local environments, and especially in our learning environments, how those cues are shaped and how they influence student motivation, engagement, learning, and performance. And so I have done a lot of research in the area of mindset. You probably have heard of the Fixed in the Growth Mindset by Carol Dweck. Well, for years, we've only thought of mindset as a characteristic in our mind. What's your mindset? How does it affect you? What's my mindset? How does it affect me?

But in the last 15 years or so, my students and I have really been reconceptualizing that idea to look at mindset cultures and look at how culture creators, teachers, principals, superintendents, faculty members in college settings, how we create the mindset culture of our classrooms.

and how those mindset cultures and what we say we do, the assignments we give, the feedback we give, the first day of class, look to your left, look to your right, only a couple of you are gonna be here at the end of the term, very fixed -minded language, right? These cues, how they actually influence students' motivation, engagement, and learning, and their willingness to actually stay in the educational system over time. We look at persistence. And so that's one area of my research, looking at how these contexts and the culture creators that make them,

How do we give them the tools and resources to actually make more growth -minded cultures, right? These cultures of growth is what I call them. That's name of my book. And it really sort of focuses on this research, tells a bunch of stories from the classroom settings, but also in organizational and team settings. We also do this work in families and look at how families create the mindset culture among their relationships and their children. And yeah, just one example of some of the work we do on how context really shapes us.

That is so interesting. I think as we look at different paths for learning, as you think about that context, the learning environment, whether it's a classroom or, you know, it's on the job professional about whatever it might be, we're watching that evolve into this lifelong learning experience, right? So I'm going to come in and out of these experiences. And as you were talking about that, I'm so fascinated in how those different moments also shape your mindset because you're going to you're in a traditional K -12 and then you go.

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and do two years of college and then you go into the workplace or you go down Ben and I's path where we step out and Ben goes back smartly. But how does that shape that mindset as learning experiences change over time? Absolutely, absolutely. And looking at that longitudinally, as you say, sort of over people's lifespan, we can see how the messages we get about I'm good at math or I'm not good at math or I'm the artsy one or I'm the sporty one or I'm the, you know.

We have these identities that are shaped by the messages we receive in these learning environments and from those who care about us and try to mentor and support us. But those learning environments are really critical in communicating what's possible for us and what we're good at doing, right? And whether we're like school people or not, whether we're learners and that really can shape us over the course of the lifespan. Wow. Yeah. It's funny. I see that with my own.

kids. My son would be like, I'm good at math. You know, my daughter would be like, I'm the personality child, right? That's right. could be empowering or limiting in so many different ways. That's right. That's right.

Ben, you studied the relationship between cognitive theories of human learning, psychological theories of student engagement, and what goes on in the education setting. What are you working on now? Yeah, well, I'm actually starting to come around to this social psychology thing that Mary's talking about, actually. So one of the things that I like doing is thinking about ways in which we're not thinking about the influences that actually do impact how people learn in context. Education, just to like...

I with everything that Mary said. Education is a fundamentally social activity. The only reason that you would do anything in an education setting is because there's a social reason to do it. Like we wouldn't otherwise just kind of like start learning what Plato said or start learning how to graph a parabola. And whether you're doing it for the fact that your teacher assigned you to do it or whether you're doing it for the reason that you're actually curious about it, these are factors that the cognitive psychology of learning hasn't traditionally explored. So I'm really enjoying the opportunity to get to

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with social psychologists more as I'm starting to think about education R &D and yeah what ways in which the traditional silos don't seem to fit so a lot of my current interests are kind of like breaking barriers as it relates to how we generate theory about how learning happens in education yeah and I don't know I could tell you a bunch of other really nerdy things I'm excited about a particular kind of Bayesian data analysis and man it's keeping me up at night I'm so happy

It's been incredible. Like the last, I say a lot, the last five years have been the most disruptive in the history of education, really with COVID and it turned everything on its head. And now post COVID everything was going to get back to normal and suddenly generative AI is here. So how do you, what does the next 10 years look like? What do we have to look forward to? I mean, I'm a crushing optimist. I will tell you this. I, I'm pro AI. think we can, you can overcome all the challenges, right? And so I see an incredibly bright future for education.

We carry phones with all the world's knowledge in our pockets, and yet we still need teachers as guides, I think, to both you made. What does it look like in the next five to 10 years? The way I think about it through my lens and kind of my expertise is that a lot of this AI, generative AI, is going to be built into our learning platforms. And I think that it's really important for us to be paying attention to the data that is used to train these AI algorithms to be sure they're unbiased, they're...

producing good outcomes, but more than bias. I think each of these learning platforms is going to have in my language, a mindset culture. It's going to give us points or not for learning and development. It's going to give us either the right or wrong answer. That's the only thing that matters or our learning over time, our persistence through challenges, right? And the ways in which we create these learning platforms and the things we incentivize in them as the AI is giving us new

problems to work on or new strategies to work on, right? The way in which those incentives are set up can really shape our mindset and our motivation and then our willingness to actually engage in them and learn. And so I think that we really need to be paying attention to the cultures that these AI platforms and products are actually creating for us.

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and how that's going to shape our own motivation and interest in pursuing them and getting the most use out of them that we can for our own growth and development. Yeah, I actually gave a presentation recently about we just need to eat our vegetables. And it was really focused on, we've got these guidelines in place for security and privacy and accessibility. We just need to make sure the AI tools align to those will be in good shape. But like you're adding this additional dimension of that mindset. It's really incredible. It's interesting. Does AI become part of the social fabric?

I'm thinking about that as you were talking. I mean, that's how we expect to use it, I think. I think we expect it to be in some ways a tutor or a teacher or a coach, right? And we expect it to actually be helping us guide our learning, guide our learning and development, give us new strategies, help us see a different way to see problems. That's the best of it, right? Like that's the most optimistic view of AI in our learning and teaching.

And so in the same way that we attend to how these culture creators set up that culture and communicate to students what they're good at, what they're not good at, the strategies they need to take in order to persist, how to overcome challenges, right? And the incentives that are built in that will help students do that, that's what we're gonna have to be attending to, I think, in all of these platforms.

This is exactly the nerdy stuff we like to talk about. Let's get it. Yeah. I've even got a practical example of this. So I'm really excited to be collaborating with our friends at Arizona State University on a grant that is called Active Learning at Scale. So one of the least favorite things for students to do in a class is to like do the reading or to like read the chapter or to read the article that's assigned. And yeah, one could.

even assign students to do this and expect that maybe like most of the students won't actually do it. So a solution that they're exploring is like maybe we could make the readings instead of just these passive things that you're supposed to do into conversations. And how can we make agents that actually know the text of the PDF or know the text of the chapter and it can be a support so that it's asking you questions along the way and giving you feedback on your questions. And as you think about it in this regard, then absolutely, this is a social agent.

InstructureCast (32:08.55)

what we are, we're social creatures and no longer is it going to be the case that you're just kind of like expect to make it up for yourself. There's a tool that's there to make it so that it is actually engaging and it does make you feel like you could grow and it's giving you the right sorts of encouragement along the way. So yeah, Terracotta is going to be the interesting tool that they use to be able to do A -B testing in classes.

tune it so that we can say like, okay, like when we assign students to do the conversation thing, then obviously they learn more. And this is how they feel about what they can learn in the future. And this is their willingness to read more afterwards. So yeah, yeah, it's exciting. I love it too. What aren't we talking about? What are we learning now that we didn't know five years ago, 10 years ago about how we learn and how we set our mindsets? What isn't education talking about? I don't think we're talking enough about how to create structures.

to have teachers on the ground and their insights raised enough so that we can actually recognize patterns in that and actually help to create research and also strategies to help support that learning on the ground. I feel like we get a lot of talking heads who might say sort of certain things, but I wonder how much they're actually in conversation with people on the ground who are actually in front of students on a day -to -day basis and the wisdom of that.

those individuals, right, who are seeing the educational challenges playing out in their own classrooms. And so I want to see the United States government. I want to see districts and systems actually create structure that's going to allow us to hear those voices, hear those challenges, and then to be able to respond to those. So I feel like we need a more bottom up kind of approach structure and infrastructure.

to sort of do that. And I'm hopeful. think that building some of this technology, some of the infrastructure solutions will sort of have that baked into them. But I think we need to be talking about how to do that more. love Mary and I didn't talk about this, but that's exactly what I was going to say. we just - Yeah, we did not prep this. It's amazing. so maybe it actually is a big problem. Yeah.

InstructureCast (34:05.612)

Yeah, so I mean, it's funny. I hear from teachers all the time who are interested to use Terracotta and they submit it to their IT department or like to do the LMS tool request thing and then they hear back from them and say, sorry, there isn't enough interest here or there's only one person who's requested it. So it's not going to be turned on. It's not a cost issue. Again, Terracotta is free. It's just that for many IT departments or many of the kind of like decision makers and administration about what tools get used, there needs to be this kind of like large consensus of support before anybody will do anything.

And that is a problem because it means that nobody will actually do anything unless it's already grown to this level. And that fundamentally disincentivizes discovery or innovation or anything that actually would cause the teacher to get credit for their new idea about what should work. yeah, mean, infrastructure is a paradox. You build infrastructure and in many ways what you do is you make some things possible while limiting others or making other things harder.

Great challenges we're imagining research infrastructure is to avoid disincentivizing or making it impossible for individuals to actually succeed or to grow or to discover or to innovate. So yeah, no, there needs to be much more bottom -up approaches. There needs to be fewer kind of obstacles as we get to like larger scale adoptions if we're actually going to do anything better than what we've got right now. Yeah. Yeah. I think so much about the individual teacher and the school and the district. And there's so much to your point innovation happening. There's just no way to capture that.

And they're being stifled because they don't have the opportunity to truly branch and experiment in the way they want. And it is, it is a government issue. It is a, you know, how do we all rally around that? You know, I think sometimes you see in the press too, education slow to change. Well, perhaps the larger problem is...

Education isn't being given the support it needs in the right way to be able to experiment, innovate and drive change, especially of those that are just their lights are on in the classroom and they're seeing it and they're doing it. But how do we, you know, again, surface that, test that and bring that out as practice in meaningful ways? Yes.

InstructureCast (36:07.022)

Mary, Ben, this has been an incredible conversation. could probably keep talking for another couple hours about this, but it's just amazing. Mary, we'll drop a link to the book in the show notes, and Ben will drop some information on Terracotta for people that are interested in getting involved with that in the show notes as well. But wow, really, really insightful. Great having you on the show.

Thanks for listening to this episode of Educast 3000. Don't forget to like, subscribe, and drop us a review on your favorite podcast player so you don't miss an episode. If you have a topic you'd like us to explore more, please email us at Instructurecast at Instructure .com, or you can drop us a line on any of the socials. You can find more contact info in the show notes. Thanks for listening, and we'll catch you on the next episode of Educast 3000.