Christel Bruno: Yeah.
Abel Maestas: All right, welcome everybody to the Teaching the Counts podcast. Once again, I am Abel Myestus, and I am so glad to have everyone listening this month. I'm super excited about this. I say I'm super excited every month, and every podcast, I think, even the NCSM one, I say I'm super excited about my guests, but I really am. I always learn a lot. And I have a passion. Everybody that listens knows I have a passion for data science and statistics, and we've got some. A pair of educators that have been on the charge to get data science in every classroom, K twelve, and they're doing some great work in the state of Arizona. So I'm I'm super excited to to hear from them and have a discussion about how we can get data science and statistics. And I'm gonna say data science because data science is statistics is just like a part of data science. And I think that's an important piece, and we'll talk about. So I'd like to invite Are my guests, okay. I'm gonna mess up the last name here. Marissa Tuala, is that right? all right.
Marisa Tualla: You actually said it correctly. Good job.
Christel Bruno: Yeah.
Abel Maestas: so Marissa's a K-12 math specialist for the Arizona Department of Education. She's been in math education for 17 years and previously doing work as an instructional specialist, curriculum assessment, data, professional development, classroom coaching. So all the things with teachers, with students, and Chris. Christelle, is that right, or Christelle? Christelle, all right.
Christel Bruno: Crystal. Mm-hmm. Crystal.
Abel Maestas: Christelle Bruno brings more than two decades of experience to math education. She's a teacher, instructional coach, math specialist, STEM specialist with the Arizona Department of Education. And currently you're focusing your work on K-12 instructional systems. And we were just talking a little bit before we started. I know that there's a shift, so you could talk about what you do right now. And I'll let both of them introduce yourself. Sells to everyone? A little bit more than I just did?
Marisa Tualla: Yeah, I wanna say I'm very impressed you said my name. yeah, so I taught mostly math, but my experience was sixth grade through eleventh grade and mostly in middle school was my spent most of my time in the classroom and one of my favorite units to teach really was like the the statistics and probability unit because I thought those standards were so rich. and then I got to meet Christelle once I got to the state level 'cause she's does a lot of work to support math in the whole state of Arizona. And so Christelle.
Christel Bruno: so I'm Crystal Bruno. I think you kind of hit everything. I've done a little bit of everything. I have been in education exclusively in Arizona for over two decades. Marissa and I actually got to start the data science journey together with this grant when we were both working at the Department of Ed. I am not currently working at the Department of Ed, but I get to do this. I just took over. my presidency for the Arizona affiliate of NCTM. So I get to we just get to walk around all over Arizona talking about data science and being nerdy.
Abel Maestas: That's awesome. I I have gotten to do that a little bit in California, being able to go around California and talk to teachers and be math nerdy. I love that. I love that.
Christel Bruno: Yeah.
Abel Maestas: So let's I'm so happy you're here talk about data science. Like I said before, I'm a a longtime statistics lover, and it took a while for me to get there early in my career, but I truly believe statistics and data science in particular. Are probably now more than ever, one of the most important branches of mathematics that all our kids need to be need to experience. So I know you recently did a blog for NCSM, and in it you started with everyone is a data scientist, a data person. And I know that like echoes everyone is a math person. So why is it really important to like explicitly Have that as a working agreement before doing professional learning sessions or anything even get started.
Christel Bruno: So Marissa and I definitely are in front of teachers all the time. Not all of them are math people, right? Like not all of them are math teachers and they frequently tell you they're not math people. And so as
Abel Maestas: Right.
Marisa Tualla: Mm-hmm.
Christel Bruno: we kind of started jumping in and thinking about what was important to us as we th thought about data science, we did latch on to not everybody wants to say they're a math person. And we are frequently in places where we're like, nope, you are a math person. You maybe just didn't have a great math experience. And so it 100% is a nod to that. We really do believe that, well, first off, data science isn't just in math, right? And so we are in spaces where we're talking about data and being in a data rich space with people who don't believe that they're math people. So they really don't believe that they're data science people. And so it really starts that conversation about the fact that We are in classrooms. We are saying things that are important to students that students are hearing and mimicking by our actions and our behaviors. So we really hit that very quickly, very intentionally and very purposefully when we start our professional learning experience because we want people to recognize you're going to be experiencing data, your students are going to be experiencing data, and you get to control what some of those feels are and how how they get introduced to those things. So let's take a deep breath and recognize that we are all in a space where we're seeing data, we're interacting with data, and we have the ability to explore that data together. So you're not wrong. It 100% is a nod to everybody is a math person and
Marisa Tualla: Mm-hmm.
Christel Bruno: we need to start saying
Abel Maestas: Mm-hmm.
Christel Bruno: that proudly.
Marisa Tualla: Yeah, 'cause data really does associate with math whenever th people think about data. And people have feels about math, which means they also have feels about data and statistics. you know, we hear all the stories, people's experiences in classes, whether they got it or they didn't get it. And so at the end of the day, data is everywhere in the world and we cannot avoid it. And so the best is what we can do is making sure that we and our students all can have the skills we need to analyze and understand what the data really means. and be skeptics and all those data habits of mind and really support that 'cause we all we all need those skills, they're very important in today's world and we want to make sure our students have those skills too.
Abel Maestas: Yeah, I you know, and I think many teachers they hear data science and they're like their first thought is, it's statistics. And I have to do,
Marisa Tualla: Mm-hmm.
Abel Maestas: I have to know statistics to do data science. And sometimes that's that's kind of scary for for many teachers. They're like, I didn't I didn't do any statistics. I don't know how to interpret them. But really statistics is not the whole of data science. I think we talked about that. So for teachers who've only like ever experienced statistics and have only really done the statistics standards and whatever their state standards are, what's the biggest mental shift that they need to make so that they can see data science as like its own full process for kids?
Marisa Tualla: Yes, so echoing what you said, a lot of people think statistics when they hear it and But really data science is for every content area. Like you do it in science, you do it in social studies, you could even support it in ELA. And so a lot of people when they think statistics too, they think procedures and algorithms and like follow these steps and this gives you the mean. Follow these steps, this gives you, you know, chi squared or whatever the you know things that you're doing. but really data science isn't necessarily about calculations and procedures, it's more of about what is the big pi question. That we're trying to answer and what statistics support us in understanding that. And so we focus less on just calculating things, and there's a lot of great computer science programs out there that will do the calculations for you. So it's more about what's gonna best help me support and understand what this data is telling me or how I can communicate it. And we try to do that as well for our summer program when we invite all content areas to come, not just math teachers, to be like it's okay. Okay, if you don't know all the, you know, higher level statistics, like we're gonna focus on all these other areas and then we'll f help support like when we need to when it comes to statistics, 'cause we don't want that to be a deterrent for anyone who's never done data science before. Christelle?
Abel Maestas: Yeah.
Christel Bruno: I I think mirroring a lot of what Marissa said and Abel, kind of what you alluded to, I also was an AP stats teacher, right? And so when you're preparing the kids, we're talking about really small data sets because they have to be able to calculate quickly. And so I'm s AP stats, you're definitely analyzing the data. You're definitely talking about what this value actually means in relation to the data set. But we focus a little bit before the calculations. That I think is really where we're bringing all of the content areas in. Yes, we're absolutely doing statistics. We absolutely need to talk about what those statistical measures are helping us with. But we're also starting before that. We're starting with that that messy question that could be anything that maybe doesn't even feel mathematical in in conversation. But the more you start to look at it, the more you are like, you know what, I probably could find some values that would help me find a pattern and help me see some things in here and help me investigate it. So we definitely start, especially like with our introductory pathway, we start with those conversations about, you know, what's surprising you, what's standing out to you. And we just start with a conversation less a calculation, if that makes any sense.
Abel Maestas: Yeah, absolutely. conversation, you know, we want kids to talk. We want kids to have a conversation and we want kids to experience what so right now I teach a college level stats course, but this is I I'm actually coming back to teaching it. I was teaching for a while, then I stepped out because I got really busy with my with coaching, and then I stepped back into it this this semester. And one thing that I wanted to do is I want even at the college level, I It's an introductory statistics course, and I still don't think that students experience data visually like like I'd want them to. So I start every every class off with a data visualization and a simple notice and wonder. Like what do you notice? What do you wonder? Or a slow reveal graph, but something that's different that is Maybe not like just a set of data and a histogram, right? I think we get enough
Marisa Tualla: Yeah.
Abel Maestas: of those histograms and box plots. But
Marisa Tualla: Mm-hmm.
Abel Maestas: the other day we were doing a heat map and we did a heat map of the risk of wildfires in California and different counties. And it really is really cool to listen to like what they think it is, why they think it's colored red and orange and those types of things get kids just really talking about what they're seeing. And I think that's really rich. And to start a class off like that with rich thinking and a rich and rich discussion is not the way that we've historically taught like really any mathematics, right? It's always I think the
Marisa Tualla: Yeah.
Abel Maestas: the I do, we do, you do has been
Marisa Tualla: Yeah.
Abel Maestas: of the past, right? Has is not really the way to get into thinking and And you guys express like it's not really a great way to get into data literacy. So that even data literacy requires productive struggle and inquiry. So I gave a couple examples, but what what what does that look like? So if if a teacher's not doing I do, we do, you do, or they've done it for a long time, like that's like their direct instruction mode every day. What would a data literacy kind of Inquiry look like on just like a Tuesday morning in the classroom.
Marisa Tualla: Well, you said a lot of great things, Abel, that we also try to do with our teachers, like the Soviel Graphs, so what did you notice? What do you wonder? And so, the biggest shift for the teacher in the classroom Is going from telling students to asking students. So, you
Abel Maestas: yeah.
Marisa Tualla: know, that the idea was like I'm gonna tell you everything about this data, I'm gonna tell you everything about this graph, versus okay, instead I'm gonna ask you what do you notice? Is there a pattern? why do you think what what a c what's a claim you can make? And it's so it's it's just sh that shift from telling to asking. Because as you said, like when we tell students everything, they're not thinking, they're not reasoning, they're not you know problem solving. And the only way we do that is we can give of them facilitate by asking questions, turning and talk to your partner for 30 seconds. What else do you know? What what do you want to know more about? And taking it like, you know, just beyond that one visualization. and so it and it's something that doesn't change overnight. It's something we've, you know, when working with teachers for years, especially math teachers, about switching the I'm gonna tell you everything versus I'm gonna help you problem solve through it. And so it's a big shift for a lot of people. And so we you know we always just try to tell teachers, you know, one thing at a time. Try one thing. And then hopefully it helps to move to the next thing. And it's also switching the ownership from the teacher doing all all the work to the student doing all the work. And we always say, you know, the your students should leave more tired than you because they did more work. And we also say who's
Abel Maestas: Ha ha.
Marisa Tualla: ever doing the talking is doing the learning. So if you're doing all the talking, you're you're you're the one doing all the learning versus if the students are talking, they're the ones doing the learning.
Christel Bruno: To to echo what Marissa just said, I actually read some feedback from a teacher. I want to say this, well, today's only Tuesday, so it had to have been last week, where they literally said, Now that I'm doing some level of inquiry, I am so exhausted. I am so exhausted. And really that is the thing. It I think people hear some of the things we say until they've actually jumped in and started it, they don't realize. just how integral their role is, how much they have to prep and how much they have to plan to make it look like they've stepped back and done nothing and that the kids are just leading the conversation. So we really
Marisa Tualla: Mm-hmm.
Christel Bruno: are focused on asking people to invite students into kind of those low floor, high ceiling opportunities and really let students, we're not letting students loose, but letting students
Marisa Tualla: Hehehe.
Christel Bruno: feel free to explore, right? So yeah, no, sh she definitely she definitely talks about all of the conversations that we've had with teachers where teachers are just like, Mm, I don't know how comfortable I feel about that. And and
Marisa Tualla: Mm-hmm.
Christel Bruno: we do know that math teachers we we like our routines and our processes and our procedures. So finding new ones that allow students to feel really empowered is important.
Abel Maestas: Yeah, the that was just it's so funny, the the exhausted, right? That the it's a different
Marisa Tualla: Ha ha ha.
Abel Maestas: type. When you're when you're doing I guess if you've been doing direct instruction for so long, there's like a different type, there's like a different energy that goes to it than when you are facilitating. And I had one teacher tell me once, she said, she said, Yeah, I I I feel like I'm doing Like I'm walking around more and I'm I'm I'm I'm tired a little bit more, but I'm enjoying teaching again. And that's
Marisa Tualla: Wow.
Abel Maestas: so I mean that that made me feel good as a coach, right? That that
Marisa Tualla: Mm-hmm.
Abel Maestas: that's kind of what we're hoping for. but I think one of the i issues with data science, and you can you know help me out with this a little bit, is I've I've been frustrated a little bit as in when I was in in the as a district, as a district coach. One of the things that gets me frustrated is that historically the statistics standards or the data standard, like those are the ones that that teachers are like, well, we're gonna just go ahead and like we don't have time to do all the other stuff, so we're just gonna let that go and not. worry about it. And then when they get and then we get a lot of kids that want to take statistics when they get to high school and they I mean they've never heard of a mean or a median, right? That that they they haven't heard of these things. And we can go over that, which is fine. But if they don't take statistics, then they're missing all of the data science, all of the stats things that are really, really, really important nowadays in the world that we're we're going into with, you know, misinformation and AI that could, you know, that could sway you one way or the other. So what are some like I guess what are some shifts that that teachers can make to think, okay, how can I integrate this within my classroom where it doesn't seem like a huge lift? And I'm not like just focusing on like why are those things so important for us to be doing? That we just don't like, let's just throw away these standards because they don't have enough time to do all the other stuff.
Marisa Tualla: I mean, yes, we we s hear that all the time as well and we look at district like pacing guides and they're putting always stats and data at the end, which means they're not gonna get to it. And so one of the things that you've actually already mentioned is something we tell teachers as a great entry point is like is to do those instructional routines regularly. Whether it's there let's look at let's do a data talk from like you cube or let's do a slow real graph or let's do a a NASA data talk. There's so many different things or let's just get up and do a data walk real quick so that everyone's up and talking about, you know, data. And so those could be like five routines that you do once a week to start at least getting kids talking and looking at data. And the other thing too is why we also open up data science to all subject areas is because it's a lot to put on math teachers to do everything. And so but really
Abel Maestas: Mm.
Marisa Tualla: data science should be in context of science. It should be in social studies context. It should be in all of these areas too. So when we have other subject areas supporting data science, it's going to also help our kids in the long run as well.
Christel Bruno: Adding to that, I think part of the reason it's important to us for it to be so cross-curricular is like one of our first activities we do is voting trends. Voting trends don't s don't historically live in a math classroom. They very much live in a social studies context. And my husband actually co-presented with us because he identifies as a social studies teacher, and Marissa and I were like, We don't we don't know social studies. We're not We didn't say we weren't social studies people. We just didn't know all of the things that we needed to know,
Marisa Tualla: Mm-hmm.
Christel Bruno: right? And it and so it really is one of those places where we are looking for just opportunities to bring other contents in and feel empowered to talk about data that would naturally occur in their in their curriculum, in their content, in their day to day. Because I I think we can both agree, regardless of if we've ever taught social studies, because Marissa and I have not, we absolutely know that social studies teachers, all of the things they're talking about, really were based on data informed decision making, right? Presidents are making decisions based on their cabinet, right? Like all of those things. And so we're really just trying to find places for that to really just naturally flow in. We're not trying to make it one more thing. We're not trying to make it something that you have to go find extra things. We're looking at things you're already doing and adding on to that in a natural and seamless way.
Marisa Tualla: Yeah, and to add Christelle, like we're trying
Abel Maestas: Yeah.
Marisa Tualla: to you'll have your standards you're s you know, should be teaching. we don't want to add to your plate, but a lot of times at math standards you can teach multiple standards together. Right? You can be teaching mean
Abel Maestas: Mm. Yeah.
Marisa Tualla: while also supporting your number system standards with the calculations that you're doing. Like so we try to also encourage teachers to not ignore them, but how can you incorporate them into other areas or other standards so that you get like double duty with your number system standards while still getting that statistic standard in.
Abel Maestas: Yeah, we in in here in California, we've adopted a new framework and in that that uses the idea from Joe Bowler with the big ideas, and so wrapping those standards into multiple things and having tasks that give you more than just one standard. I think for many, many years we've chunked things like we're gonna do this and then this and then this unit
Marisa Tualla: Mm-hmm.
Abel Maestas: and then this unit and then this unit, and then there's there isn't really a an interweaving of mathematics that we know makes it. So beautiful. And so I know that that would be a great a great thing for teachers to think about. I had a another question here that just you know, I just thought about. a few years ago, one of the the schools I was working with had asked, like, you know, we want to we know that math is important and we want to find ways of integrating some mathematics or numeracy across. our entire site. And this was a a high school site. And for you know, for many years it's always been like, you know, let's integrate ELA and let's integrate literacy in every class, in every subject. Like you're a re you're a a a a reading teacher and a literacy teacher as well. And so they wanted to try to do like, okay, how do we do this for mathematics? So I thought about it for a while and I made the suggestion, well, I think the easiest entry point for everyone across the the The site would be looking at data and charts and like thinking about data literacy. Like how do you integrate that within all your other classes? And I think that's an easy entry point. We see it in social studies, we see it in English, we see it in everywhere you can do some sort of display, some sort of graphs, some sort of data tracking. So they started, we started to work the entire school with looking at how to integrate statistics and data science in there. And then when I left, the the coaches still were working on integrating those things for the whole site. So my question is to you, because you you brought this up, have you worked with sites on a on a larger scale than just math teachers in looking at like how do we integrate data science or statistics across sites, across curriculum to help To help that inquiry for students.
Christel Bruno: So I
Marisa Tualla: Sorry.
Christel Bruno: I I don't know if Marissa wants to take this. I will say that in terms of the work we're doing, we're not necessarily partnered with a site. So what
Abel Maestas: okay.
Christel Bruno: we have asked when we were doing some of the recruiting is we were like, it would be delightful if we had groups of teachers. And so if you look at our populations for year one and year two, technically year zero and year one, I think according to the grant stuff. We did have groups of teachers that came in with us so that we could talk about how they were working together. But in terms of this grant opportunity, we haven't had the opportunity to do that. But I know that Marissa has had the opportunity with the math standards to be on campuses and do a little more. So I don't know if she wants to talk about that. It's just not the data science lens necessarily.
Marisa Tualla: Yeah, like Christelle said, we're just kind of opening it up to the whole state and trying to see like, you know, and hit some of those rural areas and some people that you know, don't always get these opportunities to come and do these things and so we had not been able to do something site specific. we are the wild west in Arizona is what we like to say.
Abel Maestas: Ha ha ha.
Marisa Tualla: local control and so there's a lot of things that even like me at a state level I'd I don't necessarily have any like authority or power. So it's always like, Hey, would you like some help? Would you like and then no, yes, no, maybe and so supporting it as we can based on requests. But we have a lot of relationships with district level math people or instructional coaches at the site. And so most of our support is we support them if they want to do it. We'll give them ideas. We can work this together. And then they're the ones actually like boots on the ground that can support that at their actual school school site or district. And so this first this summer we had someone who was a district level math sup specialist and he has a very big district and so something that, you know, we hope that what we do with him he can then take on and do that with at a bigger level scale. But what you explained sounds like a really, really cool idea and I definitely a great way to get all teachers and all subject areas in data. Like we even had an ELA teacher at our trainings this summer and she wants to do more data science in ELA, which we love. Yeah.
Abel Maestas: that's awesome. Yeah. Well, cool. So you're you're what are they what's the technical term? You're creating capacity, right? Is that what it is? Creating
Marisa Tualla: Yes, yes.
Abel Maestas: capacity for
Christel Bruno: Yes.
Abel Maestas: for their school districts. that's great. Well, let's talk about some things that are coming up. because I'd love to to promote you guys a little bit if you if the people are around. So I know. That you are presenting at NCSM, which is is super cool. I'm I'm excited to I I'm gonna put it on my list of ones to go to. As long as it's not at the exact same time as our live podcast for NCSM, you can expect me in the room there. So you've got a session called Integrating Data Science into K-12 Math for Innovation and Deeper Learning. Can you just kind of give The listeners a taste of what they can expect.
Marisa Tualla: Yes. I will say a lot of it is things that we've we've talked about here. we go through examples of what does it look like in a classroom where kind of like the participants are the students. we think it's a very important when we have teachers to have them experiencing it as students so they can kind of go back and model that back in their classroom and what like we talk about all the pedagogy and stuff. So it's what are some resources that you can use? How do you use instructional teams? How do you use data sets and like Codap and what are the free things that we have we also won't think promote free things because we can't, you know we know we don't have With the budgets at our school, so what do we have that's free and available that anyone can use and interact with with? And we also share what we've been working with with the graphs we have or with the grant, and so we have different pictures, different teacher experiences that we want to share and kind of how are we doing this at our level? Because a lot of times it's like how can I take the what I learned at NCSM and apply it back when I go to my school or district, and so we kind of go through the what the grant is, how. we're interacting with t teachers, what does it look like for support throughout the school year? 'Cause if you know we don't don't do sh just do a one and done and then we never see each other again. so how can we get that support, that implementation? And we share lots of resources because we love resources, especially free resources.
Abel Maestas: Mm-hmm.
Christel Bruno: Yeah, so we're we're we're definitely, Marissa talked about it, we're definitely going to get on student hat and do a couple of activities together. but because we don't necessarily have the time and space to go through the entirety of the two years that we've been working together, we're gonna share a couple of examples of some things with the resources so that everybody has a little bit of something to take home and try.
Abel Maestas: That's great. I'm also doing a data science presentation at Cal the California Math Council South, CMC South in Palm Springs in November. It's called
Christel Bruno: Ooh, okay, November.
Marisa Tualla: Ooh.
Abel Maestas: it's called data routines that count. So could kind of goes with
Marisa Tualla: Hmm.
Abel Maestas: my podcast, Teaching That Counts, but
Marisa Tualla: Mm-hmm.
Abel Maestas: we're gonna be looking at data routines that you can do to level up your class. And let students start thinking about data. So things like notice and wonders, you know, classics, notice and wonders, which one doesn't belong, but also slow reveal graphs, and then how do you integrate some of this with just simple tweaks that you can do to get your kids excited about data data and thinking about data? And mine is gonna be 612. So I'm really gonna look, you know, specifically what what teachers can be be doing at the middle school and high school level. So I I'm excited to hear yours and take some see go, maybe I can add some of that in my presentation in a week, right after
Marisa Tualla: He
Abel Maestas: math week. But I talk about these conferences because a lot of teachers and leaders for that matter, we go to conferences and we we get a lot of learning, but the learning doesn't stop there, right? Like
Marisa Tualla: Mm-hmm.
Abel Maestas: They have to, there has to be some continued work and sustaining the momentum. So what does meaningful fall like? What does that what does the follow-through look like once a teacher goes back to their own classroom and use what they've learned either in you know a conference workshop or in the workshops that you guys have been running in in your state? what have you learned about what makes that support, the continued support actually stick versus fade out?
Christel Bruno: Well, we will also disclose that this is our first time doing this support. So we're learning in real time and we are growing with feedback from teachers. So I do want to give that caveat. But you did allude to the fact that we are absolutely supporting throughout the year. So we built something called communities of practice so that our teachers are coming back monthly, more or less. to meet. We're having them do some more learning. So you talked about Joe Bowler. We just had Joe on with our teachers this month well, this month, because it's still September, yeah. So
Marisa Tualla: Mm-hmm.
Christel Bruno: she talked a little bit about data science with them. We had a great conversation. And then at the end of the learning, the primary invest the what is he, the principal investigator, the PI for the grant, kind of leads them through check-ins on some of the research components and some of the grant specific deliverables. Ultimately our focus is always on pedagogy. So we just want our teachers to feel comfortable to come back and say, I tried something, it worked, it didn't work. Does anybody have a suggestion on how to make it go better? So we're kind of facilitating those parts of the aspect. as the check in like how are how is it actually landing? You're trying this with real students and what went well, what didn't go well. So that's kind of what we're doing.
Marisa Tualla: I will add, you know, this census is grant funded, that means we have money to pay teachers. And so they are expected to try. We say try something, maybe eventually you'll get to a full investigation and then they're gonna get a stipend for doing the work. And so, whenever we can, you know, support teachers for the extra work that they're doing, we wanna try to do that as much as we can.
Abel Maestas: Yeah, support with money. That's that that's always good.
Christel Bruno: Mm.
Abel Maestas: all right. Yeah, what was that?
Christel Bruno: She's not she's not wrong though. It definitely helps with
Marisa Tualla: Ha ha ha.
Christel Bruno: motivation to try. there are some additional components that I know that they're collecting artifacts from things and I know we're advocating for a final project at the end that's a day or two going through like the data and s data science investigation process. So we're definitely building capacity throughout the year and working in a very gradual build up to bigger and bigger and more impressive things. But we're starting with baby steps and we're happy about our baby steps.
Abel Maestas: Cool.
Marisa Tualla: Mm-hmm.
Abel Maestas: Yeah. Always always starting with the small small part. So you've been at
Marisa Tualla: Mm-hmm.
Abel Maestas: this for two years now?
Christel Bruno: Marissa and I have, yeah.
Abel Maestas: Yeah. How much growth have you seen in your s you know, in the schools that you work with, the teachers that you work with over the last two years in integrating data into their classrooms?
Marisa Tualla: I mean in general people are very excited and they are I think they're really happy with how students have been reacting to it. and how they've been like, Wow, they really they I learned something new about my students. They really took this on, they really wanna they showed a lot of interest and so there's so much motivation and interest students have in these a lot of these investigations and these activities and and so a lot of them once they experiencing with their students like, yeah, I wanna keep doing this. Like there's that like, it's working, so let's keep doing this. anything else, Crystal?
Christel Bruno: I so Marissa definitely kind of alluded to I think part of the reason that we also are seeing teachers go, ooh, I want to try this. We have, I think we've been really purposeful about some of the resources that we've brought. And so like things that we like, I shout out to Data Classroom, right? We have it's my favorite activity to do. We do an activity around Taylor Swift. And so the reality is
Abel Maestas: Ha ha.
Christel Bruno: that it's right, it's not about data. It's not, it's not not about data, but all of all of the kids really get very invested in, we're talking about pop culture, we're talking about football, we're talking about my favorite singer. And so I think that is part of why we see teachers latch on, because we go through a different vein. On all of our activities. We want to make sure that every single content area feels seen in what we're doing, but we also want every content area to feel like, maybe I didn't love that activity for my kids, but I'm really excited about this topic. And so I'm totally excited to bring it to the classroom. So so I think that's part of the unique aspect of what we're doing. We're definitely advocating for free resources. We're definitely bringing a lot of variety to teachers so that if I'm feeling really experienced with technology, I can jump in there. But if I'm not feeling experienced with technology, we have unplugged activities as well. So we we try to build a balance for whatever the comfort level is around data and around the use of the materials. I think that's kind of one of the one of the great great balances that we've struck with the materials that we've brought to the teachers.
Abel Maestas: Awesome. Yeah, that relevance and ability for teachers to easily have things available is is great. You know, I was just talking to somebody the other day that's teaching some data and data science, and they say, you know, I don't get the question in that class, when am I ever gonna use this? Like that's the one question I don't get in that class that I get in the other classes. So you want students to stop saying that? Put some data science in your class.
Marisa Tualla: Yes.
Christel Bruno: For real.
Abel Maestas: All right, Christelle and Marissa, it was so great talking to you and having you on the podcast today. I wanna give you a little bit of time to just let people know how they can learn a little more about your work, where they can get in contact if they're interested, or if their districts are interested.
Marisa Tualla: Yeah, I would say there's probably two avenues.
Christel Bruno: So I would say,
Marisa Tualla: Yeah.
Christel Bruno: yeah, what are you thinking?
Marisa Tualla: one was the our Arizona Association of Teachers of Mathematics. w Christelle's our president. we are using that platform to share out our webinar series to teachers and using so that's a free website is also you can join for free so if people want to get those email blasts they can go to atm dot org. the other side is my side which is the Arizona State Department. So if they want to also get it from our side at the Arizona Department of Education math standards webpage or you just Google AA A D E math we have our own like list server we we share that information as well. So those are two things you could sign up for if you want to know what's what's happening in Arizona and how to get some more information about that. we also have our own email addresses and we people are free to even email us and reach out and we've talked to other people in other states as well.
Christel Bruno: Yeah, I was also thinking Marissa does an amazing job of trying to shout out all of the things that we're doing on LinkedIn so that people have the actual
Marisa Tualla: Mm-hmm.
Christel Bruno: links in real time. So that was the other thing I was like, I'm trying to think. But yeah, she's absolutely right. We've got both of those listservs that we're pushing all of that information out on, trying to make sure that Arizona know what's knows what's going on, but we're also doing we're trying very hard to get more connected with the affiliates in the region and share some of those resources. And AATM is free as is the Department of Education. So all of those are things that no there's no cost to know what we're doing and and beyond those listservs.
Marisa Tualla: I totally forgot about LinkedIn. That's how Abel like and I were talking was LinkedIn. So yeah, Christelle and I are also on LinkedIn.
Abel Maestas: Yeah. I was gonna say, like
Christel Bruno: Yeah.
Abel Maestas: LinkedIn is where I remember getting that information. So yeah.
Marisa Tualla: Yes.
Abel Maestas: Yeah, great job with keeping up on that LinkedIn. all right, Marissa and Christelle, thank you so much for joining and joining me on Teaching the Counts. And I hope to have you guys on our other podcast, NCSM's Learning with Leaders. Everyone out there, when you're listening and you are off to the NCSM conference in Denver. Please join Christelle and Marissa's session. And I hope you all had a good time in our conversation. I know I did. Thank you so much for joining everyone. Thank you so much for listening. And we'll catch you next month.
Marisa Tualla: Thank you.
Christel Bruno: Thank you.
Abel Maestas: All right, welcome everybody to the Teaching the Counts podcast. Once again, I am Abel Myestus, and I am so glad to have everyone listening this month. I'm super excited about this. I say I'm super excited every month, and every podcast, I think, even the NCSM one, I say I'm super excited about my guests, but I really am. I always learn a lot. And I have a passion. Everybody that listens knows I have a passion for data science and statistics, and we've got some. A pair of educators that have been on the charge to get data science in every classroom, K twelve, and they're doing some great work in the state of Arizona. So I'm I'm super excited to to hear from them and have a discussion about how we can get data science and statistics. And I'm gonna say data science because data science is statistics is just like a part of data science. And I think that's an important piece, and we'll talk about. So I'd like to invite Are my guests, okay. I'm gonna mess up the last name here. Marissa Tuala, is that right? all right.
Marisa Tualla: You actually said it correctly. Good job.
Christel Bruno: Yeah.
Abel Maestas: so Marissa's a K-12 math specialist for the Arizona Department of Education. She's been in math education for 17 years and previously doing work as an instructional specialist, curriculum assessment, data, professional development, classroom coaching. So all the things with teachers, with students, and Chris. Christelle, is that right, or Christelle? Christelle, all right.
Christel Bruno: Crystal. Mm-hmm. Crystal.
Abel Maestas: Christelle Bruno brings more than two decades of experience to math education. She's a teacher, instructional coach, math specialist, STEM specialist with the Arizona Department of Education. And currently you're focusing your work on K-12 instructional systems. And we were just talking a little bit before we started. I know that there's a shift, so you could talk about what you do right now. And I'll let both of them introduce yourself. Sells to everyone? A little bit more than I just did?
Marisa Tualla: Yeah, I wanna say I'm very impressed you said my name. yeah, so I taught mostly math, but my experience was sixth grade through eleventh grade and mostly in middle school was my spent most of my time in the classroom and one of my favorite units to teach really was like the the statistics and probability unit because I thought those standards were so rich. and then I got to meet Christelle once I got to the state level 'cause she's does a lot of work to support math in the whole state of Arizona. And so Christelle.
Christel Bruno: so I'm Crystal Bruno. I think you kind of hit everything. I've done a little bit of everything. I have been in education exclusively in Arizona for over two decades. Marissa and I actually got to start the data science journey together with this grant when we were both working at the Department of Ed. I am not currently working at the Department of Ed, but I get to do this. I just took over. my presidency for the Arizona affiliate of NCTM. So I get to we just get to walk around all over Arizona talking about data science and being nerdy.
Abel Maestas: That's awesome. I I have gotten to do that a little bit in California, being able to go around California and talk to teachers and be math nerdy. I love that. I love that.
Christel Bruno: Yeah.
Abel Maestas: So let's I'm so happy you're here talk about data science. Like I said before, I'm a a longtime statistics lover, and it took a while for me to get there early in my career, but I truly believe statistics and data science in particular. Are probably now more than ever, one of the most important branches of mathematics that all our kids need to be need to experience. So I know you recently did a blog for NCSM, and in it you started with everyone is a data scientist, a data person. And I know that like echoes everyone is a math person. So why is it really important to like explicitly Have that as a working agreement before doing professional learning sessions or anything even get started.
Christel Bruno: So Marissa and I definitely are in front of teachers all the time. Not all of them are math people, right? Like not all of them are math teachers and they frequently tell you they're not math people. And so as
Abel Maestas: Right.
Marisa Tualla: Mm-hmm.
Christel Bruno: we kind of started jumping in and thinking about what was important to us as we th thought about data science, we did latch on to not everybody wants to say they're a math person. And we are frequently in places where we're like, nope, you are a math person. You maybe just didn't have a great math experience. And so it 100% is a nod to that. We really do believe that, well, first off, data science isn't just in math, right? And so we are in spaces where we're talking about data and being in a data rich space with people who don't believe that they're math people. So they really don't believe that they're data science people. And so it really starts that conversation about the fact that We are in classrooms. We are saying things that are important to students that students are hearing and mimicking by our actions and our behaviors. So we really hit that very quickly, very intentionally and very purposefully when we start our professional learning experience because we want people to recognize you're going to be experiencing data, your students are going to be experiencing data, and you get to control what some of those feels are and how how they get introduced to those things. So let's take a deep breath and recognize that we are all in a space where we're seeing data, we're interacting with data, and we have the ability to explore that data together. So you're not wrong. It 100% is a nod to everybody is a math person and
Marisa Tualla: Mm-hmm.
Christel Bruno: we need to start saying
Abel Maestas: Mm-hmm.
Christel Bruno: that proudly.
Marisa Tualla: Yeah, 'cause data really does associate with math whenever th people think about data. And people have feels about math, which means they also have feels about data and statistics. you know, we hear all the stories, people's experiences in classes, whether they got it or they didn't get it. And so at the end of the day, data is everywhere in the world and we cannot avoid it. And so the best is what we can do is making sure that we and our students all can have the skills we need to analyze and understand what the data really means. and be skeptics and all those data habits of mind and really support that 'cause we all we all need those skills, they're very important in today's world and we want to make sure our students have those skills too.
Abel Maestas: Yeah, I you know, and I think many teachers they hear data science and they're like their first thought is, it's statistics. And I have to do,
Marisa Tualla: Mm-hmm.
Abel Maestas: I have to know statistics to do data science. And sometimes that's that's kind of scary for for many teachers. They're like, I didn't I didn't do any statistics. I don't know how to interpret them. But really statistics is not the whole of data science. I think we talked about that. So for teachers who've only like ever experienced statistics and have only really done the statistics standards and whatever their state standards are, what's the biggest mental shift that they need to make so that they can see data science as like its own full process for kids?
Marisa Tualla: Yes, so echoing what you said, a lot of people think statistics when they hear it and But really data science is for every content area. Like you do it in science, you do it in social studies, you could even support it in ELA. And so a lot of people when they think statistics too, they think procedures and algorithms and like follow these steps and this gives you the mean. Follow these steps, this gives you, you know, chi squared or whatever the you know things that you're doing. but really data science isn't necessarily about calculations and procedures, it's more of about what is the big pi question. That we're trying to answer and what statistics support us in understanding that. And so we focus less on just calculating things, and there's a lot of great computer science programs out there that will do the calculations for you. So it's more about what's gonna best help me support and understand what this data is telling me or how I can communicate it. And we try to do that as well for our summer program when we invite all content areas to come, not just math teachers, to be like it's okay. Okay, if you don't know all the, you know, higher level statistics, like we're gonna focus on all these other areas and then we'll f help support like when we need to when it comes to statistics, 'cause we don't want that to be a deterrent for anyone who's never done data science before. Christelle?
Abel Maestas: Yeah.
Christel Bruno: I I think mirroring a lot of what Marissa said and Abel, kind of what you alluded to, I also was an AP stats teacher, right? And so when you're preparing the kids, we're talking about really small data sets because they have to be able to calculate quickly. And so I'm s AP stats, you're definitely analyzing the data. You're definitely talking about what this value actually means in relation to the data set. But we focus a little bit before the calculations. That I think is really where we're bringing all of the content areas in. Yes, we're absolutely doing statistics. We absolutely need to talk about what those statistical measures are helping us with. But we're also starting before that. We're starting with that that messy question that could be anything that maybe doesn't even feel mathematical in in conversation. But the more you start to look at it, the more you are like, you know what, I probably could find some values that would help me find a pattern and help me see some things in here and help me investigate it. So we definitely start, especially like with our introductory pathway, we start with those conversations about, you know, what's surprising you, what's standing out to you. And we just start with a conversation less a calculation, if that makes any sense.
Abel Maestas: Yeah, absolutely. conversation, you know, we want kids to talk. We want kids to have a conversation and we want kids to experience what so right now I teach a college level stats course, but this is I I'm actually coming back to teaching it. I was teaching for a while, then I stepped out because I got really busy with my with coaching, and then I stepped back into it this this semester. And one thing that I wanted to do is I want even at the college level, I It's an introductory statistics course, and I still don't think that students experience data visually like like I'd want them to. So I start every every class off with a data visualization and a simple notice and wonder. Like what do you notice? What do you wonder? Or a slow reveal graph, but something that's different that is Maybe not like just a set of data and a histogram, right? I think we get enough
Marisa Tualla: Yeah.
Abel Maestas: of those histograms and box plots. But
Marisa Tualla: Mm-hmm.
Abel Maestas: the other day we were doing a heat map and we did a heat map of the risk of wildfires in California and different counties. And it really is really cool to listen to like what they think it is, why they think it's colored red and orange and those types of things get kids just really talking about what they're seeing. And I think that's really rich. And to start a class off like that with rich thinking and a rich and rich discussion is not the way that we've historically taught like really any mathematics, right? It's always I think the
Marisa Tualla: Yeah.
Abel Maestas: the I do, we do, you do has been
Marisa Tualla: Yeah.
Abel Maestas: of the past, right? Has is not really the way to get into thinking and And you guys express like it's not really a great way to get into data literacy. So that even data literacy requires productive struggle and inquiry. So I gave a couple examples, but what what what does that look like? So if if a teacher's not doing I do, we do, you do, or they've done it for a long time, like that's like their direct instruction mode every day. What would a data literacy kind of Inquiry look like on just like a Tuesday morning in the classroom.
Marisa Tualla: Well, you said a lot of great things, Abel, that we also try to do with our teachers, like the Soviel Graphs, so what did you notice? What do you wonder? And so, the biggest shift for the teacher in the classroom Is going from telling students to asking students. So, you
Abel Maestas: yeah.
Marisa Tualla: know, that the idea was like I'm gonna tell you everything about this data, I'm gonna tell you everything about this graph, versus okay, instead I'm gonna ask you what do you notice? Is there a pattern? why do you think what what a c what's a claim you can make? And it's so it's it's just sh that shift from telling to asking. Because as you said, like when we tell students everything, they're not thinking, they're not reasoning, they're not you know problem solving. And the only way we do that is we can give of them facilitate by asking questions, turning and talk to your partner for 30 seconds. What else do you know? What what do you want to know more about? And taking it like, you know, just beyond that one visualization. and so it and it's something that doesn't change overnight. It's something we've, you know, when working with teachers for years, especially math teachers, about switching the I'm gonna tell you everything versus I'm gonna help you problem solve through it. And so it's a big shift for a lot of people. And so we you know we always just try to tell teachers, you know, one thing at a time. Try one thing. And then hopefully it helps to move to the next thing. And it's also switching the ownership from the teacher doing all all the work to the student doing all the work. And we always say, you know, the your students should leave more tired than you because they did more work. And we also say who's
Abel Maestas: Ha ha.
Marisa Tualla: ever doing the talking is doing the learning. So if you're doing all the talking, you're you're you're the one doing all the learning versus if the students are talking, they're the ones doing the learning.
Christel Bruno: To to echo what Marissa just said, I actually read some feedback from a teacher. I want to say this, well, today's only Tuesday, so it had to have been last week, where they literally said, Now that I'm doing some level of inquiry, I am so exhausted. I am so exhausted. And really that is the thing. It I think people hear some of the things we say until they've actually jumped in and started it, they don't realize. just how integral their role is, how much they have to prep and how much they have to plan to make it look like they've stepped back and done nothing and that the kids are just leading the conversation. So we really
Marisa Tualla: Mm-hmm.
Christel Bruno: are focused on asking people to invite students into kind of those low floor, high ceiling opportunities and really let students, we're not letting students loose, but letting students
Marisa Tualla: Hehehe.
Christel Bruno: feel free to explore, right? So yeah, no, sh she definitely she definitely talks about all of the conversations that we've had with teachers where teachers are just like, Mm, I don't know how comfortable I feel about that. And and
Marisa Tualla: Mm-hmm.
Christel Bruno: we do know that math teachers we we like our routines and our processes and our procedures. So finding new ones that allow students to feel really empowered is important.
Abel Maestas: Yeah, the that was just it's so funny, the the exhausted, right? That the it's a different
Marisa Tualla: Ha ha ha.
Abel Maestas: type. When you're when you're doing I guess if you've been doing direct instruction for so long, there's like a different type, there's like a different energy that goes to it than when you are facilitating. And I had one teacher tell me once, she said, she said, Yeah, I I I feel like I'm doing Like I'm walking around more and I'm I'm I'm I'm tired a little bit more, but I'm enjoying teaching again. And that's
Marisa Tualla: Wow.
Abel Maestas: so I mean that that made me feel good as a coach, right? That that
Marisa Tualla: Mm-hmm.
Abel Maestas: that's kind of what we're hoping for. but I think one of the i issues with data science, and you can you know help me out with this a little bit, is I've I've been frustrated a little bit as in when I was in in the as a district, as a district coach. One of the things that gets me frustrated is that historically the statistics standards or the data standard, like those are the ones that that teachers are like, well, we're gonna just go ahead and like we don't have time to do all the other stuff, so we're just gonna let that go and not. worry about it. And then when they get and then we get a lot of kids that want to take statistics when they get to high school and they I mean they've never heard of a mean or a median, right? That that they they haven't heard of these things. And we can go over that, which is fine. But if they don't take statistics, then they're missing all of the data science, all of the stats things that are really, really, really important nowadays in the world that we're we're going into with, you know, misinformation and AI that could, you know, that could sway you one way or the other. So what are some like I guess what are some shifts that that teachers can make to think, okay, how can I integrate this within my classroom where it doesn't seem like a huge lift? And I'm not like just focusing on like why are those things so important for us to be doing? That we just don't like, let's just throw away these standards because they don't have enough time to do all the other stuff.
Marisa Tualla: I mean, yes, we we s hear that all the time as well and we look at district like pacing guides and they're putting always stats and data at the end, which means they're not gonna get to it. And so one of the things that you've actually already mentioned is something we tell teachers as a great entry point is like is to do those instructional routines regularly. Whether it's there let's look at let's do a data talk from like you cube or let's do a slow real graph or let's do a a NASA data talk. There's so many different things or let's just get up and do a data walk real quick so that everyone's up and talking about, you know, data. And so those could be like five routines that you do once a week to start at least getting kids talking and looking at data. And the other thing too is why we also open up data science to all subject areas is because it's a lot to put on math teachers to do everything. And so but really
Abel Maestas: Mm.
Marisa Tualla: data science should be in context of science. It should be in social studies context. It should be in all of these areas too. So when we have other subject areas supporting data science, it's going to also help our kids in the long run as well.
Christel Bruno: Adding to that, I think part of the reason it's important to us for it to be so cross-curricular is like one of our first activities we do is voting trends. Voting trends don't s don't historically live in a math classroom. They very much live in a social studies context. And my husband actually co-presented with us because he identifies as a social studies teacher, and Marissa and I were like, We don't we don't know social studies. We're not We didn't say we weren't social studies people. We just didn't know all of the things that we needed to know,
Marisa Tualla: Mm-hmm.
Christel Bruno: right? And it and so it really is one of those places where we are looking for just opportunities to bring other contents in and feel empowered to talk about data that would naturally occur in their in their curriculum, in their content, in their day to day. Because I I think we can both agree, regardless of if we've ever taught social studies, because Marissa and I have not, we absolutely know that social studies teachers, all of the things they're talking about, really were based on data informed decision making, right? Presidents are making decisions based on their cabinet, right? Like all of those things. And so we're really just trying to find places for that to really just naturally flow in. We're not trying to make it one more thing. We're not trying to make it something that you have to go find extra things. We're looking at things you're already doing and adding on to that in a natural and seamless way.
Marisa Tualla: Yeah, and to add Christelle, like we're trying
Abel Maestas: Yeah.
Marisa Tualla: to you'll have your standards you're s you know, should be teaching. we don't want to add to your plate, but a lot of times at math standards you can teach multiple standards together. Right? You can be teaching mean
Abel Maestas: Mm. Yeah.
Marisa Tualla: while also supporting your number system standards with the calculations that you're doing. Like so we try to also encourage teachers to not ignore them, but how can you incorporate them into other areas or other standards so that you get like double duty with your number system standards while still getting that statistic standard in.
Abel Maestas: Yeah, we in in here in California, we've adopted a new framework and in that that uses the idea from Joe Bowler with the big ideas, and so wrapping those standards into multiple things and having tasks that give you more than just one standard. I think for many, many years we've chunked things like we're gonna do this and then this and then this unit
Marisa Tualla: Mm-hmm.
Abel Maestas: and then this unit and then this unit, and then there's there isn't really a an interweaving of mathematics that we know makes it. So beautiful. And so I know that that would be a great a great thing for teachers to think about. I had a another question here that just you know, I just thought about. a few years ago, one of the the schools I was working with had asked, like, you know, we want to we know that math is important and we want to find ways of integrating some mathematics or numeracy across. our entire site. And this was a a high school site. And for you know, for many years it's always been like, you know, let's integrate ELA and let's integrate literacy in every class, in every subject. Like you're a re you're a a a a reading teacher and a literacy teacher as well. And so they wanted to try to do like, okay, how do we do this for mathematics? So I thought about it for a while and I made the suggestion, well, I think the easiest entry point for everyone across the the The site would be looking at data and charts and like thinking about data literacy. Like how do you integrate that within all your other classes? And I think that's an easy entry point. We see it in social studies, we see it in English, we see it in everywhere you can do some sort of display, some sort of graphs, some sort of data tracking. So they started, we started to work the entire school with looking at how to integrate statistics and data science in there. And then when I left, the the coaches still were working on integrating those things for the whole site. So my question is to you, because you you brought this up, have you worked with sites on a on a larger scale than just math teachers in looking at like how do we integrate data science or statistics across sites, across curriculum to help To help that inquiry for students.
Christel Bruno: So I
Marisa Tualla: Sorry.
Christel Bruno: I I don't know if Marissa wants to take this. I will say that in terms of the work we're doing, we're not necessarily partnered with a site. So what
Abel Maestas: okay.
Christel Bruno: we have asked when we were doing some of the recruiting is we were like, it would be delightful if we had groups of teachers. And so if you look at our populations for year one and year two, technically year zero and year one, I think according to the grant stuff. We did have groups of teachers that came in with us so that we could talk about how they were working together. But in terms of this grant opportunity, we haven't had the opportunity to do that. But I know that Marissa has had the opportunity with the math standards to be on campuses and do a little more. So I don't know if she wants to talk about that. It's just not the data science lens necessarily.
Marisa Tualla: Yeah, like Christelle said, we're just kind of opening it up to the whole state and trying to see like, you know, and hit some of those rural areas and some people that you know, don't always get these opportunities to come and do these things and so we had not been able to do something site specific. we are the wild west in Arizona is what we like to say.
Abel Maestas: Ha ha ha.
Marisa Tualla: local control and so there's a lot of things that even like me at a state level I'd I don't necessarily have any like authority or power. So it's always like, Hey, would you like some help? Would you like and then no, yes, no, maybe and so supporting it as we can based on requests. But we have a lot of relationships with district level math people or instructional coaches at the site. And so most of our support is we support them if they want to do it. We'll give them ideas. We can work this together. And then they're the ones actually like boots on the ground that can support that at their actual school school site or district. And so this first this summer we had someone who was a district level math sup specialist and he has a very big district and so something that, you know, we hope that what we do with him he can then take on and do that with at a bigger level scale. But what you explained sounds like a really, really cool idea and I definitely a great way to get all teachers and all subject areas in data. Like we even had an ELA teacher at our trainings this summer and she wants to do more data science in ELA, which we love. Yeah.
Abel Maestas: that's awesome. Yeah. Well, cool. So you're you're what are they what's the technical term? You're creating capacity, right? Is that what it is? Creating
Marisa Tualla: Yes, yes.
Abel Maestas: capacity for
Christel Bruno: Yes.
Abel Maestas: for their school districts. that's great. Well, let's talk about some things that are coming up. because I'd love to to promote you guys a little bit if you if the people are around. So I know. That you are presenting at NCSM, which is is super cool. I'm I'm excited to I I'm gonna put it on my list of ones to go to. As long as it's not at the exact same time as our live podcast for NCSM, you can expect me in the room there. So you've got a session called Integrating Data Science into K-12 Math for Innovation and Deeper Learning. Can you just kind of give The listeners a taste of what they can expect.
Marisa Tualla: Yes. I will say a lot of it is things that we've we've talked about here. we go through examples of what does it look like in a classroom where kind of like the participants are the students. we think it's a very important when we have teachers to have them experiencing it as students so they can kind of go back and model that back in their classroom and what like we talk about all the pedagogy and stuff. So it's what are some resources that you can use? How do you use instructional teams? How do you use data sets and like Codap and what are the free things that we have we also won't think promote free things because we can't, you know we know we don't have With the budgets at our school, so what do we have that's free and available that anyone can use and interact with with? And we also share what we've been working with with the graphs we have or with the grant, and so we have different pictures, different teacher experiences that we want to share and kind of how are we doing this at our level? Because a lot of times it's like how can I take the what I learned at NCSM and apply it back when I go to my school or district, and so we kind of go through the what the grant is, how. we're interacting with t teachers, what does it look like for support throughout the school year? 'Cause if you know we don't don't do sh just do a one and done and then we never see each other again. so how can we get that support, that implementation? And we share lots of resources because we love resources, especially free resources.
Abel Maestas: Mm-hmm.
Christel Bruno: Yeah, so we're we're we're definitely, Marissa talked about it, we're definitely going to get on student hat and do a couple of activities together. but because we don't necessarily have the time and space to go through the entirety of the two years that we've been working together, we're gonna share a couple of examples of some things with the resources so that everybody has a little bit of something to take home and try.
Abel Maestas: That's great. I'm also doing a data science presentation at Cal the California Math Council South, CMC South in Palm Springs in November. It's called
Christel Bruno: Ooh, okay, November.
Marisa Tualla: Ooh.
Abel Maestas: it's called data routines that count. So could kind of goes with
Marisa Tualla: Hmm.
Abel Maestas: my podcast, Teaching That Counts, but
Marisa Tualla: Mm-hmm.
Abel Maestas: we're gonna be looking at data routines that you can do to level up your class. And let students start thinking about data. So things like notice and wonders, you know, classics, notice and wonders, which one doesn't belong, but also slow reveal graphs, and then how do you integrate some of this with just simple tweaks that you can do to get your kids excited about data data and thinking about data? And mine is gonna be 612. So I'm really gonna look, you know, specifically what what teachers can be be doing at the middle school and high school level. So I I'm excited to hear yours and take some see go, maybe I can add some of that in my presentation in a week, right after
Marisa Tualla: He
Abel Maestas: math week. But I talk about these conferences because a lot of teachers and leaders for that matter, we go to conferences and we we get a lot of learning, but the learning doesn't stop there, right? Like
Marisa Tualla: Mm-hmm.
Abel Maestas: They have to, there has to be some continued work and sustaining the momentum. So what does meaningful fall like? What does that what does the follow-through look like once a teacher goes back to their own classroom and use what they've learned either in you know a conference workshop or in the workshops that you guys have been running in in your state? what have you learned about what makes that support, the continued support actually stick versus fade out?
Christel Bruno: Well, we will also disclose that this is our first time doing this support. So we're learning in real time and we are growing with feedback from teachers. So I do want to give that caveat. But you did allude to the fact that we are absolutely supporting throughout the year. So we built something called communities of practice so that our teachers are coming back monthly, more or less. to meet. We're having them do some more learning. So you talked about Joe Bowler. We just had Joe on with our teachers this month well, this month, because it's still September, yeah. So
Marisa Tualla: Mm-hmm.
Christel Bruno: she talked a little bit about data science with them. We had a great conversation. And then at the end of the learning, the primary invest the what is he, the principal investigator, the PI for the grant, kind of leads them through check-ins on some of the research components and some of the grant specific deliverables. Ultimately our focus is always on pedagogy. So we just want our teachers to feel comfortable to come back and say, I tried something, it worked, it didn't work. Does anybody have a suggestion on how to make it go better? So we're kind of facilitating those parts of the aspect. as the check in like how are how is it actually landing? You're trying this with real students and what went well, what didn't go well. So that's kind of what we're doing.
Marisa Tualla: I will add, you know, this census is grant funded, that means we have money to pay teachers. And so they are expected to try. We say try something, maybe eventually you'll get to a full investigation and then they're gonna get a stipend for doing the work. And so, whenever we can, you know, support teachers for the extra work that they're doing, we wanna try to do that as much as we can.
Abel Maestas: Yeah, support with money. That's that that's always good.
Christel Bruno: Mm.
Abel Maestas: all right. Yeah, what was that?
Christel Bruno: She's not she's not wrong though. It definitely helps with
Marisa Tualla: Ha ha ha.
Christel Bruno: motivation to try. there are some additional components that I know that they're collecting artifacts from things and I know we're advocating for a final project at the end that's a day or two going through like the data and s data science investigation process. So we're definitely building capacity throughout the year and working in a very gradual build up to bigger and bigger and more impressive things. But we're starting with baby steps and we're happy about our baby steps.
Abel Maestas: Cool.
Marisa Tualla: Mm-hmm.
Abel Maestas: Yeah. Always always starting with the small small part. So you've been at
Marisa Tualla: Mm-hmm.
Abel Maestas: this for two years now?
Christel Bruno: Marissa and I have, yeah.
Abel Maestas: Yeah. How much growth have you seen in your s you know, in the schools that you work with, the teachers that you work with over the last two years in integrating data into their classrooms?
Marisa Tualla: I mean in general people are very excited and they are I think they're really happy with how students have been reacting to it. and how they've been like, Wow, they really they I learned something new about my students. They really took this on, they really wanna they showed a lot of interest and so there's so much motivation and interest students have in these a lot of these investigations and these activities and and so a lot of them once they experiencing with their students like, yeah, I wanna keep doing this. Like there's that like, it's working, so let's keep doing this. anything else, Crystal?
Christel Bruno: I so Marissa definitely kind of alluded to I think part of the reason that we also are seeing teachers go, ooh, I want to try this. We have, I think we've been really purposeful about some of the resources that we've brought. And so like things that we like, I shout out to Data Classroom, right? We have it's my favorite activity to do. We do an activity around Taylor Swift. And so the reality is
Abel Maestas: Ha ha.
Christel Bruno: that it's right, it's not about data. It's not, it's not not about data, but all of all of the kids really get very invested in, we're talking about pop culture, we're talking about football, we're talking about my favorite singer. And so I think that is part of why we see teachers latch on, because we go through a different vein. On all of our activities. We want to make sure that every single content area feels seen in what we're doing, but we also want every content area to feel like, maybe I didn't love that activity for my kids, but I'm really excited about this topic. And so I'm totally excited to bring it to the classroom. So so I think that's part of the unique aspect of what we're doing. We're definitely advocating for free resources. We're definitely bringing a lot of variety to teachers so that if I'm feeling really experienced with technology, I can jump in there. But if I'm not feeling experienced with technology, we have unplugged activities as well. So we we try to build a balance for whatever the comfort level is around data and around the use of the materials. I think that's kind of one of the one of the great great balances that we've struck with the materials that we've brought to the teachers.
Abel Maestas: Awesome. Yeah, that relevance and ability for teachers to easily have things available is is great. You know, I was just talking to somebody the other day that's teaching some data and data science, and they say, you know, I don't get the question in that class, when am I ever gonna use this? Like that's the one question I don't get in that class that I get in the other classes. So you want students to stop saying that? Put some data science in your class.
Marisa Tualla: Yes.
Christel Bruno: For real.
Abel Maestas: All right, Christelle and Marissa, it was so great talking to you and having you on the podcast today. I wanna give you a little bit of time to just let people know how they can learn a little more about your work, where they can get in contact if they're interested, or if their districts are interested.
Marisa Tualla: Yeah, I would say there's probably two avenues.
Christel Bruno: So I would say,
Marisa Tualla: Yeah.
Christel Bruno: yeah, what are you thinking?
Marisa Tualla: one was the our Arizona Association of Teachers of Mathematics. w Christelle's our president. we are using that platform to share out our webinar series to teachers and using so that's a free website is also you can join for free so if people want to get those email blasts they can go to atm dot org. the other side is my side which is the Arizona State Department. So if they want to also get it from our side at the Arizona Department of Education math standards webpage or you just Google AA A D E math we have our own like list server we we share that information as well. So those are two things you could sign up for if you want to know what's what's happening in Arizona and how to get some more information about that. we also have our own email addresses and we people are free to even email us and reach out and we've talked to other people in other states as well.
Christel Bruno: Yeah, I was also thinking Marissa does an amazing job of trying to shout out all of the things that we're doing on LinkedIn so that people have the actual
Marisa Tualla: Mm-hmm.
Christel Bruno: links in real time. So that was the other thing I was like, I'm trying to think. But yeah, she's absolutely right. We've got both of those listservs that we're pushing all of that information out on, trying to make sure that Arizona know what's knows what's going on, but we're also doing we're trying very hard to get more connected with the affiliates in the region and share some of those resources. And AATM is free as is the Department of Education. So all of those are things that no there's no cost to know what we're doing and and beyond those listservs.
Marisa Tualla: I totally forgot about LinkedIn. That's how Abel like and I were talking was LinkedIn. So yeah, Christelle and I are also on LinkedIn.
Abel Maestas: Yeah. I was gonna say, like
Christel Bruno: Yeah.
Abel Maestas: LinkedIn is where I remember getting that information. So yeah.
Marisa Tualla: Yes.
Abel Maestas: Yeah, great job with keeping up on that LinkedIn. all right, Marissa and Christelle, thank you so much for joining and joining me on Teaching the Counts. And I hope to have you guys on our other podcast, NCSM's Learning with Leaders. Everyone out there, when you're listening and you are off to the NCSM conference in Denver. Please join Christelle and Marissa's session. And I hope you all had a good time in our conversation. I know I did. Thank you so much for joining everyone. Thank you so much for listening. And we'll catch you next month.
Marisa Tualla: Thank you.
Christel Bruno: Thank you.
