Sean Tibor: Hello, and welcome to Teaching Python. This is episode 142, and today we're speaking with Kelly Powers, a fellow middle school educator and designer of curriculum and pathways for students to learn computer science. So this is right up our alley. My name's Sean Tyber. I'm a coder who teaches. Kelly Schuster-Paredes: And my name's Kelly Schuster Britis. And I'm a teacher who codes, I. Sean Tibor: Think, Kel to the podcast. Kelly Schuster-Paredes: She's a teacher who codes too, huh? Sean Tibor: Well, we're excited to have you join us today. You know, why don't you give us just maybe a couple sentences about who you are, where you come from, and then we'll jump right into the wins of the week. Kelly Powers: My name is Kelly Powers. I'm from grew up in New York City, and right now I'm teaching at school in Tarrytown, New York Police school and teaching middle school. And I've been teaching for about 25 years, always computer science, which is pretty cool. Before I joined the education workforce, I was in business and worked for a company that most students don't know, the IBM company. So I was really happy to have that work experience and then transition into education back in 98. Sean Tibor: That's fantastic. Kelly Schuster-Paredes: She's, like, the best of both of us, right? A coder who teaches and a teacher who codes. She, like, just smashed us right there together. Kelly Powers: That's why when I listen to you guys, I'm. I'm feeling like so much of your pedagogy and philosophy, so I feel like we've known each other for a long time. Kelly Schuster-Paredes: Awesome. Sean Tibor: That's it. I'm excited to talk more. It's gonna be a lot of fun today. Why don't we start with the wins of the week? And Kelly Powers, I'm gonna have you go first since you're our guest. Kelly Powers: Okay, so this is only our second week of teaching, and I always introduce a person of the week, and my person this week was Ada Lovelace, and I try to show my students, like, a little bio, and I look. Look for a short video, like, less than five minutes. And this week, I actually showed one from Brain Brain Pop, which was really good. If you're looking for, like, a something that really cap captures Ada's story in a five minutes. And my win was students in grades five and six. I showed it to all students I teach. They were able to seriously say, you know what? This woman who was known as the first programmer, she had a lot of challenges in her life, and she did because she was sick as a child, and she Died young. So they were able to take that, take away like these ideas about her being a woman, her being sick. Yet she persevered right through her struggles and challenges. One was also noticed that she was tutored often. Her mom got her tutors because her mom almost demanded that she study math and science. So that was really important to her mother. And the one student said, hmm, she must have been wealthy to afford having tutors. So just little insights that I was really surprised that the students were able to take from this really short five minute video. So that's a big win for me. And that was today, actually, like they got it right. So she's a woman in tech in the 1800 period. That's kind of odd. But she had to struggle and yet she was super successful, which was great. Kelly Schuster-Paredes: Are awesome connections. And I love that like when they can sit and just make the connections and sort of give them somebody to connect to themselves and bring it into light by like. Good, good win. Sean Tibor: I also love Ada Lovelace because she came from a time that, you know, it is really clear, like there were no computers in the 1800s when she was living. How can you be a programmer when there are no computers? Right. And it really illustrates the point, like all of those, you know, heroes, early days of computer science that were doing all this work. It just illustrates the fact that this is really about thinking and it's about organizing your thoughts and analyzing things and paying attention and sorting through all of that and thinking about things in different ways. And none of that requires a computer. And that's one of the things that I love about Ada Lovelace and Alan Turing and even Grace Hopper to some degree. Right. Like all of them are pioneers in the field and I'm overlooking a million people, but they did all this amazing work and none of them had VS code or a Python language or anything like that. Um, it was really about power of thinking. Kelly Schuster-Paredes: Yeah, we don't do that often enough. The power of. In the classroom, I bet. I try, I think all the time. But in the classroom it's like we always try to get them to do the thinking without the computer and everything around that. And it's. Sometimes we lose out. But anyways, I know what your win. Sean Tibor: Is, Sean, but yeah, I just going to point out the window, but Kelly, you go first. Kelly Schuster-Paredes: So I'm excited. Tomorrow I am doing a new activity with the eighth grade. And I. I love the eighth grade. Cause I keep. There's no, like, not really any curriculum that I'm set to. I just kind of deciding Flow as, as the, as the wheels turn, I do follow like certain standard libraries and certain folds. But tomorrow I'm doing this activity with Snapchat sentiment analysis, but in a really easy way. So not pulling anything yet because the concept is really about opening files and saving files and writing files. And I just wanted to have a good way that could like segue into APIs and possibly beautiful soup. So the idea is I got, with the help of ChatGPT, three text files with positive words, negative words, and neutral words. So I'm going to be importing in those files, looking at them and reading them. And then they're going to enter in comments from hopefully not their Snapchat cause they don't have phones, but from like made out comments that they might put. And then it's gonna analyze whether it's a positive or negative and give an emojis symbol and then it's going to put it on another file that they can then write to. So I was just practicing, right? And I was on tragedy. Like, no, this is boring. Give me another idea. I've done this. I've done this. I've done this, I've done this. No, this is bored. And I finally was like, what about like something with Snapchat? And there you go. Gotta love that brainstorming colleague. I have ChatGPT, so it was a really fun activity that I'm. I planned out like a presentation and talking about sentiment analysis and how there's actually AI now that sells sentiment analysis for companies, which was really cool. And yeah. And then I got the whole thing about where it's used on Netflix and. Sean Tibor: Amazon and just makes me ponder, is it talking to yourself if you're chatting with ChatGPT to brainstorm or. Kelly Schuster-Paredes: But it's better mirrored image of myself, I think, because it's more cohesive with my ideas. Because you know how my ideas are all swirly. So it like, it knows what I want now because I've talked to it so much. So we're good. Sean Tibor: I have a just. I'm just picturing Kelly's engineered her prompt to make chatgpt, like super complimentary. That's a wonderful idea, Kelly And Macy, your hair looks lovely today. And why don't you think about this also? Kelly Schuster-Paredes: Yes. And focus, Kelly. Kelly Powers: It's great. Kelly Schuster-Paredes: Well done. Kelly Powers: And it's. Sean Tibor: And if you haven't done that yet, you probably should. Like, wouldn't it be nice if you just had someone who's always saying nice things to you about you and your ideas and gently steering you into other Directions. Kelly Schuster-Paredes: That's when I go to Gemini or Claude. Sean Tibor: Well, I'm not there anymore to do it for you. Kelly Schuster-Paredes: So, you know, Anyways, you win. Go ahead. Sean Tibor: My, my win is that I am not in front of a computer. For the last few days. I had an invitation from a friend to come out to Lake Tahoe for a few days with friends and just be outdoors and hike and everything. And this is, you know, very, very familiar for me. This is a lot like where I grew up in Alaska, where it's just in the mountains and there's hiking and outdoor stuff. So I've swam in Lake Tahoe like three out of the last four days. We've hiked 10 miler. I did an amazing ropes course. Like, I still have the blisters on my fingers from it. I didn't die, which was also a win. But it was one of those things. I really needed this. Like, I needed the time to get away and be out in the, in the woods, be out in the forest and breathe clean air, breathe mountain air that's not, you know, too humid, not too hot. And it's just been really good and, and be with family and friends out here. So it's been just really good to kind of recuperate. And then I go back and write into the thick of things with family and work, travel and all kinds of stuff. So it's, it's been a much needed little break from everything that's normal. Business as usual. Kelly Powers: Wow. Kelly Schuster-Paredes: Yeah. I have to say, you look barely rested for once. Sean Tibor: It might be the time zones. I wake up at 6:30 and it's like I slept in. Kelly Schuster-Paredes: Great. Well, let's jump in. I'm excited to hear about Kelly and I've heard so much about her through a common friend. And so tell us, tell us a short story about you and, and then we can get into talking teaching. Kelly Powers: Yeah, you know, it's. I left the classroom in 2018 to work at Cornell Tech. I hear some. But my job at Cornell Tech was to go out to New York City public schools and teach teachers how to integrate computational thinking? And I know you guys talk about, you're in my world a lot about computational thinking skills to elementary school teachers. So how do we prepare elementary school teachers to start beginning to integrate computational thinking concepts into the two most popular disciplines taught in the country, which is mathematics and ela, first in an unplugged manner and then with the goal of getting them to use a computational tool in their classroom with their students. And that model is really successful because we're not demanding the elementary teachers to use the computers right away. Right. It's more like how can we think about these thinking skills and integrate them into your everyday math lesson or everyday ELA lesson. So that was a fun project. I've never taught element elementary, so I had my utmost respect for elementary school teachers. It's incredible what they do. And I was in classrooms from kindergarten to grade five and just master teaching, you know, in practice every day. So that was fun. But then I was, you know, I wanted to really think about the middle school space. I have a lot. You know, the high school curriculum is looking great for us around the country. We've got plenty of resources, right? We've got the AP curriculum, the CS principles curriculum, and lots of great curriculum out there that's kind of been tested, iterated upon. So I feel like that's a nice space, the curriculum, not necessarily access. Right. Access for all is still challenging and whether or not it's an elective or required, we're still dealing with that across the country. But the middle school is interesting like because that's where actually earlier fourth grade, fifth grade students start to have an identity. Like I am a STEM kid or I'm not a STEM kid or they start to feel certain ways towards certain subjects. I'm not good at that. So what could we do as computer science educators in the middle school space to ensure that then not turned off to computing technology? Because regardless, as you all know, whatever they choose to do, they're going to have to have be deeply skilled in using tools and very comfortable in them and using their thinking skills to be successful. So that I'm curious about this. I've been talking to a lot of people. How should we structure the pathway so that we're making sure that what we give them has two ingredients? And this is where I live, in the eye, rigor and joy. So it's gotta be rigorous and it's gotta be joyous. And if I don't have those two ingredients, then I have to really mix it up because the last thing we wanna do is turn a kit off to computing and computer science. So that's what I'm like playing like the puzzle. And that's where I met Zora Pali, who was a prior guest and I heard her resources intrigued me because it's about using art and Python, pixel art. So it's like that head fake, like, oh, I'm learning lots, but I'm creating my art, you know, using her tools. And I love. And the resources for teachers are there like the slides are there dashboard for kids. So a couple of. When we choose curriculum, you know, do we have what we need to really run with it or is it only going to be up at night chatting with ChatGPT saying help. You know, how do I structure this learning experience so that I get the outcome I'm looking for with my students? So that, that's what I've been looking at. I teach Python right now in grade seven but I've structured, you know, the experience to hit on what I think is really important today. And I want all my kids to get a unit in AI. I want my kids to get a UN in data science. I want to them to get a unit in some sort of programming tool block and then off, off to text. What's on my list, which I can't bring in yet because I'm just like too busy is cyber cybersecurity. So that will be my next like piece that I would like to add to the, the experiences and I'm struggling with. Do I want to give fifth grade a piece of each, sixth grade a piece of each or do I want to really build a hardcore. I know I don't want to build a hardcore progression in programming from year to year because I don't have anything that I think could really maybe Python because there's different tools but can just expose them to things that might interest them in their, you know, further academic journey. Yeah. So that's my challenge. Kelly Schuster-Paredes: What lots of unpacked. I was thinking, so do you teach fifth and sixth, have computer science just note, not Python. And then eighth grade. Kelly Powers: Yeah. So we have it required which is kind of nice. And what's nice about our schedule too, which I'm really proud of, is, and that's why I, I wanted this position is because we, I get 90 hours per year with each with fifth, sixth and seventh. Another colleague teaches eighth in some sections in the high school. So I've got 90 hours to play. Well, they're 45 minute periods but just let's. Well 90 times that I see them, what can I do with that? And it's like 30 per term. We have three terms. So that's a lot of time compared to other schools where they might see them once every six days and it's super challenging. So that's what I have to play with. So what do I want to do with that time? Kelly Schuster-Paredes: Yeah, I was thinking how many hours do we have? It was nine weeks and 70 minutes every other day. So it's funny because it's like either have Short amount of time or length of time and long classes or short classes and long spread out. I wish, I wish I had short classes on long spread outs. It was like a continuous learning at. The idea of the computational thinking can weave in throughout the school year. But it's, it's interesting. And have you thought about some sort of spiral curriculum kind of idea? Kelly Powers: Well, when you, when you're talking about spiraling the concepts, we definitely do that. Like whatever tool we're using, we're, we're hitting the, you know, the sequence conditionals, the statements. So you're hitting control statements, sequence, iteration. Kelly Schuster-Paredes: Right. Kelly Powers: Those three concepts, they keep being readdressed with different tools, you know, so I'll start with scratch in 5th grade and then 6th grade we use code.orgcsdies a little bit. But then you may feel this, but some of the tools that the kids have experience with a lot of code.org, which is great, but I call it puzzle fatigue. Right. So it's like puzzle fatigue because they get tired of just solving a puzzle and I want them to be thankful that I'm leading the class because we don't just do a puzzle and keep going. We stop and we have a conversation and we launch. Like, what's the learning goal for this particular series? But they definitely start to feel puzzle fatigue. So that's when I feel that I switch it up, you know, so it. Kelly Schuster-Paredes: We started like when we were in our, in our early days of Python, we did start with Tinker and that was something that kind of helped, at least helped me as a non coder and I do recommend those for people who are new in the, in the gig. Right. So need the learning. I think one, one full year, you've never taught Python. Go get yourself a tool. And then that just becomes something that happens when you're sick and you need a quick last minute lesson plan or like a change of, change of activities. I'm not a huge, personally not a huge fan of those packets of curriculum that are just there and like go for it. Kelly Powers: Right. Sean Tibor: And so like, yeah, the other challenge that you brought up, Kelly, that I think is really good is, you know, the, like it's about having something of substance and something that is meaningful for the students and being able to, you know, like, it sounds to me, and I want to dig into this poor. It sounds to me also that what you're, what you're trying to do in fifth and sixth grade is create some foundational knowledge that they can then build on as you want to layer in these Other units of AI and cyber and other, you know, other approaches so that, you know, it's, you know, they, they have practical skills that they can use also, and it's stuff that they can use to create something or build something or put two things together. And, you know, I heard it said, I think it was probably, I think it was probably repeated by Michael Kennedy, but someone else said it like, Python is a great duct tape programming language. Right. It's, it's something that you can use to bring things together and make them work in a great way. Right. And there are other languages out there like that, there's other tools and other platforms that help do those things. But I think what, what it sounds like you've been getting into is a lot of the, the how do I create something that is not just a puzzle? It's not just, I know how to make things move around on a screen or how to solve a game or whatever. It's. They have real skills that they can use to go solve problems that they actually care about as well. Kelly Powers: Absolutely. The application is really key. Kelly Schuster-Paredes: Yeah. And that's what I was thinking. What. As you were talking for me. It's funny when I think about computer science and coding. In our Python, we code a lot, but I don't, I don't teach specifically coding skills, except for in sixth grade, like, foundational basis. I'm like, this is a conditional. This is a variable. I teach it one, one time and then every other time. It's my tool for teaching other things. So, like, for example, that Instagram activity I'm going to do tomorrow, we touch on AI literacy skills, we touch on safety, we touch on digital citizenship, we talk about who you are online. And so we have all this opportunity to weave in the content of everything that's evolving while using Python as a tool to get to the content. So cybersecurity, all these little things. And it's almost like you can say, I'm going to do this unit in first period. Yep. I check off at cybersecurity, but then maybe next year, maybe I'll do cybersecurity at the end. It's just how it flows. And I think that sometimes, for me at least, when you see computer science as only you need to go through a list, you need to pop out the list method. Like, I just want to yaw. I can't even teach it. I get so bored. And I think when you, when you weave in those really cool conversations about AI or whatever, natural language processing, how it develops with AI, you can have These really great conversations. And so it's almost like a way to shift it, regardless of whether it's 5th, 6th, 7th, and 8. Just like, you know, writing like, you know, I know how teachers, English teachers teach sentence structure, but to be honest, what's a better way to teach sentence structure is to actually write. Write something. Right. So I think that's the same philosophy for me when it comes to teaching code. Kelly Powers: I love that example. And it's so, like, when you take a step back and listen to you describe that, that lesson you're going to deliver, it's like, whoa, yeah, you're right. You know, you're bringing in a lot of these other concepts by using the tool. So I'll try to keep that lens on. I think I. I do that. But it's nice to just like, take a minute and just say, hmm, like, what else are we hitting here? Right? Kelly Schuster-Paredes: Which is. Kelly Powers: That's pretty power. It's huge. It's powerful. Kelly Schuster-Paredes: Yeah. And you just have to unpack it and just like, really be. What's the word? Not focused, but, like, my. Blank. Blank, blank. But, like, forward towards that tool. Thinking about the cybersecurity and knowing that it's upfront and putting it into the conversation. Transparent. That was the word I was looking for. Trans day today. It's a Monday. Sean Tibor: Kelly, I. I was going to ask you a little bit about connecting some of your prior corporate experience before you came into teaching and working in the business world. You know, one of the things that I found being back in the business world is how much connection there is and how much commonality there is between the way adult learners learn and the way that middle school students learn. Right. The. For me, it's been interesting to see how much that establishing context, establishing knowledge, creating foundational, you know, understanding before you can teach more advanced concepts applies equally to someone in middle school as it does to junior engineer or even a pretty experienced engineer. I was curious, like, as you were making that transaction, you know, from the business world over to education, were there other things that you saw or were there parts of teaching and learning that you were able to draw from your business experience and say, oh, yeah, this is, you know, the same idea. Or was it at the, you know, especially at the time, a little bit different than it is today? Kelly Powers: I'm so glad you raised that because in terms of, like, it's not so much the coding, it's the collaboration. So back in the 80s, IBM hired like, kids right out of college. I mean, 300 kids at the same time came from Like New York City, around the northeast area. And they, they sent this off to IBM school and we learned, you know, how to code and how to really work in teams and making changes to a production system and the change management process and documenting and communicating was key. And they really raised us to be professionals. I mean, I value that experience. And one of the things, and I'm big in always talking about computational thinking in my classroom, we actually have a focus. And I'll say to the kids, okay, our CT focus today might be, is abstraction, but you might use other skills. But this is, this I feel like we're going to use today. And at the end of class, I end with my poster up on the wall. It's like, which computational thinking skill did you use today to complete today's activity? And that is just mind blowing because you'll get kids from. I have three different areas in my room and I could take one from each row and they share out and it's like, oh, you know, I didn't think of it that way, but awesome. It's not the one that I necessarily highlighted, but so I bring that up because what I also am trying to do is have them build their knowledge base from listening to their peers, which is, you know, try out, really trying to create a learning lab in the classroom, a true learning lab where students learn from listening and engaging in the conversation. So I share with the students that my two focus areas this year is talk moves. It's like being able to communicate with other students so that we're building a more knowledge for the, for the classroom community that we're learning in. And then always using your thinking skills so it's not fixing like finishing a problem quickly. Which skills helped you come up with a solution. And then so, so bringing those two together is you're using your thinking skills and now you're using your thinking skills with a partner and collaborating, persevering, debugging, problem solving. So I'm really working on the teamwork aspect that I got exposed to a lot in at IBM. And what's kind of interesting too is I actually shared the story today. When I joined IBM, it was really diverse, which is mind blowing. In the 80s, right? So there was, I was on a team with three women. One was Asian, one was African American and me. And we were young, just out of college, and we were scared. Like, I'm not, I don't, I don't want to put that change in. We might, you know, take down the production system, but together, you know, we share knowledge, we Collaborated. We had a diverse lens, a diverse inputs from each other to really come up with a solution and then take the consequences if it worked or if it didn't work. So that's, I guess what I bring from the work workforce is the processes and the collaboration, which was super rich back in, back in the day. And that's what I'm really trying to get my kids to this year. That's my focus, creating a learning lab where kids are truly communicating and learning from each other. And I started it right away. It's your elbow partner today, next, next week when we start a new lesson, might be your 3:00 partner or your 5:00 partner. We're not talking about. You want to be with your friend. That's not happening. It's diverse like lenses, and that's how we learn best. So that's my focus this year and I'll let you know how it goes at the end. Sean Tibor: But, you know, I want to follow up because I think a lot of people that haven't taught middle school or, you know, haven't been in a classroom maybe for a while or curious about it, they're probably wondering how it works to have middle school students collaborating with each other to write code and if it works. Right? Like, does it work? How does it work? And I guess the really important question to me is, does it matter if it works or it's successful all the time? Is there still learning that? Kelly Powers: Right. So that's where roles are really important. The driver. We play driver navigator. I'm sure you know what that means. But also I really give them their own think time before we partner. Right. So get process at first because it's really hard to go into something fresh or cold and then start trying to work together. Just try to understand your idea so that you can communicate and engage together. So we do. We. I have played with the. Actually just working on one assignment together and having kids switch. So they better be sharing their thinking because if you don't, if you're not, you're really going to struggle as a driver when you get to, when you're listening to your navigator direct you. So, yeah, it's challenging, I think, especially with code, but I think giving them individual time is super important. Kelly Schuster-Paredes: Yeah. I was thinking while you're talking, you know, in the ideal world, I'm like, man, you know, I wish, I wish I would have all those kids that would just communicate and collaborate. Well, you know, you have that one or two. That's awesome. And I always say this line and Maybe you can give me some advice on how you, how you fix this. And you'll laugh as soon as I say it's not sharing the work, it's collaborating. So it's like, I'll do 1 through 5, you do 6 to 10. And I'm just like, that just defeats the whole purpose. And you set up the roles. How else do you combat that issue? The kids doing half the work or one kid doing all the work and the other kid like sitting back? Kelly Powers: That's a challenge for all of us. I mean, if we. And that's why I, I'm taking it on this year, y'all. I'm taking it on this year. And that's, you know, you have, you can't just do one to five because everybody has to leave with gaining the same knowledge to be able to do that independent project. You know, we need the same. You need to build your own skills that you can proceed in the curriculum. So I've been listening to. There's a couple of episodes maybe on. Have you heard of Cult of Pedagogy? So Jennifer Gonzalez, like, I know there's a couple episodes that talk about collaboration and so there's some insights there about making sure that, yeah, you can say you present slides 1 through 5 in whatever they were studying, but ultimately everybody has to be responsible for the content. So. So she was saying she was. Had some tips on doing that. Nothing that really stuck with me, but I guess individual prompts, you know, the exit slip or like a follow up, like to talk about what they took away and if that won't be real evidence that they just did 1 to 5 or 6 to 10. So, yeah, I haven't figured it completely out, but I'm taking my time just to make sure that there's. Kelly Schuster-Paredes: There's so many hiccups and so many things. I was also thinking one thing and I don't know if you do this. I just started. I learned this from my, my teaching partner. She likes to. Talking about your. I like the idea that you said your. Everything's like a learning lab, right? So she takes and she splits up little sections or little codes and then she sets a timer and then the kids have to get out and they have to reteach it. So the entire class is like reteaching this little section and everyone has to then submit from all the code or whatever. So it's interesting. I don't do that all the time. I have to say, I'm really bad at that. I'm always like, everyone code. You can Talk, we'll share out loud. But everybody's doing this. I have to get better at club. Like, it's a personal. Sean Tibor: It's funny, it reminds me of a story just from yesterday. And it, like, it doesn't really have a. You know, there's no moral to the story necessarily, but it feels like it fits. Here. We went to go watch, you know, go to Microbrewery and have a beer after a long day of doing stuff. And there was live music and there was this musician up there, kind of, you know, mountain man from California up there playing. And he played his first song. We all kind of applauded. And he says, you know, thank you. Thank you very much. You know, your support means a lot to me. It's off my album. I self produced it as an independent artist. It's really important that, you know, if you like what you're hearing, go listen. And that helps support me, right? He's like, and it's really important because I do this a hundred percent on my own, and I get no help from anyone. I do it all on my own. I do all of the recording, I do all the editing, I do all of the promotion, I do the social media. I do everything from beginning to end. And that's the way I like it because I want it to be entirely mine. And then we listened to more of his music and I was like, maybe you should consider getting some help. Because I don't know that being able to say I did it all by myself is always the best thing. Right? It's not. We don't live in that world where doing everything all by yourself without any help from anyone is, you know, a good thing necessarily. Right. There's probably exceptions, of course, but it just. As we were talking about this importance of collaboration, I thought about the I did this a hundred percent on my own approach. And maybe that's not always the best approach. And in fact, probably rarely. Kelly Schuster-Paredes: Yeah. Kelly Powers: So I just thought of something, Kelly, that might. That we can apply because I was part of a learning group this summer with digital promise. Basically, we. Kelly Schuster-Paredes: We. Kelly Powers: We read all the research on collaborative learning and classroom discourse. Right. So one of the things that we left with was there's a paper about nine talk moves. And as you're speaking, so there's one called Revoice. So if you truly did 1 to 4, and Sean did, you know, 5 to 10, you can say, okay, Sean, I want you to revoice. So in write it a different way, what Kelly just wrote. And Kelly, you now go to. So I'M just thinking, hmm, that might be a way to use that talk move called revoice. It's making it clearer, putting it in a different way so others can understand. So, yeah, today that my talk rule was add on. And I'm making kids deliberately say, I want to add on to what Kelly said. So they, you know, they're not used to speaking freely in the middle school because there's so much going on in middle school. But that's my initial prompt. They have to say those words, and if they want to use the symbol, it's like fist over fist add on. So that's all I'm working on this week. And next week, we'll talk about revoice and very deliberate prompts. You know, I want to revoice. And this way, hopefully, we're building their like. Like their muscle memory to take part in classroom conversations or at least with their partner. Right. Kelly Schuster-Paredes: Or just any conversations. I think that's awesome. And even, you know, I was thinking again, triggering, like, those are great prompting for how to use AI. So there you go. You're getting AI literacy skills because it's using that. Kelly Powers: Right. Kelly Schuster-Paredes: Content and context. Kelly Powers: Right. Kelly Schuster-Paredes: So many good things that just came out of your mouth about that. I'm thinking, like, routine and trigger words, you know, all those good things and a lot of nuggets to take away. Sean Tibor: From the other thing that I. Kelly Powers: So let's see. I'm going slow to go fast. Kelly Schuster-Paredes: That's what my goal is committed on podcasts. So now you have to stick with it. Sean Tibor: I'm really curious to see how it's going to go with the kids that are usually a little bit quieter. Right. Because, you know, that was always one of the things that I worried about in the classroom was, you know, am I giving every student a chance to have a voice? Right. Especially the ones who are, you know, maybe a little insecure about their abilities or, you know, in some cases, we even had the opposite problems of kids that were quiet in every other subject, but this was their jam in computer science and that you couldn't get them to stop talking or to make it a productive conversation. Right. So I'm curious to know and if you have any early feedback on how the structure of those talk moves, you know, being able to say it's a revoice this time or an add on is helping to guide that conversation, especially for the kids who, you know, maybe feel a little bit less comfortable speaking up in class or to be able to voice their opinion. Kelly Powers: I'm glad you raised that because we do have to respect that. The child's like, I had one student who was super nervous about saying anything because in middle school, she was afraid if she was wrong that others would mock her intelligence. And it was. That's not the kind of environment I had in my classroom. But, you know, that's a real nervousness about that. That feeling is real. So I actually do say to them, I understand that some students may not be. Feel comfortable yet, the power yet sharing their voice with the class, but because we work in teams, I'll be sure to have a conversation with you to make sure that I am hearing your voice. And I. Yeah, we really have to be acknowledged that that's very uncomfortable for some students. But you. You must talk to me when I'm in your partner, at least when I visit you, to make sure I check in with the groups who I don't hear or the students that I don't hear within the classroom discussions. Yeah. So that's how I would address that. Really working, working with those pairs and making sure that they're using the talk moves, and I'm getting to hear what. What they're learning in the way they're reasoning. Sean Tibor: And I'm. I'm curious to see how that would change over the course of the. The unit or the course of the semester. Also gaining that confidence and the feeling of competency from having performed and having done things and being able to be knowledgeable and have that reinforcement, even if it's in a small group setting with you and the. And the. The pair, if that leads to that. That willingness to speak up in class, because now they're coming from a place of. Of greater strength and confidence in their own abilities. Right. And that maybe just be one of those circumstances that leads to students not wanting to speak up, but hopefully that structure and the power of yet will get them to a place where they feel comfortable expressing themselves. Kelly Powers: Yeah. Kelly Schuster-Paredes: Going all the way back to the beginning, you were talking about your role in kind of doing computational thinking skills and unplugged activities. And it got me to thinking about all the skills and how there are actually a lot of life skills, you know, going back to your idea of work skills and everything. And I'm thinking, you know, pattern recognition, abstraction, and how. How cool would it be. How cool would it be if doing the same thing that you were just doing with, you know, making those communication trigger word. How cool would it be if, like during an advisory or during English class or something, we're talking about data analysis or we're talking about how do we automate something? Or you know, what do we notice about pattern recognition? So then, because a lot of teachers always say what, how do we get computer science into the classroom? Or how do you do it? Simple, simple words that are transferable across curriculum kind of help support that coding. Yeah. I was wondering if you, if you had seen any of that happen. I mean you, now that you know it's in your head, you're probably like, yeah, I've done that like fifth grade in math and English and ela. Kelly Powers: Yeah. So what's interesting, like I've been part of the COMP CSTA Computer Science Teachers association since it was founded. So since 2005 when we were a tiny organization and now it's grown international organization. And during that journey and still today, you know, we have been part of some National Science foundation grants focusing on computational thinking and integration. And what we, we have like a, we almost have like an algorithm for onboarding teachers. Right. Because if you do enter the building to coach, they're already like they want me to teach computer science. And they, you know, an elementary school teacher too. I mean it's really, they have five preps a day plus the development of social, emotional learning, everything going on in that school. But we really feel if we can get them to internalize the language and understand that hey, I'm doing this anyway. So it might be just changing some of my vocabulary in. Let's start with the classroom routine and in my classroom routine. And it's funny because the dean of our grade, he used this word today. It was awesome. And he's like. And the algorithm is powers for collecting our lanyards today or get receiving our lanyards today is as follows. The series of steps. And he looked at me, how'd I do? Kelly Schuster-Paredes: Like awesome. Kelly Powers: So in terms of when we onboard teachers for anybody integrating, we actually make them create an anchor chart, right? Take a word abstraction and we say show a short definition. They read like a paragraph about what this term means. And then many elementary school teachers, they have like tons of anchor charts all over there walls. But what is an abstraction in your daily life? What is an algorithm in your daily life? So make a chart during teacher prep and then make one with your students, right? How do you use, do you use algorithms at home? What is it? What does that look like? Can you show me and the kids co create this anchor chart with you. So you start like living and practicing the language with kids in a non computing setting. So that's like, that's your first journey. But we don't leave this journey without using your computational tool. That's key. So you can't stay there. You have to progress. So that's what we, we do. And the some of my colleagues who work in the City University of New York in the education department, they're infusing the future educators will have computational thinking exposure in their education to become teachers. So that's that they get. That's getting spread throughout the country, which is a big win for us. Like what is it? What do these words mean? What does it sound like? What does it look like? And then what tools are we using to have kids create and practice those skills using a computational tool like Scratch Junior or Scratch Python, you know, that's getting them there. So like you said, if you have the whole. I always say to teachers, imagine a kindergarten. We've done this at a school in the Bronx. The kindergartners were using algorithm. You know, they with the angle. But they know what it means. It's not as they're not saying the word. They actually know what this means. So we can have children understand what these practices and skills looks like and sounds like in kindergarten. And we do this year to year. What might that student look like and sound like and be able to do as a problem solver when they leave 12th grade? We don't. I don't know yet because we haven't watched a student progress. But like if we can get at least the language and the practicing of it. I play with teachers even in the copy room, you know, it's not working. Oh, we got to debug that together. You want to help, you collaborate. And they laugh at me. But it's like it's getting it to be part of the culture. It's a culture of problem solving. Right? Kelly Schuster-Paredes: It is. And you know what? Some of the ones that I actually too too is debugging with the kids like given the conference debug and solving their own problems. But pattern recognition, I think more so it's been a lifesaver for me when I was learning to code is like, oh, why is input and print and you're defining of a function. A function. Look at the way that the pattern is and you can see when you call it. And I think, I don't think we teach pattern recognition enough or explicitly I should say explicitly. We kind of say, oh, this is how your essay is in five. In a five paragraph. But let's recognize other pieces of work or let's recognize why we use a certain math problem to solve this math. I Think if we put pattern recognition, we do it in lower school, right? We do, you know, looking for patterns. If we kept it through, imagine how easy our jobs would be as coders. Sean Tibor: Well, it's. But I think it's. You're getting to a point too, where you're talking about a lot of the pattern recognition that we've done is the stuff that, like, ends up on the SATs, right? It's like the pattern recognition recognition we do is like, oh, these numbers go in order. 1, 1, 2, 3, 5. Oh, look, it's a Fibonacci sequence. You recognize the pattern. Congratulations. Right, but what I think. What I think you're getting at is probably this is kind. I think we've had this conversation many times about how computational thinking, computer science borrows a lot from math, but it has so much more in common with language, right? Like, how much. How much do we do with patterns in language? You know, sentence structures or patterns of documents or patterns of speech. Patterns of writing. Yeah, right. All of these things that. That probably would help in a practical sense for pattern. Right? And pattern recognition, that when you see it, oh, I see how this is fitting together, or I see the structure of this, and that's, I think, way more valuable not just as a. As a coder, but as a business person, as an analyst, as a scientist, as a writer, as a. I mean, seeing. Analyzing the pattern of a plot structure of a movie, right? Like, here's the first act, second act, act, third act, right? Like where the acts change, right? Those things, to me, feel like really practical skills. But what we've been calling pattern recognition is, you know, a, B, B, C, B, B, B, C, D, right? Like these things that you look at and you start to see patterns, but it's very simplistic and it's very mathematical. But the real value, I think, is when we start to see patterns and way more than just sequences. Right? Kelly Schuster-Paredes: Yeah. Now you got me thinking about decomposition now, too. Just throw that around as well. Composition problem. Sean Tibor: So I have to. I have to switch gears. I know we're kind of running. Running towards the end here, but it feels like a golden opportunity, like, because we have middle school teachers on the podcast, right? Like, it's. It's middle school. It's our. It's our little space where we have. Have, you know, where we have developed our expertise, where we've got our passions. And, you know, I. Having left teaching, one of the things that was always funny was how many people were like, oh, my God, I can't believe you Taught middle school. Like how awful was that? I'm like, no, actually it was pretty wonderful, right? Like you had to understand what was going on now at work. But Kelly, I just want to like I have to ask what to you is the best thing about teaching middle school students? Like what is the best thing about this particular age that makes it a special opportunity or special experience for teaching? Kelly Powers: I wouldn't just say creativity. You know, they're just so different and I think differently and giving them the opportunity to create. So you know, like as we talk about building skill and then apply that's that's huge like creative self expression. And when I see it, give them that opportunity and they, they take this knowledge that they've been building throughout a period of time. So that really is, is mind blowing to me. It's just to see what they can produce, giving that freedom but with, with some constraints, you know, they have to meet certain requirements but then go for it. Their creativity, curiosity, it's, that's what, what I love and I learned from them. That's why even at the end of class, my end of routine is which computational thinking skill helped you complete today's work regardless of what it was? And just to listen to them, it's like oh, you know, they are thinkers when they're given that opportunity, when you have the setting set so that this is a thinking class, it's not a race. And given that the opportunity to have the time to create something that's important and meaningful to them. That's what I love seeing what they do with the knowledge that we're trying to help co create with, with the classroom. Kelly Schuster-Paredes: You wait, are you waiting for dark. Sean Tibor: To give you a chance? Kelly Schuster-Paredes: Say. I can say it changes every year, but I think like what's keeping me in there is it's never the same thing every day because it's like I get bored very easily. I love excitement and I can't imagine, you know, even when I was teaching science in the cell for 12, 10 years, it's never the same, it's never the same unit. It changes with every class of every kid. And you never know what you're going to get from a sixth grader to an eighth grader, especially the eighth graders. So I mean I love the creativity I love, I love the sweetness of sixth graders and I love the snarkiness and the having to do like a dance and kind of pony show for the 8th graders to keep them awake and not falling asleep. Odette didn't mention that my teaching putter partner Brought in weighted blankets. So give a weighted blanket to an eighth grader in a game, in a gaming chairing. What happens to them? They fall asleep. Sean Tibor: Which much easier to teach them when they're unconscious. Kelly Schuster-Paredes: Kelly, we're taking very good care of their social, emotional. They do love us. But I have to like, just ruin. Kelly Powers: Their logical thinking skills. Or is that. That teaches logical thinking skills when I brought. Kelly Schuster-Paredes: She's okay. They love them though. They weighted blankets, just so, you know, don't give into the eighth graders. Sean Tibor: I mean, I have to, I have to agree with both of you. I think my favorite thing about teaching middle school was that there was that moment of discovery. And it wasn't usually about. It wasn't really about the technology. It was the moment of discovery where they realized, like, whoa, I can do this. Like, I did that and it worked. And it's like something that I thought of and I was able to make it happen and I can see it in front of me. And that to me was always the magic of middle school because it's. They have enough knowledge and they have enough development and enough critical thinking skills and like, ability to reason their way through things that they can do it. Like, they can pull it off in middle school. And they're also not stressed out by having to get good grades for college and what school am I going to get into? And, you know, what, what sports are happening and how do I, you know, like, there's this beautiful sweet spot in middle school where they are incredibly capable, incredibly creative, and yet they don't know what they're capable of doing and being able to create those moments for them. And I feel like we found more of that in computer science than we probably deserved, right? Like, it was, it was it we created something there that there was an environment for that. And, you know, I know that there are other middle school teachers who teach other disciplines who see those same things. And that was, to me, always the best part about teaching middle school was that discovery of self and discovery of possibility. Kelly Powers: And I just want to add on. On this aside, like the discipline of computer science, those aha moments and that achievement, right, by getting the opportunity to use their creativity in computer science is kind of like instant, right? You're working through a problem instantly. Unlike other subjects, it might take a full period so you get your paper back. Like, how did I do on that draft? Kelly Schuster-Paredes: Right? Kelly Powers: So you're really having. You could have a lot of aha moments and immediate, like, sense of achievement, which is awesome. You did this. You know, this was complex and I got it done. So the discipline allows, allows for that, which is very, makes it very different and unique from a lot of the other discipline, problem solving in the moment and getting the results good or bad. Kelly Schuster-Paredes: It's the feedback, right? Sean Tibor: Yeah. It's the, in fast iteration. Right. Like that, that fast cycle. I can try something, check it, see if it worked, get feedback on it and implement a change and do that, you know, in a 30 minute class, 20 times. Right. And, and I like how that also flows potentially into other subjects where they start to see the power of that iteration and the feedback. And it also lowers the, the penalty of making a mistake. Right. Because what's really a mistake, it's, it's just something I haven't fixed. And when they can bring that to math, to English, to science, to social studies and apply that same sort of like, hey, it's not that big of a deal, I made a mistake, I'm going to go try something else based on what I learned from that to do something new and see how that works. They start to crave that feedback in other subjects also. And you know, it's probably a pain for our other colleagues to keep up with that once they get going on it. Kelly Schuster-Paredes: Sure. Sean Tibor: Well, I know, Kelly, you wanted to ask us some questions potentially or explore some topics around the curriculum development and the pathways that you're creating as well. So I wanted to make sure we had some space for you to be able to ask those questions. Kelly Powers: Yeah. Are you, it sounds like, Kelly, you're thinking about like tackling some of the. I have a unit in AI which is. You're making me think about this differently. Where we actually are using Scrum Scratch. Right. The playground version of Scratch that has AI blocks. And we're using, we're using some curriculum from the MIT Riker group R. AICA group. And basically they get to create, they create a model, they create an image recognition model. They have other units to study. But so like are you thinking about AI in your pathway or even data science, which I stumbled across Bootstrap from Brown University and I've had some pretty interesting like moments with that curriculum that I wasn't sure if my kids would like. So sticking in Data Science in 7th grade AI, a unit of study, how are you addressing some of the, like the. These areas of computing that are, are growing like even at rapid rates at AI, data science, cybersecurity in what you're delivering in your instruction for the kids? Kelly Schuster-Paredes: I. It's a great question. I find myself constantly talking about AI and generative AI and AI everywhere in the 8th grade, just kind of in conversations whenever we bring up stuff. But starting from maybe the sixth graders, we do a lot more playing with AI and big topics. And I do introduce a lot of the words and their machine learning neural networks, but it's such a short unit. But it's more of just a, here are the words. This is where generative AI came from. I make sure that they know that generative AI was born because of Python. And, and we have all these libraries in Python with natural language processing and the sentiment analysis. And it, it starts there, right? It, you can literally do a chat bot or whatever if you want to. And even, even though, you know, things that we do is something that's, you know, builds something bigger in AI. So I try to make that huge connection from our tiny little piece of script code to what it really looks like inside of. So that's always on my mind. And I think it's just because one, I'm passionate about AI and I just can't stop thinking, talking about it. But in eighth grade, I also love data science, so that's something that I wish, if I had my wish. I keep hinting to my boss all the time. I'm like, let me teach a post AP data science course. Let me teach. I will love data science because data science in Python's so much fun. And you can, you can get the kids doing graphing and understanding that their graphs don't necessarily necessarily match what they really want to say in just 10 lines of code with matplotlib. And then you can give them generative AI and collab and say, okay, here's matplotlib, here's the basic. Now make this graph actually interactive. Find how to use it with generative AI. So I probably could spend the entire nine weeks teaching data science to the eighth graders, but I don't, I do it in like one unit, but. And it depends, it changes every time. I sometimes start with graphs and I make them explain the grasp because that's something that I don't think they get enough of. Kelly Powers: Right, right. Kelly Schuster-Paredes: What else? Yeah. And then seventh grade, we always talk about the use of generative AI and how do we do it ethically? I think that's a huge conversation. We're not opposed to generative AI, at least when you're even online, because replit used to have generative AI and now that it's not free, it's, it's. They only get one piece of code or something when they use Repl it. But collab has generative AI in there. They start typing and it goes. And I said, yeah, we can go, but if you don't know what it means or what it's not going to help you. So it's good. Write comments, figure it out. So I think it's like you can avoid data science and generative AI and you don't really have to keep them separate. When you talk about data science, you're talking about all the data from the web that it was trained on, generative AI. So you could talk then about beautiful soup and scraping and how they did a common crawl. Not necessarily the same, but you can still access. I can go on and on. This is like a passion of mine. We'll talk later about this. Kelly Powers: Oh yeah, and I love how you really, you're using the tool Python to do all these great things with the students. I mean I'm really admire like how far you take your kids. I'm still not sure though, you know, in like if you get a few kids who aren't turned off by coding. Right. So that's where I struggle. So now, you know, I've gone through imagi first like all kids and then I moved some of them into the tool. We were the, we had a subscription to Code hs which was different. Like that's more like pure straight up text based coding in python. And about 70% of my kids who were in seventh grade last year were okay with it, you know, oh, this is different. And I was trying to get the transfer strong too. Like we just did loops, really complex loops in, you know, pixel art. Like we're just doing the same thing in Python. And some of them were getting. It wasn't at some of them actually that 30% was like, can we please go back to magic with powers? That was so much more fun. So that's, that keeps me up at night, right, Trying to figure out. And then like you're preparing them with really core. I mean you guys are really going deep with the kids. I love it. Like I love what you're doing. But what happens in high school? Do they then move into a regular AP? They go right to AP, like as a 9th grader or. Sean Tibor: Yeah, 9th or 10th grade, depending on what they're interested in. It's an, it's an elective for them. Well, they can if they want to go straight into it in ninth grade and they have, you know, demonstrated that they have good academic skills and can cope with the rigor of it in ninth grade they go straight into it and there's Four years of computer science curriculum in the upper school. Kelly Schuster-Paredes: Five now. Sean Tibor: Five now. Okay. Kelly Schuster-Paredes: Yeah. So it's funny, it's funny. When Shadow and I first started teaching I know they had classes in ap, but we have I think like doubled the amount of classes that they now have in 9th grade AP. So a lot of our kids, I would say probably about 75% of our students go on to take the AP course in ninth grade. And they come back, they're like this is so easy. And like yeah, because we are, I, we are a very challenging course. I do like to have it challenging but I do make sure that everybody is successful and understands at least. But I never, never underestimate the power of a kid making a graph with eight lines of code or ten lines of code. Because I tell you what, when they, I've turned more students on to using graph coding with graph, there's something pretty about them especially when you like you have a wordle even or a pie chart and they put all their names of their friends and whatever or they, they can also my colleague, she had them. I forget what she did. It was, she did it with a matplotlib where you can do an image kind of trace in a wordle. So those little things are really neat. Kelly Powers: Yeah, I love, I love your approach. Like really. It sounds like it create really great engaging experiences for the kids having rigor and joy, you know, so you're able to infuse even the data science. So I'm going to just take a step back and try to think about this some more. You know, I, yeah, so it's, it seems like you're able to do a lot with Python as you build your student skill base. Right. Kelly Schuster-Paredes: Going forward and you just keep adding on. Kelly Powers: But I want like even now I'm adding a VR unit like immersive, immersive reality. Like whoa, this is like what might. Because that could be their future too, right? Designing immersive experiences. And that's picking up quite a bit around the country. So that, that I'm tinkering with that a little bit. So but yeah, I'm gonna, I'm gonna think about the resources again. Cause I struggle too finding resources that helpful not always have to pay for them too. Cause that could increase the cost of buying so much software which might be okay if we balance like make trade offs. So we also are on the Chromebook, right. So that I know you have some tools that you use that you actually download to use a laptop. Kelly Schuster-Paredes: But Colab works well on the Chromebook and I Think you'll find that it works, really? With the new generative AI feature and built in, I think you would be able to really get into data science without having to worry too much about the code. So you can say, I want to make a graph this way. And Colab will let you help you generate, as long as you import the library first. And then those conversations can happen. Like, okay, well, let's look at how many people, you know, how many girls or whatever, how many boys, how many. How many teachers, what of our age group, you know, just whatever. How many people have Snapchat? How many pushups can you do? That's a fun one Plank challenge. Kelly Powers: Collecting data and then using the data in the classroom. Yes. Sean Tibor: The other thing that I always thought was really fun, too was especially when you get into data science. Like, data science isn't really small data sets of like 15, 20, 30 things. Right. Start them there, like, get them to understand it as a base case, and then give them something with like, 30,000 rows of data or a million rows. Right? Yeah. Kelly Schuster-Paredes: Great. Sean Tibor: We analyzed the dictionary, the dictionary file in macOS. So there's a hidden file, not quite so hidden, but it's a system file that has a list of words, and it's, I don't know, a couple hundred thousand of them. And we went through and used that for all sorts of things, like graphing out word length of what was in there, being able to look at. I think we ended up doing some stuff on, like, algorithm processing times, like the really large lists. You did loops through the lists. Yep. Kelly Schuster-Paredes: Writing files, reading files, because you're freaking. You could do the. You can graph out the number of letters and take it from that. It was a really good. I still use that. Some of that. Kelly Powers: It's pretty fun. Sean Tibor: But I like that. That is a way to kind of get that whoa moment when they see that, like, what they did for 10, you know, elements in a data set works for 10,000 or 10 million also. That's a really empowering moment for them. Like, that what they did still works, and it scales up in a beautiful way also. So I definitely recommend that for anybody who's doing stuff with data sciences. Make sure that wherever you start has a nice scaling point to something really big and meaningful for them so they can look at it and go, wow, I did that. It was like millions of rows of data, and it only took like, 42 seconds because it was Python. Kelly Powers: Right? Nice. Kelly Schuster-Paredes: Hey, Kelly, you're a celebrity. Because Brianne Kaplan was like, Kelly Powers. Kelly Powers: Well, Brianna Kaplan. Yeah. Yes. I met her at csta and I'm really impressed. You know, a lot. There's a lot of young women creating companies and just doing amazing things internationally. So I got to hang out with Brianna Kaplan, Dora Palfi, and also Emily Jolie, like three woman entrepreneurs that I can't say what I want to say, like, amazing woman on, you know, with deep degrees in their education, neuroscience, engineering. So it was a privilege to hang out with them at CSTA and learn, you know, what their focus is, what their goals are. But, yeah, amazing, Amazing. Kelly Schuster-Paredes: Well, we'll definitely have to have a return conversation because I think. I think we could go on forever, but Sean's last night of vacation, it's. Sean Tibor: Was going to say, I think we should hold off on the conversation about cybersecurity and that unit. I think that worth doing it. Kelly Schuster-Paredes: Yeah, that's worth another episode, for sure. Sean Tibor: For sure. I think there's. We haven't even really scratched the surface of what's possible there, and I'm not sure even what's available out there in terms of curriculum that people have tested and tried and shared. But I mean, just thinking about that as an. As an opportunity. There's a lot of things that we've done in terms of kind of personal safety on the Internet, but how can we turn that into a real cybersecurity unit? I think would be a really fascinating topic for sure. Kelly Powers: So before we leave, I'll ask you, as I end every class, which computational thinking skills helped us get through this podcast tonight? Kelly Schuster-Paredes: Go first. Sean Tibor: Well, I've been finding a lot of abstraction, right? Like being able to take a lot of the specific things the. That we've talked about and think about how we can broaden them or connect them to other concepts that are out there. So for me, abstraction was definitely the big one this episode. Kelly Schuster-Paredes: Well, give me a hand of some. So let me think. Kelly Powers: We got. We use computing at school. Six concepts. Logical thinking, evaluation, abstraction, algorithm thinking, pattern recognition. And I don't know if I said evaluation already. Kelly Schuster-Paredes: I don't know. Wow, that was a tough one. It's brainstorming one, because I feel like. Kelly Powers: I do patterns in our discussion today, though. Ap. Kelly Schuster-Paredes: You know what I do. That is true. That is true. Thank you for the help out there. Do think there's a lot of patterns. There's a lot of similarities that we can pull from in the way that we teach and what we believe in. I think that's a good one because when you were speaking, I was like, triggering some extra thoughts and I was like Oh, I do that. Well, that's cool. Or looking where I don't do that. So. Yes, thank you. Sorry. You got me. Kelly Powers: Yeah. So see, closing the. Maybe you'll do this in your future cast. Closing. Kelly Schuster-Paredes: I really like that. I do like that. I'll learn it better and I'll be able to pull it together. Kelly Powers: That's a good poster in the back of your classroom. And say the kids look at that poster. Tell me what and defend it. Like, explain yourself. Kelly Schuster-Paredes: I was thinking we'd add it onto the podcast. Sean Tibor: I like it because I do think, you know, it would. It would help us just, you know, kind of close the loop. We start with Wins the week. I love with the what strategies helped us on this. On this show. Like, I really like that. Kelly Schuster-Paredes: Yeah, I do. I was thinking that we in iste, don't they have like 10 or 10? 10 for computational thinking? I'm going to have to look that up because I think they have more. Kelly Powers: They might, but the four key ones that we can agree with across the country are pattern recognition, algorithmic thinking, decomposition, and abstraction. You won't get into any arguments if you talk about those four. Kelly Schuster-Paredes: Good to know. Good to know. I'll stick to this. Awesome. Sean Tibor: But the arguments are so much fun. All right, well, why don't we wrap up here? Kelly, do. Do we have any announcements this week or anything to share with our listeners? Kelly Schuster-Paredes: No, somewhat's going on. No, all good. We have a lot of organ. We're going to take a little hiatus, I think. Sean Tibor: Fine, fine, I'll do it then. We have a thousand followers on LinkedIn now, thanks to all Kelly's hard work. Kelly Schuster-Paredes: Hi. Yes, a thousand and one. Sean Tibor: One thousand one. Well, Kelly, well done. Congrats to you. You have spearheaded all of our social media on LinkedIn and brought us to this milestone. And I just wanted to say thank you for all your hard work on that. Kelly Schuster-Paredes: I have got zero, I think, followers now on Twitter. I never post, but yeah, if you know anybody and they're on LinkedIn, point them to our LinkedIn page because that's where we do a lot of the live streaming, also on our YouTube. But I think it's nice because when we start getting those conversations happening on the live stream, it really takes the conversation deeper and then people can start sharing the resources. That's sort of my hope of where I want LinkedIn to go is that people can go back and look at the live stream, add in some comments, share out some resources. So we should plug in, say, Kelly, if they have some computational thinking ideas or strategies or anything else they want to add for us because we always need more suggestions to keep it fun after. I don't know how long you've been teaching, but it's been a really long time for me. So anything that's new and a new way to do things, it's always a welcome back. Kelly Powers: I will do. And it's been a real pleasure, you know, finally getting to see you and talk to you kind of in person, it feels like, because I listen to you all the time. Sean Tibor: This has been. This has been a lot of fun to talk and like I said, it's a golden opportunity to be able to speak to a fellow middle school teacher. It really is a special place to be and we love to hear about all the things that you're doing and thinking about and figuring out in the space because it's never. The work here is never done. It's always something new and exciting and worth trying and adjusting. So thank you for all the hard work that you do to make it possible. And if people want to learn more about what you're doing or connect with you, where's the best place for them to reach you? Kelly Powers: I'm on LinkedIn. My Twitter handle is elpowers5 because I'm the fifth child of 11 unfit. So Kelpower is 5. That's a good way to remember me. Kelly Schuster-Paredes: That's why you're communicator. Kelly Powers: And a pipe for the floor. Sean Tibor: Yoing. Very good. Well, I think that'll do it for this week. So for teaching Python, this is Sean. Kelly Schuster-Paredes: And this is Kelly signing off.